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Entrepreneurship unfolding : the effect of entrepreneurship on family wellbeing—a family embedded perspective Houshmand, Marjan 2015

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   ENTREPRENEURSHIP UNFOLDING: THE EFFECT OF ENTREPRENEURSHIP ON FAMILY WELLBEING—A FAMILY EMBEDDED PERSPECTIVE  by  Marjan Houshmand  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF   DOCTOR OF PHILOSOPHY  in  THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Business Administration)   THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  August 2015  © Marjan Houshmand, 2015    ii  Abstract  Family business is an important and prevalent type of organization. The intertwined relationship between business and family has deep implications for the success of the family business and the welfare of the business family. In this dissertation, I aim to contribute to a deeper understanding of that relationship by using a dynamic approach to study how family businesses evolve and how they impact the family. I focus on opportunity entrepreneurship and study its antecedents and outcomes. I study (1) the factors that shape the path of individuals into opportunity entrepreneurship, and (2) the implications of the business for the entrepreneur and for other members of the family as it evolves into a business family. I develop an unfolding model of entrepreneurship that captures the impact of business involvement of family members on their psychological and financial wellbeing.  My core thesis is that the involvement of family members in a family business has important consequences for the business family. I formulate hypotheses about four forms of involvement: (1) direct involvement through self-employment, (2) indirect involvement through living with a self-employed relative, (3) direct and dependent involvement through working for a relative, and (4) family-level involvement in terms of the proportion and intensity of family members work in the business. Moreover, I argue that the effects of these forms of business involvement are moderated by the household roles that family members play. I explore empirically how these forms of involvement coupled with household roles affect family members' psychological wellbeing (life satisfaction) and financial wellbeing (income). I use a comprehensive large panel dataset from Germany that spans over 28 years and use fixed effect models. I find that family  iii  business involvement has positive effects for the entrepreneur, while it has negative effects for the other members of the family. Family-level business involvement has overall negative effects. I also find that the effect of business involvement on family member's wellbeing is not moderated by gender, nor is it moderated by household roles. Overall, the findings support my unfolding model of entrepreneurship. Entrepreneurship is a mixed blessing in terms of the wellbeing of family members.    iv  Preface  This dissertation is original, unpublished, independent work by Marjan Houshmand.   v  Table of Contents  Abstract ...................................................................................................................................... ii Preface ....................................................................................................................................... iv Table of Contents ...................................................................................................................... v List of Tables .......................................................................................................................... viii List of Figures ............................................................................................................................ x Acknowledgements .................................................................................................................. xi Dedication ............................................................................................................................... xiv Chapter 1: Introduction ........................................................................................................... 1 Chapter 2: Conceptual Framework ...................................................................................... 11 2.1 Role Theory ................................................................................................................ 12 2.2 From Self-Employment to Family Business .............................................................. 15 2.3 Family Business Definition and Relevant Literature ................................................. 19 Chapter 3: Who Becomes an Opportunity Entrepreneur .................................................. 23 3.1 Opportunity Entrepreneurship and Risk Seeking ....................................................... 25 3.2 Opportunity Entrepreneurship and Barrier to Entry ................................................... 26 Chapter 4: Psychological Wellbeing—Life Satisfaction ...................................................... 29 4.1 Opportunity Entrepreneurship and Entrepreneur's Life Satisfaction .......................... 30 4.2 Opportunity Entrepreneurship and Other Family Member's Life Satisfaction........... 32  vi  4.3 Working in the Family Business and Family Business Employee/Helper’s Life Satisfaction ............................................................................................................................ 34 4.4 Whole-Family Involvement in the Family Business and Member Life Satisfaction . 36 Chapter 5: Financial Wellbeing—Income ............................................................................ 40 5.1 Opportunity Entrepreneurship and Entrepreneur's Income ........................................ 40 5.2 Opportunity Entrepreneurship and Other Family Members' Income ......................... 43 5.3 Working in the Family Business and Family Business Employee's Income .............. 45 5.4 Whole-Family Involvement in the Family Business and Their Income ..................... 47 Chapter 6: Methods ................................................................................................................ 49 6.1 Data and Sample Overview ........................................................................................ 49 6.2 SOEP Subsamples ...................................................................................................... 50 6.3 Survey Participants ..................................................................................................... 50 6.4 Survey Types .............................................................................................................. 51 6.5 Data Files .................................................................................................................... 51 6.6 Statistical Software ..................................................................................................... 52 6.7 Variables ..................................................................................................................... 52 6.8 Models ........................................................................................................................ 65 Chapter 7: Results .................................................................................................................. 67 7.1 Becoming an Opportunity Entrepreneur ..................................................................... 68 7.2 Life Satisfaction .......................................................................................................... 70  vii  7.3 Income ........................................................................................................................ 88 7.4 Summary of Results.................................................................................................. 105 Chapter 8: Discussion ........................................................................................................... 108 8.1 Antecedents of the Transition into Opportunity Entrepreneurship —When Individuals Enter into Self-Employment ............................................................................................... 109 8.2 Outcomes of Entrepreneurship —How Business Involvement Affects Psychological and Financial Wellbeing of Family Members .................................................................... 111 8.3 Contributions to Theory............................................................................................ 116 8.4 Implications for Managerial Practice ....................................................................... 121 8.5 Future Research ........................................................................................................ 124 Chapter 9: Conclusion .......................................................................................................... 128 References .............................................................................................................................. 131 Appendices ............................................................................................................................. 148 Appendix A: The Effect of Opportunity Entrepreneurship on Income (excluding those higher incomers above €1,150,000) .................................................................................... 148 Appendix B: The Combined Effect of Working in the Family Business and Living with an Opportunity Entrepreneur on Life Satisfaction................................................................... 151 Appendix C: The Effect of Helping in the Family Business on Focal Actor's Life Satisfaction .......................................................................................................................... 154 Appendix D: The Combined Effect of Working in the Family Business and Living with Opportunity Entrepreneur on Income ................................................................................. 160  viii  List of Tables  Table 1: Frequency Table of Opportunity Entrepreneurship Status (Wide Format) .................... 54 Table 2: Frequency Table of Life Satisfaction (Wide Format)..................................................... 56 Table 3: Frequency Table of Income (Wide Format) ................................................................... 57 Table 4: The Frequency Tables of Variables in the Long Format ................................................ 62 Table 5: The Cross-Tabulation between Opportunity Entrepreneurship and Life Satisfaction.... 64 Table 6: The Cross-Tabulation between Opportunity Entrepreneurship and Life Satisfaction.... 65 Table 7: Effects of Risk Seeking Attitude and Access to Resources on Becoming an Opportunity Entrepreneur .................................................................................................................................. 69 Table 8: The Effect of Opportunity Entrepreneurship on Life Satisfaction of focal Individual... 72 Table 9: The Effect of Living with an Opportunity Entrepreneur on Focal Family Members' Life Satisfaction .................................................................................................................................... 75 Table 10: The Effect of Working in the Family Business on Life Satisfaction of Focal Individual....................................................................................................................................................... 79 Table 11: The Effect of Proportion of Family Members Involved in the Family Business on Life Satisfaction of Focal Individual .................................................................................................... 83 Table 12: The Effect of Time Intensity of Business Involvement of Family on Life Satisfaction86 Table 13: The Effect of Opportunity Entrepreneurship on Individual Income ............................ 90 Table 14: The Effect of Living with Opportunity Entrepreneur on Focal Member's Income ...... 93 Table 15: The Effect of Working for Opportunity Entrepreneur on Focal Family Member's Income........................................................................................................................................... 97 Table 16: The Effect of Proportion of Members Involved on Focal Member’s Income ............ 100  ix  Table 17: The Effect of Intensity of Business Involvement of Family on Family Members' Income......................................................................................................................................... 103     x  List of Figures  Figure 1: Family and Business Roles in a Family Business ......................................................... 16 Figure 2: Entrepreneurship Unfolding—from Self-Employment to Family Business ................. 17 Figure 3: Entrepreneurship Unfolding—from Self-Employment to Family Business ................. 18     xi  Acknowledgements  Embarking on the path of higher education is truly a privilege for which I am very grateful. I feel genuinely thankful and humbled by the help and support of many people who have made this journey possible.   First and foremost, I would like to thank my amazing dissertation committee (Dr. Martin Schulz, Dr. Marc-David Seidel, and Dr. Thomas Hellmann) who have taught, inspired, challenged, helped and supported me more than I could have imagined. I have been lucky to have such brilliant scholars and yet kind mentors on my side.   I would like to express my deep gratitude to the chair of my committee—Dr. Martin Schulz who has been a wonderful advisor. Martin, I have learned many valuable lessons from you. Thanks very much for everything you have done—for challenging me to think more deeply and critically and for giving me all the training and kind support I needed throughout these years. I will cherish our very interesting—and yet, at times, heated—conversations. I would also like to sincerely thank Dr. Marc-David Seidel. Marc-David, you have played a significant role in my PhD training. Thanks a lot for being a great mentor and being so supportive while pushing and encouraging me to improve in many areas, from teaching to conducting research. Finally, I would like to thank Dr. Thomas Hellmann, who has been such a great and supportive advisor. Thomas, many thanks for all your guidance and kindness.    xii  I would also like to thank the rest of my academic family at Sauder. I am very grateful to all the faculty and staff at the OBHR department. A special thank you to Dr. Sally Maitlis and Dr. Sandra Robinson for all their kind guidance and help in the past few years. Thanks as well to all the other PhD students from whom I have learnt so much and received such support, particularly those in the OBHR division—a special shout out to my PhD cohort (Anthony, Leah, Luke), and research collaborators (Dennis, Kejia). I would like to particularly thank Ms. Nancy Tang for her invaluable support. Nancy, I truly appreciate everything you have done. Finally, I would like to thank Ms. Elaine Cho for patiently guiding me through all the logistics and steps since day one.   My PhD experience would not have been the same without the support I have received from the Sauder School of Business and the Business Family Centre at UBC, as well as the financial support from generous donors such as Mr. Garry M Zlotnik. Thank you. I also would like to recognize and thank all the staff at the SOEP center and all households and participants of SOEP survey in Germany who have made it possible for this research to be conducted.   I would also like to take this opportunity to truly thank my immediate family (Mehdi, Zari and Mahmoud) who have been a great source of strength in this process. Dad, mom, thank you from the bottom of my heart for bringing our family to this great country that I gratefully call home, and thank you for encouraging and supporting me in any way you could have throughout this journey. Mahmoud, thank you for all your help and support and for being an amazing brother and a great friend. I feel quite lucky to have you guys in my life. Special thanks as well to my wonderful extended family and friends. Thank you very much, everyone.    xiii  Finally, I would like to thank my lifelong mentor, Dr. Parviz Sahabi— a true master of knowledge, an exceptional teacher, and an inspiring human being. Dr. Sahabi, thank you for sharing your wisdom with your students and for being a remarkable role model. I am forever indebted to your teachings and kindness. I would like to dedicate this very small contribution of knowledge to you, to all my wonderful advisors and mentors and to those amazing beings who dedicate their lives to seeking, discovering, and disseminating knowledge for the betterment of all.     xiv  Dedication  To Masters and Mentors of Knowledge  1  Chapter 1: Introduction  Two key institutions of many societies are business and family. The intertwined relationship between these systems has inspired scholars from diverse academic disciplines to explore their connection from different angles and shed light on many insightful and interesting findings. Weber discussed the role of patriarchs in the realm of traditional domination as a basis of people's beliefs about accepting authority (Weber, 1978). Prestigious positions in patrimonial systems are inherited rather than being earned and blood ties play a key role in career advancement. In the modern era, rational domination has become a popular form of organizing collective efforts. Although rational domination is rooted in the legality and rationality of rules, the interlocked relationship between family and business still persists (Dick & Morgan, 1987). Family ties still play an enormous role in business — in small and large firms, and in developed and underdeveloped countries as well. Consequently, in organizational scholarship, there have been numerous calls to include family as a variable in research (Aldrich & Cliff, 2003; Dyer, 2003; Moen, 2003).  Despite these calls for exploring the relationship between family and business, little attention has been paid to the connection between these two institutions. In the few cases where it has been explored in the literature, the relationship has mostly been analyzed uni-directionally—the impact of family on business. Notable research in this line of work includes studies on the impact of fatherhood on CEO decisions regarding wage distribution at work (Dahl, Dezső, & Ross, 2012) and the impact of work life balance on organizational outcomes such as job satisfaction and organizational commitment (Aryee, Srinivas, & Tan, 2005).   2  Even in the literature on entrepreneurship and family business, the interdependency between family and business has usually been studied from the angle of the impact of family on business. This is surprising because the relevance of embracing the family in organizational studies is more salient within the fields of entrepreneurship and in family business in which family plays an important and visible role. In family businesses "the strands of the family system are so intertwined with those of the business system that they cannot be disentangled without seriously disrupting one or both systems" (Kepner, 1983, p. 57). This interconnectedness is rooted in market and non-market ties through which family members are connected with each other. The overlapping of these ties, therefore, has the potential to create spill-over effects from the family to the business and vice versa (Pollak, 1985) and make these two systems interdependent on one another.   Given the importance of entrepreneurship and family business for a vibrant economy, organizational scholars in these fields have recently begun to pay particular attention to the interdependency of family and business systems. However, the focus of entrepreneurship research, for the most part, has been on the effect of family on business outcomes. Entrepreneurship studies suggest that entrepreneurial families have a salient influence on their businesses. For example, within the entrepreneurship and family business contexts, family members—regardless of their involvement in the business—are viewed as a source of financial, human and social capital to their entrepreneurial family member (Aldrich & Cliff, 2003; Arregle, Hitt, Sirmon, & Very, 2007; Dyer & Handler, 1994). The dominant perspective is that family involvement shapes business outcomes, and studies in this line of thinking find significant effects of family characteristics (e.g., its social capital, its dynamics) on family businesses' succession  3  and performance (Anderson & Reeb, 2003; Chrisman, Chua, & Sharma, 2005; Chua, Steier, & Chrisman, 2006; Miller, Le Breton-Miller, & Scholnick, 2008; Pérez-González, 2006).  These studies have justifiably recognized the importance of family on business outcomes. The reverse direction —the impact of the business on the members of a business family — has found considerably less attention. Given the importance of family for business outcomes, this lack of attention to understanding how business influences family is surprising. If the family is so important for business, its wellbeing is clearly relevant, and studies on the effect of the business involvement of members on family outcomes can produce a deeper understanding of the conditions and constraints that families encounter when they become involved in a business. To close this gap, in this dissertation I adopt a family embeddedness perspective (Aldrich & Cliff, 2003) to theorize and explore the effect of business on family.   The family embeddedness perspective highlights the interconnectedness of the family and business. It currently focuses attention on the importance of the family for entrepreneurship and family business success (Carter, 2011). While studies have explored the ways in which family can facilitate success or failure for a business, we know less about the implications for family members becoming involved in their own business on the wellbeing of their family. In this dissertation, I underscore this intriguing yet understudied relationship in order to better understand and discover the strengths and weaknesses of entrepreneurial and business families.  In order to explore the relationship between the business involvement of family members and their wellbeing, I apply a life course perspective (Elder Jr, Johnson, & Crosnoe, 2003). Life  4  course perspectives highlight the role of transitions in life courses of individuals, and in this study, they can illuminate how transitions of family members into business roles and family roles can impact their wellbeing. This perspective is a suitable approach in studying and tracing families and households over time (e.g. Schulz, 1982; Kaufmann et al.,1984 ).   Life course research has become more prominent and more rigorous in recent years due to the advancement in data collection methods (in particular, multi-wave panel studies) and the availability of powerful statistical methods to analyze these data (fixed-effects methods). The longitudinal data structures support the analysis of within-individual effects and facilitate powerful statistical testing of causal relationships in unfolding life courses. Life course models (theoretical and statistical) facilitate a deeper understanding of how transitions in the social context impact individuals. Numerous studies have emerged that have made substantial contributions to applying and developing life course theory. Some early examples of these studies involve tracing children born in early 20th century over time— for instance, the Oakland Growth study (Jones, Bayley, MacFarlane, & Honzik, 1971), and the Stanford-Terman Study (Oden & Terman, 1959). Such studies have contributed to the establishment of the life course paradigm in sociology and have encouraged other scholars to investigate and include in their research change across different life stages (Elder Jr, 1994), such as tracing the effect of work on adolescent development and beyond (Mortimer, 2003; Mortimer & Jon, 1979; Mortimer & Shanahan, 2003).   One of the key implications of the life course perspective is the recognition of interdependency among lives between which the social context shapes an entire network of ties. The  5  interdependency among individuals implies that as individuals go through transitions, they influence other people in their network (Elder Jr et al., 2003). Transitions refer to "changes in states or roles," and examples include "leaving the parental home, becoming a parent, or retiring" (Elder Jr et al., 2003, p. 8). Life course transitions can leave deep footprints of prior experiences (Uhlenberg & Mueller, 2003); they can create entirely new contexts for living and working and decision making. For families, the transition of family members into business roles combined with the natural dynamic of family role transitions can produce rather dramatic context shifts for members as well as significant changes of outcomes (for themselves and others). As the business involvement of families increases, the implications in terms of the experience and wellbeing of family members can become more salient. Untangling these relationships is not easy, but I will draw on life course methodologies to develop a deeper and clearer understanding of the underlying causal mechanisms.   My study aims to produce a deeper understanding of the externalities associated with the transition of a family member into self-employment. The decision of a member to take up self-employment sets the stage for an unfolding process that can draw other members into the business and thereby produce life course transitions for them with deep implications for their wellbeing. The externalities of involvement in a business arise dynamically as family members become exposed to the business, either directly by helping out or working for the family business, or indirectly in terms of exposure to a family in which other members are involved. Family members not only transit between different forms of business involvement, they also transit between family roles, e.g., they might become a sibling or a parent. The dynamic interplay between family and business roles can produce complex and surprising outcomes. To study these  6  complex dynamic processes, I take a longitudinal approach and trace individuals and the households they live in each year. I analyze the household composition to determine the family structure and the role(s) that the focal individual plays in the family. I analyze the business involvement of the focal member and of other members in the household to determine the family business structure and the business role(s) that that focal individual plays in the family business. "Although 'family' is not synonymous with 'household,' family structure most often refers to household composition" (Uhlenberg & Mueller, 2003, p. 126), and taking a household focus provides a powerful tool to analyze the unfolding of entrepreneurship and the ensuing externalities.   I direct my analytical lens on the family business unfolding process that starts when a family member in a household becomes an entrepreneur, and which then creates the possibility for other family members to become involved in the business — directly or indirectly. My unfolding model of entrepreneurship traces the life courses of individuals as they transit in and out of family and business roles over time. The model leads to a deeper understanding of the effect of the business involvement of family members on their wellbeing, and the way in which family roles can moderate the effects of business involvement.   In my unfolding model of entrepreneurship, a family member develops entrepreneurial passion and voluntarily enters self-employment. As a result of the presence of a business in the household, other family members are drawn into the business, both directly and indirectly. Both family and business change as family members broaden their familial roles and adopt business roles—from becoming an entrepreneur to actually working in the family business as helpers or  7  dependent employees. Depending on the extent of the business involvement of family members, the business and family both evolve and change dramatically in character – e.g., starting with the self-employment of one member and evolving into an all-encompassing family business with the direct involvement of everyone in the household. Different forms of business involvement can have dramatically different implications for members and their wellbeing. To study the effects of different forms of business involvement, I observe the transitions between self-employment and family business when other family members become directly involved in the business of their relative entrepreneur (Dyer & Handler, 1994). The transition from self-employment to family business coincides with the family transitioning from a regular household to low involved and high involved business family. While previously in the literature, the family cycle has been traced through marriage, having children and death of partners (Glick, 1947; Hill, 1970), I trace the family cycle through the business involvement of family members—from no involvement to high involvement.   I focus my attention on opportunity entrepreneurship in this study because of its volunteer aspect that is closely tied to the motivation behind why individuals pursue entrepreneurship. Opportunity entrepreneurship refers to starting a new business in order to exploit a market opportunity (Block & Wagner, 2006; Kirzner, 1973; Shane & Venkataraman, 2000). Opportunity entrepreneurship is usually distinguished from necessity entrepreneurship. Opportunity entrepreneurship occurs often when individuals seek autonomy and independence, develop a risk-taking mindset, and grow interested in (even passionate about) starting up their own business. Opportunity entrepreneurship is often the product of a (perceived or real) opportunity that motivates individuals to become entrepreneurs (Reynolds et al., 2005). In contrast, necessity  8  entrepreneurship is more similar to regular employment in terms of the underlying motive of generating an income. It is the elevated level of risk taking and passion that makes opportunity entrepreneurship stand out, and— as I will show below—it has unusual implications for the individual and his family.   In sum, the aim of this dissertation is to theorize about the self-selection process of family members into opportunity entrepreneurship and to understand how the choice to become an opportunity entrepreneur impacts family members depending on the business and family roles they assume. The specific research questions I pursue are—how does the degree of family members’ business involvement impact their and other family members' psychological and financial wellbeing? And how do their family roles moderate the above-mentioned relationship? Answering these questions requires suitable—i.e., longitudinal—data. Multi-wave surveys conducted on the same individuals repeatedly (panel data) can offer opportunities to study my research questions. Panel studies have become increasingly popular in the social sciences. These studies follow individuals and their families over time, which makes them fitting for life course analysis, in particular as their longitudinal design addresses problems of heterogeneity (Halaby, 2003a). For this dissertation, I have found a suitable dataset: the German Socio-Economic Panel dataset (GSEOP), an individual-level dataset spanning the years from 1984 to 2011. This dataset currently consists of 28 panel waves which allows me to empirically test my research questions.   I believe that my unfolding model of entrepreneurship can offer several theoretical contributions and lead to important and interesting empirical insights. First, the model is interdisciplinary in nature, connecting to various literatures such as entrepreneurship, family business, sociology,  9  economics, family studies and psychology. The interdisciplinary nature of the model allows this dissertation to contribute to a number of scholarly fields. It contributes to organizational studies by bringing new light into the intertwined nature of business and family systems and the effect of the business system on the family, particularly as business roles and family roles are combined and produce complicated work-life balance for family members. Second, it highlights the externalities associated with entrepreneurship that have been understudied in the fields of entrepreneurship and family business. Taking into account the transitions that family and business experience within entrepreneurship and family business contexts and using a longitudinal dataset further deepens our understanding of the unfolding of life courses when individuals become directly or indirectly involved in a business. This approach demonstrates the power of life course perspectives for analyzing and understanding the dynamic interplay between business and family. Third, this dissertation offers a host of practical managerial implications for entrepreneurs, family business owners and family business consultants. It offers a new model for understanding and analyzing the outcomes of the family business for business families. Finally, it is my hope that this dissertation is a stepping stone that will open interesting avenues of research in this area and help us to better grasp the intertwined relationship between family and business.   I follow my research questions in the next four chapters. First, in Chapter 2, I describe my conceptual framework in detail. I provide a literature review on role theory and family business to position this dissertation within the relevant conversations in general management literature. In Chapter 3, I discuss how risk preference and barriers to entrepreneurship affect the self-selection process of opportunity entrepreneurs. In Chapter 4, I examine the effect of opportunity  10  entrepreneurship on the psychological wellbeing of family, specifically their life satisfaction. Similarly, in Chapter 5, I explore the effect of opportunity entrepreneurship on family members' income as a measure of family financial wellbeing. Chapter 6 covers the methods and explains the data set, variables, and type of analysis employed. Chapter 7 presents the analysis and the findings. In Chapter 8, I discuss the findings and the ways in which this dissertation contributes to organizational literatures. Finally in Chapter 9, I provide a roadmap for future work that can extend the findings of this dissertation.    11  Chapter 2: Conceptual Framework   In this dissertation, I aim to explore and theorize the effect of business on the wellbeing of family members within the entrepreneurship and family business contexts. I propose a conceptual model, which I call the unfolding model of entrepreneurship, that traces business and family in various possible states. The unfolding model of entrepreneurship takes into account the self-selection process of family members into entrepreneurship as they strive to exploit a market opportunity, as well as the subsequent business involvement of other family members in the business.  Applying this framework, I seek to better understand the underlying processes that lead individuals into opportunity entrepreneurship and investigate the influence of entrepreneurship on the psychological and financial wellbeing of family members. I focus on opportunity entrepreneurship to analyze how passion and risk-taking attitudes can drive a family member into entrepreneurship and how that in turn can produce ripple effects for the entire household. Therefore, my conceptual framework of unfolding entrepreneurship explores businesses and families in the context of opportunity entrepreneurship.    I draw on role theory to analyze the intertwined relationship between business and family—as an entrepreneurial business unfolds into a family business and the degree of business involvement of a family increases. Role theory can connect family members to each other in both the family and business systems and help us to understand how family members assume business roles on top of their family roles. Role theory highlights the different roles family members play in family  12  and business systems and thus can help to illuminate the effect of business involvement on family members' wellbeing while considering the family roles members play in their household.   In this chapter, I explain the unfolding model of entrepreneurship in more detail, first by articulating the connection between role theory and my conceptual model of unfolding entrepreneurship. I describe various potential states of business and family systems as they evolve from dependent employment to self-employment to family business, and within the family business, from a state of low involvement in the business to high involvement. Secondly, I connect this research to the broader discourse on family business in the extant literature. The framework portrayed in this chapter serves as a reference point for chapters 3, 4 and 5, in which I delve into my research questions in more depth.   2.1 Role Theory The unfolding of entrepreneurship from self-employment to family business is embedded in the emerging business roles for family members. For example, a wife can be involved in the business by (informally) assisting her entrepreneur husband in running the business, or she could be employed in the family business. The family business unfolds as more family members take on roles in the family business. Therefore, a role-theoretical approach can lead to a deeper understanding of how the business involvement of family members affects their wellbeing.  Role theory is rooted in social positions that are associated with a set of expectations and norms of behavior (Biddle, 1986). The patterned behaviors inherited in roles have made role theory an attractive theoretical framework within organizational studies in dealing with the context of  13  organizations that are hierarchical and task-focused (Biddle, 1986). In the context of exchange systems in organizations, roles provide guidance for behaviors and delineate obligations. Roles, however, can also be a source of stress and discomfort. An excessive perceived amount of demand on one's role leads to role strain, which Goode defined as "the felt difficulty in fulfilling role obligations" (1960, p. 483). Role strain is related to another concept, role conflict, in which a social actor faces conflicting demands arising from her multiple roles. Kahn et al. have defined role conflict as the "simultaneous occurrence of two (or more) sets of pressures such that compliance with one would make more difficult compliance with the other" (1964, p. 19).   Role strain and conflict are costly for actors. A good example of role conflict is that between work and family. Spending more time and energy at each setting results in having less time and energy in the other setting (Greenhaus & Beutell, 1985). Work-family conflict entails undesirable consequences (Allen, Herst, Bruck, & Sutton, 2000); it is positively related to turnover intentions (Netemeyer, Boles, & McMurrian, 1996) and predicts actual turnover (Greenhaus, Parasuraman, & Collins, 2001). It is also identified as one of the dangers to individual wellbeing. Numerous studies have linked higher levels of work-family conflict with psychological distress and depression (Frone, 2000; Hammer, Neal, Newsom, Brockwood, & Colton, 2005).  When people occupy different roles in different settings and there exists an overlapping of network between two settings, the combination of these roles produces a unique effect different from each role. This is called role multiplexity (Ashforth, Kreiner, & Fugate, 2000; Valcour, 2002). Role multiplexity is closely tied to the concepts of role segmentation and integration.  14  Contrary to role segmentation, role integration refers to "roles that are weakly differentiated and are not tied to specific places and times and allow cross-role interruptions" (Ashforth et al., 2000, p. 479). Role integration is highly relevant for business families and family business as family members assume business roles on top of their family roles. For example, a mother and daughter working together also assume the roles of owner and employee and their roles can be activated in both the work and home settings—i.e., the owner feeling motherly sentiments towards her employee at work or the mother talking to her daughter about work-related issues at home.    Therefore, due to role multiplexity, roles in self-employment and family business become more complicated as the layer of roles in the family setting influences the performance of business roles in the economic setting. The business and family roles operate in two distinct social exchange systems. The complexity between managing expectations in each social exchange system produces unique effects as family members become involved in the business. Family members' experience is shaped by both the business role and the family role they assume. Husband and wife assuming the roles of entrepreneur and family business employee have different experiences when it comes to the ways in which their business involvement affects their own and each other's wellbeing.    As I explain in the next section, the unfolding model of entrepreneurship takes off when a family member voluntarily takes up self-employment to seize a perceived business opportunity. This sets the stage for the active participation of other family members in the business. Performing business roles can affect the wellbeing of family members, while their family roles moderate  15  these effects. The business roles and family roles, therefore, form the building blocks of my unfolding model of entrepreneurship.   2.2 From Self-Employment to Family Business My unfolding model of entrepreneurship connects the self-selection of individuals into opportunity entrepreneurship with the subsequent business involvement of family members. It provides us with a framework for investigating the influence of entrepreneurship on the wellbeing of family members. I conceive entrepreneurship as a form of behavior that directly and indirectly draws other family members into its course. Family members are exposed to the consequences of decisions by entrepreneurial members who have followed their passion into becoming self-employed. As family members become directly and indirectly involved in the business, problems and opportunities can arise and “post-decision surprises” (Harrison & March, 1984) can occur that can severely impact family life.     The involvement of family members in the business can vary considerably in form and degree, and this has important implications for both subsystems—the family business and the business family. The uptake of self-employment by a family member sets the stage for the involvement of other members in the family business. The process can unfold in diverse ways and lead to different outcomes for members, depending on their degree and type of involvement and the roles they play in the family.   As explained in the previous section, family members can play different roles in the business and the family. The performance of these roles impacts how these two sides interact with each other.  16  The business roles signify the degree of involvement of family members in the business and can take several forms: entrepreneur, family business worker, family business helper, or indirect involvement through residing with an entrepreneur. The family roles, on the other hand, capture conventional familial positions in a household. Family roles are defined as "mutual expectations negotiated by the actors that define each actor's responsibility to other family members in a given context" (Hood, 1983, p. 5). I treat actors based on their role in a household and focus less on gender roles (see Figure 1).   Figure 1: Family and Business Roles in a Family Business Systems Roles Family head of household, partner, child, extended relative, and non-relative Business entrepreneur, indirectly involved (residing with an entrepreneur), and directly involved (family business employee, family business helper)   Family members can, therefore, be involved in the family business in several ways, and different forms of involvement can produce a burden or a benefit for different parts of the family. I distinguish three forms of involvement in a family business. First, a family member can be directly involved as the opportunity entrepreneur—the self-employed owner of a business. Second, family members can be not directly involved in the family business but still part of the  17  business family due to residing in the same household. Third, a family member can be directly involved by working for her family business as a paid employee or as a family business helper.  A family member motivated by entrepreneurial passion may take up entrepreneurship. Their self-employment affects other family members, drawing them directly or indirectly into the business. This elicits new and changed behaviors from family members and creates a new form of family—business family. Depending on the degree of involvement of other family members the new business may become a family business (see Figure 2). Additionally, as the proportion of family members involved in the business increases, so does the “businessness” of the family, making the family a high involved business family.   Figure 2: Entrepreneurship Unfolding—from Self-Employment to Family Business  Let's take the example of a household of four members—the head of household, the partner and two children (Fig 3). In this household, when one of them (the head of the household) decides to become self-employed, the family becomes a low involved business family. The presence of a  18  business in the family creates a new setting that can powerfully impact the wellbeing of its members. The business can offer family members opportunities to become involved in the business through business roles—working or helping out in the business. If one of the members (in this case, the partner) enters the business by formally working for the family business, it changes both the business and family systems. In this scenario, the business and family evolve into a family business with involved business family members.   Figure 3: Entrepreneurship Unfolding—from Self-Employment to Family Business  As family members assume business roles on top of their family roles, they experience role multiplexity. In the previous example, the head of the household and partner are connected through both their family and business roles. An important feature of this system is “living together,” which intensifies the role multiplexity experience for actors. For instance, let's imagine a situation with two brothers, who live in two different households but work together in their family business, with one of them being the founder. They experience role multiplexity at  19  work and family gatherings, as in addition to being each other's brother, one is the boss and the other is the employee. However, they can nevertheless escape their role multiplexity for some part of their daily lives upon returning to their separate households. Conversely, a wife and husband working and living together have fewer chances of leaving behind their work and family roles. Therefore, I consider not only the way in which the business involvement of family members affects the wellbeing of the family members but also the effect of "working and living together" on family members' wellbeing.    The effects of "working and living" together are likely to intensify as the business involvement of family members increases (i.e., an increase in the proportion of members directly involved in the business), and this can affect family members' wellbeing. As the intensity of family members being engaged in the business increases, so does the degree of businessness of the family. This can produce unintended consequences for family members in the household.   My unfolding model describes how a family transitions into a family business. As more members start working alongside the entrepreneur, his/her self-employment evolves into a family business. In the next section, I position my dissertation within the broader literature on family business.  2.3 Family Business Definition and Relevant Literature  Research has shown that a large percentage of the firms across the globe are family business firms. For example, in a study of 27 countries, family owners were shown to control an average of 25 percent of the total value produced by the top 20 firms in a given country (La Porta, Lopez- 20  de-Silanes, & Shleifer, 1999). Family businesses require their own studies due to their unique nature that entails both family and business life (Arregle, Hitt, Sirmon, & Very, 2007; Chua, Chrisman, & Steier, 2003; Gersick, Lansberg, Desjardins, & Dunn, 1999). They possess unique characteristics that separate them from non-family firms (Hoffman, Hoelscher, & Sorenson, 2006). Simultaneous roles, shared identity, lifelong common history, and emotional involvement are some examples of these unique traits (Tagiuri & Davis, 1996).  A popular conceptual presentation of the family business is through the systems lens. A family business system consists of three overlapping systems of family, business and ownership (Gersick et al., 1999; Sharma, 2004). Family members can belong to one, two or all three systems. The systems are open systems (Scott, 2004; Wiener, 1954) and their overlapping nature implies that a high level of complexity is involved in analyzing such businesses. The state of each system influences the outcomes of other systems in a complex and dynamic manner.   Conversely, there have been many definitions about what constitutes a family business. “Defining the family firm is the first and most obvious challenge facing family business researchers” (Handler, 1989, p. 258), and to date, there are still many definitions in the literature depending on the perspectives authors take (Astrachan, Klein, & Smyrnios, 2002). For instance, a business is a family firm to the extent its “ownership and management are concentrated within a family unit and to the extent its members strive to achieve and/or maintain intra-organizational family-based relatedness” (Sharma, Chrisman, & Chua, 1996, p. 185).    21  In this dissertation, for both theoretical and empirical reasons, I have simplified the systems perspective to two systems of family and business and, additionally, developed my own conception of a family business. Theoretically, I am interested in exploring the way in which business and family roles shape family members' wellbeing. In my dataset, I do not have access to the ownership structure of the family business firm. However, this does not impose a limitation on my study as I am not interested in exploring how the ownership structure could potentially affect family members. Instead, my interest lies in the choice a family member makes in becoming an entrepreneur and the implications this has for family members. Therefore, in my conceptual framing, I have included only the family and business systems.   My concept of family business takes into account whether family members "perceive" that they work in their family business or not. Furthermore, because of the importance of the "working and living" concept in my model, I focus on family businesses that have one or more family members working for, and living with, their entrepreneur relative. Similar to prior studies, I highlight the type and intensity of the business involvement of family members in the business (e.g. Astrachan et al., 2002), and explore how the form, degree and intensity of the business involvement of family members could shape family members' psychological and financial wellbeing. My conceptual model is broad and does not rely on a specific definition of family business. It provides a general guideline for analyzing how the business involvement of family members affects their wellbeing.   The family business literature of the past two decades has made significant progress towards a broader understanding of the unique characteristics and behaviors of these firms. For the most  22  part, these studies have looked into how the family shapes business management decisions. We know much less about the reverse direction: how family firm management choices influence the families concerned. Understanding this reverse linkage is critical to fully understanding the differences between family and non-family firms (Sharma, 2004), as family is an important source of capital for entrepreneurial and family business firms. Bubolz suggests that “the family is a source, builder and user of social capital” (2001, p. 130), which in turn serves as a potential competitive advantage for family firms (Arregle et al., 2007) compared to their non-family counterparts.  My research questions aim to address this important gap in the literature and offer valuable and interesting findings on the repercussions for the family when a family member decides to follow a market opportunity and becomes an entrepreneur. While passion pushes entrepreneurs forward in their quest to fulfill a vision and establish a business, entrepreneurs often turn to their families for support and resources (Aldrich & Cliff, 2003; Dyer & Handler, 1994). The decision to become an entrepreneur—usually motivated by an entrepreneurial passion for realizing a vision—is therefore an individual decision that has implications for both the entrepreneur and the rest of the family. I argue that the decision to become self-employed has both intended and unintended consequences that affect the psychological and financial wellbeing of family members differently depending on their degree of involvement in the business. In the next three chapters, I build on the framework discussed in this chapter, explore my research questions in detail, and develop testable hypotheses about the processes that lead individuals into opportunity entrepreneurship and the effect of business involvement on family members' psychological and financial wellbeing.   23  Chapter 3: Who Becomes an Opportunity Entrepreneur  Sociologists and organizational theorists have highlighted several contextual and individual factors in explaining actors’ decision to pursue entrepreneurship (Shane & Venkataraman, 2000). While some examine situational characteristics such as the negative influence of working in a bureaucratic organization on entrepreneurial behaviors (Sørensen, 2007), others point to more individual differences such as values and intentions formed by actors prior to embarking on self-employment (Kolvereid & Isaksen, 2006).   Similarly, research has shown various motivations that lead to the choice of becoming an entrepreneur. Professional motives such as career advancement and mobility often lead individuals into self-employment (Sørensen & Sharkey, 2014). At the same time, empirical evidence has indicated that the motivation behind the pursuit of self-employment goes above and beyond financial incentives (Benz & Frey, 2008). Passion plays an important role in entrepreneurship. In the past few decades, researchers and practitioners have attributed passion to as being one of the main mechanisms responsible for the uncommon behaviors and attitudes of an entrepreneur, such as " unconventional risk taking, uncommon intensity of focus, and unwavering belief in a dream" (Cardon, Wincent, Singh, & Drnovsek, 2009: p. 511).   Before I theorize about how entrepreneurship influences family members, it is important to clarify what type of entrepreneurship I refer to in this dissertation and how family members self select themselves into it. Entrepreneurship can be taken up for different reasons. Prior research distinguishes two main types: opportunity and necessity entrepreneurship. Opportunity  24  entrepreneurship is characterized by a voluntary transition into self-employment, often in response to a perceived opportunity (Reynolds, Camp, Bygrave, Autio, Hay, 2002). Necessity entrepreneurship lacks this voluntary character, and the uptake of self-employment arises from the necessity of circumstances and the lack of other opportunities (Block & Wagner, 2006).    The Global Entrepreneurship Monitor (GEM) studies explore these two types of entrepreneurship at a more macro level—national level— and reveal interesting findings associated with each type. For examples, findings suggest that opportunity entrepreneurship is positively related to economic growth at the national level (Acs, Amorós, Bosma, & Levie, 2009). The difference in motivation behind each type, not surprisingly, leads to different individual outcomes (such as financial ones), with opportunity entrepreneurs outperforming necessity entrepreneurs (Block & Wagner, 2006).  I argue that the higher level of passion in opportunity entrepreneurship creates a higher willingness of the entrepreneur to introduce more radical changes and to take risks and bear their consequences. This can produce tensions with other family members who are not as focused on the business and have their own careers and life plans. Often, dramatic changes in life style are involved, and the business can make intense demands on members who might resent the new state of affairs. For these reasons, I center this dissertation around opportunity entrepreneurship and how it affects the psychological and financial wellbeing of family members as family members become directly and indirectly involved in the business.    25  I focus on two factors that play a key role in the self-selection of individuals into opportunity entrepreneurship—risk tolerance and access to resources, both of which lead individuals to embarking on the path of self-employment.   3.1 Opportunity Entrepreneurship and Risk Seeking Entrepreneurship is often seen as being connected to individual’s risk preferences (Cramer, Hartog, Jonker, & Van Praag, 2002) such that those willing to take risks are more inclined to become entrepreneurs (Marshall, 1965; Van Praag & Cramer, 2001). Risk taking is positively associated with optimism (Puri & Robinson, 2007) and constitutes an important factor that leads individuals into self-employment. Thus, risk-seekers are more prone to start their own business than risk adverse individuals (Halaby, 2003b; Valdez, Doktor, Singer, & Dana, 2011). Kihlstrom and Laffont demonstrated in their proposed model that even though all individuals have similar entrepreneurial abilities, those who are more risk averse choose wage employment as opposed to their less risk averse counterparts, who choose entrepreneurship (1979). It is, therefore, not surprising that those who have a more positive attitude toward risk taking are more likely to develop entrepreneurial intention (Douglas & Shepherd, 2002).   Risk taking in individuals, however, depends on a given situation and context (Berg, Dickhaut, & McCabe, 2005). Risk taking varies quite dramatically over the life course of individuals. Individuals take different risks at different stages of their life course. Individuals mature and are shaped by their experiences (Elder Jr et al., 2003), and their awareness and assessments of risks are not but rather, evolve. As individuals go through life, they encounter learning experiences and adjust their understandings, develop new perspectives, acquire skills and resources, and  26  adopt new goals that can affect their risk seeking behavior. Individuals inspired to pursue independent forms of employment might ‘test the waters’ and begin to develop a taste for risk taking, e.g., because short-term returns might outweigh concerns for (and attention to) long-term outcomes (e.g., due to favoring exploitation over exploration, as well as post-decision mechanisms, etc. (Harrison & March, 1984; James G. March, 1991)).   Individuals evolve over their life course, and so do their perceptions about their own risk seeking behavior. Shifts in risk seeking perceptions can affect decisions about self-employment. Entrepreneurship is a risky behavior, and unlike wage-based employment, there is no guarantee that expected future income will materialize due, to the unpredictability of market outcomes (Carter, 2011). For these reasons, one should expect that individuals will be more likely to take up opportunity self-employment in risk-seeking periods of their life than in risk-avoiding periods.   H1: When individuals perceive themselves as more risk-seeking, they are more likely to take up opportunity entrepreneurship.  3.2 Opportunity Entrepreneurship and Barrier to Entry Individuals evolve into entrepreneurs in a social and economic context that can facilitate startups, but it can also present barriers. Those equipped with resources that are a better match for their situation, are more likely to overcome such barriers. For example, a longitudinal study of Canadian immigrants reveals that human capital may play a more important role for certain types of immigrants who are categorized as economic immigrants as opposed to other types of immigrants such as family immigrants and refugees (Roth, Seidel, Ma, & Lo, 2012). Similarly,  27  entrepreneurship in certain situations may require various resources such as access to human and financial capital.   Contexts with high barriers to entry can pose challenges for individuals who consider taking up self-employment. Barriers to entry can vary considerably. A look at World Bank indices suggests that barriers to entrepreneurship vary across nations, reflecting differences in their governance and institutional infrastructure. For example, comparing the United States and Germany (two members of G7 with large economies), I find rankings suggesting that barriers to entry are higher in Germany than in the United States. According to World Bank indices, the ease of doing business is significantly higher in the US (rank of 4) than in Germany (rank of 21), suggesting that startups in Germany might face a more challenging context (World-Bank, 2014a). Also, the strength of legal rights of lenders and borrowers is stronger in the US than in Germany, which implies that the US laws better facilitate access to credit: 9 versus 7 with a higher score indicating higher strength of legal rights (World-Bank, 2014b).   In a context with a relatively high barrier to entrepreneurship, those with access to higher resource levels are more likely to enter self-employment because they have greater means to overcome these barriers. Moreover, higher resource levels can induce “slack search” (Cyert & March, 1963; Greve, 2003; Levinthal & March, 1981; March, Olsen, Christensen, & Cohen, 1976; Nohria & Gulati, 1996), and produce solutions that can overcome entry barriers. In a context characterized by relatively high barriers to entrepreneurship, access to higher resource levels should make it easier to take up self-employment. In terms of human capital theory, access to resources is a form of human capital (Becker, 1962) that improves the chances of individuals  28  overcoming the barriers to entering into self-employment (whereas individuals with low levels of human capital might be deterred and/or fail quickly). Previous studies have shown that human capital such as education influences an individual's decision to become an entrepreneur and how they perform as one (Van Praag & Cramer, 2001). Likewise, the financial resources of individuals and their families can allow individuals to escape financial constraints (Carter, 2011; Fletcher, 2004; Kan & Tsai, 2006; Reynolds et al., 2005) and allow them to leave dependent employment behind to pursue their entrepreneurial passions. Therefore, I argue that in a context with high barriers to entrepreneurship, one should expect that individuals will be more likely to take up self-employment during time periods in their life when they have access to more resources compared to time periods with fewer resources.   H2: In a context with a relatively high barrier to entrepreneurship, individuals are more likely to enter opportunity self-employment when they have more resources available.  29  Chapter 4: Psychological Wellbeing—Life Satisfaction  In this chapter, I will explore my research questions with regards to psychological wellbeing—i.e., how does the business involvement of family members affect their psychological wellbeing, specifically their life satisfaction? When a family member takes up opportunity entrepreneurship, they set the stage for an unfolding process that affects the roles other members can play. The unfolding process can lead to different forms and degrees of business involvement of members and can interact in powerful ways with family roles to affect member’s psychological welfare.  Life Satisfaction which is related to positive emotions (Kuppens, Realo, & Diener, 2008) is important for both families and businesses. Its absence can contribute to dysfunctional families and have negative impact for the success and functioning of the business. Bearing in mind the importance of entrepreneurship and family business’ economic power and social implications of family ties in our society, understanding how business affects family members' life satisfaction is an essential question which I strive to address in this chapter.   Entrepreneurship can offer family members living in the same household opportunities, but it can also put a burden on them. Self-employment of a member can have positive and negative externalities for other family members and affect their life satisfaction. This magnitude of this effect could be dependent on roles family members assume in their households. In households, household work can be divided among family members in a number of ways. Two common ways of this division of labor within a household are relative resources and gender perspectives  (Bianchi, Milkie, Sayer, & Robinson, 2000). Relative resources perspective theorizes that the  30  division of labor is a function of relative power dynamic among family members which is mostly based on their income. Those family members who can bring more money to the family have higher negotiation power to assume less household work. On the contrary, the gender perspective argues that compared to husbands, wives assume more household work responsibilities to fulfill their gender role ideologies (Brines, 1994). In this and next chapters, I look at family roles through relative power perspective in which the roles of family members are defined by the positions they occupy in their household. Therefore, the experience and effect of entrepreneurship on a family member identified as a head of household could potentially be different from those of family members in different roles. For these reasons, in the following sections, I argue that the effect of entrepreneurship is moderated by family roles and I explore in detail how different forms of business involvement combine with family roles to affect life satisfaction of members.   4.1 Opportunity Entrepreneurship and Entrepreneur's Life Satisfaction The effect of opportunity entrepreneurship on life satisfaction is likely to be related to the reasons why individuals enter into entrepreneurship. In the previous chapter I have argued that risk seeking can induce entrepreneurship. Prior research finds that risk seekers often have a higher need for autonomy (Cromie, 2000). They are motivated not only by the economic returns, but also by the autonomy that self-employment grants to them (Halaby, 2003b). Entrepreneurs, compared to other professions, enjoy a higher level of autonomy (Schjoedt, 2009), and thus one would expect that when individuals take up self-employment, they will experience a higher level of life satisfaction because their autonomy needs are met.    31  The positive link between entrepreneurship and life satisfaction finds also support in related research on the effects of entrepreneurship and autonomy on job satisfaction. A recent study on entrepreneurship in 23 countries found that entrepreneurs are noticeably more satisfied with their work than their peers (Benz & Frey, 2008). The main reasons for the elevated job satisfaction in those studies were that the jobs were more interesting and offered greater autonomy. Research in this line finds that higher level of autonomy, flexibility, and skill utilization in entrepreneurs leads to a higher job satisfaction (Hundley, 2001).   Opportunity entrepreneurship will probably not only increase job-satisfaction but also the life satisfaction of individuals. Prior research finds a positive relationship between job satisfaction and life satisfaction (Judge & Watanabe, 1993), and it finds that the relationship is stronger for self-employed individuals because of higher emotional, physical and financial investment in their jobs (Thompson, Kopelman, & Schriesheim, 1992). One should thus expect that life satisfaction is closely related to job satisfaction of entrepreneurs. Extending this line, I argue that those family members, who voluntarily take up self-employment, can derive a broad range of psychological returns from their work that extends to other domains of their life and contributes positively to their general life satisfaction. Supporting this link, a study based on British Household Panel Survey (BHPS) showed that the life satisfaction of respondents increased for up to two years after they took up opportunity entrepreneurship (defined as moving from regular employment into self-employment) (Binder & Coad, 2013). Thus, we should expect that opportunity entrepreneurship has a positive effect on life satisfaction (i.e., its baseline will be elevated in time periods in which the individual is an opportunity entrepreneur).  H3a: There is a positive effect of opportunity entrepreneurship on the entrepreneur's life satisfaction.   32  The positive effect of opportunity entrepreneurship on life satisfaction can be significantly moderated by one's family role as well as the business roles other play. For example, there is a higher likelihood for the business involvement of an entrepreneur to clash with family chores and child-rearing if it is assumed by the partner of a head of household instead of a head of household (i.e. compared to the head of household, when someone who identifies themselves as the partner in a household becomes an entrepreneur, they are more likely to face more complicated work-life conflict). The head of household is often expected to be the breadwinner of the family and spending long hours at work is consistent with her family role. When the partner starts up a business, though work life conflicts can arise, and her entrepreneurship can clash with home obligations (Burke, FitzRoy, & Nolan, 2002).  H3b: The positive effect of opportunity entrepreneurship on the entrepreneur's life satisfaction is moderated by family roles.  4.2 Opportunity Entrepreneurship and Other Family Member's Life Satisfaction The career choice of one family member becoming an entrepreneur can have powerful (and often unintended) positive and negative externalities for other members. The mere presence of an opportunity entrepreneur in the household can expose others to experiences that are misaligned with their preferences and thereby can impact their life satisfaction. The self-selection of family members into self-employment is a main source of misaligned experiences and this can affect all family members, whether directly involved in the business or not.   The self-selection of risk-takers into entrepreneurship establishes a fundamental imbalance between family members. Risk-seeking members are drawn into risky self-employment while  33  risk-averse members are taken along on an adventure that frightens them and exposes them to uncertainty and turbulence. The rest of the family might feel obligated to support and get involved in forms of interaction and transaction that they are not comfortable with. They might experience the business as an emotional rollercoaster through high and low economic times, with the risk-taking self-employed family member being on the driver seat. The discomfort in dealing with uncertainties of running a business without having the motive or control over it, in turn, may diminish the life satisfaction of those with lower risk preferences. It is possible that this effect is stronger during the early years of a business while it struggles with liability of newness (Freeman, Carroll, & Hannan, 1983).  The self-selection of others into entrepreneurship can also produce burdensome obligations on others. Often, family members regard the family business not only as a career choice of their loved ones which they need to support, but also as an investment for the entire family. They often feel obligated to contribute to the business in informal ways (Dyer & Handler, 1994). Although the “familiness” of family businesses and “forbearance” by members can contribute significantly to distinctive family business resources, capabilities, and competitive advantage (Arregle et al., 2007; Pearson, Carr, & Shaw, 2008), it often has severe drawbacks for individual members of a family.   H4a: The presence of opportunity entrepreneurship in a household has a negative effect on other family members' life satisfaction.  The burden is, however, likely to be experienced differently by family members depending on their family roles. For example, the burden may be not felt as strongly for a child compared to  34  those of a partner or head of household as children are usually excluded from the conversations about financial planning for family and the business. Comparing the partner to the head of household, I argue that the burden is stronger for a partner as the success of a business initiated by a head of household is more critical for the wellbeing of the family given the role of the head of household is associated with being the provide for the family. On the contrary, if someone who is the partner in the family becomes self-employed, the business outcomes are not as critical to the family and the business risk do not pose a serious threat to the financial wellbeing of the family.   H4b: The negative effect of opportunity entrepreneurship on other family members' life satisfaction, is moderated by family roles.   4.3 Working in the Family Business and Family Business Employee/Helper’s Life Satisfaction The self-selection of a family member into self-employment creates the possibility that other members play a direct role in the business, e.g., as employee or helper of the family business. The availability of these roles can create tensions for family members that feel obligated to play these roles when they are not well aligned with their own career plans and aspirations. While working or helping in the family business can be a great match in some situations, in many instances it imposes a burden on those who take on a business role out of obligation (Sharma & Irving, 2005).   When a family member takes up entrepreneurship, he/she makes family business roles available to other members..The availability of business roles creates the possibility for others to get  35  involved and to heed family obligations and support the family business. Past findings indicate that many of small firms rely on families of owners to take part in the business and actively assume work related responsibilities (Poutziouris & Chittenden, 1996). Members feel obligated to sacrifice their career interests for the wellbeing of the family business. Tensions can arise because not everyone in the family shares the enthusiasm of becoming involved in the business (Stewart, 2003). Individual life aspirations can clash with the business and present a persistent source of dissatisfaction. "Uncomfortable tension between a woman’s personal desires and the family project of the business" (Baines & Wheelock, 1998, p. 589) can erode life satisfaction of a wife working in her husband's business.   H5a: There is a negative effect of family business employee/helper on their life satisfaction.  The extent to which the business involvement of individual members (as employees or helpers of the family business) burdens these members is likely to depend on their family role and the business role of others in the family. Among family roles, I argue that, in order to be consistent with their roles, partners are more likely to play a supportive business role and might feel pressured to join their family business, and, as a result, experience diminished life satisfaction. For children, the moderation might be positive; they might enjoy working in their family firms as they might be exposed to more unique working experiences compared to dependent employment for strangers (Houshmand, Seidel, & Ma, 2014).   H5b: The negative effect of family business employee/helper on their life satisfaction is moderated by family roles.    36  4.4 Whole-Family Involvement in the Family Business and Member Life Satisfaction The involvement of a large proportion of family members in the family business can produce a tightening web of business and family roles and thereby shape the life satisfaction of family members. The proportion of family members involved in the family business reflects the degree to which the (cohabiting) family is involved in the business. It is a family-level characteristic, and it can change as the family evolves and members enter and exit family and business roles. At the high end, is the case of full involvement – perhaps a winery where family members spend a large amount of time at the family business. At the low end, only one family member is involved in his/her business – e.g., an engineer might have his own consulting business, and the rest of the family is not involved in it.  The intensity of involvement reflects the degree of "businessness" of the family, and it can affect individual members (that is, a cross-level effect from family level to family member level). As family involvement increases, work related problems often become conversational topics at dinner tables and family gathering are spent discussing work issues, engulfing family deeper into the business and creating a total institution. Likewise, family-related problems can intrude into the business, produce inferior decisions, and stress for family members working together.   Family involvement can negatively affect life satisfaction of members. When family members work and live together, they experience a complicated work life conflict, and prior research suggests that experiencing work life conflict is directly linked to lower life satisfaction (Ernst Kossek & Ozeki, 1998). Likewise, a high family involvement can produce a form of  “total institution”. Total institution refers to integration of life activities such as sleep, play and work under one set of authority (Goffman, 1961). As the businessness of a family increases, it  37  increasingly determines every aspect of their lives. Living such constrained and heavily controlled lives is associated with dissatisfaction and depression.  On high levels of family involvement, role strain and role multiplexity can negatively affect life satisfaction. Working and living together makes the roles that members play more intricate because members struggle to simultaneously fulfill the different (and potentially divergent) role demands from the family and the business. In many family business, husband and wife assume the roles of entrepreneur and family business employee, in other cases, a mother might run a business and employ her children formally or informally as family business helpers. In all family businesses it is important to manage the obligations both at home and work spheres, and this can produce role strain as a consequence of the increase in number of roles (Goode, 1960) and this can produce conflicts between members (Dyer & Handler, 1994) and between the different roles they play (Harvey & Evans, 1994).  Role multiplexity refers to individuals occupying different roles in different settings and the overlapping of network between two settings produce a unique effect different from each role (Ashforth et al., 2000; Dyer, 2003). It can lead to ambiguous role boundaries and can create problems and difficult dilemmas for members. For example, an entrepreneur might have fatherly sentiments towards his son working for him, and might be more lenient about his recent poor performance. A mother might become over protective of her daughter because she is working long hours in her father's business. The role multiplexity among family members and business colleagues makes role boundaries more ambiguous. This can provide flexibility and accommodate diverse and shifting conditions arising in the business and family (Ashforth et al.,  38  2000). But at the same time, the ambiguity of role boundaries can be a source of confusion (Kaslow & Kaslow, 1992). For example a father might face the choice of playing a father role of being supportive to his son or the owner role of doing what is good for the business. In this case, playing a business role in the family business becomes a very different work experience because there is no clear distinction between work and home.   If others are involved in the business, the role multiplexity at work and home and role strain are likely to intensify and create tensions and depress life satisfaction. Tensions experiences at work cannot be left at work and are instead brought into the family home life. The traditional role of the family to buffer role strain experienced at work (Goode, 1960) is drastically diminished, perhaps even reversed for business families. The multiplexity and role strain of family members can, therefore, produce confusion and intensify stress that affect other family members. Thus, I  would expect that family involvement in the business will negatively impact life satisfaction of family members.   H6a: There is a negative effect of the business involvement of family as a whole on focal member's life satisfaction.  However, the impact is different depending on one's own involvement in the family business. The involvement in the business can create a faultline. Faultline refers to any division based issue to create majority and minority groups (Lau & Murnighan, 2005). As the intensity of family members involved in the business increases, the businessness of a family intensifies and the family actively engages in the business. Participating in the business becomes a norm and  39  those who do not adhere to this norm – and stay out of the business – may be regarded as having inferior status in the family. Therefore, I expect to see that business involvement of a family member moderating the relationship between the intensity of family members involved in the business on one's life satisfaction.   H6b: The negative effect of the business involvement of family as a whole on focal member's life satisfaction is moderated by their business roles.     40  Chapter 5: Financial Wellbeing—Income  In this chapter, I will explore my research questions with regards to family financial wellbeing—i.e., how does the business involvement of family members affect their financial wellbeing, specifically their income? And how does the family role moderate this relationship?  I am interested in the impact of family members' business involvement on their own and other's income as entrepreneurial households have different financial behaviors than non-entrepreneurial households. I will focus my attention on individual income as a form of financial wellbeing of a family member. In particular, I theorize about how the business roles coupled with family roles affect change of income for members of a family.    5.1 Opportunity Entrepreneurship and Entrepreneur's Income Analyzing the underlying motives and processes that lead to voluntarily self-employment can help us to understand the effect of self-employment on entrepreneur's income. Hamilton (2000), in his study about entrepreneurship pay, found that self-employed individuals have both lower initial earnings and lower earnings growth compared to paid employment. He attributed the differences between the two groups to "non-pecuniary benefits" self-employed individuals are willing to gain in exchange for sacrificing the earnings they could have earned, had they offered their labor in the paid employment market. An important source of these non financial benefits include the autonomy that self-employed actors enjoy at work (Hamilton, 2000).     41  Conversely, other studies since then have challenged this finding and illuminated that entrepreneurship pay is rather a complex story. Hamilton's study has been criticized because the study design was based on cross-sectional data (Manso, 2013) and because the heterogeneity that exists among entrepreneurs can produce different outcomes. For example, a recent study shows that those who incorporate their business earn more than their salaried counterparts, in comparison to those who do not incorporate their business (Levine & Rubinstein, 2013). Consistent with this line of argument, I theorize that the effect of self-employment on entrepreneur's income is closely linked to motivation behind entrepreneurship as well as the contextual factors such as barriers to entrepreneurship and cultural factors that potentially alter entrepreneurial activities.   The motivation behind opportunity entrepreneurship is to exploit a perceived market opportunity. These individuals also have a higher growth aspirations in terms of how fast they want their company to grow compared to their counterparts who are pushed into entrepreneurship. For example, Global Entrepreneurship Monitor findings suggest that 14% of opportunity entrepreneurs inspired to create more than 20 jobs as opposed to 2% of necessity entrepreneurs who had such expectations (Reynolds et al., 2002). Such aspirations likely stem from the confidence these entrepreneurs have in their success.     On the other hand, in a context with a higher barrier to entrepreneurship, it is more difficult for individuals to become entrepreneurs. To overcome the higher barriers to entry, entrepreneurs, therefore, need to be more competent and resourceful. In that light, it is not too surprising that in Germany with relatively a higher barrier to entry, a recent study of self-employed individuals in  42  the year 2000 found that self-employed men on average had higher earnings than their counterparts in paid employment (Constant & Shachmurove, 2006).   Cultural factors also contribute to entrepreneurship pay. In a more relatively risk averse culture, individuals are more likely to engage in entrepreneurship if they can earn a premium for the risk they take. The risk averse culture coupled with the higher barrier to entrepreneurship prompts entrepreneurs to seek and expect an earnings premium (Kanbur, 1982) in their pursuit of self-employment. Risky and unworthy businesses are avoided by entrepreneurs, and instead, they tend to start businesses with more carefully developed business plans, often in protected niches, and with secured access to resources. Furthermore given the voluntary aspect of opportunity entrepreneurship, it is not surprising to expect those who leave their regular employment to seize a market opportunity earn higher income. Previous studies using GSOEP dataset have indicated that those who voluntarily become an entrepreneur earn higher than their counterparts who are pushed into entrepreneurship (Block & Wagner, 2006). As a result, I expect that in this type of context, opportunity entrepreneurship has a positive baseline effect on the income of self-employed individuals.  H7a: In a context characterized by a relatively high barrier to entrepreneurship and risk averse culture, there is a positive effect of opportunity entrepreneurship on the entrepreneur's income.  The effect of opportunity entrepreneurship on income is moderated by the family roles these entrepreneurs play. Prior studies suggest that there is a difference between male and female entrepreneurs (Burke et al., 2002). This difference can perhaps be rooted in their orientation toward gender role ideology and more specifically toward the "provider role" that make male and  43  female respond differently towards job opportunities (Bielby & Bielby, 1992). Although in this dissertation, I do not differentiate between men and women, I theorize about different roles individuals play in their households and make a distinction between the head of household and the partner.  The underlying assumption, here, is that there is a higher likelihood of the head of household to be playing the role of the provider. Consequently, there is a higher pressure on the head of household to be successful in her entrepreneurial venture compared to those of the partner or child, as being in the role of the head of household creates the expectation of being the "breadwinner" of the family. I also argue that the role of head of household usually is associated with taking on financial related responsibilities that are valuable and transferable skills in managing one's own business. The family financial management is a good preparation for an entrepreneur before embarking on supervising business financials. Taking all this into account, I anticipate to see that the positive effect of self-employment on income to be the strongest for those who are in the role of the head of the household.  H7b: The effect of opportunity entrepreneurship on the entrepreneur's income is moderated by household roles.   5.2 Opportunity Entrepreneurship and Other Family Members' Income The choice of a family member to become self-employed influences the rest of the family. Members are drawn into the business irrespective of their formal business roles. Entrepreneurs discuss their business challenges with their family and in many instances ask for their advice or expect that they support or help in the business. Entrepreneurs can even derive economic benefits  44  from accessing their spouse's knowledge resources or human capital (Wong, 1986). Not only can the self-employed individual financially benefit from the family, the presence of a business connected to the family can also affect financial wellbeing of the other family members.    Being part of an entrepreneurial family alters the economical behavior of family members who live with their self-employed relative. For example, prior findings suggest that entrepreneurial households have a higher incentive to save money due to their interest in reducing future external liabilities and mitigating market risks (Gentry & Hubbard, 2004). Not only do entrepreneurial families tend to save more money, but the risky nature of running a business can also  prompt other family members to balance the situation by taking a more (financially) conservative approach towards their own career.   Family members often take an altruistic approach in an attempt to minimize the business risk through their own income contributions. Altruism is “a unique role in family firms that is not generally found in other enterprises” (Dyer, 2003, p. 408). In situations where the business is perceived to be exposed to relatively high risk—for instance in the initial stages of the business (Freeman et al., 1983), family members of an entrepreneur may pursue financially rewarding positions outside the family business with the aim of offsetting the initial costs and the risks of running a business.   H8a: There is a positive effect of opportunity entrepreneurship on other family members' income.  The effect of self-employment on other family members' income is likely moderated by the family roles that each member plays in a household. In case the new business faces a high risk, a  45  partner (wife) is, for instance, more likely to directly align her professional career outcomes to balance her husband's business results whereas the head of household could afford to be a mere observer in his partner's entrepreneurial activities (due to his/her independent income).   H8b: The positive effect of opportunity entrepreneurship on other family members' income, is moderated by household roles.   5.3 Working in the Family Business and Family Business Employee's Income When individuals take up self-employment, they have to grow their business, and they need to bring additional human capital to their company. One way is to offer business roles to their family members as family business employee. In hiring their own family members into their business, they face the dilemma of determining how they should be compensated. On one hand, they may have to deal with the "free rider" problem where family members are given positions based on their ties rather than their merits (Stewart, 2003). This might be more prevalent in relatively richer and larger family business firms where dynastic succession passes the business to the next generation through blood ties instead of meritocracy (de Lima, 2000; Stewart, 2003). A positive income effect can also arise when family members demand a risk premium for working in the family business (which is relatively more risky than regular dependent employment for outside companies).   However it is more likely that negative income effects arise for members working in the family business. Entrepreneurs often frame their business as a "family business" to signify its role in benefiting all family members through its success. Family members, in return, are expected to be supportive of the family business and to contribute to its success (E. J. Miller & Rice, 1988) and  46  the overall family financial wellbeing. Members are often obliged to sacrifice their individual careers and earnings for the good of the family business. They are obliged to maximize family utilities rather than their personal ones. "Family members were valued as employees because they could be trusted and because they worked from obligation and may not even demand to be fully rewarded for all their work" (Baines & Wheelock, 1998, p. 591). Viewing the family business firm as an economic asset for the family, previous findings suggest that family members, mostly female family members, are willing to contribute to the business with little or zero financial compensation (Ram, 1994; Ram & Holliday, 1993). Therefore, I expect to see that on average there is a negative effect of working in a family business on one's income.  H9a: There is a negative effect of family business worker on their income.  The negative effect of working in one's family business on income can be influenced by the family role these family business employees have in their households. Their family role likely plays a part in income negotiation with the business owner. For example, a head of household working for his family business still needs to pay the bills at home and probably demands a higher financial return for his labor than someone in the role of partner or child who is not required to be the main provider in a household.   In some situations, women are more susceptible of exchanging their labor in family business at a lower economic return (Chiu, 1998) as the nature of involvement for women in the business is often different than for men (Dick & Morgan, 1987). Even though women contribute significantly to their family firms, their contributions are usually not well recognized (Ram,  47  2001), and underpaid. Therefore, I suspect that the negative relationship between working in family business and income to be moderated by household roles.   H9b: The negative effect of family business worker on their income is moderated by household roles.   5.4 Whole-Family Involvement in the Family Business and Their Income When a member takes on the role of self-employment, other family members "sacrifice certainty and regularity in household income" (Carter, 2011, p. 47). This increase in uncertainty is more salient for those business families in which more than one member is involved in the family business. While family business firms have advantage over non family members due to personal relationships among members and the existing trust that reduce the transaction cost in a business transaction (Pollak, 1985), the altruism and loyalty towards the family (Baines & Wheelock, 1998), decrease the likelihood of family members negotiating higher income for themselves. In these cases, the business evolves into the dominant provider of revenue for the entire family (E. J. Miller & Rice, 1988) and family members may feel obliged to forgo their direct profits for the betterment of their family. Whole family involvement in the business can produce intense pressures on members to conform and to sacrifice their own career plans and outside employment opportunities. Moreover, giving family members important positions in the family business can interfere with the needs of the business to select the best fitting employees from the labor market. As a result, family business performance can suffer, and this can affect its ability to pay family members adequate income.    48  H10a: There is a negative effect of the business involvement of family as a whole on focal member's income.  The willingness and capacity of family members to accept lower wages from their employment in the family business is likely to be affected by the business roles they play. For instance, as the businessness of the family increases, it will be more difficult for family business workers to bargain for a higher wage. Family members are more likely to view the business as a family asset and personal financial gains take a secondary priority.   H10b: The negative effect of the business involvement of family as a whole on focal member's income is moderated by business roles.  49  Chapter 6: Methods   6.1 Data and Sample Overview I empirically test the proposed hypotheses using the rich longitudinal data from the German Socio-Economic Panel Study (GSOEP). GSOEP is a household panel study that has been collected annually since 1984 to capture micro-data on person, households and families that were selected randomly from randomly selected regions in Germany. While the sample initially included only households from West Germany, starting in 1990 the sample broadened its reach to also include Eastern Germany. I have chosen this dataset for both its richness in terms of content and the context it provides. Due to institutional and cultural factors, Germany can be characterized as a context with relatively high barriers to entrepreneurship (Klapper, Laeven, & Rajan, 2006) and a risk averse culture (Hall & Hall, 1990).   The surveys were conducted using face-to-face interviews for the majority of the participants. For those who had been part of the panel multiple times, the data was collected through self-administered questionnaires (Gerstorf et al., 2008). All members of a selected household who were 17 years and older participated in this study. The response rates for GSOEP have been relatively high–between 60% to 70%, with a relatively low attrition rate across years (4% to 14% annually). The overall demographics captured in the panel data are representative of the broader population of Germany’s private households (Haisken-De New & Frick, 2006).    For the current study, I plan to use all of the data accessible to me from 1984-2011. Due to attrition and the addition of participants, the number of observations fluctuated between panel  50  waves, starting in 1984 with 11,654 participants, reaching a peak of 23,332 in the year 2000, and finishing with 20,046 individuals in 2011. By merging over all panel waves, my final sample includes observations of 41,348 individuals (the number of records in the “wide-format” data set). Because individuals participated in numerous panel waves, the number of time point observations (i.e., the number of records in the “long-format” data set) was 325,219 person years in total.   6.2 SOEP Subsamples SOEP started in 1984, targeting German households in West Germany. 5,975 households participated in the survey with 1,393 households having a head of household with Turkish, Italian, Spanish, Greek or Yugoslavian background. In 1990, the survey was expanded to East Germany to include an additional 2,179 households. In 1994/1995, 522 households were added that had a head of household who had immigrated to Germany after 1984. In the years 1998, 2000 and 2006 the survey inserted fresh samples consisting of a random sample of the total population that respectively integrated 1,067, 6,052 and 1,506 households into the survey. In 2002, the survey aimed to include high income households, which resulted in an additional 1,224 households with a monthly net household income exceeding 4,500 Euros. From 5,975 households and 11,654 participants in 1984, SOEP has grown to 11,695 households and 20,046 individuals in 2011.   6.3 Survey Participants SOEP analysts have strongly encouraged all members of the household aged 17 years and older to take part in the survey. They track these individuals even after they move out of the initial  51  households. New individuals can enter the survey through moving into a SOEP survey participating household, when they reach the age of 17 in the household, or through living with someone who moved out of a participating household. Individuals exit the survey through death or by moving abroad.   6.4 Survey Types Every year, all members of a household above the age of 17 fill in an individual questionnaire that asks respondents a wide range of questions from their life situation to their current employment status. Every head of a household also fills in a household form requesting information on the household, with the majority of the questions concerning the financial activities of a household—from mortgage-related questions to total household income and saving. There are additional forms that participants fill in only once during their involvement in SOEP—for example, when the child of a household is 2 or 3 years of age.   6.5 Data Files  I have gained access to SOEP data through communication with SOEP Research Data Center at Cornell University and by applying for access through my advisor, Dr. Martin Schulz. I have received a CD containing all data files and other relevant information. Initially, the CD contained only information from 1984 to 2009. Subsequently, we received a CD containing data files from 1984 to 2011, which are used in the analysis.   There is a set of files associated with each survey year, and I have processed them and transformed them into data structures that facilitate my analysis. For most of the variables, I have  52  used the information from the panel surveys and consolidated all the personal information across years. Some information, such as the household roles, have been extracted from data files provided by the SOEP centre and merged with other data files to build the master file.  For the analysis, I have converted the master file from wide format (one way of describing data in which the information belonging to each individual is presented in only one row) to long format (each individual appears in multiple rows corresponding to the number of years being interviewed) to trace individuals across years and to study how individuals change over time. For the parameter estimation, I have used the long file to model how changing characteristics of individuals (including the households they live in and their family business involvement) affect their financial and psychological outcomes. I use fixed-effects models in order to focus my analysis on the causal processes operating within the individual.   6.6 Statistical Software  I have done most of the coding for cleaning and preparing the final master data file in SAS, which includes thousands of lines of codes. The SAS programs extract the variables of interests and produce all the necessary information in the master file. For the estimation of the parameters, I have used fixed effects models both in SAS and STATA. The tables presented in this document are mostly generated with STATA.   6.7 Variables  6.7.1 Dependent Variables  To empirically test my hypotheses, I focus on three dependent variables—opportunity entrepreneurship status in a given year, life satisfaction, and individual income. In the following  53  section, I explain each of them in detail and describe how I operationalize each variable using the data files.  Opportunity Entrepreneurship Status:  I used two steps to capture the opportunity entrepreneurship status. First, I identified self-employed individuals, and second, I examined how they became self-employed. The following paragraphs describe these steps in more depth.     The personal survey asks every respondent annually about his/her current occupational status. Self-employment is one of the options to choose from. Within the self-employment categories, respondents have to choose whether they are farmers, independent freelancers or another type of self-employment.  I have created a dummy variable to capture the self-employment status of the respondents; it is set to "1" in years in which the respondent is self-employed, and “0” otherwise. I did not include farmers in this variable because of the distinct nature of agriculture (Astrachan & Shanker, 2003; Dumas, Dupuis, Richer, & St.-Cyr, 1995; Steier, 2001). Farmers are not typical for my core construct of opportunity entrepreneurship, and thus the self-employment dummy is set to “0” for them. (I have run a robustness check that excludes farmers from the sample and run the analysis. The results demonstrate similar pattern presented in this dissertation. I have left farmers in the final sample to boost the overall observations and having a complete representation of the full population).   Finally, following prior panel research on opportunity entrepreneurship (Block & Wagner, 2006), I operationalized opportunity entrepreneurship based on the way an individual becomes self-employed. The survey asks individuals each year whether their job was terminated in the previous year and if so, how it was terminated. Those individuals who indicated that they had  54  quit their jobs voluntarily (or left their jobs based on mutual agreement with their employers) prior to becoming self-employed are categorized as opportunity entrepreneurs. I take the voluntary transition from regular employment into self-employment as an indicator of opportunity seizing. These entrepreneurs have voluntarily become self-employed, while they gave up a regular job (dependent employment). I assign opportunity entrepreneurship status to all consecutive years for these individuals, until they exit self-employment. This means that the path into self-employment determines the opportunity entrepreneurship status of the entire self-employment spell of a given individual.   In summary, for an individual to be considered an opportunity entrepreneur, she must have declared herself as self-employed (and not be a farmer). Furthermore, the year before becoming self-employed she must have held a regular job and quit her job or left the job on mutual agreements with her employer before embarking on entrepreneurship. Please see Table 1 for the frequency table of the opportunity entrepreneurship status. The data starts from 1985 because I have access to the 1984 information and can identify those who were regularly employed in 1984 and switched to self-employment in 1985. The data suggest that opportunity entrepreneurship is a comparatively rare state of affairs in the life of most individuals – between 0.1 and 1 percent of the individuals observed in a given year are self-employed in opportunity entrepreneurship.   Table 1: Frequency Table of Opportunity Entrepreneurship Status (Wide Format) Years Number of Observations Frequency Of Opportunity Entrepreneurship  Mean Variance  Min Max 1984 . . . . . . 1985                                10,503                15  0.001428 0.001426 0 1 1986                                10,101                27  0.002673 0.002666 0 1 1987                                 9,970                35  0.003511 0.003499 0 1  55  Years Number of Observations Frequency Of Opportunity Entrepreneurship  Mean Variance  Min Max 1988                                 9,509                40  0.004207 0.004189 0 1 1989                                 9,195                38  0.004133 0.004116 0 1 1990                                13,245                51  0.003851 0.003836 0 1 1991                                12,941                83  0.006414 0.006373 0 1 1992                                12,676                91  0.007179 0.007128 0 1 1993                                12,475              116  0.009299 0.009213 0 1 1994                                12,697              121  0.00953 0.00944 0 1 1995                                13,031              119  0.009132 0.009049 0 1 1996                                12,779              121  0.009469 0.00938 0 1 1997                                12,560              120  0.009554 0.009464 0 1 1998                                13,882              127  0.009149 0.009066 0 1 1999                                13,367              137  0.010249 0.010145 0 1 2000                                23,332              163  0.006986 0.006938 0 1 2001                                21,206              162  0.007639 0.007581 0 1 2002                                22,670              191  0.008425 0.008355 0 1 2003                                21,436              190  0.008864 0.008785 0 1 2004                                20,914              185  0.008846 0.008768 0 1 2005                                20,035              156  0.007786 0.007726 0 1 2006                                21,477              168  0.007822 0.007762 0 1 2007                                20,146              178  0.008836 0.008758 0 1 2008                                18,940              164  0.008659 0.008584 0 1 2009                                19,969              151  0.007562 0.007505 0 1 2010                                18,157              143  0.007876 0.007814 0 1 2011                                20,270              136  0.006709 0.006665 0 1   Life Satisfaction: The personal survey annually asks respondents about their life satisfaction using a one-item measure. The question asks participants to answer “Wie zufrieden sind Sie gegenwartig, alles in allem, mit ihrem Leben?” (“How satisfied are you with your life, all things considered?”) on a scale of 0 to 10 (totally unsatisfied to totally satisfied). Please see Table 2 for the frequency table.     56  Table 2: Frequency Table of Life Satisfaction (Wide Format) Years Number of Observations Mean Variance  Min Max 1984 11557 7.421476 4.5728617 0 10 1985                                10,463  7.232534 4.1784788 0 10 1986                                10,067  7.286481 3.7490354 0 10 1987                                 9,936  7.133454 3.8281872 0 10 1988                                 9,469  7.082374 3.8362641 0 10 1989                                 9,165  7.100491 3.7425194 0 10 1990                                 8,978  7.269771 3.2956016 0 10 1991                                12,812  6.945442 3.623516 0 10 1992                                12,592  6.915661 3.3151006 0 10 1993                                12,413  6.882543 3.5674144 0 10 1994                                12,628  6.862845 3.3859544 0 10 1995                                12,969  6.89606 3.3534769 0 10 1996                                12,757  6.904993 3.1799037 0 10 1997                                12,537  6.794847 3.1965816 0 10 1998                                13,847  6.955586 3.1517901 0 10 1999                                13,337  6.973757 3.1902231 0 10 2000                                23,266  7.089616 3.1743886 0 10 2001                                21,156  7.104179 3.0339112 0 10 2002                                22,624  7.045306 3.0477196 0 10 2003                                21,395  6.967095 3.1557836 0 10 2004                                20,861  6.798715 3.3327807 0 10 2005                                19,972  6.946225 3.3720017 0 10 2006                                21,110  6.916011 3.2331275 0 10 2007                                19,771  6.944464 3.1821458 0 10 2008                                18,647  6.981927 3.089934 0 10 2009                                19,687  6.983593 3.150955 0 10 2010                                17,913  7.110702 3.0651786 0 10 2011                                17,548  7.019205 3.011713 0 10  Individual Income: Among the set of files for each year, there is a file provided by SOEP Research Center that contains generated individual variables derived from personal surveys. It contains basic information on each individual including their overall labor earning. The overall labor earning refers to all earnings from all employment plus earnings from bonuses, overtime and profit sharing. The advantage of using this generated variable is that the values across all years use the same currency, the Euro. This makes it easier to conduct comparison across waves,  57  even though they are not inflation adjusted. Please see Table 3 for the frequency table of income rounded up to nearest 100.   As seen in the table, the maximum income fluctuates over years. Some of the fluctuation is due to the fact the many higher earners in the sample are self-employed and depending on how well their business does, their earnings fluctuate. The three repeated high numbers (€1,199,988) which are rounded up in the table as €1,200,000 are associated with four individuals with one of them having the same income over two years. All of these four individuals have entered the survey as self-employed. However, while their income fluctuates over time, none of these individuals at any point become opportunity entrepreneurs because they do not engage in paid employment prior embarking on self-employment. Therefore, their high income is not part of the income pool of opportunity entrepreneurs. As part of the robustness check, I have rerun additional analysis by excluding those observations whose reported income is higher than €1,150,000 which resulted in removing six observations in total. The outcomes are consistent with other findings presented in Chapter 7.   Table 3: Frequency Table of Income (Wide Format)  Years Number of Observations Mean Variance  Min  Max  1984                                11,610          9,809  1.59E+08 0          283,300  1985                                10,503        10,061  2.07E+08 0          526,600  1986                                10,101        10,311  1.75E+08 0          457,900  1987                                 9,970        10,744  1.62E+08 0          204,300  1988                                 9,509        11,097  1.71E+08 0          186,500  1989                                 9,195        11,655  2.00E+08 0          276,100  1990                                 9,016        12,323  2.62E+08 0          451,900  1991                                 8,950        12,880  2.38E+08 0          296,500  1992                                12,676        12,121  1.93E+08 0          272,000  1993                                12,475        12,941  2.31E+08 0          377,800  1994                                12,697        13,480  2.45E+08 0          260,800   58  Years Number of Observations Mean Variance  Min  Max  1995                                13,031        13,599  2.61E+08 0          390,100  1996                                12,779        14,219  2.77E+08 0          306,800  1997                                12,560        14,277  2.91E+08 0          351,000  1998                                13,882        14,372  3.41E+08 0          613,500  1999                                13,367        14,738  3.36E+08 0          493,900  2000                                23,332        15,266  3.99E+08 0          499,800  2001                                21,206        15,406  4.07E+08 0          429,500  2002                                22,670        19,096  1.02E+09 0       1,200,000  2003                                21,436        18,677  7.73E+08 0          540,000  2004                                20,914        18,254  7.47E+08 0          720,000  2005                                20,035        18,023  6.84E+08 0          525,400  2006                                21,477        17,818  8.90E+08 0       1,200,000  2007                                20,146        18,011  8.47E+08 0       1,200,000  2008                                18,940        18,143  7.65E+08 0          900,000  2009                                19,969        18,673  9.79E+08 0       1,152,000  2010                                18,157        18,541  7.83E+08 0          720,000  2011                                20,270        18,275  9.49E+08 0       1,920,000    6.7.2 Independent Variables  Risk Seeking Attitude: In the years 2004, 2006 and 2008, 2009, 2010 and 2011, the survey asks respondents to rate their general willingness to take risks. The questions states: "Are you generally a person who is fully prepared to take risks or do you try to avoid taking risks?" with 0 indicating "risk averse" and 10 "fully prepared to take risks."   Higher Access to Resource Levels: In order to determine higher access to resource levels, I use two measures—years of education and household income. The combination of these variables is reflective of individuals with higher access to resource levels whether through their own human and financial capital or the financial capital available to them through their family.    59  Opportunity Entrepreneurship Status:  In order to test the hypotheses in Chapter 4 and 5, I use the opportunity entrepreneurship status variable as an independent variable rather than a dependent variable in these models. I have described this variable in detail in the dependent variable section. Please refer to section 6.7.1 for more information.   Working for a Family Business: Using the occupational status question in the personal survey, I have identified those who work in the family business of another household member. The question explicitly provides "family member working for self-employed relative" as one of the options. Those who have selected this option are assigned "1" on the dummy variable "family business employee."   Helping in a Family Business: I have, further, created a dummy variable to capture those who help in their family business. The variable is based on the information taken from the following question: "It is possible to work in addition to regular employment, household work, education and also as a pensioner. Do you engage in any of the following activities?" There are four possible answers: 1) work in family business, 2) regularly paid secondary employment, 3) occasional paid work, and 4) no, none of these. Those who said yes to the option of "work in family business" receive a value of "1" on the dummy variable of helping in their family business.  A Family Member in Household is Opportunity Entrepreneur: I have developed the SAS code that assigns household characteristics to individuals who live in the same household. In this case, those who live with an opportunity entrepreneur in the same household receive a value of "1" on  60  the dummy variable “living with an opportunity entrepreneur.” This dummy variable is measured regardless of the focal actor's business role.   Family-level Involvement in the Business: This variable captures the proportion as well as the intensity of the involvement of a household in the family business. I use two constructs to explore this idea. One is based on the proportion of people involved, and the other on the proportion of available work hours invested (i.e. intensity). I have calculated the proportion of members involved in the family business by calculating the number of people formally involved in the business divided by the number of people from the household who have participated in the survey. To capture the intensity, on the other hand, I have calculated the average number of hours spent in a family business either by the entrepreneur or family business employees compared to the total working hours spent by all household members who have participated in the survey. To ensure that these numbers are not driven by the focal actor's number of working hours, I have included, for the models including this variable, both the linear and non-linear effects of the focal actor's number of work hours as control variables.   Household Roles: SOEP provides files that contain basic information about individuals and how different members of a household are related to one another. Every household has someone who identifies herself/himself as the head of household. Heads of households are responsible to answer additional survey questions that concern the household as a whole. The SOEP data allow me to reconstruct how the people living in the same household relate to the head of household, and to determine what their own position is. I have used these files to categorize individuals into  61  five household member types —head of household, partner, child, extended relative (including parents, in-laws, grandchildren, etc.) and non-relative.     6.7.3 Control variables I control for a number of time-variant attributes that could influence opportunity entrepreneurship, individual life satisfaction, and individual income. Specifically, I control for the number of children (Angeles, 2010) and household size to capture how the change in the size of the household impact life satisfaction of family members. Household income and the region of Germany (East versus West) to which individuals move are other important factors (Frijters, Haisken-DeNew, & Shields, 2004).   Children at different age interact differently with their parents (MacDonald & Parke, 1986). This interaction might, in turn, affect their parents' life satisfaction. Therefore, I have created three dummies to capture the presence of children in each of the following categories—new born to 4 years old, 5 to 12 years old, and 13 to 18 years old.  I also control for the employment status of individuals. Besides being directly related to income, employment is a powerful source of meaning and resources for individuals, and I would expect it to have a positive effect on life satisfaction and the opposite effect in cases of its absence. At the same time, controlling for the employment status of individuals provides a powerful contrast to the opportunity entrepreneurship effect while it reveals its true effect. All individuals are categorized into four different career statuses—opportunity entrepreneur, family business employee, regular employee and not employed.  In the analysis, I have chosen regular  62  employment as the reference category and have included unemployment status as part of the control variables.    I have also controlled for macro variables such as unemployment rates per German Bundesland (state) (Gustafsson & Johansson, 1999). To account for historical shifts of contextual factors (such as the unification of Germany and its joining to the European Union) (Fujita & Diener, 2005), I have included a year dummy for each year. Including year dummies accounts for annual variables such as age of respondent and annual GDP.  Please see Table 4 for the frequency tables of variables of interest in the long format.  Table 4: The Frequency Tables of Variables in the Long Format        VARIABLES N Mean SD Min Max       Wave 1985 325,219 0.0279 0.165 0 1 Wave 1986 325,219 0.0269 0.162 0 1 Wave 1987 325,219 0.0265 0.161 0 1 Wave 1988 325,219 0.0251 0.156 0 1 Wave 1989 325,219 0.0242 0.154 0 1 Wave 1990 325,219 0.0235 0.152 0 1 Wave 1991 325,219 0.0230 0.150 0 1 Wave 1992 325,219 0.0327 0.178 0 1 Wave 1993 325,219 0.0319 0.176 0 1 Wave 1994 325,219 0.0326 0.178 0 1 Wave 1995 325,219 0.0335 0.180 0 1 Wave 1996 325,219 0.0325 0.177 0 1 Wave 1997 325,219 0.0315 0.175 0 1 Wave 1998 325,219 0.0333 0.179 0 1 Wave 1999 325,219 0.0326 0.178 0 1 Wave 2000 325,219 0.0561 0.230 0 1 Wave 2001 325,219 0.0506 0.219 0 1 Wave 2002 325,219 0.0540 0.226 0 1 Wave 2003 325,219 0.0507 0.219 0 1 Wave 2004 325,219 0.0491 0.216 0 1 Wave 2005 325,219 0.0461 0.210 0 1 Wave 2006 325,219 0.0482 0.214 0 1  63        VARIABLES N Mean SD Min Max       Wave 2007 325,219 0.0453 0.208 0 1 Wave 2008 325,219 0.0423 0.201 0 1 Wave 2009 325,219 0.0436 0.204 0 1 Wave 2010 325,219 0.0397 0.195 0 1 Wave 2011 325,219 0.0365 0.187 0 1 Opportunity entrep 325,219 0.00777 0.0878 0 1 Working in business 325,219 0.00321 0.0566 0 1 Regular employment  325,219 0.630 0.483 0 1 Unemployment status 325,219 0.359 0.480 0 1 Helping in business 325,219 0.0109 0.104 0 1 Helper living wth entrp 325,219 0.000664 0.0258 0 1 Worker living wth entrp 325,219 0.000268 0.0164 0 1 Living with entrep 325,219 0.00997 0.0994 0 1 Life Satisfaction  325,219 7.058 1.777 0 10 Others' life satisfaction  325,219 7.071 1.657 0 10 #People household 325,219 3.148 1.232 2 17 #Children household 325,219 0.667 0.980 0 10 Child in HH (0-4 yrs) 325,219 0.119 0.324 0 1 Child in HH (5-12yrs) 325,219 0.213 0.409 0 1 Child in HH (13-18yrs) 325,219 0.198 0.398 0 1 East 325,219 0.212 0.409 0 1 Years of education 325,219 11.60 2.623 7 18 Head of household 325,219 0.442 0.497 0 1 Partner 325,219 0.412 0.492 0 1 Child 325,219 0.130 0.337 0 1 Extended relative 325,219 0.0124 0.111 0 1 Non-relative 325,219 0.00301 0.0548 0 1 Unemployment rate 325,219 10.51 4.382 3.7 22.10 Income (log) 325,219 6.510 4.615 0 14.00 Others' income (log) 325,219 6.836 4.142 0 14.00 Household income (log) 325,219 8.900 3.816 0 14.03       Number of persons 41,347 41,347 41,347 41,347 41,347   6.7.4 Additional Descriptive Analysis   Given the importance of opportunity entrepreneurship in my models, I have run a number of cross-tabulation analyses with relevant variables. Table 5 shows the cross tabulation between  64  opportunity entrepreneurship and life satisfaction. Opportunity entrepreneurship takes the possible values of 0 or 1 whereas life satisfaction ranges from 0-10. Table 6 describes the gender distribution across opportunity entrepreneurship. As expected, the majority of the entrepreneurs are men.   Table 5: The Cross-Tabulation between Opportunity Entrepreneurship and Life Satisfaction       Opportunity Entrepreneurship  0 Opportunity Entrepreneurship  1  Freq Freq Life Satisfaction (Percent) (Percent)    0 1,333 3  (0.413) (0.119) 1 1,257 6  (0.390) (0.237) 2 3,597 22  (1.115) (0.871) 3 7,757 55  (2.404) (2.176) 4 10,832 76  (3.357) (3.008) 5 37,750 253  (11.70) (10.01) 6 35,633 303  (11.04) (11.99) 7 70,433 591  (21.83) (23.39) 8 98,390 847  (30.49) (33.52) 9 37,478 292  (11.61) (11.56) 10 18,232 79  (5.650) (3.126)    Number of persons 41,347 41,347 Total 322,692 2,527    65  Table 6: The Cross-Tabulation between Opportunity Entrepreneurship and Life Satisfaction    Opportunity Entrepreneurship  0 Opportunity Entrepreneurship  1  Freq Freq Gender (Percent) (Percent)    Female 160,604 665  (49.77) (26.32) Male 162,088 1,862  (50.23) (73.68)    Number of persons 41,347 41,347 Total 322,692 2,527   6.8 Models I model the transition into self employment as an opportunity entrepreneur with fixed-effect logit models. The fixed-effect logit model can be described as: P(Yit=1)=exp(β'X𝑖𝑖𝑖𝑖+𝑣𝑣𝑖𝑖+ε𝑖𝑖𝑖𝑖 )1+exp(β'X𝑖𝑖𝑖𝑖+𝑣𝑣𝑖𝑖+ε𝑖𝑖𝑖𝑖 ) where P(Yit=1) stands for the probability that in an individual (i) becomes an opportunity entrepreneur at time (t). X𝑖𝑖𝑖𝑖  a vector of time-varying covariates, which are updated at the beginning of each year. 𝑣𝑣𝑖𝑖+ε𝑖𝑖𝑖𝑖  represents time-invariant and time-variant errors. Unlike random effects, 𝑣𝑣𝑖𝑖  is allowed to correlate with X𝑖𝑖𝑖𝑖  and since the model estimates within effects, the time-invariant error becomes removed. The estimation uses a form of maximum likelihood, and I thus use likelihood maximum improvement test to assess model fit (Allison, 2005).   Similarly, I model changes in individual life satisfaction and income with fixed-effects linear models. The model can be described as: Yit=X𝑖𝑖𝑖𝑖+ε𝑖𝑖𝑖𝑖   66  where Yit is the predicted variable (life satisfaction or income) of individual (i) in a given year (t) and Xit is a vector of time-varying covariates (which are updated at the beginning of each year), and ε𝑖𝑖𝑖𝑖  is the time variant error term for each individual in a given year. The fixed effects is the individual (i). I also use clustering to accommodate heteroscedasticity and autocorrelation (within individual) over the panels, and report standard errors that are adjusted accordingly. The estimation is essentially OLS, and thus I can use partial F tests to assess model fit and improvement of fit.    67  Chapter 7: Results  Investigating general wellbeing such as life satisfaction has been a challenging endeavor in literature due to the effect of unobserved heterogeneity (Clark, Etilé, Postel-Vinay, Senik, & Straeten, 2005). An important part of my empirical design involves controlling for such unobserved heterogeneity inherent in individuals. I control for unobservable individual attributes by using individual level fixed effects. The use of fixed-effects allows me to account for all the time-invariant individual characteristics that influence an individual to become an entrepreneur and the implications it has on one's life satisfaction and income. In contrast to random effects, fixed effects does not detect variations across individuals but instead captures the variations of covariates and dependent variables within persons to account for all the time-invariant unobserved heterogeneity (Frees, 2004).  To make findings more robust, I have also included cluster-robust estimation which produces more conservative results (Petersen, 2009). The parameter estimates are identical; however, applying cluster-robust estimation method yields larger standard errors. The reported significance levels are more conservative and robust.   The purpose of this chapter is to report the results of the fixed-effects analyses. Each section is dedicated to presenting the analysis findings for each dependent variable in relation with numerous independent variables of interest. At the end of the chapter, I provide a summary of results.  68  7.1 Becoming an Opportunity Entrepreneur   In the first part of my theoretical framework, I connect the transition of family members into entrepreneurship to their risk seeking attitudes and their access to resources. Because the dependent variable is a binary variable, I use logit models to analyze the likelihood of individuals becoming an opportunity entrepreneur.   Table 7 displays fixed effects logit models that explore how risk seeking attitudes and access to resources influence the likelihood of individuals to become self-employed.  Model 1 includes all the control variables. Only data from 2005, 2007, 2009, 2010 and 2011 are included because the risk seeking attitude which reflects a lagged varible was only measured in 2004, 2006, 2008, 2009, 2010 and 2011. The year 2011 is excluded from the model because it is used as the reference category. Additionally, since I am running fixed effect analysis, only those individuals who experience a change in their opportunity entrepreneurship status are kept. These two reasons have led to noticeably fewer observations used in the analysis.  Model 2 adds the first independent variable of interest—risk seeking attitude from the previous year. The estimated parameter (0.14, P<0.05) suggests that those who experience a positive change in their risk seeking attitude are more likely to seek opportunity entrepreneurship. This evidence lends supports for H1 which states that when individuals perceive themselves as more risk seeking, they are more likely to take up opportunity entrepreneurship.   Model 3 and 4 explore the effects of two different measures of access to resources—household income from the previous year and years of education. While a positive change in household  69  income in the last year has a significant positive effect on the likelihood of someone to becoming an opportunity entrepreneur, years of education does not play a significant role. These results partially support H2 and suggests that in a context with a relatively high barrier to entrepreneurship, individuals are more likely to enter opportunity self-employment in situations where they have access to higher financial resources.  Table 7: Effects of Risk Seeking Attitude and Access to Resources on Becoming an Opportunity Entrepreneur      VARIABLES Model 1 Model 2 Model 3 Model 4      wave   2005 -2.469** -2.453** -2.556** -2.561**  (0.677) (0.687) (0.710) (0.710) wave   2007 -0.801* -0.926* -1.024** -1.031**  (0.362) (0.375) (0.385) (0.386) wave   2009 -0.549+ -0.595+ -0.601+ -0.598+  (0.313) (0.317) (0.328) (0.328) wave   2010 -0.328 -0.361 -0.407 -0.409  (0.295) (0.301) (0.309) (0.309) east -2.433 -2.572 -2.455 -2.448  (1.552) (1.617) (1.619) (1.620) child in HH (0-4 yrs) -1.181** -1.137** -1.116** -1.116**  (0.408) (0.415) (0.432) (0.432) child in HH (5-12yrs) 0.818* 0.557 0.549 0.549  (0.382) (0.401) (0.416) (0.416) child in HH (13-18yrs) 0.502 0.389 0.407 0.401  (0.354) (0.368) (0.372) (0.372) unemployment/state 0.259* 0.233+ 0.243+ 0.242+  (0.121) (0.122) (0.126) (0.126) risk seeking(t-1)  0.140* 0.138* 0.138*   (0.062) (0.064) (0.064) household income(t-1)   0.825** 0.825**    (0.232) (0.232) years of education    -0.105     (0.376)      Observations 586 554 554 554 Number of persons 139 131 131 131 ll -198.856 -187.314 -178.616 -178.575 chi2 50.5353 48.2929 65.6894 65.7709  70       VARIABLES Model 1 Model 2 Model 3 Model 4      df_m 9 10 11 12  7.2 Life Satisfaction  This section presents the findings of models that take life satisfaction as the dependent variable. The following subsections follow the flow of ideas in the theoretical chapter on life satisfaction (Chapter 4). I look at each hypothesis separately in these sub-sections and present the results in the same order.   The Effect of Opportunity Entrepreneurship on the Entrepreneur: This section is related to H3a and H3b which postulate a positive effect of self-employment on the entrepreneur's life satisfaction and a moderation by household roles. The following table, Table 8, presents the analysis findings for the effect of opportunity entrepreneurship on the entrepreneur.   Model 1 includes all the relevant control variables, in particular the year dummies, number of people in the household, number of children in the household, the log of household income from previous year, region(west/east), the presence of children at various ages, log of individual income from previous year, years of education, unemployment status, unemployment rate in the state in which the household resides, and the average life satisfaction of other family members in the household. Evidently, the number of people living in the household has a negative effect on life satisfaction while the number of children has a positive effect on life satisfaction. Household income and region do not have any significant effect. The presence of a young child has a positive effect on life satisfaction, while the number of years of education has a negative effect.  71  The unemployment rate has a negative effect on life satisfaction. Finally, there is a strong emotional contagion effect among family members as the average life satisfaction of others have a positive and significant effect on individual life satisfaction.  Model 2 includes the opportunity entrepreneurship status. The findings reveal that being an opportunity entrepreneur has a significant and positive effect on the life satisfaction of individuals. The effect is within individual, that is, compared to his/her life as a regular dependent employee, he/she experiences higher levels of life satisfaction while he/she is an opportunity entrepreneur. My findings suggest that, compared to regular employment, on average, individuals are happier when they voluntarily leave their job in the labor market to become an entrepreneur. Overall, the results provide support for H3a which states that there is a positive effect of self-employment on the entrepreneur's life satisfaction.  Next, in models 3 and 4, I examine the moderating effect of household roles on the positive relationship between opportunity entrepreneurship and life satisfaction. The reference category is partner. Therefore, all other household roles are compared to the role of partner. None of the interaction terms except for extended relative is significant. Compared to household partner, extended relatives feel less happy when they are the entrepreneur in the household. It could indicate that patriarchs of the family derive less joy from running the business than other members of the nuclear family would. However, the significance level is marginal. Moreover, the lack of findings for other roles suggest that the moderating effects of household roles are relatively weak. H3b thus finds insufficient statistical support.  Finally, in model 5, I explore whether gender drives any potential effect, and the interaction between gender and opportunity  72  entrepreneurship is not significant which implies women and men are not different in terms of experiencing life satisfaction from being self-employed.   Table 8: The Effect of Opportunity Entrepreneurship on Life Satisfaction of Focal Individual       VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.680** 0.682** 0.668** 0.668** 0.682**  (0.028) (0.028) (0.029) (0.029) (0.028) wave   1986 0.672** 0.675** 0.661** 0.662** 0.675**  (0.027) (0.027) (0.027) (0.027) (0.027) wave   1987 0.562** 0.564** 0.551** 0.551** 0.564**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1988 0.495** 0.497** 0.485** 0.485** 0.497**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1989 0.472** 0.474** 0.462** 0.462** 0.474**  (0.025) (0.025) (0.026) (0.026) (0.025) wave   1990 0.554** 0.556** 0.544** 0.544** 0.556**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1991 0.580** 0.582** 0.571** 0.571** 0.582**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1992 0.418** 0.420** 0.410** 0.411** 0.420**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1993 0.405** 0.407** 0.398** 0.398** 0.407**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1994 0.377** 0.378** 0.370** 0.370** 0.378**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1995 0.382** 0.383** 0.375** 0.376** 0.383**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1996 0.382** 0.383** 0.376** 0.376** 0.383**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1997 0.318** 0.319** 0.312** 0.313** 0.319**  (0.025) (0.025) (0.025) (0.025) (0.025) wave   1998 0.376** 0.377** 0.371** 0.372** 0.377**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1999 0.376** 0.377** 0.371** 0.372** 0.377**  (0.022) (0.022) (0.023) (0.023) (0.022) wave   2000 0.353** 0.354** 0.350** 0.350** 0.354**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2001 0.348** 0.349** 0.345** 0.345** 0.349**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2002 0.233** 0.234** 0.230** 0.230** 0.234**  (0.019) (0.019) (0.019) (0.019) (0.019)  73        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   2003 0.192** 0.192** 0.189** 0.189** 0.192**  (0.020) (0.020) (0.021) (0.021) (0.020) wave   2004 0.080** 0.080** 0.078** 0.078** 0.080**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2005 0.173** 0.174** 0.172** 0.172** 0.174**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   2006 0.117** 0.118** 0.116** 0.116** 0.118**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2007 0.078** 0.078** 0.077** 0.077** 0.078**  (0.017) (0.017) (0.017) (0.017) (0.017) wave   2008 0.084** 0.084** 0.083** 0.083** 0.084**  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2009 0.019 0.020 0.019 0.019 0.020  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2010 0.088** 0.088** 0.087** 0.087** 0.088**  (0.015) (0.015) (0.015) (0.015) (0.015) #people household -0.045** -0.045** -0.051** -0.051** -0.045**  (0.006) (0.006) (0.007) (0.007) (0.006) #children household 0.042** 0.042** 0.046** 0.046** 0.042**  (0.010) (0.010) (0.010) (0.010) (0.010) household income(t-1) 0.001 0.001 0.001 0.001 0.001  (0.002) (0.002) (0.002) (0.002) (0.002) east -0.047 -0.046 -0.053 -0.052 -0.046  (0.061) (0.061) (0.061) (0.061) (0.061) child in HH (0-4 yrs) 0.030* 0.030* 0.036** 0.036** 0.030*  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (5-12yrs) 0.027+ 0.026+ 0.028* 0.028* 0.026+  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (13-18yrs) 0.014 0.014 0.012 0.012 0.014  (0.012) (0.012) (0.012) (0.012) (0.012) individual income(t-1) 0.009** 0.009** 0.010** 0.010** 0.009**  (0.002) (0.002) (0.002) (0.002) (0.002) years of education -0.015** -0.015** -0.012* -0.012* -0.015**  (0.005) (0.005) (0.005) (0.005) (0.005) unemployment status 0.008 0.008 0.008 0.008 0.008  (0.018) (0.018) (0.018) (0.018) (0.018) unemployment/state -0.019** -0.019** -0.019** -0.019** -0.019**  (0.003) (0.003) (0.003) (0.003) (0.003) avg others life sat 0.359** 0.359** 0.360** 0.360** 0.359**  (0.003) (0.003) (0.003) (0.003) (0.003) opportunity entrep  0.171** 0.174** 0.168+ 0.139   (0.053) (0.053) (0.090) (0.091) head of household   -0.045 -0.045   74        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5          (0.036) (0.036)  child   0.024 0.025     (0.043) (0.043)  extended relative    -0.075 -0.072     (0.081) (0.081)  non-relative    -0.208* -0.205*     (0.099) (0.099)  opp*head     0.026      (0.112)  opp*child    -0.037      (0.312)  opp*extended relative     -2.222+      (1.254)  opp*non_relative    -0.449      (0.608)  opp*gender     0.044      (0.112) Constant 4.631** 4.632** 4.635** 4.635** 4.632**  (0.073) (0.073) (0.076) (0.076) (0.073)       Observations 325,219 325,219 325,219 325,219 325,219 R-squared 0.136 0.137 0.137 0.137 0.137 Number of persons 41,347 41,347 41,347 41,347 41,347 F(improvement of fit)  23.2606 7.21523 3.46743 0.30254 degree freedom diff  1 4 4 1 p(improvement of fit)  1.4200e-06 8.3500e-06 7.7236e-03 0.58229  The Effect of Living with an Opportunity Entrepreneur on Other Family Members: Living with an opportunity entrepreneur may have implications for other household members. In this section, I test  H4a and H4b which postulate that the presence of opportunity entrepreneurship in a household should have a negative effect on other family member's life satisfaction, and this negative relationship should be moderated by household roles. Table 7 presents the findings for fixed effect analyses predicting individual life satisfaction.   75  Similarly as before, Model 1 includes only control variables. In this model, I also included the opportunity entrepreneurship status of the focal individual, and thus subsequent models are net of this effect. This helps me to focus my analysis on the effect of the presence of an entrepreneur in the household, net of the self-employment status of the focal individual. Model 2 adds the dummy variable of living with an opportunity entrepreneur in the household in a given year. The results suggest that those who live with someone who is self-employed will experience a reduction of their life satisfaction. The significant p value of the improvement of fit further suggests that Model 2 is a more comprehensive and statistically better fit model than Model 1. The presence of an opportunity entrepreneur in the household matters. In sum, these findings support H4a.  Model 3 and 4 add household roles and their interactions with the presence of an opportunity entrepreneur. The interactions are not significant and thereby do not support the hypothesis that the negative relationship between living with someone in the household who is opportunity entrepreneur is moderated by household roles. H4b is thus not supported. Further, I find no support that the mentioned relationship is moderated by gender.   Table 9: The Effect of Living with an Opportunity Entrepreneur on Focal Family Members' Life Satisfaction        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.682** 0.681** 0.667** 0.667** 0.681**  (0.028) (0.028) (0.029) (0.029) (0.028) wave   1986 0.675** 0.674** 0.660** 0.660** 0.674**  (0.027) (0.027) (0.027) (0.027) (0.027) wave   1987 0.564** 0.563** 0.550** 0.550** 0.563**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1988 0.497** 0.496** 0.484** 0.484** 0.496**  76        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.026) (0.026) (0.027) (0.027) (0.026) wave   1989 0.474** 0.473** 0.461** 0.461** 0.473**  (0.025) (0.025) (0.026) (0.026) (0.025) wave   1990 0.556** 0.555** 0.544** 0.544** 0.555**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1991 0.582** 0.581** 0.571** 0.571** 0.581**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1992 0.420** 0.419** 0.410** 0.410** 0.419**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1993 0.407** 0.406** 0.397** 0.397** 0.406**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1994 0.378** 0.378** 0.370** 0.370** 0.378**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1995 0.383** 0.383** 0.375** 0.375** 0.383**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1996 0.383** 0.383** 0.376** 0.375** 0.383**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1997 0.319** 0.319** 0.312** 0.312** 0.318**  (0.025) (0.025) (0.025) (0.025) (0.025) wave   1998 0.377** 0.377** 0.371** 0.371** 0.377**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1999 0.377** 0.377** 0.371** 0.371** 0.377**  (0.022) (0.022) (0.023) (0.023) (0.022) wave   2000 0.354** 0.354** 0.349** 0.349** 0.354**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2001 0.349** 0.349** 0.345** 0.345** 0.349**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2002 0.234** 0.234** 0.230** 0.230** 0.234**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2003 0.192** 0.192** 0.189** 0.189** 0.192**  (0.020) (0.020) (0.021) (0.020) (0.020) wave   2004 0.080** 0.080** 0.078** 0.078** 0.080**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2005 0.174** 0.174** 0.172** 0.172** 0.174**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   2006 0.118** 0.118** 0.116** 0.116** 0.118**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2007 0.078** 0.078** 0.077** 0.077** 0.078**  (0.017) (0.017) (0.017) (0.017) (0.017) wave   2008 0.084** 0.084** 0.084** 0.084** 0.084**  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2009 0.020 0.020 0.019 0.019 0.020  (0.015) (0.015) (0.015) (0.015) (0.015)  77        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   2010 0.088** 0.088** 0.087** 0.087** 0.088**  (0.015) (0.015) (0.015) (0.015) (0.015) #people household -0.045** -0.045** -0.050** -0.050** -0.045**  (0.006) (0.006) (0.007) (0.007) (0.006) #children household 0.042** 0.042** 0.046** 0.046** 0.042**  (0.010) (0.010) (0.010) (0.010) (0.010) household income(t-1) 0.001 0.001 0.001 0.001 0.001  (0.002) (0.002) (0.002) (0.002) (0.002) east -0.046 -0.046 -0.053 -0.053 -0.046  (0.061) (0.061) (0.061) (0.061) (0.061) child in HH (0-4 yrs) 0.030* 0.030* 0.036** 0.036** 0.030*  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (5-12yrs) 0.026+ 0.026+ 0.028* 0.028* 0.026+  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (13-18yrs) 0.014 0.014 0.012 0.012 0.014  (0.012) (0.012) (0.012) (0.012) (0.012) individual income(t-1) 0.009** 0.009** 0.010** 0.010** 0.009**  (0.002) (0.002) (0.002) (0.002) (0.002) years of education -0.015** -0.015** -0.012* -0.012* -0.015**  (0.005) (0.005) (0.005) (0.005) (0.005) unemployment status 0.008 0.008 0.008 0.008 0.008  (0.018) (0.018) (0.018) (0.018) (0.018) unemployment/state -0.019** -0.019** -0.019** -0.019** -0.019**  (0.003) (0.003) (0.003) (0.003) (0.003) avg others life sat 0.359** 0.359** 0.360** 0.360** 0.359**  (0.003) (0.003) (0.003) (0.003) (0.003) opportunity entrep 0.171** 0.172** 0.175** 0.175** 0.172**  (0.053) (0.053) (0.053) (0.053) (0.053) living with opp entrp  -0.093* -0.094* -0.111+ -0.134*   (0.046) (0.045) (0.068) (0.057) head of household   -0.046 -0.046     (0.036) (0.036)  child   0.023 0.022     (0.043) (0.043)  extended relative    -0.076 -0.075     (0.081) (0.081)  other   -0.208* -0.204*     (0.099) (0.099)  living*headh    0.009      (0.094)  living *child    0.126      (0.159)  living *exte_relative     -0.188   78        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5           (0.296)  living *non_relative    -0.244      (0.308)  living *gender     0.123      (0.094) Constant 4.632** 4.632** 4.636** 4.636** 4.632**  (0.073) (0.073) (0.076) (0.076) (0.073)       Observations 325,219 325,219 325,219 325,219 325,219 R-squared 0.137 0.137 0.137 0.137 0.137 Number of persons 41,347 41,347 41,347 41,347 41,347 F(improvement of fit)  8.40271 7.28392 0.74242 3.27943 degree freedom diff  1 4 4 1 p(improvement of fit)  3.7469e-03 7.3400e-06 0.56291 0.070154  The Effect of Working in the Family Business on Individuals life satisfaction: Table 10 depicts a part of the analysis results for H5a and H5b which postulate that there is a negative effect of working/helping in family business on individual life satisfaction and this relationship is moderated by household roles. Similarly as before, Model 1 includes all the control variables plus business involvement variables supported in preceding models (opportunity entrepreneurship status and living with someone who is an opportunity entrepreneur).  Model 2 adds the dummy variable indicating that the focal individual is working for the family business in a given year. As Model 2 shows, working as a dependent employee for one's family business has a significant and negative effect on one's life satisfaction. The significant p value of improvement of fit between Model 2 and Model 1 further suggests that Model 2 is, statistically, a better fitting model. These findings provide support for H5a. On the other hand, household roles and gender seem to not play a significant role in moderating the mentioned relationship. Hence, H5b is not supported.   79  I have run similar models to specifically look at those who work in their family business and also live with an opportunity entrepreneur and assess whether the results are strengthened. Please see Appendix B to see the findings. Surprisingly, the results are not significant. A possible explanation is lack of statistical power due to fewer cases of having those who work in their family business and living with their employer. I also run similar analyses for those who help in their family business and no solid support is found that helping in family business has a negative effect on life satisfaction. These results are presented in Appendix C.  Table 10: The Effect of Working in the Family Business on Life Satisfaction of Focal Individual        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.681** 0.682** 0.667** 0.668** 0.682**  (0.028) (0.028) (0.029) (0.029) (0.028) wave   1986 0.674** 0.674** 0.661** 0.661** 0.674**  (0.027) (0.027) (0.027) (0.027) (0.027) wave   1987 0.563** 0.564** 0.551** 0.551** 0.564**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1988 0.496** 0.497** 0.484** 0.484** 0.497**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1989 0.473** 0.473** 0.461** 0.461** 0.473**  (0.025) (0.025) (0.026) (0.026) (0.025) wave   1990 0.555** 0.555** 0.544** 0.544** 0.555**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1991 0.581** 0.581** 0.571** 0.571** 0.581**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1992 0.419** 0.419** 0.410** 0.410** 0.419**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1993 0.406** 0.406** 0.398** 0.398** 0.406**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1994 0.378** 0.378** 0.370** 0.370** 0.378**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1995 0.383** 0.383** 0.375** 0.375** 0.383**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1996 0.383** 0.383** 0.376** 0.376** 0.383**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1997 0.319** 0.319** 0.312** 0.312** 0.319**  (0.025) (0.025) (0.025) (0.025) (0.025)  80        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1998 0.377** 0.377** 0.371** 0.371** 0.377**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1999 0.377** 0.377** 0.371** 0.372** 0.377**  (0.022) (0.022) (0.023) (0.023) (0.022) wave   2000 0.354** 0.354** 0.350** 0.350** 0.354**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2001 0.349** 0.349** 0.345** 0.345** 0.349**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2002 0.234** 0.234** 0.230** 0.230** 0.234**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2003 0.192** 0.192** 0.189** 0.189** 0.192**  (0.020) (0.020) (0.021) (0.021) (0.020) wave   2004 0.080** 0.081** 0.078** 0.078** 0.081**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2005 0.174** 0.174** 0.172** 0.172** 0.174**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   2006 0.118** 0.118** 0.116** 0.117** 0.118**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2007 0.078** 0.079** 0.078** 0.078** 0.079**  (0.017) (0.017) (0.017) (0.017) (0.017) wave   2008 0.084** 0.084** 0.084** 0.084** 0.084**  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2009 0.020 0.020 0.019 0.019 0.020  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2010 0.088** 0.088** 0.087** 0.087** 0.088**  (0.015) (0.015) (0.015) (0.015) (0.015) #people household -0.045** -0.045** -0.050** -0.050** -0.045**  (0.006) (0.006) (0.007) (0.007) (0.006) #children household 0.042** 0.042** 0.046** 0.046** 0.042**  (0.010) (0.010) (0.010) (0.010) (0.010) household income(t-1) 0.001 0.001 0.001 0.001 0.001  (0.002) (0.002) (0.002) (0.002) (0.002) east -0.046 -0.046 -0.053 -0.053 -0.046  (0.061) (0.061) (0.061) (0.061) (0.061) child in HH (0-4 yrs) 0.030* 0.030* 0.036** 0.036** 0.030*  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (5-12yrs) 0.026+ 0.027+ 0.028* 0.028* 0.027+  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (13-18yrs) 0.014 0.014 0.012 0.012 0.014  (0.012) (0.012) (0.012) (0.012) (0.012) individual income(t-1) 0.009** 0.009** 0.009** 0.009** 0.009**  (0.002) (0.002) (0.002) (0.002) (0.002) years of education -0.015** -0.015** -0.012* -0.012* -0.015**  81        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.005) (0.005) (0.005) (0.005) (0.005) unemployment status 0.008 0.005 0.005 0.005 0.005  (0.018) (0.018) (0.018) (0.018) (0.018) unemployment/state -0.019** -0.019** -0.019** -0.019** -0.019**  (0.003) (0.003) (0.003) (0.003) (0.003) avg others life sat 0.359** 0.359** 0.360** 0.360** 0.359**  (0.003) (0.003) (0.003) (0.003) (0.003) opportunity entrep 0.172** 0.170** 0.173** 0.138 0.170**  (0.053) (0.053) (0.053) (0.091) (0.053) living with opp entrp -0.093* -0.089+ -0.090* -0.090* -0.089+  (0.046) (0.046) (0.045) (0.045) (0.046) working in fb  -0.177** -0.177** -0.220** -0.173**   (0.050) (0.050) (0.060) (0.054) head of household   -0.046 -0.047     (0.036) (0.036)  child   0.023 0.023     (0.043) (0.043)  extended relative    -0.077 -0.076     (0.081) (0.081)  other   -0.209* -0.209*     (0.099) (0.099)  employed*headh    0.172      (0.114)  employed*child    -0.026      (0.264)  employed*ext_relative     -0.304      (0.604)  employed*other    -        employed*gender     -0.015      (0.139) Constant 4.632** 4.635** 4.639** 4.639** 4.635**  (0.073) (0.073) (0.076) (0.076) (0.073)       Observations 325,219 325,219 325,219 325,219 325,219 R-squared 0.137 0.137 0.137 0.137 0.137 Number of persons 41,347 41,347 41,347 41,347 41,347 F(improvement of fit)  17.0681 7.32330 1.49835 0.021476 degree freedom diff  1 4 3 1 p(improvement of fit)  3.6100e-05 6.8200e-06 0.21273 0.88349   82  The Effect of Whole-Family Business Involvement: Table 11 and 12 present the findings for the effect of the degree of business involvement of the family on individual life satisfaction. The business involvement is a family-level construct, and it is measured in two ways. First, it is measured by the proportion of family members involved in the business either by being the entrepreneur or by formally working in the family business. Second, it is measured by the intensity of family members' involvement in the business by calculating the average number of hours spent in the business. In both cases, I include a second degree polynomial transform of the hours worked (per day) by the focal individual as part of the control variables (to eliminate spurious effects of individual-level burnout etc). I did not include the dummy variable indicating the presence of an opportunity entrepreneur in these models because it overlaps with the family involvement variables.  Table 11 shows the effect of the family-level involvement, in terms of the proportion of family members involved in the business, on the focal member's life satisfaction. Model 1 includes all the control variables in addition to whether a family member is the opportunity entrepreneur or a dependent employee of the family business. Model 2 adds the proportion of members involved. The estimates indicate that the proportion of members involved in the business has a significant and negative effect on individual life satisfaction. H6a is thus supported. In model 3 I explore whether the effect of family involvement is moderated by the focal actor's business involvement, but I find no significant effect, nor is the improvement of fit significant. Therefore, H6b is not supported in this analysis.     83  Table 11: The Effect of Proportion of Family Members Involved in the Family Business on Life Satisfaction of Focal Individual      VARIABLES Model 1 Model 2 Model 3     wave   1985 0.673** 0.672** 0.671**  (0.029) (0.029) (0.029) wave   1986 0.666** 0.665** 0.665**  (0.027) (0.027) (0.027) wave   1987 0.555** 0.554** 0.554**  (0.026) (0.026) (0.026) wave   1988 0.489** 0.488** 0.488**  (0.026) (0.026) (0.026) wave   1989 0.465** 0.465** 0.464**  (0.025) (0.025) (0.025) wave   1990 0.548** 0.547** 0.547**  (0.024) (0.024) (0.024) wave   1991 0.574** 0.573** 0.573**  (0.023) (0.023) (0.023) wave   1992 0.411** 0.411** 0.411**  (0.021) (0.021) (0.021) wave   1993 0.400** 0.399** 0.399**  (0.022) (0.022) (0.022) wave   1994 0.372** 0.372** 0.371**  (0.022) (0.022) (0.022) wave   1995 0.377** 0.377** 0.377**  (0.021) (0.021) (0.021) wave   1996 0.377** 0.377** 0.377**  (0.023) (0.023) (0.023) wave   1997 0.313** 0.313** 0.313**  (0.025) (0.025) (0.025) wave   1998 0.372** 0.372** 0.372**  (0.024) (0.024) (0.024) wave   1999 0.372** 0.372** 0.372**  (0.022) (0.022) (0.022) wave   2000 0.352** 0.352** 0.352**  (0.019) (0.019) (0.019) wave   2001 0.347** 0.347** 0.347**  (0.019) (0.019) (0.019) wave   2002 0.232** 0.232** 0.232**  (0.019) (0.019) (0.019) wave   2003 0.190** 0.190** 0.190**  (0.020) (0.020) (0.020) wave   2004 0.079** 0.079** 0.079**  (0.021) (0.021) (0.021) wave   2005 0.173** 0.173** 0.173**  84      VARIABLES Model 1 Model 2 Model 3      (0.024) (0.024) (0.024) wave   2006 0.117** 0.117** 0.117**  (0.021) (0.021) (0.021) wave   2007 0.078** 0.078** 0.078**  (0.017) (0.017) (0.017) wave   2008 0.083** 0.083** 0.083**  (0.015) (0.015) (0.015) wave   2009 0.019 0.019 0.019  (0.015) (0.015) (0.015) wave   2010 0.087** 0.087** 0.087**  (0.015) (0.015) (0.015) #people household -0.045** -0.045** -0.045**  (0.006) (0.006) (0.006) #children household 0.043** 0.044** 0.043**  (0.010) (0.010) (0.010) household income(t-1) 0.001 0.001 0.001  (0.002) (0.002) (0.002) east -0.045 -0.045 -0.046  (0.061) (0.061) (0.061) child in HH (0-4 yrs) 0.034* 0.034* 0.034*  (0.014) (0.014) (0.014) child in HH (5-12yrs) 0.027* 0.027* 0.027*  (0.014) (0.014) (0.014) child in HH (13-18yrs) 0.013 0.013 0.013  (0.012) (0.012) (0.012) individual income(t-1) 0.006** 0.006** 0.006**  (0.002) (0.002) (0.002) hours work/day 0.039** 0.039** 0.039**  (0.006) (0.006) (0.006) hours work/day (sqr) -0.003** -0.003** -0.003**  (0.001) (0.001) (0.001) years of education -0.017** -0.017** -0.017**  (0.005) (0.005) (0.005) unemployment status 0.067** 0.067** 0.066**  (0.020) (0.020) (0.020) unemployment/state -0.019** -0.019** -0.019**  (0.003) (0.003) (0.003) avg others life sat 0.359** 0.359** 0.359**  (0.003) (0.003) (0.003) opportunity entrep 0.172** 0.265** 0.136  (0.053) (0.070) (0.135) working in fb -0.173** -0.162** -0.164**  (0.051) (0.050) (0.051)  85      VARIABLES Model 1 Model 2 Model 3     fb involvement proportion   -0.200* -0.242*   (0.094) (0.102) opp*propfmly   0.314    (0.272) employed_propfmly   0.050    (0.252) Constant 4.596** 4.597** 4.597**  (0.073) (0.073) (0.073)     Observations 325,214 325,214 325,214 R-squared 0.137 0.137 0.137 Number of persons 41,345 41,345 41,345 F(improvement of fit)  8.82734 1.14206 degree freedom diff  1 2 p(improvement of fit)  2.9677e-03 0.31916  Table 12 presents the results of the effect of the intensity of business involvement of family members, in terms of the use of their available time, on life satisfaction. As the table shows, in Model 2, there is a marginally significant and negative effect of the time intensity of business involvement on family member's life satisfaction. Model 2 as a whole yields a significant improvement of fit compared to Model 1. These results provide further evidence for H6a. In Model 3, I explore the moderating effect of business role as the family becomes more engaged in the business. The positive coefficient implies that as the business becomes more involved, the entrepreneur derives higher life satisfaction from the situation. However, statistically the coefficient is only marginally significant and the model as a whole produces an only marginally significant improvement of fit compared to Model 2. H6b thus receives only weak support in this analysis.    86  Table 12: The Effect of Time Intensity of Business Involvement of Family on Life Satisfaction       VARIABLES Model 1 Model 2 Model 3     wave   1985 0.673** 0.672** 0.672**  (0.029) (0.029) (0.029) wave   1986 0.666** 0.665** 0.665**  (0.027) (0.027) (0.027) wave   1987 0.555** 0.554** 0.554**  (0.026) (0.026) (0.026) wave   1988 0.489** 0.489** 0.488**  (0.026) (0.026) (0.026) wave   1989 0.465** 0.465** 0.465**  (0.025) (0.025) (0.025) wave   1990 0.548** 0.547** 0.547**  (0.024) (0.024) (0.024) wave   1991 0.574** 0.573** 0.573**  (0.023) (0.023) (0.023) wave   1992 0.411** 0.411** 0.411**  (0.021) (0.021) (0.021) wave   1993 0.400** 0.399** 0.399**  (0.022) (0.022) (0.022) wave   1994 0.372** 0.372** 0.372**  (0.022) (0.022) (0.022) wave   1995 0.377** 0.377** 0.377**  (0.021) (0.021) (0.021) wave   1996 0.377** 0.378** 0.377**  (0.023) (0.023) (0.023) wave   1997 0.313** 0.313** 0.313**  (0.025) (0.025) (0.025) wave   1998 0.372** 0.372** 0.372**  (0.024) (0.024) (0.024) wave   1999 0.372** 0.372** 0.372**  (0.022) (0.022) (0.022) wave   2000 0.352** 0.352** 0.352**  (0.019) (0.019) (0.019) wave   2001 0.347** 0.347** 0.347**  (0.019) (0.019) (0.019) wave   2002 0.232** 0.232** 0.232**  (0.019) (0.019) (0.019) wave   2003 0.190** 0.190** 0.190**  (0.020) (0.020) (0.020) wave   2004 0.079** 0.079** 0.079**  (0.021) (0.021) (0.021) wave   2005 0.173** 0.173** 0.173**  (0.024) (0.024) (0.024)  87      VARIABLES Model 1 Model 2 Model 3     wave   2006 0.117** 0.117** 0.117**  (0.021) (0.021) (0.021) wave   2007 0.078** 0.078** 0.078**  (0.017) (0.017) (0.017) wave   2008 0.083** 0.083** 0.083**  (0.015) (0.015) (0.015) wave   2009 0.019 0.019 0.019  (0.015) (0.015) (0.015) wave   2010 0.087** 0.087** 0.087**  (0.015) (0.015) (0.015) #people household -0.045** -0.045** -0.045**  (0.006) (0.006) (0.006) #children household 0.043** 0.044** 0.043**  (0.010) (0.010) (0.010) household income(t-1) 0.001 0.001 0.001  (0.002) (0.002) (0.002) east -0.045 -0.046 -0.046  (0.061) (0.061) (0.061) child in HH (0-4 yrs) 0.034* 0.034* 0.034*  (0.014) (0.014) (0.014) child in HH (5-12yrs) 0.027* 0.027* 0.027*  (0.014) (0.014) (0.014) child in HH (13-18yrs) 0.013 0.013 0.013  (0.012) (0.012) (0.012) individual income(t-1) 0.006** 0.006** 0.006**  (0.002) (0.002) (0.002) hours work/day 0.039** 0.039** 0.039**  (0.006) (0.006) (0.006) hours work/day (sqr) -0.003** -0.003** -0.003**  (0.001) (0.001) (0.001) years of education -0.017** -0.017** -0.017**  (0.005) (0.005) (0.005) unemployment status 0.067** 0.067** 0.066**  (0.020) (0.020) (0.020) unemployment/state -0.019** -0.019** -0.019**  (0.003) (0.003) (0.003) avg others life sat 0.359** 0.359** 0.359**  (0.003) (0.003) (0.003) opportunity entrep 0.172** 0.238** 0.120  (0.053) (0.065) (0.089) working in fb -0.173** -0.167** -0.161**  (0.051) (0.050) (0.051) fb involvement intensity   -0.022+ -0.031*  88      VARIABLES Model 1 Model 2 Model 3       (0.013) (0.015) opp*avgfbhrs   0.048+    (0.028) employed_avgfbhrs   -0.008    (0.045) Constant 4.596** 4.597** 4.596**  (0.073) (0.073) (0.073)     Observations 325,214 325,214 325,214 R-squared 0.137 0.137 0.137 Number of persons 41,345 41,345 41,345 F(improvement of fit)  6.53210 2.58584 degree freedom diff  1 2 p(improvement of fit)  0.010595 0.075334  7.3 Income This section presents the results for the fixed effect analyses. It concerns the effect of opportunity entrepreneurship on income of the focal individual. As before, I will present the results in the same order as the income hypotheses in Chapter 5.   The Effect of Opportunity Entrepreneurship on the Entrepreneur: Table 13 presents parameter estimates of the effect of opportunity entrepreneurship on the entrepreneur's income. Model 1 includes only the control variables. As expected, weekly hours work and years of education have positive effects on individual income, while the rate of unemployment in the state (Bundesland) in a given year has a negative effect. It is interesting to note that the individual’s life satisfaction has a positive and significant effect on his/her income.   Model 2 includes the opportunity entrepreneurship status variable. The estimates suggest that being self-employed as an opportunity entrepreneur has a significant and positive effect on  89  individual  income. This provides support for the argument that those who leave regular employment voluntarily to become an opportunity entrepreneur have higher earnings. Taking into account the significant improvement of fit in going to Model 2 from Model 1, I infer that H7a is supported. As part of the sensitively analysis of my models, I also explored the effect of duration of entrepreneurship on individual income. As expected, I find that in the first couple of years, compared to later years, the income tends to be lower. Although income levels fluctuate with the duration of the business, the overall effect is positive —individuals earn higher income as opportunity entrepreneurs compared to working in regular employment.   Model 3 explores the effect of household roles on income. As anticipated, the results suggest that the head of household makes more money than partner while the child and other household roles make less money compared to partner. This empirically supports the notion that those who identify themselves as the head of household are the breadwinners of their households. It also suggests that household roles significantly affect individual income. These are main-effects, and thus in Model 4 I explore the interaction effects of opportunity entrepreneurship with household roles. Although the parameter estimates of these interaction effects are numerically not small, they are statistically not significant, nor is the improvement of fit of the model. The returns of being an opportunity entrepreneur are not systematically affected by the role the individual plays in the family. The model does not provide any support for H7b. In Model 5, I include the interactions with gender. The results suggest that there is no significant difference between men and women when it comes to how much more they make as an opportunity entrepreneur compared to regular employment.      90  Table 13: The Effect of Opportunity Entrepreneurship on Individual Income         VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.707** 0.710** 0.915** 0.915** 0.710**  (0.044) (0.044) (0.045) (0.045) (0.044) wave   1986 0.698** 0.700** 0.898** 0.898** 0.701**  (0.043) (0.043) (0.044) (0.044) (0.043) wave   1987 0.629** 0.632** 0.823** 0.823** 0.632**  (0.042) (0.042) (0.043) (0.043) (0.042) wave   1988 0.654** 0.657** 0.838** 0.838** 0.657**  (0.042) (0.042) (0.043) (0.043) (0.042) wave   1989 0.690** 0.692** 0.867** 0.867** 0.692**  (0.040) (0.040) (0.041) (0.041) (0.040) wave   1990 0.716** 0.718** 0.882** 0.883** 0.718**  (0.039) (0.039) (0.040) (0.040) (0.039) wave   1991 0.629** 0.631** 0.785** 0.785** 0.631**  (0.039) (0.039) (0.040) (0.040) (0.039) wave   1992 0.589** 0.591** 0.738** 0.739** 0.591**  (0.035) (0.036) (0.036) (0.036) (0.036) wave   1993 0.630** 0.632** 0.769** 0.769** 0.632**  (0.038) (0.038) (0.038) (0.038) (0.038) wave   1994 0.608** 0.609** 0.736** 0.736** 0.609**  (0.038) (0.038) (0.039) (0.039) (0.038) wave   1995 0.604** 0.606** 0.722** 0.722** 0.606**  (0.036) (0.036) (0.036) (0.036) (0.036) wave   1996 0.550** 0.551** 0.660** 0.660** 0.551**  (0.038) (0.038) (0.038) (0.038) (0.038) wave   1997 0.554** 0.555** 0.657** 0.657** 0.555**  (0.042) (0.042) (0.042) (0.042) (0.042) wave   1998 0.561** 0.563** 0.653** 0.653** 0.562**  (0.040) (0.040) (0.040) (0.040) (0.040) wave   1999 0.456** 0.457** 0.540** 0.540** 0.457**  (0.037) (0.037) (0.037) (0.037) (0.037) wave   2000 0.482** 0.483** 0.554** 0.554** 0.483**  (0.031) (0.031) (0.031) (0.031) (0.031) wave   2001 0.405** 0.406** 0.469** 0.469** 0.406**  (0.030) (0.030) (0.030) (0.030) (0.030) wave   2002 0.363** 0.364** 0.420** 0.420** 0.364**  (0.031) (0.031) (0.031) (0.031) (0.031) wave   2003 0.307** 0.308** 0.356** 0.356** 0.308**  (0.033) (0.033) (0.033) (0.033) (0.033) wave   2004 0.303** 0.304** 0.343** 0.343** 0.304**  (0.033) (0.033) (0.033) (0.033) (0.033) wave   2005 0.278** 0.279** 0.311** 0.311** 0.279**  (0.039) (0.039) (0.039) (0.039) (0.039)  91        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   2006 0.277** 0.278** 0.304** 0.304** 0.278**  (0.034) (0.034) (0.034) (0.034) (0.034) wave   2007 0.188** 0.188** 0.207** 0.207** 0.188**  (0.026) (0.026) (0.026) (0.026) (0.026) wave   2008 0.085** 0.085** 0.096** 0.096** 0.085**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   2009 0.019 0.020 0.027 0.027 0.020  (0.021) (0.021) (0.021) (0.021) (0.021) #people household 0.162** 0.162** 0.262** 0.262** 0.162**  (0.012) (0.012) (0.013) (0.013) (0.012) #children household -0.121** -0.121** -0.205** -0.205** -0.121**  (0.018) (0.018) (0.019) (0.019) (0.018) avg others' income(t-1) 0.031** 0.031** 0.027** 0.027** 0.031**  (0.002) (0.002) (0.002) (0.002) (0.002) east 0.034 0.035 0.120 0.120 0.035  (0.102) (0.102) (0.101) (0.101) (0.102) child in HH (0-4 yrs) -0.534** -0.534** -0.620** -0.620** -0.534**  (0.026) (0.026) (0.026) (0.027) (0.026) child in HH (5-12yrs) 0.096** 0.095** 0.069** 0.069** 0.096**  (0.024) (0.024) (0.024) (0.024) (0.024) child in HH (13-18yrs) 0.223** 0.223** 0.243** 0.243** 0.223**  (0.022) (0.022) (0.022) (0.022) (0.022) hours work/day 0.833** 0.833** 0.819** 0.819** 0.833**  (0.013) (0.013) (0.013) (0.013) (0.013) hours work/day (sqr) -0.044** -0.044** -0.043** -0.043** -0.044**  (0.001) (0.001) (0.001) (0.001) (0.001) years of education 0.215** 0.215** 0.186** 0.186** 0.215**  (0.010) (0.010) (0.010) (0.010) (0.010) unemployment status -2.427** -2.426** -2.416** -2.416** -2.426**  (0.038) (0.038) (0.038) (0.038) (0.038) unemployment/state -0.034** -0.034** -0.035** -0.035** -0.034**  (0.006) (0.006) (0.006) (0.006) (0.006) life satisfaction  0.027** 0.027** 0.026** 0.026** 0.027**  (0.004) (0.004) (0.004) (0.004) (0.004) opportunity entrep  0.188** 0.165** 0.273* 0.112   (0.063) (0.063) (0.122) (0.132) head of household   0.420** 0.421**     (0.053) (0.053)  child   -0.405** -0.404**     (0.065) (0.065)  extended relative    -0.820** -0.818**     (0.136) (0.136)  non-relative    -0.370* -0.371*   92        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5          (0.171) (0.171)  opp*head of household    -0.129      (0.142)  opp*child    -0.358      (0.251)  opp*extended relative     -1.585      (1.139)  opp*non_relative    0.042      (0.582)  opp*gender     0.108      (0.150) Constant 2.135** 2.135** 2.068** 2.067** 2.135**  (0.142) (0.142) (0.147) (0.147) (0.142)       Observations 316,828 316,828 316,828 316,828 316,828 R-squared 0.391 0.391 0.392 0.392 0.391 Number of persons 38,225 38,225 38,225 38,225 38,225 F(improvement of fit)  9.43307 234.233 0.88020 0.66306 degree freedom diff  1 4 4 1 p(improvement of fit)  2.1313e-03 0 0.47472 0.41548  The Effect of Presence of an Opportunity Entrepreneur on Other Family Members: Living with an opportunity entrepreneur may have implications on career choices and income level of other family members. Table 14 presents the fixed effect results of the effect of presence of an opportunity entrepreneur in the household on the income of the focal family member. Model 1 consists of all the control variables and includes the opportunity entrepreneurship status variable. Model 2 adds the variable of living with an opportunity entrepreneur. The results suggest that the effect of living with an opportunity entrepreneur is not significant. Therefore, H8a is not supported.     93  Models 3 and 4 include the household roles and moderation effects of household roles with living with an entrepreneur on individual income. The parameter estimates in Model 3 indicate that different household roles are associated with significantly different levels of income. Adding the interaction effects in Model 4 contributes significantly to improvement of model fit. The strongest interactions are for distal family members – extended members and non-relatives benefit financially from the presence of an opportunity entrepreneur in the household (and the effects more than compensate for the main effects of household role). In contrast, the nuclear members of the family appear to derive no significant returns in terms of income from the presence of an opportunity entrepreneur in the household. It seems that income moderation operates mainly through peripheral household roles – and produce immediate financial rewards for them, and much less (or delayed) financial rewards for the core members (head, partner, children). Therefore, I infer that H8b is only partially supported.  Finally, in Model 5, I find that gender has no significant interaction effect.  Table 14: The Effect of Living with Opportunity Entrepreneur on Focal Member's Income         VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.710** 0.710** 0.916** 0.915** 0.710**  (0.044) (0.044) (0.045) (0.045) (0.044) wave   1986 0.700** 0.701** 0.898** 0.898** 0.701**  (0.043) (0.043) (0.044) (0.044) (0.043) wave   1987 0.632** 0.632** 0.823** 0.822** 0.632**  (0.042) (0.042) (0.043) (0.043) (0.042) wave   1988 0.657** 0.657** 0.839** 0.838** 0.657**  (0.042) (0.042) (0.043) (0.043) (0.042) wave   1989 0.692** 0.693** 0.867** 0.866** 0.693**  (0.040) (0.040) (0.041) (0.041) (0.040) wave   1990 0.718** 0.718** 0.883** 0.882** 0.718**  (0.039) (0.039) (0.040) (0.040) (0.039) wave   1991 0.631** 0.631** 0.785** 0.785** 0.631**  (0.039) (0.039) (0.040) (0.040) (0.039)  94        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1992 0.591** 0.591** 0.739** 0.738** 0.591**  (0.036) (0.036) (0.036) (0.036) (0.036) wave   1993 0.632** 0.632** 0.769** 0.768** 0.632**  (0.038) (0.038) (0.038) (0.038) (0.038) wave   1994 0.609** 0.609** 0.736** 0.736** 0.610**  (0.038) (0.038) (0.039) (0.039) (0.038) wave   1995 0.606** 0.606** 0.722** 0.722** 0.606**  (0.036) (0.036) (0.036) (0.036) (0.036) wave   1996 0.551** 0.551** 0.660** 0.660** 0.551**  (0.038) (0.038) (0.038) (0.038) (0.038) wave   1997 0.555** 0.555** 0.657** 0.656** 0.555**  (0.042) (0.042) (0.042) (0.042) (0.042) wave   1998 0.563** 0.563** 0.653** 0.652** 0.563**  (0.040) (0.040) (0.040) (0.040) (0.040) wave   1999 0.457** 0.457** 0.540** 0.540** 0.457**  (0.037) (0.037) (0.037) (0.037) (0.037) wave   2000 0.483** 0.483** 0.555** 0.554** 0.483**  (0.031) (0.031) (0.031) (0.031) (0.031) wave   2001 0.406** 0.406** 0.469** 0.469** 0.406**  (0.030) (0.030) (0.030) (0.030) (0.030) wave   2002 0.364** 0.364** 0.421** 0.420** 0.364**  (0.031) (0.031) (0.031) (0.031) (0.031) wave   2003 0.308** 0.308** 0.356** 0.356** 0.308**  (0.033) (0.033) (0.033) (0.033) (0.033) wave   2004 0.304** 0.304** 0.343** 0.343** 0.304**  (0.033) (0.033) (0.033) (0.033) (0.033) wave   2005 0.279** 0.279** 0.311** 0.311** 0.279**  (0.039) (0.039) (0.039) (0.039) (0.039) wave   2006 0.278** 0.278** 0.304** 0.303** 0.278**  (0.034) (0.034) (0.034) (0.034) (0.034) wave   2007 0.188** 0.188** 0.206** 0.206** 0.188**  (0.026) (0.026) (0.026) (0.026) (0.026) wave   2008 0.085** 0.085** 0.096** 0.096** 0.085**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   2009 0.020 0.020 0.027 0.027 0.020  (0.021) (0.021) (0.021) (0.021) (0.021) #people household 0.162** 0.162** 0.262** 0.262** 0.162**  (0.012) (0.012) (0.013) (0.013) (0.012) #children household -0.121** -0.121** -0.205** -0.205** -0.121**  (0.018) (0.018) (0.019) (0.019) (0.018) avg others' income(t-1) 0.031** 0.031** 0.027** 0.027** 0.031**  (0.002) (0.002) (0.002) (0.002) (0.002) east 0.035 0.036 0.120 0.116 0.036  95        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.102) (0.102) (0.101) (0.101) (0.102) child in HH (0-4 yrs) -0.534** -0.534** -0.620** -0.620** -0.534**  (0.026) (0.026) (0.027) (0.027) (0.026) child in HH (5-12yrs) 0.095** 0.095** 0.069** 0.069** 0.096**  (0.024) (0.024) (0.024) (0.024) (0.024) child in HH (13-18yrs) 0.223** 0.223** 0.243** 0.244** 0.223**  (0.022) (0.022) (0.022) (0.022) (0.022) hours work/day 0.833** 0.833** 0.819** 0.819** 0.833**  (0.013) (0.013) (0.013) (0.013) (0.013) hours work/day (sqr) -0.044** -0.044** -0.043** -0.043** -0.044**  (0.001) (0.001) (0.001) (0.001) (0.001) years of education 0.215** 0.215** 0.186** 0.186** 0.215**  (0.010) (0.010) (0.010) (0.010) (0.010) unemployment status -2.426** -2.426** -2.416** -2.416** -2.426**  (0.038) (0.038) (0.038) (0.038) (0.038) unemployment/state -0.034** -0.034** -0.035** -0.035** -0.034**  (0.006) (0.006) (0.006) (0.006) (0.006) life satisfaction  0.027** 0.027** 0.026** 0.026** 0.027**  (0.004) (0.004) (0.004) (0.004) (0.004) opportunity entrep 0.188** 0.188** 0.165** 0.200+ 0.188**  (0.063) (0.063) (0.063) (0.108) (0.063) living with opp entrp  0.026 0.046 0.116 0.063   (0.082) (0.083) (0.110) (0.102) head of household   0.421** 0.421**     (0.053) (0.053)  child   -0.405** -0.404**     (0.065) (0.066)  extended relative    -0.819** -0.829**     (0.136) (0.136)  non-relative    -0.370* -0.404*     (0.171) (0.172)  living*head of household    -0.187      (0.180)  living*child    -0.246      (0.259)  living*extended relative     1.146*      (0.544)  living*non_relative    2.521**      (0.528)  living*gender     -0.115      (0.172) Constant 2.135** 2.135** 2.067** 2.067** 2.135**  (0.142) (0.142) (0.147) (0.147) (0.142)  96        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5             Observations 316,828 316,828 316,828 316,828 316,828 R-squared 0.391 0.391 0.392 0.392 0.391 Number of persons 38,225 38,225 38,225 38,225 38,225 F(improvement of fit)  0.21293 234.344 6.35114 0.89663 degree freedom diff  1 4 4 1 p(improvement of fit)  0.64448 0 4.1700e-05 0.34369  The Effect of Working in the Family Business on Individual Income: Table 15 shows models that analyze the effects of working in the family business on the income of the focal individual. Model 1 includes all the control variables. Model 2 adds the working in family business variable. The parameter is positive, but not significant, suggesting that working in the family business does not significantly alter individual income compared to regular employment. The finding is surprising. It does not support H9a.  Model 3 adds the family roles to the model, and I find that they have significant effect; the income level is clearly affected by the family role that an individual plays in a given year. However, as Model 4 shows, these roles do not interact much with the family business employment effect. The income differences between family roles do not vary significantly with family business employment, although for children, there appears to be a marginally negative effect, indicating that children, when employed in the family business, might be underpaid compared to regular employment (but this could as well signal delayed returns). The findings thus lend only weak support to H9b. Model 5, again, suggests that the income difference between regular employment and family business employment does not depend on the gender of the focal individual (the main effect of gender on income is not included in this analysis due to fixed- 97  effects, nor is it the subject of this study).  As part of my sensitivity analysis, I have run similar models with those who work and live with an opportunity entrepreneur. The results provide no support, neither for H9a nor H9b. Please see Appendix D for these results. Overall, I conclude that H9a and H9b are not supported.   Table 15: The Effect of Working for Opportunity Entrepreneur on Focal Family Member's Income         VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.710** 0.710** 0.916** 0.915** 0.710**  (0.044) (0.044) (0.045) (0.045) (0.044) wave   1986 0.701** 0.700** 0.898** 0.898** 0.700**  (0.043) (0.043) (0.044) (0.044) (0.043) wave   1987 0.632** 0.632** 0.823** 0.822** 0.632**  (0.042) (0.042) (0.043) (0.043) (0.042) wave   1988 0.657** 0.657** 0.839** 0.838** 0.657**  (0.042) (0.042) (0.043) (0.043) (0.042) wave   1989 0.693** 0.693** 0.867** 0.867** 0.693**  (0.040) (0.040) (0.041) (0.041) (0.040) wave   1990 0.718** 0.718** 0.883** 0.883** 0.718**  (0.039) (0.039) (0.040) (0.040) (0.039) wave   1991 0.631** 0.631** 0.785** 0.786** 0.631**  (0.039) (0.039) (0.040) (0.040) (0.039) wave   1992 0.591** 0.591** 0.739** 0.739** 0.591**  (0.036) (0.036) (0.036) (0.036) (0.036) wave   1993 0.632** 0.632** 0.769** 0.769** 0.632**  (0.038) (0.038) (0.038) (0.038) (0.038) wave   1994 0.609** 0.609** 0.736** 0.736** 0.609**  (0.038) (0.038) (0.039) (0.039) (0.038) wave   1995 0.606** 0.606** 0.722** 0.722** 0.606**  (0.036) (0.036) (0.036) (0.036) (0.036) wave   1996 0.551** 0.551** 0.660** 0.660** 0.551**  (0.038) (0.038) (0.038) (0.038) (0.038) wave   1997 0.555** 0.555** 0.657** 0.657** 0.555**  (0.042) (0.042) (0.042) (0.042) (0.042) wave   1998 0.563** 0.563** 0.653** 0.653** 0.563**  (0.040) (0.040) (0.040) (0.040) (0.040) wave   1999 0.457** 0.457** 0.540** 0.540** 0.457**  (0.037) (0.037) (0.037) (0.037) (0.037) wave   2000 0.483** 0.483** 0.554** 0.554** 0.483**  98        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.031) (0.031) (0.031) (0.031) (0.031) wave   2001 0.406** 0.406** 0.469** 0.469** 0.406**  (0.030) (0.030) (0.030) (0.030) (0.030) wave   2002 0.364** 0.364** 0.420** 0.420** 0.364**  (0.031) (0.031) (0.031) (0.031) (0.031) wave   2003 0.308** 0.308** 0.356** 0.356** 0.308**  (0.033) (0.033) (0.033) (0.033) (0.033) wave   2004 0.304** 0.303** 0.343** 0.343** 0.303**  (0.033) (0.033) (0.033) (0.033) (0.033) wave   2005 0.279** 0.278** 0.311** 0.311** 0.278**  (0.039) (0.039) (0.039) (0.039) (0.039) wave   2006 0.278** 0.277** 0.303** 0.303** 0.277**  (0.034) (0.034) (0.034) (0.034) (0.034) wave   2007 0.188** 0.188** 0.206** 0.206** 0.188**  (0.026) (0.026) (0.026) (0.026) (0.026) wave   2008 0.085** 0.085** 0.096** 0.096** 0.085**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   2009 0.020 0.020 0.027 0.027 0.020  (0.021) (0.021) (0.021) (0.021) (0.021) #people household 0.162** 0.162** 0.262** 0.262** 0.162**  (0.012) (0.012) (0.013) (0.013) (0.012) #children household -0.121** -0.121** -0.205** -0.205** -0.121**  (0.018) (0.018) (0.019) (0.019) (0.018) avg others' income(t-1) 0.031** 0.031** 0.027** 0.027** 0.031**  (0.002) (0.002) (0.002) (0.002) (0.002) east 0.036 0.035 0.120 0.120 0.035  (0.102) (0.102) (0.101) (0.101) (0.102) child in HH (0-4 yrs) -0.534** -0.534** -0.620** -0.620** -0.534**  (0.026) (0.026) (0.026) (0.027) (0.026) child in HH (5-12yrs) 0.095** 0.095** 0.069** 0.069** 0.095**  (0.024) (0.024) (0.024) (0.024) (0.024) child in HH (13-18yrs) 0.223** 0.223** 0.243** 0.243** 0.223**  (0.022) (0.022) (0.022) (0.022) (0.022) hours work/day 0.833** 0.834** 0.819** 0.819** 0.834**  (0.013) (0.013) (0.013) (0.013) (0.013) hours work/day (sqr) -0.044** -0.044** -0.043** -0.043** -0.044**  (0.001) (0.001) (0.001) (0.001) (0.001) years of education 0.215** 0.215** 0.186** 0.186** 0.215**  (0.010) (0.010) (0.010) (0.010) (0.010) unemployment status -2.426** -2.425** -2.415** -2.415** -2.425**  (0.038) (0.038) (0.038) (0.038) (0.038) unemployment/state -0.034** -0.034** -0.035** -0.035** -0.034**  (0.006) (0.006) (0.006) (0.006) (0.006)  99        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       life satisfaction  0.027** 0.027** 0.026** 0.026** 0.027**  (0.004) (0.004) (0.004) (0.004) (0.004) opportunity entrep 0.188** 0.189** 0.166** 0.204+ 0.189**  (0.063) (0.063) (0.063) (0.108) (0.063) living with opp entrp 0.026 0.024 0.043 0.044 0.024  (0.082) (0.082) (0.083) (0.083) (0.082) working in fb  0.101 0.108 0.216 0.100   (0.112) (0.112) (0.137) (0.131) head of household   0.421** 0.422**     (0.053) (0.053)  child   -0.405** -0.403**     (0.065) (0.065)  extended relative    -0.819** -0.818**     (0.136) (0.136)  non-relative    -0.370* -0.369*     (0.171) (0.171)  employed*headh    -0.216      (0.244)  employed*child    -0.882+      (0.518)  employed*extend_relative     0.089      (1.172)  employed*non_relative    -        employed*gender     0.006      (0.245) Constant 2.135** 2.134** 2.066** 2.066** 2.134**  (0.142) (0.142) (0.147) (0.147) (0.142)       Observations 316,828 316,828 316,828 316,828 316,828 R-squared 0.391 0.391 0.392 0.392 0.391 Number of persons 38,225 38,225 38,225 38,225 38,225 F(improvement of fit)  1.85456 234.409 2.65328 1.1297e-03 degree freedom diff  1 4 3 1 p(improvement of fit)  0.17326 0 0.046851 0.97319  The Effect of Whole-Family Business Involvement: I investigate the effect of family business involvement on individual income by examining two measures of business involvement of family. The first one is the proportion of family members involved in the business and the  100  second is the time intensity of involvement measured by the average hours a family spent in the business.  Table 16 illustrates the results of the effects of the proportion of family members involved in the business on income. Model 1 includes all the control variables in addition to the opportunity entrepreneurship status and working in family business variables. In Model 2, I add the proportion of members involved in the business, and find no significant effect. In Model 3, I probe interactions with family business roles, and find no significant effects. H10a and H10b thus find no support in this analysis.  Table 16: The Effect of Proportion of Members Involved on Focal Member’s Income      VARIABLES Model 1 Model 2 Model 3     wave   1985 0.710** 0.710** 0.710**  (0.044) (0.044) (0.044) wave   1986 0.700** 0.700** 0.700**  (0.043) (0.043) (0.043) wave   1987 0.632** 0.632** 0.632**  (0.042) (0.042) (0.042) wave   1988 0.657** 0.657** 0.657**  (0.042) (0.042) (0.042) wave   1989 0.692** 0.692** 0.692**  (0.040) (0.040) (0.040) wave   1990 0.718** 0.718** 0.718**  (0.039) (0.039) (0.039) wave   1991 0.631** 0.631** 0.631**  (0.039) (0.039) (0.039) wave   1992 0.591** 0.591** 0.591**  (0.036) (0.036) (0.036) wave   1993 0.632** 0.632** 0.632**  (0.038) (0.038) (0.038) wave   1994 0.609** 0.609** 0.609**  (0.038) (0.038) (0.038) wave   1995 0.606** 0.606** 0.606**  (0.036) (0.036) (0.036)  101      VARIABLES Model 1 Model 2 Model 3     wave   1996 0.551** 0.551** 0.551**  (0.038) (0.038) (0.038) wave   1997 0.555** 0.555** 0.555**  (0.042) (0.042) (0.042) wave   1998 0.563** 0.563** 0.563**  (0.040) (0.040) (0.040) wave   1999 0.457** 0.457** 0.457**  (0.037) (0.037) (0.037) wave   2000 0.483** 0.483** 0.483**  (0.031) (0.031) (0.031) wave   2001 0.406** 0.406** 0.406**  (0.030) (0.030) (0.030) wave   2002 0.364** 0.364** 0.364**  (0.031) (0.031) (0.031) wave   2003 0.308** 0.308** 0.308**  (0.033) (0.033) (0.033) wave   2004 0.303** 0.303** 0.303**  (0.033) (0.033) (0.033) wave   2005 0.278** 0.278** 0.278**  (0.039) (0.039) (0.039) wave   2006 0.277** 0.277** 0.277**  (0.034) (0.034) (0.034) wave   2007 0.188** 0.188** 0.188**  (0.026) (0.026) (0.026) wave   2008 0.085** 0.085** 0.085**  (0.022) (0.022) (0.022) wave   2009 0.020 0.020 0.020  (0.021) (0.021) (0.021) #people household 0.162** 0.162** 0.162**  (0.012) (0.012) (0.012) #children household -0.121** -0.121** -0.121**  (0.018) (0.018) (0.018) avg others' income(t-1) 0.031** 0.031** 0.031**  (0.002) (0.002) (0.002) east 0.035 0.035 0.035  (0.102) (0.102) (0.102) child in HH (0-4 yrs) -0.534** -0.534** -0.534**  (0.026) (0.026) (0.026) child in HH (5-12yrs) 0.095** 0.095** 0.095**  (0.024) (0.024) (0.024) child in HH (13-18yrs) 0.223** 0.223** 0.223**  (0.022) (0.022) (0.022) hours work/day 0.834** 0.834** 0.834**  102      VARIABLES Model 1 Model 2 Model 3      (0.013) (0.013) (0.013) hours work/day (sqr) -0.044** -0.044** -0.044**  (0.001) (0.001) (0.001) years of education 0.215** 0.215** 0.215**  (0.010) (0.010) (0.010) unemployment status -2.425** -2.425** -2.425**  (0.038) (0.038) (0.038) unemployment/state -0.034** -0.034** -0.034**  (0.006) (0.006) (0.006) life satisfaction  0.027** 0.027** 0.027**  (0.004) (0.004) (0.004) opportunity entrep 0.189** 0.198+ 0.213+  (0.063) (0.103) (0.128) working in fb 0.102 0.103 0.108  (0.112) (0.112) (0.116) fb involvement proportion   -0.019 -0.002   (0.161) (0.193) opp*propfmly   -0.045    (0.277) employed_propfmly   -0.066    (0.541) Constant 2.134** 2.134** 2.134**  (0.142) (0.142) (0.142)     Observations 316,828 316,828 316,828 R-squared 0.391 0.391 0.391 Number of persons 38,225 38,225 38,225 F(improvement of fit)  0.026960 0.030840 degree freedom diff  1 2 p(improvement of fit)  0.86958 0.96963  Table 17 presents models that test the effect of time intensity of family business involvement. Model 1 includes control variables only. Model 2 adds the average number of hours that family members spend in their family business per day. The findings suggest that there is a significant and negative effect of the time intensity of involvement of family members on individual income. As the intensity of time involvement increases, family members earn less money. This lends some support to H10a. Model 3 also suggests that this effect is also dependent on the  103  business roles family members assume. In this case, as the time intensity of family involvement in the business increases, the income of the entrepreneur decreases, providing partial support for H10b.   Table 17: The Effect of Time Intensity of Business Involvement of Family on Family Members' Income       VARIABLES Model 1 Model 2 Model 3     wave   1985 0.710** 0.708** 0.709**  (0.044) (0.044) (0.044) wave   1986 0.700** 0.699** 0.700**  (0.043) (0.043) (0.043) wave   1987 0.632** 0.631** 0.632**  (0.042) (0.042) (0.042) wave   1988 0.657** 0.656** 0.657**  (0.042) (0.042) (0.042) wave   1989 0.692** 0.692** 0.693**  (0.040) (0.040) (0.040) wave   1990 0.718** 0.717** 0.718**  (0.039) (0.039) (0.039) wave   1991 0.631** 0.630** 0.631**  (0.039) (0.039) (0.039) wave   1992 0.591** 0.591** 0.591**  (0.036) (0.036) (0.036) wave   1993 0.632** 0.631** 0.632**  (0.038) (0.038) (0.038) wave   1994 0.609** 0.609** 0.609**  (0.038) (0.038) (0.038) wave   1995 0.606** 0.605** 0.606**  (0.036) (0.036) (0.036) wave   1996 0.551** 0.551** 0.552**  (0.038) (0.038) (0.038) wave   1997 0.555** 0.555** 0.555**  (0.042) (0.042) (0.042) wave   1998 0.563** 0.563** 0.563**  (0.040) (0.040) (0.040) wave   1999 0.457** 0.457** 0.457**  (0.037) (0.037) (0.037) wave   2000 0.483** 0.483** 0.483**  (0.031) (0.031) (0.031) wave   2001 0.406** 0.406** 0.406**  104      VARIABLES Model 1 Model 2 Model 3      (0.030) (0.030) (0.030) wave   2002 0.364** 0.364** 0.364**  (0.031) (0.031) (0.031) wave   2003 0.308** 0.308** 0.308**  (0.033) (0.033) (0.033) wave   2004 0.303** 0.303** 0.304**  (0.033) (0.033) (0.033) wave   2005 0.278** 0.278** 0.278**  (0.039) (0.039) (0.039) wave   2006 0.277** 0.278** 0.278**  (0.034) (0.034) (0.034) wave   2007 0.188** 0.188** 0.188**  (0.026) (0.026) (0.026) wave   2008 0.085** 0.085** 0.085**  (0.022) (0.022) (0.022) wave   2009 0.020 0.019 0.019  (0.021) (0.021) (0.021) #people household 0.162** 0.161** 0.160**  (0.012) (0.012) (0.012) #children household -0.121** -0.120** -0.120**  (0.018) (0.018) (0.018) avg others' income(t-1) 0.031** 0.031** 0.031**  (0.002) (0.002) (0.002) east 0.035 0.034 0.035  (0.102) (0.102) (0.102) child in HH (0-4 yrs) -0.534** -0.535** -0.535**  (0.026) (0.026) (0.026) child in HH (5-12yrs) 0.095** 0.095** 0.095**  (0.024) (0.024) (0.024) child in HH (13-18yrs) 0.223** 0.223** 0.223**  (0.022) (0.022) (0.022) hours work/day 0.834** 0.833** 0.831**  (0.013) (0.013) (0.013) hours work/day (sqr) -0.044** -0.044** -0.043**  (0.001) (0.001) (0.001) years of education 0.215** 0.215** 0.214**  (0.010) (0.010) (0.010) unemployment status -2.425** -2.426** -2.425**  (0.038) (0.038) (0.038) unemployment/state -0.034** -0.034** -0.034**  (0.006) (0.006) (0.006) life satisfaction  0.027** 0.027** 0.027**  (0.004) (0.004) (0.004)  105      VARIABLES Model 1 Model 2 Model 3     opportunity entrep 0.189** 0.363** 0.780**  (0.063) (0.091) (0.104) working in fb 0.102 0.118 0.121  (0.112) (0.112) (0.115) fb involvement intensity   -0.055** -0.005   (0.020) (0.027) opp*avgfbhrs   -0.178**    (0.036) employed_avgfbhrs   -0.037    (0.067) Constant 2.134** 2.135** 2.137**  (0.142) (0.142) (0.142)     Observations 316,828 316,828 316,828 R-squared 0.391 0.391 0.391 Number of persons 38,225 38,225 38,225 F(improvement of fit)  13.9249 13.8796 degree freedom diff  1 2 p(improvement of fit)  1.9030e-04 9.3900e-07  7.4 Summary of Results    In this chapter, I have provided the empirical findings of my analyses. I have found mixed support for the hypotheses I described in Chapters 2 to 5. While some of them have found strong support, many of them are not supported. In this subsection, I provide a concise summary of these results.   The findings suggest that, consistent with H1, those individuals who develop a higher attitude for risk seeking are more likely to take up self-employment as an opportunity entrepreneur. Some support has also been found for H2—those who have access to higher resources, mainly in terms of household income, are also more likely to become an opportunity entrepreneur. I also find that  106  resources in terms of years of education do not play a significant role in shaping individual’s decision to take up opportunity self-employment.   Next, my findings indicate that opportunity entrepreneurship significantly affects the psychological and financial wellbeing of family members in terms of life satisfaction and income. Those who voluntarily become self-employed tend to have higher life satisfaction and income compared to other years in which they hold a regular employment. While living with an opportunity entrepreneur reduces the focal family members' life satisfaction, there was little support that it would alter their income. A similar pattern arises for members that work in the family business. Those who work in the family business as a dependent employee report lower life satisfaction compared to times when they work elsewhere. However, there is no significant effect on their income – their income levels are not significantly different from other years in which they were regular (non-family business) employees. Finally, I find that the family-level involvement of the family in the family business can have negative effects on both life satisfaction and income of family members.   In terms of household roles, the findings provide only little support for assuming that they moderate the above mentioned relationships. Although I do find significant main effects of household roles, I find little indication that they influence how the involvement of members in the business affects their income. I have chosen partner to be the reference category and have included all possible household roles comprising extended relatives and non-relative members. The non-significant results are a little surprising , but we also have to consider that the main  107  effects in my models capture many (complex) aspects of the underlying processes (including the fixed effects) and can produce rather rich patterns.  108  Chapter 8: Discussion   Previous research has recognized the intertwined relationship between family and business systems. Numerous studies, particularly in family business and entrepreneurship contexts, have explored the ways in which family influences business outcomes. We know less about the reverse effect—how does business involvement affect the wellbeing of family members? This dissertation aims to find potential answers for this important and yet understudied question.  My study focuses on the antecedents and outcomes of opportunity entrepreneurship. My analysis sheds light a) on the factors that shape the path of individuals into opportunity entrepreneurship, and b) on the implications of the business for themselves and others as the family transforms into a business family. My study illuminates the unfolding of entrepreneurship, and how it is shaped by the risk taking and passion inherent in opportunity entrepreneurship. I draw on extant theory to develop my unfolding model and to derive testable hypotheses. I have empirically tested the proposed hypotheses using a large panel data set from Germany. The German SOEP data capture information on individuals and households over 28 years, and this allows me to conduct rather advanced statistical models and avoid biases that are common in cross-sectional studies.   In the following sections, I discuss the findings in more depth and develop the theoretical contributions of this dissertation. I also draw implications for managerial practice that can be useful for business owners and family business practitioners. Finally, I conclude this dissertation by briefly providing an overview of future research for myself and other researchers.    109  8.1 Antecedents of the Transition into Opportunity Entrepreneurship —When Individuals Enter into Self-Employment This dissertation aims to shed light on some of the factors shaping the decisions of individuals to voluntarily take up self-employment. Given the importance of risk taking for creating a new venture (Cramer et al., 2002), and considering the importance of the voluntary aspect of opportunity entrepreneurship (Reynolds, Camp, Bygrave, Autio, & Hay, 2002), it is not too surprising that when individuals in my sample dataset develop higher risk seeking attitudes, they are more likely to seize an opportunity and take up self-employment. The finding is nevertheless noteworthy because it does not reflect a between-individual effect. Instead, my findings reflect within-individual effects. Individuals develop (perhaps learn) a risk-seeking mind set and decide to seize an opportunity. Leaving regular employment where one can expect pay checks to arrive on a periodic basis is not easy, and even if these individuals might have a solid plan in place, it takes a certain degree of courage and risk seeking to actually go through with it.   Risk taking and passion for entrepreneurship can lead individuals into starting a business and set the stage for subsequent involvement of other family members. My study highlights the dynamic nature of the underlying forces. My analysis shows that the level of risk seeking of individuals is not fixed but rather, varies over time. It significantly affects the transition into self-employment. I find that when individuals grow more risk-seeking, they are more likely to leave their current job and become self-employed. This effect is the net of individual level fixed characteristics (including the fixed risk preferences and cognitive styles of individuals). The finding supports the interpretation that risk seeking plays a causal role for the transition into opportunity self-employment. It means that opportunity entrepreneurship is a process in which individuals go  110  through changes in their thinking before embarking on an entrepreneurial path. Entrepreneurship entails risk taking, and transiting into the role of entrepreneur requires an elevated willingness to take risks. Fixed risk preferences do not explain when individuals take up self-employment. It requires a wave of enthusiasm that elevates the willingness of individuals to take risks. It is the elevation of risk seeking self-perceptions that helps to overcome inertia and fear, and thereby eases the path into entrepreneurship.   The family context of the individual can play a significant role in mitigating the risks associated with the transition into self-employment. Especially in a context with high barriers to entrepreneurship such as Germany, it is critical to have access to resources that facilitate the startup. My findings suggest that individuals are more likely to take up self-employment when they live in a household with financial resources. The rate increases significantly with household income. Several mechanisms can contribute to this finding. One is financial support from the family to start a business (Aldrich & Cliff, 2003). Affluent families can provide more support and facilitate the transition into self-employment. A second is the safety-net that the family can provide. A family's high level of financial wellbeing protects individuals in the event of a failure of the business, and allows them to be more risk taking and to follow their vision1. The non-significant effect of years of education suggests that opportunity entrepreneurship can be realized by people with diverse educational training2.                                                   1 I have also explored the income of other family members' income as opposed to the whole household income and the findings are consistent. 2 I have also explored the non-linear effects of education and the findings are not significant.   111  8.2  Outcomes of Entrepreneurship —How Business Involvement Affects Psychological and Financial Wellbeing of Family Members The self-employment of a family member opens the door for other members to get involved in the business, and this can significantly affect the welfare of the focal individual and other members of the family. My findings confirm the main hypotheses about the effect of business involvement on the welfare of family members but also include surprising non significant results. Overall, I explore four forms of involvement of family members in the family business.   The first type of involvement is the direct business involvement of the focal individual in the form of self-employment as an opportunity entrepreneur. Building on ideas about risk taking, autonomy needs, and entry barriers, I hypothesized that the involvement of family members on self-employment is positively related to their own life satisfaction and their income. I find strong statistical support for both hypotheses. These findings suggest that leaving dependent employment behind and taking up self-employment  is associated with positive psychological and financial returns for the entrepreneur. Because their autonomy needs are met, entrepreneurs experience a higher level of life satisfaction. Due to risk aversion and market entry barriers, entrepreneurs tend to pick opportunities carefully (low risk with high return) and earn positive financial returns.  It is important to note that my models focus on state effects and do not explore sequential effects. In particular, I do not distinguish between the effect of entry into opportunity entrepreneurship and the effect of exit from it. My model specification assumes symmetric effects. I find that being an opportunity entrepreneur produces more life satisfaction than regular employment. It is  112  possible that this finding reflects the increase in life satisfaction that individual experience when they shift from regular employment into opportunity entrepreneurship, but it could also reflect the decrease in life satisfaction that individuals experience when they exit from opportunity entrepreneurship and return to regular employment. In the latter case, the decrease might follow from a number of underlying forces, including the loss of autonomy, but it could also reflect the disappointment of having failed with the business. It is likely that loss of autonomy has longer lasting effects than disappointment of failing with a business, but more research is needed to explore these issues in more detail. Doing so would require moving the analysis to a more complex state space that distinguishes between regular employment following an exit from an unsuccessful business, exit from a successful business, or no prior entrepreneurship experience at all. Prior research suggests that the theoretical and statistical issues of analyzing sequence effects in life courses is not trivial (Schulz & Strohmeier, 1984) and often the effects of these sequences are weak (Schulz, 1989). In my data, because of cell size limitations, such an analysis would encounter problems of statistical power, but I hope future research will be able to overcome these limitations.  Those individuals who self select themselves into opportunity entrepreneurship have a positive experience in terms of their psychological and financial wellbeing —at least in Germany. In other contexts, the effects might be different; e.g., low entry barriers or reckless attitudes might lead to less positive outcomes, or in collectivistic cultures, autonomy might be pursued with less passion and produce less life satisfaction. Future research will have to explore how these findings extend to different cultural and economic contexts.   113  The second type of involvement is indirect, produced by living together with a relative who has left the safety of dependent employment and embarked on a more turbulent path of opportunity entrepreneurship. I find that living with an opportunity entrepreneur negatively impacts the life satisfaction of the other family members in a household. This implies that although entrepreneurs themselves experience a positive change in their life satisfaction, their family members experience a negative effect in terms of life satisfaction. However, the presence of an entrepreneur in the family (by itself) does not have a significant impact on the other members’ income. This might be due to the fact that opportunity entrepreneurs tend to do well financially—they went into it deliberately—and other family members (on average) neither benefit nor suffer from it in economic terms. The fact of living with an opportunity entrepreneur (by itself) matters significantly for the other family members, but it has more psychological implications than financial ones. Entrepreneurship is much more challenging and turbulent than regular employment. It generates (on average) adequate income, but it burdens the family psychologically (e.g., dominating dinner conversations and inserting unpredictability in their lives). It poses difficult trade-offs for entrepreneurs and their families.   The third type of involvement is dependent employment of the focal member in the family business. It is a direct form of involvement that can arise from obligations to be involved in the business. Sacrificing one’s career in order to work in the family business can place a burden on family members working in the family business. Likewise, differences in risk tolerance between the family’s entrepreneur and the other members working for him/her can produce stress for them. The parameter estimates of my analyses indicate that working in a family business negatively impacts one's life satisfaction. However, it does not significantly affect their income. I  114  find that income from employment in the family business is not significantly different from regular (dependent) income. This finding is not consistent with interpretations of exploitation of family members—in terms of financial outcomes. Psychologically, however, there are significant burdens arising from working for the family business. The pattern might be rooted in German culture, which is conservative and yet individualistic. Thus, while individuals may sacrifice their own independent career for the sake of the family and endure a decline in their life satisfaction, they are less likely to accept lower financial compensation. This suggests that the dark side (or downside) of working in a family business is less related to financial issues, and more produced by social and psychological processes, such as obligations that constrain individual careers (and dreams) and role multiplexity mechanisms that create strain and potentially conflict between family members. The situation appears to be easier for family business helpers (those helping but not employed in the family business). Helping out in the family business does not negatively impact their psychological wellbeing (nor does it affect their income). The business involvement of helpers often entails important returns to them in terms of experiences and career advancement. They also contribute to the business in times of need and provide a flexible resource that is often required for running a small business, giving them a sense of responsibility and opportunities for learning to play relevant business roles.  The fourth type of business involvement is the degree to which the whole family is involved in the business. This family-level involvement reflects the proximity to an extreme (perhaps ideal) type of business family in which everyone works for the family business full time. I focus on two measures: the proportion of members involved, and the time intensity in terms of average hours that members work for the family business. I find that there is a negative effect of family-level  115  involvement on both individual's life satisfaction and income. The proportion of family members as well as the time intensity of involvement in the family business negatively affects individual's psychological and financial wellbeing. This suggests that whole family involvement poses its own burden on business family members. As the whole family becomes more involved, it approaches a total institution, and it becomes harder to separate work and family from each other. The intensity of interactions and obligations can overload individuals and reduce their life satisfaction. On the other hand, the negative effect of family-level involvement on income is a little harder to understand. It could reflect sentimental commitments to a traditional business model of a family business that employs every family member, but suffers economically because it relies on internal hires from the family. Hiring from the family is (on average) inferior compared to hiring external managers (non-relatives, experts, from the competitive labor market) for the business, and this can negatively affect the capacity of the business to pay adequate income to family members. The sentimental commitment mechanism could also explain the negative effect of family involvement on life satisfaction—forcing members into the business will make them unhappy. Nevertheless, alternative explanations need to be considered. It is possible that family members feel obligated to join the business when it is on the way down—that is, working for it to save it from failure. Family-level involvement would then be partially endogenous to the model. Although this is a conceivable scenario, it is not clear why (presumably rational) actors would join a failing family business when employment for other companies during that time might help to offset the risks of the family business. Furthermore, would such actors exit the family business when it is on the way up? Exploring these questions would not be easy, and require more detailed information about the financial situation of the  116  family business (which are not available in the SOEP data). I hope to address these questions in future research.   Finally and surprisingly, the household roles did not play a significant role in moderating the effect of opportunity entrepreneurship on the life satisfaction and income of family members. Although my models include a host of control variables (including fixed effects), and thus are not likely to be biased, it is possible that specific configurations in families can have effects that my analysis has missed.  This could be due to heterogeneity in household roles. For example, the head of household in a family comprised of a couple is potentially faced with a different set of responsibilities than a family with multiple children. As part of my future research, I plan to probe deeper into this issue. Exploring such detailed configurations is not easy, but can be performed with SOEP and related data sets. I plan to explore such configurations further in my future research as I believe it is a promising research direction.  8.3 Contributions to Theory The unfolding model of entrepreneurship provides significant and intriguing theoretical contributions. The model connects to various literatures such as entrepreneurship, family business, sociology, economics, family studies and psychology. Due to its interdisciplinary nature, the contribution of this dissertation is multifold.   My study contributes to organizational studies by focusing on the interdependency between business and family systems and looking into both the family and the individual as units of analysis. In family business firms, business and family roles are intensely intertwined. The  117  interdependencies are so intense that previous studies have referred to these businesses as a 'familial economic unit’ (Wheelock, 1992). "Once we look at people in households, it becomes apparent that they have a variety of motivations besides narrow economic gain: actions may be based on traditional or patriarchal reasoning, people have a need for dignity and self respect, and a need to care and nurture. Actions can also be based on reciprocity or cooperation between people" (Wheelock & Oughton, 1996, pp. 143-144). My study highlights how the tightness of interactions between business and family roles is exacerbated when risk taking and passion come into play, and how this can negatively affect psychological and financial outcomes. By focusing on the family as a primary support system for family firms, this dissertation follows scholarly calls for research on the family of the family business (Michael-Tsabari et al., 2014; Moores, 2009). Moreover, this dissertation contributes to work-life balance literature in entrepreneurship (Jennings & McDougald, 2007) by examining related issues within special circumstances in which separation between work and family life is blurry. In a typical family business, working and living with family members make it more difficult to know when and where to discuss work and when to stop. Therefore, work-life balance becomes more complex and more difficult to achieve.  Family business is a form of organization that relies on primary relationships. It shares characteristics with (and provides the foundation for) many traditional forms of domination, in particular patrimonialism (Adams, 2005). In such governance structures, the power is concentrated into a leader (often a male3 figure) that governs his familial estate. Family ties provide the foundation for these structures, and they incorporate elements typical for primary                                                  3 While usually it is a male figure who leads a family or a patrimonial estate, I take a broader view that also includes women as heads of their households or estates. My approach reflects the fact that more men are increasingly taking up more household chores as more women are engaged in paid employment market (Bianchi et al., 2000).  118  relationships, such as trust, obedience, obligations, norms and traditions. The financial and psychological outcomes of organizations that rely on primary relationships can be significant. My study highlights some of the less pleasant and unintended consequences of combining family and business. My finding of negative externalities of business involvement might signal a fundamental weakness of organizations that rely on primary relationships. In that perspective, my study points to a need for more longitudinal research on the antecedents and outcomes of such organizations.   This study also contributes to the life course literature by highlighting the importance of life course transitions for the unfolding of entrepreneurship. My study shows that taking a life course perspective can lead to a deeper understanding of the antecedents and outcomes of entrepreneurship—it reveals the dynamic nature of the underlying processes. Becoming an entrepreneur is a critical turning point in the family dynamics, and the involvement of family members in the business can produce significant change in the life of the family and its members (Wethington, Pixley, & Kavey, 2003), and it can significantly impact psychological and financial outcomes. Furthermore, my study focuses on the wellbeing of individuals in the family, which has gained some prior attention within the life course literature (Elder Jr et al., 2003). My study shows that the wellbeing of individuals is significantly affected by the family and business roles they take on as they go through their lives. Life course transitions of the focal member and of others in the family can produce new conditions which can offer new opportunities and pose different challenges for members. The life course shapes every member, and within the family, the intersection of member life courses can produce a wide range of outcomes. My study also shows how powerful and useful life course approaches are. I have been able to identify a suitable  119  data set that has allowed me to empirically test my theory over time which also includes time (represented by year dummies) and place (west versus east Germany) effects. Including time and place factors is particularly important in life course research to account for variation in different environments across time and space (Dannefer, 2003). My study shows that an appropriate dataset like SOEP that contains multiple observation over time and includes different units of analysis of individuals and families facilitates a deeper and more powerful analysis and is well positioned for life course studies (Halaby, 2003a). Life course approaches can contribute greatly to understanding dynamic processes within the context of family and business, and I hope my study will encourage others to take this path.   This dissertation makes important theoretical contributions to the entrepreneurship and family business literature by highlighting the critical role of the family system. In the last couple of decades, the literature on family business has received considerable attention from a broad range of disciplines (Au & Kwan, 2009). Much of the focus, however, has been on how the "family" affects the business: its processes, strategies and outcomes (Anderson & Reeb, 2003; Chrisman et al., 2005; Chua et al., 2006; Miller et al., 2008; Pérez-González, 2006). In this dissertation, I  have studied the reverse direction—how the business affects the family. Given the prevalence of family firms around the world, understanding the effects of business on family is extremely relevant and consequential. My study illuminates how business can affect family members and shape their financial and psychological outcomes. Although effects are for the most part positive for the entrepreneur, for his/her family, the effects are mostly negative. This means that family business, in spite of its attractions and popularity, has significant negative externalities that  120  should be taken into account by practitioners and policy makers and that warrant more attention in future research.   My study draws extensively on role theory (Biddle, 1986). I have argued that the overlap of family and business roles in a business family can create tensions and challenges for family members. I find that the involvement of family members in a business affects their psychological and financial welfare. Obligations to work for the family can constrain member’s career choices and negatively affect them. Role multiplexity (Ashforth et al., 2000) in terms of being a family member and assuming a family business role negatively affects life satisfaction. But within the family, differences between roles appear less important. I find that the reduction of life satisfaction due to working in the family business does not differ for partners (wives) and children. Although they play very different family roles, their life satisfaction is affected in similar ways. Role multiplexity operates in similar ways in both—inserting business roles into primary relationships is equally detrimental to the life satisfaction of partners and children.    Finally, although my theoretical framework presented in this dissertation does not make any gender based arguments, I have also taken care to investigate the role gender plays throughout the unfolding model of entrepreneurship. My findings—the absence of gender effects—are somewhat surprising. It is important to note that my models do not compare intercept effects (as I used fixed-effects models), but rather slope effects, and those do not differ significantly for men and women. While the levels of (financial and psychological) outcomes might differ for men and women, the paths to these outcomes appear to be the same. This means that the underlying processes unfold in similar ways for men and women.   121  Overall, this dissertation reveals a complex and dynamic interaction between family and business. The focus on opportunity entrepreneurship, which is different from other types of self-employment due to its voluntary nature, reveals differences and tensions among family members. Family members' experience is shaped by their type and level of business involvement in their family business. Family members often feel (explicitly or implicitly) obligated to contribute to the business (Dyer & Handler, 1994). Although the family aspect of family businesses can contribute positively to distinctive family business resources, capabilities, and competitive advantage (Arregle et al., 2007; Pearson et al., 2008), the findings presented here show that family business involvement can also have a dark side for the family. Family business involvement is, therefore, a mixed blessing for family members, rewarding some and burdening others. At the same time, involvement in the family business is a dynamic process that unfolds as members of the family take on business and family roles.  8.4 Implications for Managerial Practice This dissertation offers valuable managerial contributions that hopefully shed light onto many existing myths involving entrepreneurial and business families that lack much scientific evidence. First, it is really interesting to note that those self-selecting themselves into entrepreneurship, experience a positive effect on their life satisfaction in Germany, and they tend to do better financially compared to their regular employment. While entrepreneurship may be a difficult and failure-prone process for many, my findings suggest that it can be a rewarding choice in some contexts (such as Germany).     122  Second, the findings of this dissertation raise awareness about the fact that the business involvement of family members can have profound effects on the family. These findings illuminate how a family member, on a quest to live out her passions, can set the stage for an unfolding process that generates positive and negative externalities for other family members. Business educators and consultants have usually warned entrepreneurs about the risks associated with founding and running a new business. These days it is commonly acknowledged that a higher percentage of  new startups fail due to their liability of newness (Freeman et al., 1983). Entrepreneurs are, however, less aware of the negative consequences their decision has on their family. The business they have founded offers several forms of involvement to the rest of the family members, and can leave an imprint on their psychological and financial wellbeing. My dissertation provides evidence that these imprints are usually negative and that family members who live with their relative entrepreneurs suffer psychologically and at times financially.   This is both bad and good news for entrepreneurs and their families. It is bad news in the sense that it adds more responsibilities to entrepreneurs' plates. Not only do they need to be concerned about the needs of their businesses—they also need to be extra careful of how the business could negatively affect their family. The good news is that by being aware of the potential pitfalls of their decision to become an entrepreneur, they can mitigate some of the harm. For example, entrepreneurs should, if possible, avoid hiring (or even forcing) family members who live with them into their business. Their relative may join the business out of obligation, which negatively impacts their life satisfaction. Living and working together also complicates the management of work-life balance as well as role-multiplexity among family members. Paying extra attention to  123  role multiplexity could also be a valuable exercise through which family members become aware about the complexity of ties that connect them in both family and business systems.    It is also significant to keep in mind that negative externalities are not limited only to other family members but can arise even for the entrepreneur herself as the proportion and intensity of whole-family business involvement increases. While there is a possibility that entrepreneurs who perform poorly turn to their family as a source of human capital, it is also possible that by including too many family members and not seeking outside talent, the necessary human capital is not brought in and the business suffers as a result. Therefore, it becomes really important for prospective and current entrepreneurs to understand how their passions and their entrepreneurship impacts the rest of their family. By mitigating the harmful effects of entrepreneurship, entrepreneurs are likely to be able to protect their family members' psychological and financial wellbeing as well as the wellbeing of their businesses.    Finally, although there are still significantly more male opportunity entrepreneurs than female ones, I have found no significant difference between female and male entrepreneurs in terms of the psychological satisfaction they receive or how they perform financially compared to their wage employment. It is encouraging news for all the aspiring female entrepreneurs that on these two scales they are not different from their male counterparts. They have equal capacity to perform well financially while enjoying their life as an entrepreneur.   124  8.5 Future Research  Within this research program, I plan to continue on the main research question that has been the inspiration guiding this dissertation—how does the business affect the family? The aim of my research program is to shed new light on the myths surrounding entrepreneurial families and businesses and to better understand the intertwined relationship between business and family systems.  First, using the same dataset, I intend to expand on the findings in this dissertation by looking at some important contextual factors that may amplify or attenuate some of the results. The first one is the duration of being self-employed. The negative externalities produced by the decision of a family member to become self-employed may diminish over time as business matures and finds stability. Therefore, I plan to study how business duration affects entrepreneurs and their family members psychologically as well as financially. Another interesting contextual factor is the growth of the business measured by number of employees hired. Similarly, as the business grows, there might be less need for family members to sacrifice their own ambition to contribute to the welfare of the family business. This study may be more difficult to conduct as I only have access to categories of numbers of employees rather than actual numbers of employees. Therefore, some information may be lost when comparing different categories as opposed to having ‘number of employees’ as a continuous measure.   Next, I plan to use the information on family characteristics on the dataset GSOEP to explore how entrepreneurship affects changes in family structure. Specifically, I am interested in looking into whether entrepreneurship increases the likelihood of couples to break up or delay the birth  125  of a new child. If family business contributes to the deterioration of life satisfaction of family members, it is likely that this decline in psychological wellbeing breaks couples apart and given how time consuming it is to run a new business, having a new child may not be very appealing to parents.   On the other hand, it is also interesting to assess whether a big change in family influences the likelihood of individuals becoming entrepreneurs. For example, it is reasonable to speculate that having a new child dissuades parents from embarking on a risky path. I am also very interested in exploring in more depth specific family and household configurations in order to understand how they produce challenges for members and their business involvement. By configurations, I mean households of couples versus households of couples with children versus households of single parents, etc. It would also be intriguing to look into marital status among couples. I suspect that those couples who are married are more committed to the family business as opposed to those couples who live together but not legally married. My overarching  interest is to see whether it is the structural position in a household that differentiates women and men in terms of their experiences or their gender.   I am also interested in investigating female entrepreneurs to better understand their career path in combination with their life choices in terms of starting a family. Do female entrepreneurs have a different career trajectory than their male counterparts? Do they start having a family earlier in life and become an entrepreneur as a means to have higher flexibility over their time, or do they start having a family later in life after establishing a successful career?    126  Conversely, using other datasets, I am in the middle of a few projects that trace adolescents who work in their family business over time. I theorize that working in a family business exposes these adolescents to unique personal and professional experiences that influence them both in the short and long run. Children who work in their family business tend to have a better relationship with their parents and better psychological wellbeing in the short run. In the long run, being exposed to entrepreneurial venture, these adolescents are more likely to have entrepreneurial intention and if they become entrepreneurs they are more successful than other entrepreneurs who did not work in their family business in their teenage years.   Finally, I am interested in exploring how the business involvement of family members impacts the business. Particularly, I would like to explore the type and intensity of the spillover from the family system to the business system to trace how disagreements and negative associations in the family setting could upset and deteriorate business relationships and vice versa. Do family members actively involved in the business bring their self-serving business interests to family relationships and dynamics?  Do business disagreements translate into family breakups? And most importantly, how does family breakup impact the business?  I am hopeful and confident that this dissertation opens promising avenues for future research. For example, how does change in family members' life satisfaction impact the performance of the family business? Do shifts in risk preferences moderate these relationships? How about generational factors (i.e., do different generations respond differently to their involvement in their business)? And lastly, it seems that we may also need to more fully understand the role that culture can play in how family members relate to each other and to the business. I hope this  127  dissertation will inspire other researchers to continue in this promising direction and develop answers to these important and interesting questions.   128  Chapter 9: Conclusion   Family and business have been connected since ancient times, and their interaction still plays a very prominent role in today’s world. Connections between business and family shape the emergence and transformation of social, economic, and political structures. Families provide a natural context for the formation of organizations that rely on primary relationships. Primary relationships offer advantages in terms of trust and predictability, but they also pose challenges. Already Weber noted that patrimonial domination—a form of organization that arises from primary relationships—is less efficient and less stable than more modern (more ‘rational’) alternatives. Family business is a form of organization that combines a family with a business, and it relies on family ties and goodwill to persist and prosper. Its reliance on the family poses challenges for the business, and it can put strain on the family. It can burden family members to a degree that it hurts the business and limits the viability of family business as an organizational form. In that light, it becomes important to understand how the family business affects family members.   My dissertation aims to contribute to a deeper understanding of the effects of the business involvement of family members on their wellbeing. I see entrepreneurship unfolding through a dynamic process that starts when a household member takes up self-employment and thereby creates the possibility of the involvement of other members in the business. I take a life course perspective to study how the transition of family members in and out of business and family roles affects their psychological and financial wellbeing. My empirical analysis validates my unfolding model and shows that the involvement of members has a significant impact on their  129  life satisfaction and income. The analysis reveals a rich interplay between family and business roles. Different forms of business involvement interact with family roles to produce significant variations in outcomes. Family entrepreneurs appear to enjoy overall positive outcomes, while other family members often experience negative effects of being involved in the business, in particular in terms of reduced life satisfaction. The degree to which the entire family is involved in the business has overall negative effects on both life satisfaction and income.   Connections between diverse spheres of social life play a significant role in many settings, and in modern societies, they intensify as individuals pursue more diverse careers and lives. My study highlights the consequences of the intertwined relationships between business and family systems. It illustrates how unintentional spillover effects can arise between any two or more interconnected systems that share some members. Shared membership entails multiple layers of roles, norms and rules to be carried out by those who belong to more than one system. As my study shows, connecting family and business leads to a dynamic process that unfolds as members fulfill multiple roles and serve divergent demands. It has a powerful effect on the distribution of costs and benefits across members and time. Connecting divergent spheres can have massive implications for each and create unintended externalities for members. It leads to different lives – sometimes enriched, but often troubled by clashes between roles, rules, and norms.  My study combines the shared membership notion with a life course perspective and can offer new and intriguing avenues of research. It could lead to studies of the evolution and outcomes of highly interconnected financial, social, and political systems and the role of powerful agents maneuvering across these systems (somewhat similar to John Padget’s studies). Understanding  130  the unfolding of individual life courses as they ascend to powerful political, social and economic positions and the long lasting consequences they have on other people could reveal novel insights about economic and political phenomena such as elitism, nepotism, and conflict of interests. Similarly to family business firms, while power concentration within a few players could be advantageous to some, for many they become inherently disadvantageous.   Despite such disadvantages, patrimonial forms of organizations (such as family businesses) still persist. Maintaining such structures in modern societies is challenging. In view of this study, it is relevant and important to ask under which circumstances traditional patrimonial structures become detrimental or beneficial, and how they can persist and prosper. My study might help practitioners and scholars to become more aware of the challenges of family business and related forms of organization based on primary relationships in modern society. I hope it can inspire more critical and deeper examinations of traditional social structures and their outcomes. I also hope that my study will open the door to more longitudinal research on the unfolding of entrepreneurship and family businesses.  131  References  Acs, Z. J., Amorós, J. E., Bosma, N. S., & Levie, J. (2009). From entrepreneurship to economic development: Celebrating ten years of Global Entrepreneurship Monitor. 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(Accessed on May 2015).  http://data.worldbank.org/indicator/IC.LGL.CRED.XQ    148  Appendices  Appendix A: The Effect of Opportunity Entrepreneurship on Income (excluding those higher incomers above €1,150,000)  (1) (2) (3) (4) (5) VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave 1985 0.707** 0.710** 0.915** 0.915** 0.710**  (0.044) (0.044) (0.045) (0.045) (0.044) wave 1986 0.698** 0.700** 0.898** 0.898** 0.701**  (0.043) (0.043) (0.044) (0.044) (0.043) wave 1987 0.629** 0.632** 0.823** 0.823** 0.632**  (0.042) (0.042) (0.043) (0.043) (0.042) wave 1988 0.654** 0.657** 0.838** 0.838** 0.657**  (0.042) (0.042) (0.043) (0.043) (0.042) wave 1989 0.690** 0.692** 0.867** 0.867** 0.692**  (0.040) (0.040) (0.041) (0.041) (0.040) wave 1990 0.716** 0.718** 0.882** 0.883** 0.718**  (0.039) (0.039) (0.040) (0.040) (0.039) wave 1991 0.629** 0.631** 0.785** 0.785** 0.631**  (0.039) (0.039) (0.040) (0.040) (0.039) wave 1992 0.589** 0.591** 0.738** 0.739** 0.591**  (0.035) (0.036) (0.036) (0.036) (0.036) wave 1993 0.630** 0.632** 0.769** 0.769** 0.632**  (0.038) (0.038) (0.038) (0.038) (0.038) wave 1994 0.608** 0.609** 0.736** 0.736** 0.609**  (0.038) (0.038) (0.039) (0.039) (0.038) wave 1995 0.604** 0.606** 0.722** 0.722** 0.606**  (0.036) (0.036) (0.036) (0.036) (0.036) wave 1996 0.550** 0.551** 0.660** 0.660** 0.551**  (0.038) (0.038) (0.038) (0.038) (0.038) wave 1997 0.554** 0.555** 0.657** 0.657** 0.555**  (0.042) (0.042) (0.042) (0.042) (0.042) wave 1998 0.561** 0.563** 0.653** 0.653** 0.563**  (0.040) (0.040) (0.040) (0.040) (0.040) wave 1999 0.456** 0.457** 0.540** 0.540** 0.457**  (0.037) (0.037) (0.037) (0.037) (0.037) wave 2000 0.482** 0.483** 0.554** 0.554** 0.483**  (0.031) (0.031) (0.031) (0.031) (0.031) wave 2001 0.405** 0.406** 0.469** 0.469** 0.406**  (0.030) (0.030) (0.030) (0.030) (0.030) wave 2002 0.363** 0.364** 0.421** 0.420** 0.364**  (0.031) (0.031) (0.031) (0.031) (0.031) wave 2003 0.307** 0.308** 0.356** 0.356** 0.308**  149   (1) (2) (3) (4) (5) VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.033) (0.033) (0.033) (0.033) (0.033) wave 2004 0.303** 0.304** 0.343** 0.343** 0.304**  (0.033) (0.033) (0.033) (0.033) (0.033) wave 2005 0.278** 0.279** 0.311** 0.311** 0.279**  (0.039) (0.039) (0.039) (0.039) (0.039) wave 2006 0.277** 0.278** 0.304** 0.304** 0.278**  (0.034) (0.034) (0.034) (0.034) (0.034) wave 2007 0.188** 0.188** 0.206** 0.207** 0.188**  (0.026) (0.026) (0.026) (0.026) (0.026) wave 2008 0.085** 0.085** 0.096** 0.096** 0.085**  (0.022) (0.022) (0.022) (0.022) (0.022) wave 2009 0.020 0.020 0.027 0.027 0.020  (0.021) (0.021) (0.021) (0.021) (0.021) #people household 0.162** 0.162** 0.262** 0.262** 0.162**  (0.012) (0.012) (0.013) (0.013) (0.012) #children household -0.121** -0.121** -0.205** -0.205** -0.121**  (0.018) (0.018) (0.019) (0.019) (0.018) household income(t-1) 0.031** 0.031** 0.027** 0.027** 0.031**  (0.002) (0.002) (0.002) (0.002) (0.002) east 0.034 0.036 0.120 0.120 0.035  (0.102) (0.102) (0.101) (0.101) (0.102) child in HH (0-4 yrs) -0.534** -0.534** -0.620** -0.620** -0.534**  (0.026) (0.026) (0.026) (0.027) (0.026) child in HH (5-12yrs) 0.096** 0.095** 0.069** 0.069** 0.096**  (0.024) (0.024) (0.024) (0.024) (0.024) child in HH (13-18yrs) 0.223** 0.223** 0.243** 0.243** 0.223**  (0.022) (0.022) (0.022) (0.022) (0.022) individual income(t-1) 0.833** 0.833** 0.819** 0.819** 0.833**  (0.013) (0.013) (0.013) (0.013) (0.013) years of education -0.044** -0.044** -0.043** -0.043** -0.044**  (0.001) (0.001) (0.001) (0.001) (0.001) unemployment status 0.215** 0.215** 0.186** 0.186** 0.215**  (0.010) (0.010) (0.010) (0.010) (0.010) unemployment/state -2.427** -2.426** -2.416** -2.416** -2.426** #people household (0.038) (0.038) (0.038) (0.038) (0.038)  -0.034** -0.034** -0.035** -0.035** -0.034**  (0.006) (0.006) (0.006) (0.006) (0.006) life satisfaction  0.027** 0.027** 0.026** 0.026** 0.027**  (0.004) (0.004) (0.004) (0.004) (0.004) opportunity entrep  0.188** 0.165** 0.273* 0.112   (0.063) (0.063) (0.122) (0.132) head of household   0.420** 0.421**     (0.053) (0.053)   150   (1) (2) (3) (4) (5) VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       child   -0.405** -0.404**     (0.065) (0.065)  extended relative    -0.820** -0.818**     (0.136) (0.136)  other   -0.370* -0.371*     (0.171) (0.171)  Opp*head of household    -0.129      (0.142)  Opp*child    -0.358      (0.251)  Opp*extended relative    -1.585      (1.139)  Opp*other    0.042      (0.582)  Opp*gender     0.108      (0.150) Constant 2.135** 2.135** 2.068** 2.067** 2.135**  (0.142) (0.142) (0.147) (0.147) (0.142)       Observations 316,822 316,822 316,822 316,822 316,822 R-squared 0.391 0.391 0.392 0.392 0.391 Number of persid 38,225 38,225 38,225 38,225 38,225 F_test Improvement of Fit  9.43421 234.243 0.88017 0.66310 Change of Degree of Freedom  1 4 4 1 P Improvement of Fit  2.1300e-03 0 0.47474 0.41547     151  Appendix B: The Combined Effect of Working in the Family Business and Living with an Opportunity Entrepreneur on Life Satisfaction         VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.682** 0.682** 0.668** 0.668** 0.682**  (0.028) (0.028) (0.029) (0.029) (0.028) wave   1986 0.675** 0.675** 0.661** 0.661** 0.675**  (0.027) (0.027) (0.027) (0.027) (0.027) wave   1987 0.564** 0.564** 0.551** 0.551** 0.564**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1988 0.497** 0.497** 0.484** 0.484** 0.497**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1989 0.474** 0.474** 0.462** 0.462** 0.474**  (0.025) (0.025) (0.026) (0.026) (0.025) wave   1990 0.556** 0.556** 0.544** 0.544** 0.556**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1991 0.582** 0.582** 0.571** 0.571** 0.582**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1992 0.420** 0.420** 0.410** 0.410** 0.420**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1993 0.407** 0.407** 0.398** 0.398** 0.407**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1994 0.378** 0.378** 0.370** 0.370** 0.378**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1995 0.383** 0.383** 0.375** 0.375** 0.383**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1996 0.383** 0.383** 0.376** 0.376** 0.383**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1997 0.319** 0.319** 0.312** 0.312** 0.319**  (0.025) (0.025) (0.025) (0.025) (0.025) wave   1998 0.377** 0.377** 0.371** 0.371** 0.377**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1999 0.377** 0.377** 0.371** 0.371** 0.377**  (0.022) (0.022) (0.023) (0.023) (0.022) wave   2000 0.354** 0.354** 0.350** 0.350** 0.354**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2001 0.349** 0.349** 0.345** 0.345** 0.349**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2002 0.234** 0.234** 0.230** 0.230** 0.234**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2003 0.192** 0.192** 0.189** 0.189** 0.192**  152        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.020) (0.020) (0.020) (0.020) (0.020) wave   2004 0.080** 0.080** 0.078** 0.078** 0.080**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2005 0.174** 0.174** 0.172** 0.172** 0.174**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   2006 0.118** 0.118** 0.116** 0.116** 0.118**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2007 0.078** 0.078** 0.077** 0.077** 0.078**  (0.017) (0.017) (0.017) (0.017) (0.017) wave   2008 0.084** 0.084** 0.083** 0.083** 0.084**  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2009 0.020 0.020 0.019 0.019 0.020  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2010 0.088** 0.088** 0.087** 0.087** 0.088**  (0.015) (0.015) (0.015) (0.015) (0.015) #people household -0.045** -0.045** -0.051** -0.051** -0.045**  (0.006) (0.006) (0.007) (0.007) (0.006) #children household 0.042** 0.042** 0.046** 0.046** 0.042**  (0.010) (0.010) (0.010) (0.010) (0.010) household income(t-1) 0.001 0.001 0.001 0.001 0.001  (0.002) (0.002) (0.002) (0.002) (0.002) east -0.046 -0.045 -0.053 -0.053 -0.045  (0.061) (0.061) (0.061) (0.061) (0.061) child in HH (0-4 yrs) 0.030* 0.030* 0.036** 0.036** 0.030*  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (5-12yrs) 0.026+ 0.027+ 0.028* 0.028* 0.027+  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (13-18yrs) 0.014 0.014 0.012 0.012 0.014  (0.012) (0.012) (0.012) (0.012) (0.012) individual income(t-1) 0.009** 0.009** 0.010** 0.010** 0.009**  (0.002) (0.002) (0.002) (0.002) (0.002) years of education -0.015** -0.015** -0.012* -0.012* -0.015**  (0.005) (0.005) (0.005) (0.005) (0.005) unemployment status 0.008 0.008 0.008 0.008 0.008  (0.018) (0.018) (0.018) (0.018) (0.018) unemployment/state -0.019** -0.019** -0.019** -0.019** -0.019**  (0.003) (0.003) (0.003) (0.003) (0.003) avg others life sat 0.359** 0.359** 0.360** 0.360** 0.359**  (0.003) (0.003) (0.003) (0.003) (0.003) opportunity entrep 0.171** 0.171** 0.173** 0.140 0.171**  (0.053) (0.053) (0.053) (0.090) (0.053) work&live _opp  -0.336 -0.339+ -0.285 -0.338   (0.206) (0.206) (0.226) (0.224)  153        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       head of household   -0.045 -0.046     (0.036) (0.036)  child   0.024 0.024     (0.043) (0.043)  extended relative    -0.075 -0.075     (0.081) (0.081)  non-relative    -0.208* -0.208*     (0.099) (0.099)  work&live_head of household    -0.392      (0.522)  work&live _child    0.259      (0.685)  o. work&live _extended relative     -        o. work&live _other    -        work&live_gender     0.023      (0.410) Constant 4.632** 4.632** 4.635** 4.635** 4.632**  (0.073) (0.073) (0.076) (0.076) (0.073)       Observations 325,219 325,219 325,219 325,219 325,219 R-squared 0.137 0.137 0.137 0.137 0.137 Number of persons 41,347 41,347 41,347 41,347 41,347 F(improvement of fit)  5.75122 7.23915 1.05189 2.2482e-03 degree freedom diff  1 4 2 1 p(improvement of fit)  0.016478 7.9800e-06 0.34928 0.96218   154  Appendix C: The Effect of Helping in the Family Business on Focal Actor's Life Satisfaction  i. The effect of general helping in family business on one's life satisfaction         VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.681** 0.681** 0.667** 0.667** 0.681**  (0.028) (0.028) (0.029) (0.029) (0.028) wave   1986 0.674** 0.674** 0.660** 0.660** 0.674**  (0.027) (0.027) (0.027) (0.027) (0.027) wave   1987 0.563** 0.564** 0.550** 0.550** 0.564**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1988 0.496** 0.496** 0.484** 0.484** 0.496**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1989 0.473** 0.473** 0.461** 0.462** 0.473**  (0.025) (0.025) (0.026) (0.026) (0.025) wave   1990 0.555** 0.555** 0.544** 0.544** 0.555**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1991 0.581** 0.581** 0.571** 0.571** 0.581**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1992 0.419** 0.419** 0.410** 0.410** 0.419**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1993 0.406** 0.406** 0.398** 0.398** 0.406**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1994 0.378** 0.378** 0.370** 0.370** 0.378**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1995 0.383** 0.383** 0.375** 0.375** 0.383**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1996 0.383** 0.383** 0.376** 0.376** 0.383**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1997 0.319** 0.319** 0.312** 0.312** 0.319**  (0.025) (0.025) (0.025) (0.025) (0.025) wave   1998 0.377** 0.377** 0.371** 0.371** 0.377**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1999 0.377** 0.377** 0.371** 0.371** 0.377**  (0.022) (0.022) (0.023) (0.023) (0.022) wave   2000 0.354** 0.354** 0.349** 0.349** 0.354**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2001 0.349** 0.349** 0.345** 0.345** 0.349**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2002 0.234** 0.234** 0.230** 0.230** 0.234**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2003 0.192** 0.192** 0.189** 0.189** 0.192**  155        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.020) (0.020) (0.021) (0.021) (0.020) wave   2004 0.080** 0.080** 0.078** 0.078** 0.080**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2005 0.174** 0.174** 0.172** 0.172** 0.174**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   2006 0.118** 0.118** 0.116** 0.116** 0.118**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2007 0.078** 0.078** 0.077** 0.077** 0.078**  (0.017) (0.017) (0.017) (0.017) (0.017) wave   2008 0.084** 0.084** 0.084** 0.084** 0.084**  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2009 0.020 0.020 0.019 0.019 0.020  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2010 0.088** 0.088** 0.087** 0.087** 0.088**  (0.015) (0.015) (0.015) (0.015) (0.015) #people household -0.045** -0.045** -0.050** -0.050** -0.045**  (0.006) (0.006) (0.007) (0.007) (0.006) #children household 0.042** 0.042** 0.046** 0.046** 0.042**  (0.010) (0.010) (0.010) (0.010) (0.010) household income(t-1) 0.001 0.001 0.001 0.001 0.001  (0.002) (0.002) (0.002) (0.002) (0.002) east -0.046 -0.046 -0.053 -0.053 -0.046  (0.061) (0.061) (0.061) (0.061) (0.061) child in HH (0-4 yrs) 0.030* 0.030* 0.036** 0.036** 0.030*  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (5-12yrs) 0.026+ 0.026+ 0.028* 0.028* 0.026+  (0.014) (0.014) (0.014) (0.014) (0.014) child in HH (13-18yrs) 0.014 0.014 0.012 0.012 0.014  (0.012) (0.012) (0.012) (0.012) (0.012) individual income(t-1) 0.009** 0.009** 0.010** 0.010** 0.009**  (0.002) (0.002) (0.002) (0.002) (0.002) years of education -0.015** -0.015** -0.012* -0.012* -0.015**  (0.005) (0.005) (0.005) (0.005) (0.005) unemployment status 0.008 0.008 0.008 0.008 0.008  (0.018) (0.018) (0.018) (0.018) (0.018) unemployment/state -0.019** -0.019** -0.019** -0.019** -0.019**  (0.003) (0.003) (0.003) (0.003) (0.003) avg others life sat 0.359** 0.359** 0.360** 0.360** 0.359**  (0.003) (0.003) (0.003) (0.003) (0.003) opportunity entrep 0.172** 0.172** 0.175** 0.142 0.172**  (0.053) (0.053) (0.053) (0.090) (0.053) living with opp entrp -0.093* -0.093* -0.094* -0.095* -0.093*  (0.046) (0.046) (0.045) (0.046) (0.046)  156        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       helping in fb  -0.005 -0.005 0.025 0.004   (0.030) (0.030) (0.044) (0.040) head of household   -0.046 -0.046     (0.036) (0.036)  child   0.024 0.025     (0.043) (0.043)  extended relative    -0.076 -0.073     (0.081) (0.082)  non-relative    -0.209* -0.216*     (0.099) (0.099)  helping*head of household    -0.022      (0.067)  helping*child    -0.131      (0.102)  helping*extended relative     -0.143      (0.198)  helping*other    1.226**      (0.425)  helping*gender     -0.020      (0.062) Constant 4.632** 4.632** 4.636** 4.636** 4.632**  (0.073) (0.073) (0.076) (0.076) (0.073)       Observations 325,219 325,219 325,219 325,219 325,219 R-squared 0.137 0.137 0.137 0.137 0.137 Number of persons 41,347 41,347 41,347 41,347 41,347 F(improvement of fit)  0.034001 7.28447 1.92410 0.16023 degree freedom diff  1 4 4 1 p(improvement of fit)  0.85370 7.3300e-06 0.10336 0.68895   ii. The combined effect of helping in the family business and living with an opportunity entrepreneur on one's life satisfaction         VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.682** 0.682** 0.668** 0.668** 0.684**  (0.028) (0.028) (0.029) (0.029) (0.028) wave   1986 0.675** 0.675** 0.661** 0.661** 0.676**  157        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.027) (0.027) (0.027) (0.027) (0.027) wave   1987 0.564** 0.564** 0.551** 0.551** 0.565**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1988 0.497** 0.497** 0.485** 0.485** 0.498**  (0.026) (0.026) (0.027) (0.027) (0.026) wave   1989 0.474** 0.474** 0.462** 0.462** 0.475**  (0.025) (0.025) (0.026) (0.026) (0.025) wave   1990 0.556** 0.556** 0.544** 0.544** 0.556**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1991 0.582** 0.582** 0.571** 0.571** 0.582**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1992 0.420** 0.420** 0.410** 0.410** 0.421**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1993 0.407** 0.407** 0.398** 0.398** 0.408**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1994 0.378** 0.378** 0.370** 0.370** 0.379**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   1995 0.383** 0.383** 0.375** 0.375** 0.384**  (0.021) (0.021) (0.022) (0.022) (0.021) wave   1996 0.383** 0.383** 0.376** 0.376** 0.384**  (0.023) (0.023) (0.023) (0.023) (0.023) wave   1997 0.319** 0.319** 0.312** 0.312** 0.320**  (0.025) (0.025) (0.025) (0.025) (0.025) wave   1998 0.377** 0.377** 0.371** 0.372** 0.378**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   1999 0.377** 0.377** 0.371** 0.372** 0.378**  (0.022) (0.022) (0.023) (0.023) (0.022) wave   2000 0.354** 0.354** 0.350** 0.350** 0.355**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2001 0.349** 0.349** 0.345** 0.345** 0.350**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2002 0.234** 0.234** 0.230** 0.230** 0.234**  (0.019) (0.019) (0.019) (0.019) (0.019) wave   2003 0.192** 0.192** 0.189** 0.189** 0.193**  (0.020) (0.020) (0.021) (0.021) (0.020) wave   2004 0.080** 0.080** 0.078** 0.078** 0.081**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2005 0.174** 0.174** 0.172** 0.172** 0.175**  (0.024) (0.024) (0.024) (0.024) (0.024) wave   2006 0.118** 0.118** 0.116** 0.116** 0.118**  (0.021) (0.021) (0.021) (0.021) (0.021) wave   2007 0.078** 0.078** 0.077** 0.077** 0.079**  (0.017) (0.017) (0.017) (0.017) (0.017)  158        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   2008 0.084** 0.084** 0.083** 0.084** 0.084**  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2009 0.020 0.020 0.019 0.019 0.020  (0.015) (0.015) (0.015) (0.015) (0.015) wave   2010 0.088** 0.088** 0.087** 0.087** 0.088**  (0.015) (0.015) (0.015) (0.015) (0.015) #people household -0.045** -0.046** -0.051** -0.051** -0.045**  (0.006) (0.006) (0.007) (0.007) (0.006) #children household 0.042** 0.042** 0.046** 0.046** 0.055**  (0.010) (0.010) (0.010) (0.010) (0.008) household income(t-1) 0.001 0.001 0.001 0.001 0.001  (0.002) (0.002) (0.002) (0.002) (0.002) east -0.046 -0.045 -0.053 -0.053 -0.044  (0.061) (0.061) (0.061) (0.061) (0.061) child in HH (0-4 yrs) 0.030* 0.030* 0.036** 0.036** 0.016  (0.014) (0.014) (0.014) (0.014) (0.012) child in HH (5-12yrs) 0.026+ 0.026+ 0.028* 0.028*   (0.014) (0.014) (0.014) (0.014)  child in HH (13-18yrs) 0.014 0.014 0.012 0.012 0.000  (0.012) (0.012) (0.012) (0.012) (0.011) individual income(t-1) 0.009** 0.009** 0.010** 0.010** 0.009**  (0.002) (0.002) (0.002) (0.002) (0.002) years of education -0.015** -0.015** -0.012* -0.012* -0.015**  (0.005) (0.005) (0.005) (0.005) (0.005) unemployment status 0.008 0.008 0.008 0.008 0.008  (0.018) (0.018) (0.018) (0.018) (0.018) unemployment/state -0.019** -0.019** -0.019** -0.019** -0.019**  (0.003) (0.003) (0.003) (0.003) (0.003) avg others life sat 0.359** 0.359** 0.360** 0.360** 0.359**  (0.003) (0.003) (0.003) (0.003) (0.003) opportunity entrep 0.171** 0.171** 0.174** 0.144 0.171**  (0.053) (0.053) (0.053) (0.090) (0.053) Helping and living with opp  0.048 0.048 0.139 0.014   (0.116) (0.116) (0.144) (0.128) head of household   -0.045 -0.045     (0.036) (0.036)  child   0.024 0.025     (0.043) (0.043)  extended relative    -0.075 -0.072     (0.081) (0.081)  non-relative    -0.208* -0.207*     (0.099) (0.099)  helping*head of household    -0.165   159        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5           (0.249)  helping*_child    -0.172      (0.483)  helping*_extended relative     -1.334      (1.269)  o_helping*other    -        helping*gender     0.162      (0.294) Constant 4.632** 4.632** 4.635** 4.635** 4.632**  (0.073) (0.073) (0.076) (0.076) (0.073)       Observations 325,219 325,219 325,219 325,219 325,219 R-squared 0.137 0.137 0.137 0.137 0.136 Number of persons 41,347 41,347 41,347 41,347 41,347 F(improvement of fit)  0.25769 7.21525 1.19752 -5.44121 degree freedom diff  1 4 3 1 p(improvement of fit)  0.61171 8.3500e-06 0.30895 1     160  Appendix D: The Combined Effect of Working in the Family Business and Living with Opportunity Entrepreneur on Income       VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       wave   1985 0.710** 0.710** 0.915** 0.915** 0.710**  (0.044) (0.044) (0.045) (0.045) (0.044) wave   1986 0.700** 0.700** 0.898** 0.898** 0.701**  (0.043) (0.043) (0.044) (0.044) (0.043) wave   1987 0.632** 0.632** 0.823** 0.822** 0.632**  (0.042) (0.042) (0.043) (0.043) (0.042) wave   1988 0.657** 0.657** 0.838** 0.838** 0.657**  (0.042) (0.042) (0.043) (0.043) (0.042) wave   1989 0.692** 0.692** 0.867** 0.867** 0.692**  (0.040) (0.040) (0.041) (0.041) (0.040) wave   1990 0.718** 0.718** 0.883** 0.882** 0.718**  (0.039) (0.039) (0.040) (0.040) (0.039) wave   1991 0.631** 0.631** 0.785** 0.785** 0.631**  (0.039) (0.039) (0.040) (0.040) (0.039) wave   1992 0.591** 0.591** 0.738** 0.738** 0.591**  (0.036) (0.036) (0.036) (0.036) (0.036) wave   1993 0.632** 0.632** 0.769** 0.768** 0.632**  (0.038) (0.038) (0.038) (0.038) (0.038) wave   1994 0.609** 0.609** 0.736** 0.736** 0.609**  (0.038) (0.038) (0.039) (0.039) (0.038) wave   1995 0.606** 0.606** 0.722** 0.722** 0.606**  (0.036) (0.036) (0.036) (0.036) (0.036) wave   1996 0.551** 0.551** 0.660** 0.660** 0.551**  (0.038) (0.038) (0.038) (0.038) (0.038) wave   1997 0.555** 0.555** 0.657** 0.657** 0.555**  (0.042) (0.042) (0.042) (0.042) (0.042) wave   1998 0.563** 0.563** 0.653** 0.653** 0.563**  (0.040) (0.040) (0.040) (0.040) (0.040) wave   1999 0.457** 0.457** 0.540** 0.540** 0.457**  (0.037) (0.037) (0.037) (0.037) (0.037) wave   2000 0.483** 0.483** 0.554** 0.554** 0.483**  (0.031) (0.031) (0.031) (0.031) (0.031) wave   2001 0.406** 0.406** 0.469** 0.469** 0.406**  (0.030) (0.030) (0.030) (0.030) (0.030) wave   2002 0.364** 0.364** 0.420** 0.420** 0.364**  (0.031) (0.031) (0.031) (0.031) (0.031) wave   2003 0.308** 0.308** 0.356** 0.356** 0.308**  (0.033) (0.033) (0.033) (0.033) (0.033) wave   2004 0.304** 0.304** 0.343** 0.343** 0.304**  161        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5        (0.033) (0.033) (0.033) (0.033) (0.033) wave   2005 0.279** 0.279** 0.311** 0.311** 0.279**  (0.039) (0.039) (0.039) (0.039) (0.039) wave   2006 0.278** 0.278** 0.304** 0.304** 0.278**  (0.034) (0.034) (0.034) (0.034) (0.034) wave   2007 0.188** 0.188** 0.207** 0.206** 0.188**  (0.026) (0.026) (0.026) (0.026) (0.026) wave   2008 0.085** 0.085** 0.096** 0.096** 0.085**  (0.022) (0.022) (0.022) (0.022) (0.022) wave   2009 0.020 0.020 0.027 0.027 0.020  (0.021) (0.021) (0.021) (0.021) (0.021) #people household 0.162** 0.162** 0.262** 0.262** 0.162**  (0.012) (0.012) (0.013) (0.013) (0.012) #children household -0.121** -0.121** -0.205** -0.205** -0.121**  (0.018) (0.018) (0.019) (0.019) (0.018) avg others' income(t-1) 0.031** 0.031** 0.027** 0.027** 0.031**  (0.002) (0.002) (0.002) (0.002) (0.002) east 0.035 0.035 0.120 0.120 0.035  (0.102) (0.102) (0.101) (0.101) (0.102) child in HH (0-4 yrs) -0.534** -0.534** -0.620** -0.620** -0.534**  (0.026) (0.026) (0.026) (0.027) (0.026) child in HH (5-12yrs) 0.095** 0.095** 0.069** 0.069** 0.095**  (0.024) (0.024) (0.024) (0.024) (0.024) child in HH (13-18yrs) 0.223** 0.223** 0.243** 0.243** 0.223**  (0.022) (0.022) (0.022) (0.022) (0.022) hours work/day 0.833** 0.833** 0.819** 0.819** 0.833**  (0.013) (0.013) (0.013) (0.013) (0.013) hours work/day (sqr) -0.044** -0.044** -0.043** -0.043** -0.044**  (0.001) (0.001) (0.001) (0.001) (0.001) years of education 0.215** 0.215** 0.186** 0.186** 0.215**  (0.010) (0.010) (0.010) (0.010) (0.010) unemployment status -2.426** -2.426** -2.416** -2.416** -2.426**  (0.038) (0.038) (0.038) (0.038) (0.038) unemployment/state -0.034** -0.034** -0.035** -0.035** -0.034**  (0.006) (0.006) (0.006) (0.006) (0.006) life satisfaction  0.027** 0.027** 0.026** 0.026** 0.027**  (0.004) (0.004) (0.004) (0.004) (0.004) opportunity entrep 0.188** 0.188** 0.165** 0.166** 0.188**  (0.063) (0.063) (0.063) (0.063) (0.063) working and living with opp  0.078 0.121 0.207 0.011   (0.415) (0.414) (0.429) (0.445) head of household   0.420** 0.420**     (0.053) (0.053)   162        VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5       child   -0.405** -0.406**     (0.065) (0.065)  extended relative    -0.820** -0.820**     (0.136) (0.136)  non-relative    -0.370* -0.371*     (0.171) (0.171)  working*head of household    -0.660      (1.290)  working*child    0.479      (0.730)  o_working*extended relative     -        o. working*other    -        working*gender     0.750      (0.973) Constant 2.135** 2.135** 2.068** 2.067** 2.135**  (0.142) (0.142) (0.147) (0.147) (0.142)       Observations 316,828 316,828 316,828 316,828 316,828 R-squared 0.391 0.391 0.392 0.392 0.391 Number of persons 38,225 38,225 38,225 38,225 38,225 F(improvement of fit)  0.097441 234.268 0.72355 0.73428 degree freedom diff  1 4 2 1 p(improvement of fit)  0.75492 0 0.48503 0.39150          

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