"Arts, Faculty of"@en . "Vancouver School of Economics"@en . "DSpace"@en . "UBCV"@en . "Lafontaine, Francine"@en . "2010-09-30T20:23:16Z"@en . "1988"@en . "Doctor of Philosophy - PhD"@en . "University of British Columbia"@en . "Contractual arrangements have been the subject of a substantial body of economic\r\nresearch. In particular, economists have sought an explanation for the existence\r\nof share contracts. Under this kind of contract, two or more parties share in the output of the production process. These contracts present a problem to economists because they imply more than one residual claimant. Thus incentives are diluted and inefficiency is expected to result. But this type of contract has existed for centuries and continues to be used today. Why is that if they are inefficient? The answer is that under conditions of uncertainty and imperfect information, share contracts can be preferable to fixed-wage (vertical integration) or fixed-rent (market transaction)\r\nagreements. In fact, many explanations for the existence of share contracts and their coexistence with fixed-wage and rental arrangements are found in the theoretical literature.\r\nWhile the theoretical literature on the subject of share contracts has flourished over the last decade, empirical analyses of these models has lagged behind. This thesis aims to rectify the situation somewhat. More precisely, recent advances in the theoretical literature are applied to the analysis of franchise contracts. An empirical\r\nmodel of franchising based on profit-maximizing behavior is developed which makes it possible to examine whether the factors theorists have suggested as potential\r\nexplanations for share contracts are relevant when it comes to explaining what one observes in the context of franchising, and whether their effects are consistent with predictions from the various theories. Both the contract mix, i.e. franchisors' decisions concerning the proportion of stores they want to operate and franchise, and the terms of the franchise contract, fixed and variable fees, are examined.\r\nIn order to carry out the analysis, data on a cross-section of 548 individual franchisors\r\nin 1986 were gathered. These franchisors are involved in a variety of business activities in the U.S., such as Fast-food Restaurants, Business Aids and Services, Construction and Maintenance, and Non-food Retailing. Censoring problems arise from the fact that a number of franchisors in the sample franchise all of their outlets. Also, some firms require no variable or no fixed fee. For these reasons, the maximum likelihood Tobit estimator is used.\r\nEmpirical work in an area such as this, where theories rely on concepts that are not easily quantifiable, can hardly provide unambiguous answers about the validity of the theories. Nevertheless, the following results emerge from the empirical analysis. First, the effect of risk, measured either by the proportion of discontinued outlets or by the variance of sales in the sector, is found to be the opposite of what pure risk-sharing and one-sided hidden-action models would predict. Second, firms resort to franchising more often when monitoring downstream operators becomes costlier, and use it proportionately less when the value of the inputs they themselves provide increases. This is consistent with two-sided hidden-action models. Results with respect to capital-market-imperfection arguments are rather inconclusive. It appears that franchising relaxes some form of constraint franchisors face in trying to expand their operations, since they use it more when they are growing faster, but whether this is a financial constraint remains unclear.\r\nThe explanatory power of the model is greater with respect to the proportion of franchised stores than it is for any of the two fees. Thus, in response to changes in the exogenous variables considered here, franchisors, who have a choice between modifying the terms of their franchise contract or changing the proportion of stores they want to franchise, tend to do mostly the latter.\r\nContrary to what one would have expected on a theoretical basis, the observed royalty rates and franchise fees are not negatively correlated in this data set. Combined\r\nwith the fact that the model is less satisfactory relative to the fees, this suggests that there are considerations in the determination of the royalty rate and the franchise\r\nfee that have not been taken into account in the theories. One possibility in the case of the fixed fee is that it may include the price of services provided by the franchisors.\r\nIt also appears that franchisors use input sales as another means to extract rent from franchisees. This may contribute to the lack of correlation between the two fees. Finally, the equation for the franchise fee was derived under the assumption that all remaining surplus at the downstream level, given the royalty rate, should be extracted through the franchise fee. The lack of relationship between the fees could be an indication that this assumption is incorrect, and that there are in fact rents left at the downstream level. This would be consistent with the existence of queues of potential franchisees in many franchise chains."@en . "https://circle.library.ubc.ca/rest/handle/2429/28849?expand=metadata"@en . "FRANCHISING AS A SHARE CONTRACT: A N EMPIRICAL ASSESSMENT by FRANCINE L A F O N T A I N E B A A . Ecole des Hautes Etudes Commerciales, 1980 M.Sc. Ecole des Hautes Etudes Commerciales, 1982 A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of D O C T O R OF PHILOSOPHY in The Faculty of Graduate Studies Department of Economics We accept this thesis as conforming to the required standard The University of British Columbia August 1988 \u00C2\u00A9 Francine Lafontaine, 1988 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of The University of British Columbia Vancouver, Canada DE-6 (2/88) ABSTRACT Contractual arrangements have been the subject of a substantial body of eco-nomic research. In particular, economists have sought an explanation for the exis-tence of share contracts. Under this kind of contract, two or more parties share in the output of the production process. These contracts present a problem to economists because they imply more than one residual claimant. Thus incentives are diluted and inefficiency is expected to result. But this type of contract has existed for centuries and continues to be used today. Why is that if they are inefficient? The answer is that under conditions of uncertainty and imperfect information, share contracts can be preferable to fixed-wage (vertical integration) or fixed-rent (market transac-tion) agreements. In fact, many explanations for the existence of share contracts and their coexistence with fixed-wage and rental arrangements are found in the theoretical literature. While the theoretical literature on the subject of share contracts has flourished over the last decade, empirical analyses of these models has lagged behind. This thesis aims to rectify the situation somewhat. More precisely, recent advances in the theoretical literature are applied to the analysis of franchise contracts. An em-pirical model of franchising based on profit-maximizing behavior is developed which makes it possible to examine whether the factors theorists have suggested as poten-tial explanations for share contracts are relevant when it comes to explaining what one observes in the context of franchising, and whether their effects are consistent with predictions from the various theories. Both the contract mix, i.e. franchisors' decisions concerning the proportion of stores they want to operate and franchise, and the terms of the franchise contract, fixed and variable fees, are examined. In order to carry out the analysis, data on a cross-section of 548 individual fran-chisors in 1986 were gathered. These franchisors are involved in a variety of business activities in the U.S., such as Fast-food Restaurants, Business Aids and Services, Construction and Maintenance, and Non-food Retailing. Censoring problems arise from the fact that a number of franchisors in the sample franchise all of their outlets. Also, some firms require no variable or no fixed fee. For these reasons, the maximum likelihood Tobit estimator is used. Empirical work in an area such as this, where theories rely on concepts that are not easily quantifiable, can hardly provide unambiguous answers about the validity of n the theories. Nevertheless, the following results emerge from the empirical analysis. First, the effect of risk, measured either by the proportion of discontinued outlets or by the variance of sales in the sector, is found to be the opposite of what pure risk-sharing and one-sided hidden-action models would predict. Second, firms resort to franchising more often when monitoring downstream operators becomes costlier, and use it proportionately less when the value of the inputs they themselves provide increases. This is consistent with two-sided hidden-action models. Results with respect to capital-market-imperfection arguments are rather inconclusive. It appears that franchising relaxes some form of constraint franchisors face in trying to expand their operations, since they use it more when they are growing faster, but whether this is a financial constraint remains unclear. The explanatory power of the model is greater with respect to the proportion of franchised stores than it is for any of the two fees. Thus, in response to changes in the exogenous variables considered here, franchisors, who have a choice between modifying the terms of their franchise contract or changing the proportion of stores they want to franchise, tend to do mostly the latter. Contrary to what one would have expected on a theoretical basis, the observed royalty rates and franchise fees are not negatively correlated in this data set. Com-bined with the fact that the model is less satisfactory relative to the fees, this suggests that there are considerations in the determination of the royalty rate and the fran-chise fee that have not been taken into account in the theories. One possibility in the case of the fixed fee is that it may include the price of services provided by the fran-chisors. It also appears that franchisors use input sales as another means to extract rent from franchisees. This may contribute to the lack of correlation between the two fees. Finally, the equation for the franchise fee was derived under the assumption that all remaining surplus at the downstream level, given the royalty rate, should be extracted through the franchise fee. The lack of relationship between the fees could be an indication that this assumption is incorrect, and that there are in fact rents left at the downstream level. This would be consistent with the existence of queues of potential franchisees in many franchise chains. m TABLE OF CONTENTS A B S T R A C T ii T A B L E OF CONTENTS iv LIST OF TABLES viii LIST OF FIGURES xi A C K N O W L E D G E M E N T xii I INTRODUCTION 1 II W H Y DOES FRANCHISING EXIST: IMPLICATIONS OF T H E CON-T R A C T U A L A R R A N G E M E N T LITERATURE 6 1. Introduction 6 2. The Nature of Franchising 6 3. An Overview of the Theoretical Literature on Share Contracts . . 10 3.1 Pure Risk-Sharing Models 11 3.2 One-Sided Hidden-Action Models 18 3.3 Two-sided Hidden-Action Models 19 3.4 Capital-Market-Imperfection Arguments 23 3.5 Self-Selection and Screening Models 24 4. Conclusion 27 III A N EMPIRICAL MODEL OF FRANCHISING 29 1. Introduction 29 2. An Overview of the Empirical Literature on Share Contracts . . . 29 - 2.1 The Empirical Literature on Sharecropping 29 2.2 Some Empirical Papers on Franchising 34 3. The Empirical Model 38 iv 3.1 Franchisors' Choices of Contractual Mix 40 3.2 Extension to the Contractual Design 46 4. Conclusion 51 IV T H E DATA: SOURCES AND CHARACTERISTICS 53 1. Introduction 53 2. The Sample of Franchisors 53 3. Some Interesting Descriptive Statistics 59 3.1 The Number of Outlets 59 3.2 The Use of Franchising 62 3.3 About the Contractual Design: Royalty Rates and Franchise Fees 65 3.4 A Comparison of the Two Samples 74 3.5 Measures of Geographical Dispersion and of Franchisors' Contri-bution 75 3.6 Some Relevant Sectoral Data 78 3.7 Alternative Measures of Risk 81 4. Conclusion 88 V T H E ECONOMETRIC SPECIFICATION AND RESULTS 90 1. Introduction 90 2. The Definition of the Variables 90 2.1 Measuring Risk or IU 91 2.2 Measuring Franchisees' Supervision Costs or i/ 92 2.3 Measuring the Franchisor's Contribution or IT 93 2.4 Measuring the Franchisors' Capital Constraint or IK 94 v 2.5 Some Other Relevant Variables 95 3. The Model Specification 98 3.1 Functional Form 98 3.2 Estimation Technique 100 3.3 Covariance Terms 103 3.4 Simultaneity Problems 104 4. The Empirical Results 104 4.1 The Effect of Risk, IU 110 4.2 The Effect of Franchisee Supervision Costs, 7/ I l l 4.3 The Effect of the Franchisor's Contribution, i j 113 4.4 The Effect of Franchisors' Capital Constraints, IK 117 4.5 The Effect of Input Sales and Royalty Rates 120 4.6 Some General Comments 120 5. Conclusion 123 VI RESULTS F R O M VARIOUS SUBSAMPLES OF FIRMS . 127 1. Introduction 127 2. Age Cohorts 128 3. Size Cohorts 136 4. Sectoral Effects 141 4.1 The Effect of Sectoral Dummy Variables 143 4.2 Differences Among Sectors 147 5. Conclusion 152 VII CONCLUSION 155 BIBLIOGRAPHY 158 vi SOURCES OF DATA 163 APPENDIX A: DESCRIPTIVE STATISTICS FOR T H E SAMPLE OF 890 FRANCHISORS 164 APPENDIX B: CORRELATION MATRIX OF T H E VARIABLES . . 170 APPENDIX C: HISTOGRAMS FOR T H E T H R E E D E P E N D E N T VARI-ABLES 172 APPENDIX D: ESTIMATION RESULTS EXCLUDING LIMIT OBSER-VATIONS 175 APPENDIX E: ESTIMATION RESULTS FOR T H E NUMBER OF FRANCHISES AND COMPANY-OPERATED STORES 180 APPENDIX F: T H E LONG T E R M T R E N D IN FRANCHISING . . . 183 APPENDIX G: RESULTS FOR GROUPS OF EIGHT COHORTS . . 185 vii LIST OF TABLES 3.1 Expected Effects of Indices on q//Q in the Various Models 51 4.1 Coverage of the Sample of 548 American Franchisors 58 4.2 Number of Outlets for the 548 Franchisors 60 4.3 Proportion of Franchised Outlets for the 548 Franchisors 63 4.4 Royalty Rates for the 548 Franchisors 66 4.5 Franchise Fees for the 548 Franchisors 68 4.6 Royalty Rates and Franchise Fees Within Size and Age Cohorts . . . . 72 4.7 Measures of Geographical Dispersion and of Franchisors' Contribution . 76 4.8 Some Relevant Sectoral Data 79 4.9 Alternative Measures of Risk 86 5.1 Descriptive Statistics for the 548 Franchisors 97 5.2 Proportion of Franchised Outlets Under a Linear Specification 106 5.3 Royalty Rates and Franchise Fees Under a Linear Specification 107 5.4 Proportion of Franchised Outlets Under a Partially Logarithmic Specifica-tion 108 5.5 Royalty Rates and Franchise Fees Under a Partially Logarithmic Specifi-cation 109 5.6 Expected and Observed Effects of the Indices on q//Q 124 6.1 The Proportion of Franchised Stores Within Age Cohorts 130 6.2 The Variable Fee Within Age Cohorts 131 6.3 The Franchise Fee Within Age Cohorts 132 6.4 The Proportion of Franchised Stores Within Size Cohorts 137 6.5 The Variable Fee Within Size Cohorts 138 viii 6.6 The Franchise Fee Within Size Cohorts 139 6.7 The Effect of Sectoral Dummy Variables Under a Linear Specification 144 6.8 The Effect of Sectoral Dummy Variables Under a Partially Logarithmic Specification 145 6.9 The Proportion of Franchised Outlets in Various Sectors 148 6.10 The Variable Fee in Various Sectors 149 6.11 The Franchise Fee in Various Sectors 150 A . l Number of Outlets for the 890 Franchisors 165 A.2 Proportion of Franchised Outlets for the 890 Franchisors 166 A.3 Royalty Rates for the 890 Franchisors 167 A.4 Franchise Fees for the 890 Franchisors 168 A. 5 Royalty Rates and Franchise Fees Within Size and Age Cohorts for the 890 Franchisors 169 B. l Correlation Matrix of the Variables (Sample of 548 Franchisors) . . . . 171 D. l OLS Regressions Without Limit Observations : Proportion of Franchised Stores - Linear 176 D.2 OLS Regressions Without Limit Observations : Proportion of Franchised Stores - in Log 177 D.3 OLS Regressions Without Limit Observations : Royalty Rates and Fran-chise Fees - Linear 178 D. 4 OLS Regressions Without Limit Observations : Royalty Rates and Fran-chise Fees - in Log 179 E. l OLS Regressions for the Number of Franchises 181 E. 2 TOBIT Regressions for the Number of Company-Operated Outlets . . 182 F. l The Proportion of Franchised Stores Within Eight Age Cohorts . . . . 186 ix F.2 The Royalty Rate Within Eight Age Cohorts 187 F.3 The Franchise Fee Within Eight Age Cohorts 188 F.4 The Proportion of Franchised Stores Within Eight Size Cohorts . . . . 189 F.5 The Royalty Rate Within Eight Size Cohorts 190 F.6 The Franchise Fee Within Eight Size Cohorts 191 x LIST OF FIGURES 1 Contractual Choices as Self-selection Mechanisms 26 2 The Trade-Off Between the Two Decision Variables, r and qf/Q . . . . 49 C . l Distribution of the Percentage of Franchised Outlets n=548 173 C.2 Distribution of Royalty Rates and Franchise Fees, n=548 174 F . l The Long Term Trend in Franchising 184 XI ACKNOWLEDGEMENT I would like to thank Mukesh Eswaran, Margaret Slade and Ken White for their continuous technical and moral support. As advisors for this thesis, they showed much patience and skill. I would also like to thank John Cragg, Ashok Kotwal and Hugh Neary for their helpful comments and advice. Most of all, I am indebted to Robert Picard; he and I both know why. I also want to acknowledge financial support from the Social Sciences and Hu-manities Research Council of Canada. xn CHAPTER I Introduction Contractual arrangements have been the subject of a substantial body of eco-nomic research. In particular, economists have sought an explanation for the existence of share contracts. Under this kind of contract, two or more parties share in the output of the production process. Examples include sharecropping, patent licensing, joint ventures, and franchising. These contracts present a problem to economists because they imply more than one residual claimant. Incentives are therefore diluted and inefficiency is expected to result. But this type of contract has existed for centuries and continues to be used today. Why is that if they are inefficient? The answer is that under conditions of uncertainty and imperfect information, share contracts can be preferable to fixed-wage (vertical integration) or fixed-rent (market transac-tion) agreements. In fact, many explanations for the existence of share contracts and their coexistence with fixed-wage and rental arrangements are found in the theoretical literature. While the theoretical literature on the subject of contractual choice has flourished over the last decade, empirical analyses of these models has lagged behind. This thesis aims to rectify the situation somewhat. More precisely, recent advances in the theoretical literature are applied to the analysis of franchise contracts. An empirical model of franchising, based on profit maximizing behavior, is developed. It will make it possible to examine whether the factors theorists have suggested as potential explanations for share contracts are relevant when it comes to explaining what one observes in the context of franchising, and whether their effects are consistent with predictions from the various theories. Because so little has been done in this area, this work is necessarily exploratory and descriptive. But such an analysis is useful in at least three different respects. First, it increases our understanding of franchising, which in and of itself is worth studying given its importance in the retailing sector and the service industries. Sec-ond, if share contracts exist for similar reasons whether in agriculture, patent licensing or the service sector, this analysis should further our understanding of this type of contract in general. Finallj', it indicates what factors seem to be especially relevant in the context of franchising, and it also suggests questions that deserve further at-1 tention. In that sense, it contributes to future theoretical and empirical research in the area. Franchising offers a rare opportunity to assess theories concerning firms' contrac-tual decisions.Franchisors tend to operate a certain number of stores and to franchise the others. In the first case, a manager, hired under a fixed-wage contract, is re-sponsible for the outlet.1 In the second case, the franchisee generally pays royalties based on sales or profits, which means that most franchise contracts are de facto share contracts. Franchisors mix these two types of contracts in varying proportions. For example, in 1986, McDonald's franchised 76.4% of its 9060 stores, and Burger King franchised 82% of its 4635 outlets. Consequently, one question that can be ad-dressed empirically is: What determines the proportion of stores each firm chooses to franchise? In other words, what are the factors that make them decide between fixed-wage and share contracts. The second advantage that arises from the use of data on franchising stems from the fact that each franchisor generally uses the same franchise contract, i.e. the same royalty rate and same franchise fee with all of its potential franchisees at any point in time. For that reason, it is possible to obtain information concerning the terms of the franchise contract for individual franchisors. Since the terms of the optimal share contract are determined endogenously in most theoretical models, one can then see if the models have some explanatory power with respect to the chosen royalty rates and franchise fees across franchisors. In order to carry out the empirical analysis, data on a cross-section of 548 individual franchisors in 1986 were gathered. These franchisors are involved in a variety of business activities in the U.S., such as Fast-food Restaurants, Business Aids and Services, Construction and Maintenance, and Non-food Retailing. Empirical work in an area such as this, where theories rely on concepts that are not easily quantifiable, can hardly provide unambiguous answers about the validity of the theories. Nevertheless, the following results emerge from the empirical analysis. 1 In reality, it is not necessary that the manager be paid a fixed wage. His compensation can be based on the outlet's performance to a large extent. What is necessary is that his contract not give him as much incentives to work as the franchise contract does. As pointed out by Goldberg (1982) and Brickley and Dark (1987), since the manager can not appropriate increases in the resale value of the outlet due to his good management, his contract necessarily gives him less incentives than that of the franchisee who gets those benefits when he sells his outlet. 2 First, franchisors' propensity to use franchising is non-decreasing in the amount of risk they face in their sector, measured either by the proportion of discontinued outlets or by the variance of sales in the sector. Similarly, royalty rates decrease with these measures of risk. Such a result is inconsistent with the risk-sharing argument for share contracts unless one is ready to assume that the franchisors are more risk-averse than their franchisees. It is also not consistent with one-sided hidden-action models, i.e. models where risk-neutral franchisors use franchising to provide insurance to their risk-averse franchisees, while at the same time giving them a type of contract that incites them to work. Of course these interpretations depend on the capacity of the measures to capture exogenous risk, as opposed to the variability that is due to moral hazard. And even if they do, in models with asymmetric information, increases in riskiness automatical!}' compound the unobservability problem. The more risk there is, the more difficult it is to assess peoples' behavior. This confuses issues and could affect the observed effect of risk on the proportion of franchised stores as well as the royalty rates. Still, if increased risk leads to a greater reliance on franchising due to the greater difficulty of evaluating franchisees' performance for example, the results imply that indeed incentive issues overwhelm risk-sharing considerations in the determination of the contract mix and of the terms of the contract. It is also found that franchisors tend to use franchising more when the cost of supervising dowstream operators increases due to increased geographical dispersion. Thus the notion that they use franchising contracts for their incentive properties vis-a-vis franchisees is supported by the data. This is in agreement with Brickley and Dark (1987) who found that outlets that are close to monitoring centers are more likely to be company-operated than those that are farther away. On the other hand, franchisors tend to franchise less when the value of their own inputs increases. Combined, these results lend empirical support to two-sided hidden-action models, i.e. those that posit that share contracts arise from market imperfections and the resulting need to provide incentives to both parties to the contract. Finally, with respect to received explanations for share contracts, it is found that franchisors use franchising more during periods of rapid expansion, which is consistent with the idea that they view franchisees as a source of capital. However, the proportion of franchised stores tends to decrease with the amount of capital required, which casts some doubt on a capital-market-imperfection explanation for 3 franchising. Thus franchisors may use franchising to relax some form of constraint that they face during periods of expansion, but the constraint need not be financial. In general, the explanatory power of the empirical model is satisfactory with respect to franchisors' decisions concerning the contractual mix, i.e. the proportion of stores they choose to franchise. Interestingly, however, the explanatory power of the variables is much lower in general for both the royalty-rate and the franchise-fee equations. Theoretical models of franchising such as those found in Rubin (1978), Blair and Kaserman (1982) and Mathewson and Winter (1985), analyse a single franchisor - franchisee pair. Comparative-static results in this case necessarily center on the terms of the franchise contract because these are the franchisor's only control variables. In a context where franchisors have many outlets, and can therefore choose to franchise some and operate others, they have an additional instrument at their disposal. And it is found here that franchisors often adjust to changes in the exogenous variables by modifying the proportion of stores they decide to franchise rather than changing the terms of their franchise contract. One explanation for this may He in the fact that each franchisor uses the same \"average\" share contract for all of its franchisees. Consequently, the franchise contract is not meant to be responsive for example to outlet-specific variables; some of the adjustments for differences among outlets or among outlet operators are handled instead through the choice of the type of contract. This behavior suggests either the existence of a significant cost associated with the development of franchise contracts, and/or the possibility that franchisors use other means to differentiate outlets and franchisees. For example, as indicated by Caves and Murphy (1976), the sale of inputs at a price greater than marginal cost can serve as another way for franchisors to extract rent from franchisees. Franchisors could specify different levels of input requirements depending on the profitability of the various outlets. However, the franchise contract is generally the same across franchisees in a given chain in this respect as well. Another variable franchisors have control over is the density of stores. They may be able to render various locations more similar by adjusting the number of stores in each area as a function of the level of demand. Finally, in the theoretical models, the fixed fee is generally assumed to be chosen so as to extract whatever rents may be left downstream given the royalty rate. Thus one would expect a negative correlation between the two fees. Also in the reduced-form equations, the same variables should explain both types of fees, although their 4 effect on each should be of opposite sign. However, this is not what is found in these data, suggesting that there is not necessarily a trade-off between the two fees. In other words, the fixed fee is not determined entirely once the variable fee is known. This could result from the inclusion in the fixed fee of amounts that represent a payment for services rendered by the franchisor, for example training. It may also be interpreted as an indication that some rents are left with the franchisees. No real surprises were found at the empirical level when the estimations were done separately for groups of firms defined on the basis of their size, measured in number of outlets, their age, measured by the number of years they have been in business, or the sector in which they operate. In general, the results that were obtained on the sample of franchisors as a whole were confirmed within subsamples of firms. The thesis is organized as follows. In the next chapter, I provide a brief de-scription of franchising, followed by an overview of the main explanations for share contracts that are found in the theoretical literature. In Chapter 3, the existing em-pirical literature on share contracts is briefly reviewed. Then, the empirical model is developed. This is done first with respect to firms' choices concerning the contract mix, and then extended to include their decisions concerning the terms of the fran-chise contract. The data used in the empirical analysis are described in Chapter 4. The econometric specification and general results obtained on the whole sample of franchisors are found in Chapter 5. Chapter 6 is concerned with estimating the model within various subsamples of firms defined on the basis of the number of years they have been in operation, the number of outlets in the franchise chain, and the sector in which the firm operates. Finally, concluding remarks are found in Chapter 7. 5 CHAPTER II Why Does Franchising Exist: Implications of the Contractual Arrangement Literature 1. Introduction This chapter contains first a brief definition and description of what franchising entails. This includes the presentation of a unifying framework to facilitate the discussion of the theoretical models in the context of franchising. The review of the theoretical literature on share contracts follows in Section 3. Most of the models discussed in this section were developed to explain the existence of sharecropping in agriculture and its coexistence with fixed-wage and fixed-rent agreements. These theories are classified here among five major categories: pure risk-sharing models, one-sided hidden-action models, two-sided hidden-action models, explanations based on capital market imperfections and, finally, self-selection and screening models. Each of these is discussed in turn, and then applied to the case of franchising. Concluding comments are found in Section 4. 2. The Nature of Franchising Franchising is a growing phenomenon: in Canada, sales through franchised outlets increased by 133% between 1976 and 1981.1 The Association of Canadian Franchisors estimates that they have grown by at least 10% each year since then. In the United States, they grew by 72% in the first half of the 1980's. Franchising now accounts for approximately 40% of Canadian and about 33% of American retail business.^ Technically, a franchise agreement is a contractual arrangement between two in-dependent firms, whereby the franchisee pays the franchisor for the right to sell the franchisor's product and/or the right to use his trademark at a given place and for a certain period of time. The U.S. Department of commerce classifies franchises ac-cording to what the main component of the transaction is. \"Product and Tradename 1 Statistics Canada, Franchising in the Canadian Economy, 1976-1981. See ITS. Department of Commerce (1986). 6 Franchising\", also referred to as \"Traditional Franchising\", is characterized by fran-chised dealers who \"concentrate on one company's product line and to some extent identify their business with that company\" ^ . Examples of this type of franchising are Car dealers and Gasoline Service stations. In \"Business Format Franchising\" on the other hand, the relationship between franchisor and franchisee \"includes not only the product, service, and trademark, but the entire business format itself \u00E2\u0080\u0094 a marketing strategy and plan, operating manuals and standards, quality control, and continu-ing two way communication\"^. Examples of this include Restaurants, Business and Employment services, and Real Estate. Most of the growth in franchising since the 1950's has been in this latter category. In most Business Format franchises, the payment made by the franchisee takes the form of a fixed fee up front, the franchise fee, and royalties that are proportional to sales or sometimes to profits. In product and tradename franchises, franchisees do not pay royalties, but they are bound to buy their inputs from their franchisors. When downstream firms produce with a fixed-proportion technology, or in those cases where they buy all of their inputs from a single manufacturer, they can not substitute away from this manufacturer's products. In those circumstances, input mark-ups become equivalent to royalties (or a tax) based on output. That is, under fixed proportions, one can write q = min(x,y), so that in equilibrium, q = x = y. Therefore, the upstream firm can obtain the same equilibrium price and quantity and the same amount of revenue by taxing either q or x and/or In traditional franchising, downstream firms simply buy goods from their fran-chisors and resell them. Thus the conditions under which input mark-ups are equiva-lent to royalties on output generally hold in this type of franchise relationship. Con-sequently, these Product and Tradename franchisors, as well as Business Format franchisors, receive some form of variable payments from their franchisees. However, the value of these variable payments as a percentage of sales is unobservable in the case of product and tradename franchises. For this reason, my analysis concentrates on Business Format franchisors. All of the franchisors studied here belong to this ^ U.S. Department of Commerce, 1987, p. 1 ^ U.S. Department of Commerce, 1987, p. 3 ^ These however remain different from royalties on sales unless the price is also controlled by the franchisor. If it was, assuming a tax on output of t dollars, and a sales price of p, the equivalent royalty rate would simply be t/p. 7 category. Because franchising generally entails variable payments, it can be taken as a type of share contract similar to sharecropping, joint ventures, and patent licensing. It is, however, possible that a contract involving only fixed fees would be included in the franchising statistics. These types of contracts are not the norm. For example, in their survey of fast-food franchises in 1971, Ozanne and Hunt found 88% of franchisors required between 1 and 18% of sales to be paid in royalties. The remaining franchisors were the major suppliers of their franchisees and used input mark-ups. Similarly, of the 548 Business Format franchisors studied here, only 36 require no variable payments from their franchisees. In this paper, the term franchising will be used in the sense of share contract, keeping in mind that in some cases fixed-rental agreements are included in this category. In addition to monetary aspects, franchising arrangements often entail stipula-tions as to the type of assistance the franchisor will provide to the franchisee (site selection, training, accounting, ongoing guidance, etc.) and the manner in which the franchisor expects the franchisee to conduct the business. One may find clauses con-cerning hours of operation, prices, recruiting, cleanliness, etc. Typically, the contract also contains numerous termination clauses such that the franchisor can terminate the contract at will. It is the existence of these constraints on the franchisee's con-duct that makes such an arrangement resemble an employer-employee relation and casts some doubt on the \"independence\" of the franchisee. Yet, franchise agreements He somewhere between market and intrafirm transactions; if in some respects they resemble labour contracts, it remains that each agreement entails the participation of two independent firms. In the next section, I will be presenting an overview of the theoretical literature on share contracts. As a unifying framework for the various models, I assume that an upstream manufacturer derives some monopoly power from a tradename. This firm can open its own retail outlets (fixed-wage contract) or it can sell the right to sell its products and to use its tradename to independent retailers (franchising). \u00C2\u00AE Assume It is worth pointing out that in reality, all franchised outlets are not necessarily individually owned and operated. In other words, it is possible for a single franchisee to be responsible for more than just one store in a chain. For example, master franchises for whole geographical areas are sometimes granted to single individuals or firms. Because outlets that are franchised in this way are not distinguished from individually owned franchises in the data, possible 8 also that, for a given p, demand at the retail level can be written as Xi = f(T,li) + 6i (2.1) for each of n franchisees. / is increasing and concave in its two arguments, T represents the value of the trademark, which is the franchisor's responsibility, while stands for local inputs provided by the franchisee. These would include such things as the franchisee's managerial inputs and local advertising. 9i is a random variable that is i.i.d. with mean 0 and variance O~Q for all franchisees. This formulation implies that uncertainty is independent of input levels. But because of this uncertainty, it is not possible for the franchisor to infer the level of l{ given T and the ex-post level of demand. Similarly the franchisee can not infer T from his knowledge of A\"; and l{. Thus there is potentially a two-sided moral hazard problem. Note that if the 6{ were perfectly correlated, the franchisor would be able to infer a ranking for the level of Z; provided by franchisees from the observed ranking of the X{. He could then use this information in devising an optimal franchise contract. In general, this would entail including some measure of other agents' performance in the contract for any one agent.7 With the 9{S independently distributed, no such ranking is possible. In that case, the optimal contract for each agent will depend on his output alone and not on anybody else's.** Observed franchise contracts are a function only of the sales level of the outlet, X{. They do not depend on any of the Xj. This can be interpreted to mean that the assumption of independence of the 6{ is reasonable in this context. The franchise contract is identical for all the franchisees of a given franchisor. It entails the payment of a fixed fee F, which is paid only once for the duration of the contract, and of royalties on sales r, where 0 < r < 1? The expected profits of the ramifications of this additional level of organization are not addressed here. As long as the effect of the franchise contract on the master franchisee is such as to make each one of his franchises benefit from the incentives he receives in a way that approaches the effect of individual franchise contracts, this should not present any problem at the empirical level. 7 See for example Lazear and Rosen (1981), Holmstrom (1982), Nalebuff and Stiglitz (1983) and Mookherjee (1984) on the problem of a single principal facing many agents. R See Mookherjee (1984) for a proof that subject to the constraint that agents play Nash among themselves, if the random variables in the agents' output function are independent, the optimal contracts are also independent in the sense that agent i:s payment scheme should not be made dependent on agent j's output. ^ The main reason for assuming an identical contract for all franchisees at this point is that this is what one observes in reality. Why this is so is not addressed here. 9 franchisor, II, and of each franchisee, iti, assuming that all outlets are franchised, are given by1^ n n = ^ [ r . p . A ' i - r F ] - C r ( n ) (2.2) Ti = (1 - r)p \u00E2\u0080\u00A2 Xi - C(Xi) - Ci{U) - F (2.3) where n is the total number of outlets in the chain, CT represents the cost of developing and upholding the value of the tradename, C(X{) stands for the costs of the retailing activity, and Ci is the cost of providing local inputs. Assuming an unlimited (infinitely elastic) supply of potential franchisees, franchisors choose the contractual structure and design the contracts in order to maximize their expected profits (or utility if they are risk-averse) subject to the participation constraint of franchisees. Competition among potential franchisees should ensure that they get only their opportunity level of utility, u. 3. An Overview of the Theoretical Literature on Share Contracts In the literature on sharecropping, it has been established that in a perfectly competitive economy, the choice between a fixed wage, a fixed-rental or a share contract would be irrelevant to the question of efficiency.11 Consequently, in such an economy, there would be nothing systematic about the contractual structure. This result of course is akin to that which has been established in the vertical integration literature about the equivalence, in terms of the upstream firm's profits, of fixed fees and/or royalties to vertical integration.12 The upstream firm could choose randomly which outlet it wishes to control which way. Nothing could explain the contractual structure in this case. It is clear that upon relaxing some of the assumptions of the perfectly competitive model in agriculture, one can gain some insight into the circumstances which would favor, for example, sharecropping over ^ Since the fixed fee is for the duration of the contract, if Xi here is interpreted as yearly sales, F would refer only to that portion of the fixed fee attributable to a year. If F represents the whole fixed fee, Xi would have to refer to total sales over the duration of the contract, which is 14 years on average according to the U.S. Department of Commerce. 1 1 See Reid (1977) p. 404. 1 2 See for example Blair and Kaserman (1980), Dixit (1983), Gallini and Winter (1983) and Mathewson and Winter (1983) on this subject. 10 other types of arrangement, and thus develop some theory of the determinants of contractual structures. Similarly, it is necessary to relax assumptions of perfect information concerning demand and costs in order to differentiate modes of vertical control from the upstream firm's point of view. Explanations for the existence of share contracts and their coexistence with fixed-wage and rental contracts that are found in the theoretical literature on contractual arrangements can be classified among five major categories. ^ I will discuss these in turn in the context of franchising. 3.1 Pure Risk-Sharing Models The possibility of risk-sharing that is embodied in the sharing rule was first put forward by Cheung (1969) as an explanation for the existence of sharecropping. When production is uncertain, the use of a fixed-wage contract makes the landlord bear all risk. Fixed-rent contracts on the other hand imply that the tenants have to bear all risk. With a share contract, both parties get fluctuations in their revenues when production varies, but the fluctuations are smaller. / / both are risk averse, they gain from this. In Cheung's (1969) model, share contracts are assumed to have higher transaction costs than either fixed-wage or fixed-rental agreements. Hence share contracts are observed when the benefits from risk-sharing outweigh the higher transaction costs. The higher the risk, the higher the gains from sharing and the higher the probability that a share contract will be chosen. The coexistence of all three types of contracts in agriculture would result from differences in risk among crops and/or regions as well as differences in risk aversion. Cheung's position has been criticised on the basis of both theoretical and empir-ical arguments. At the theoretical level, Stiglitz (1974) and\"Reid (1976) showed that the same risk-dispersion effect could be achieved for both the landowner and tenant by a combination of fixed-rental and fixed-wage agreements. In other words, if each tenant works part of his time under a fixed-wage arrangement and another part of his time under a fixed-rent contract, and the landowner rents out part of his land under a fixed rent and cultivates another part using hired labour, they both obtain the same For insightful surveys of this literature, that has mostly been developed in order to explain the existence of sharecropping, see for example Binswanger and Rosenzweig (1984), Jaynes (1984) and Singh(1987). 11 reduction in risk than if they used a single share contract. In these circumstances, given the assumed higher transaction costs of the share contract, it would not be chosen. Since then, Newbery and Stiglitz (1979) have argued that with additional independent sources of risk, or with economies of scale in agricultural production such that subdividing lots becomes inefficient, sharecropping might again be chosen as an insurance policy. However, Jaynes (1984) and Eswaran and Kotwal (1985) point out that the assumption of higher transaction costs for the share contract does not hold when one takes supervision costs into account. Thus the argument of a trade-off be-tween transaction costs and risk-sharing lacks credibility. Assuming equal transaction costs for all three contracts, sharecropping becomes optimal whenever some risk is involved just as long as it cannot be spread through a mixture of fixed-wage and rent contracts. That is unless some of the agents are risk neutral in which case they should bear all the risk. In other words we would observe fixed-rental (wage) agreements only when the landlord (tenant) is risk neutral. The amount of \"riskiness\" would have no effect on the contractual choice except in so far as one would go from certainty to uncertainty. At the empirical level, the evidence is inconclusive. Cheung (1969), Higgs (1973), Huang (1974), and to some extent Bardhan (1977) present results that are consistent with a positive relationship between risk and the use of sharecropping. On the other hand, Rao (1971), Reid (1973), and Chao (1983) present evidence to the contrary. In the context of franchising, one can imagine that the uncertainty of demand might also make some form of risk sharing appealing. The fact that the \"franchise way\" can reduce the riskiness of going into business for the franchisee is advanced as a major reason for its popularity. A recognizable name which decreases the uncertainty of demand is usually a central part of the franchise package. But the franchisee could pay a fixed lump-sum fee for this input. To justify the use of a share contract, the risk sharing argument has to be that the franchisor and the franchisee want to spread the remaining risk. With a risk-neutral franchisor and a risk-averse franchisee, and given that each party is assumed to be perfectly able to observe the other's behavior, the optimal contract would be a fixed-wage one, with the franchisor insuring the franchisee com-pletely. Thus risk aversion by franchisees is not sufficient for the emergence of share contracts. Both parties must be risk-averse. Then, assuming they are not able to spread risk by mixing fixed-wage and fixed-rental agreements, they both benefit from 12 the insurance that arises from the use of a share contract. Stiglitz (1974), for example, develops this argument. Similarly, in his survey of the principal-agent lit-erature, Rees (1985) provides a discussion of the optimal riskrsharing argument for share contracts. There are many problems with this type of explanation in the context of fran-chising. First, one has to wonder about how reasonable it is to assume franchisors are risk-averse. These are often public firms that have access to financial markets. Only those franchisors that do not have such access, for example small firms with a sin-gle owner-operator, could reasonably be assumed to be risk-averse. Thus one would expect only small firms to use share contracts, while large public firms would choose to vertically integrate, i.e. offer only fixed-wage contracts to downstream operators. But this is not the case. Second, even if one accepts the notion that franchisors and franchisees are all risk-averse, then share contracts would be chosen over fixed-wage and fixed-rent contracts as soon as erg > 0. Since there is always some amount of uncertainty present, share contracts should arise most of the time. Thus these models do not really explain the coexistence of the three types of contracts. In particular, they can not explain why franchisors generally mix franchise and fixed-wage contracts. If franchisees facing a particular franchisor all have identical attitudes with respect to risk, the optimal strategy for the franchisor will be to use a single share contract with all franchisees rather than to spread risk through a combination of fixed-wage and share arrangements. This can be shown straightforwardly. With perfect information the franchisor can enforce the level of k he prefers, Given a known level of T , demand can be rewritten as Xi=x + 6i, i = l , . . . , n (2.4) assuming l\u00C2\u00B1 = I* so that f(T,l*) = x is the same for all outlets. Also at this point, Ci(lf) is known and fixed. Hence assume the costs of distribution, including the cost ^ In a survey published in 1980 by Entrepreneur Magazine, 35% of the franchisors who answered specifically indicated they did not allow absentee-ownership of their franchised outlets. In Venture's \"Franchisor 100\", 38 out of the 100 franchisors reviewed indicated that the franchise had to be the owner's main job. Thus it is true that franchisees are not always able to mix contracts. 13 of providing I*, are given by C{x + Bi) + Ci{V) = c-{x + 6l) + FC (2.5) where c is the constant marginal cost of distribution, and FC represents plus any other fixed costs of distribution. With perfect information, the franchisor knows c and FC so the profits given in (2.2) and (2.3) is rewritten as n n = 53[a-(p-c)( a ! + fli)-rF]-CT (2.6) *i = {1 - a){p - c){x + 6i) - F - FC (2.7) where a represents a royalty rate on \"gross\" profits whereas r was based on sales.^ Competition among potential franchisees should ensure that they get only their opportunity level of utility, u. In the absence of risk, this would imply zero profits, so that the franchisor would demand a fixed fee FQ = (1 \u00E2\u0080\u0094 a)(p \u00E2\u0080\u0094 c)x \u00E2\u0080\u0094 FC. With some positive amount of risk, the fixed fee F will have to be smaller than FQ. In fact, (Fo \u00E2\u0080\u0094 F) will measure the risk premium that the franchisee requires in order to be compensated for the variance in his revenue. This premium can be written as:1*' Pi = |-Var7ri (2.8) where p is the coefficient of absolute risk aversion which is assumed to be the same for all franchisees, and VarTTi = Var[(l - a)(p - c)(x + 0;) - F - FC} (2.9) = (1 - a)2(p - c)2*l (2.10) Since this variance is the same for all franchised outlets, so is the risk premium: P = P-.{l-a)\p~cfal (2.11) ^ Keeping a sales royalty formulation would complicate the algebra without providing more insight. Basically, with royalties on sales, the franchisee bears the burden of the variance in costs on his own. The risk sharing argument cannot justify this. 1 6 See Deaton and Muelbauer (1980), p. 399. 14 Assume that the franchisor chooses to mix contracts, i.e. he vertically integrates with Tii outlets and uses franchise contracts with the others. His total profits are then ni n = \u00C2\u00A3 [ ( p - c ) ( * + * 1 - ) - F ' < 7 ] + \u00C2\u00A3 [a(P-c)(x + 6j) + F}-CT. (2.12) ,7=711+1 t=l For any amount of risk he will have to bear, the franchisor will choose a and n\ so as to maximize his expected profits, where17 E{U) = raj [(p - c)x - FC] + (n - n i ) [ a ( p - c)x + F] - C T But F = (1 - a)(p - c)x -FC - P , so that (2.13) E(U) = m[(p- c)x - FC} + {n - ni)[(p - c)x - F C - P} - C T (2.14) = n[{p-c)x-FC}-(n-n1)P-CT- (2.15) The variance of the franchisor's profit is given by T i l Var(H) = \" c)2*} + \u00C2\u00A3 (a2(p - c)2 0. Share contracts emerge in these circumstances as a compromise between the need to provide the franchisee with insurance and the need for a contract that gives him incentives to work. An example of this explanation for the existence of share contracts is found in Stiglitz (1974). This is also the structure of the basic principal-agent problem surveyed by Rees (1985).21 Clearly, this argument also relies on the idea that franchisees cannot mix contracts, i.e. work for wages part of the time, and under a fixed-rent contract for another part, as a means to obtain insurance. Note that these models do not allow for any monitoring on the part of the franchisor. Mathewson and Winter (1985) show that with any positive amount of non-noisy monitoring, a franchisor can use a forcing contract, i.e. impose such a large penalty on a franchisee caught cheating that truth telling becomes the dominant strategy for the franchisee. The incentive aspect of a share contract becomes worthless in this situation. The franchisor opts for a fixed-wage contract knowing he can enforce the level of U he chooses. This assumes however that these large penalties can be collected. If there exists a binding constraint on franchisee wealth, share contracts 91 There is nothing in the modelling of the principal-agent problem to suggest that the optimal contract should be a simple linear share contract. Often the optimal payment schedule is found to be non-linear and/or discontinuous. However, if one restricts the analysis to the set of linear contracts, as is done for example in Stiglitz (1974), share contracts are then found to be preferable to fixed-wage and rental contracts. Since franchisors use linear share contracts in general, I will concentrate on those here. 18 become optimal again, even in the presence of non-noisy monitoring. One problem with these models is that, like pure risk-sharing models, they lead to a contractual structure that entails only share contracts. Fixed-rent contracts are used only when there is no risk in production. Fixed-wage contracts are observed only in those cases where supervision is costless or there is no binding constraint on the franchisee's wealth. Thus the coexistence of the three types of contracts in reality is not explained by these models either. Nor is the tendency of franchisors to mix fixed-wage and franchise contracts. Consequently, one could say again that these models are rejected by the data on franchising. As in the previous section, if one allows for heterogeneity in franchisees's prefer-ences with respect to risk, and constrains franchisors to use a single franchise contract, then franchisors would mix contracts in the context of these models as well. Given r, in some cases franchisees would be so risk-averse that the benefit in terms of incen-tives that would arise from the use of the share contract would be offset by the high risk-premia they would require. Thus a franchisor would find it in his best interest to hire these people under a fixed-wage contract. In these circumstances, increases in risk given r would lead to more weight on the insurance component of the trade-off and should therefore lead to a greater reliance on company-operated stores. Again future references to one-sided hidden-action models should be taken as references to this modified version of the models. 3.3 Two-sided Hidden-Action Models The third and most interesting explanation of share contracts relies on market imperfections in general, and more specifically on \"hidden-action\" problems on the part of both parties. The advantage of these types of models is that not only can they explain why share contracts occur, but they can account for their coexistence with other contractual forms as well as for temporal and spatial variations in the contractual structure. Again, the models are based on Alchian and Demsetz's (1972) notion that when it is difficult to assess the marginal contribution of an input in a production process, and supervision is costly, one way to make sure the owner of the input has the incentives to provide the efficient level of this input is to make him or her a residual claimant. However, here, more than one agent is responsible for the provision of such inputs. One way to give them both incentives to cooperate and 19 self-monitor is to give them both a share of the output. Thus in such models sharing occurs strictly as a result of incentive problems. Preferences with respect to risk are not involved. In fact, both parties are assumed to be risk-neutral. An example of this view, as it applies to sharecropping, is found in Reid (1977). Eswaran and Kotwal (1985) have formalized this approach in the context of sharecropping. They assume that the agricultural production process requires two inputs for which markets are imperfect, namely supervision and management. Both inputs can be provided by either the tenant or the landlord, but the latter is more efficient in management and the former in supervision. Under a share arrangement, both parties will be allowed to specialize in the activity they are most efficient at. Un-der a fixed-wage contract, landlords must provide both supervision and management, whereas the tenant has to take care of both of these under a fixed-rental agreement. Eswaran and Kotwal then show that the landlord opts for a share contract whenever the gains from having each party specialize in the activity they are best at outweigh the losses that result from the disincentive effects associated with sharing. Which type of contract maximizes the landlord's profits depends on the importance of both super-vision and management in the production process. It also depends on the strength of the landlord and tenant's comparative advantages. Depending on the circumstances, an}r of the three types of contracts may be optimal in the sense that it maximizes the landlord's profits. The coexistence of the three types of contracts in this model is explained by the use of different technologies (i.e. various crops) that affect the importance of the two unmarketed inputs. Changes in the contractual structure occur as a result of technological change. What is interesting is that the model will hold for any two inputs for which markets are imperfect as long as they can only be made available in combination with their owner's time. Both Reid (1977) and Eswaran and Kotwal (1985) view sharecropping as a partnership and emphasize the need for ongoing cooperation between the tenant and the landlord as the basic reason for the use of share contracts. It is worth pointing out that the transactions-cost analysis proposed by Murrell (1983), while different in flavor from this type of model, is consistent with it. In both cases, one compares the properties of the three types of contracts under the constraints imposed by the production process and then determines which one is 20 best. In the case of franchising, assume, as was discussed previously, that the franchisor can not observe or infer the level of l{ provided by franchisees. But now the franchisees can not observe the value of T either (nor the value of any managerial assistance that the franchisor may provide). Rubin (1978) for example points out that the value of the tradename over the duration of the franchise contract depends non-trivially on the ex-post behavior of the franchisor, i.e. on how much effort he will put into advertising and in the monitoring of established franchisees to make sure they do not shirk on quality. Under fixed-rent contracts, and given incomplete contracting in advertising and monitoring, the franchisor would choose the ex-post level of these activities , and hence of T, to maximize the profits he would derive from future sales of franchises. In this maximization the franchisor need not consider the effect his choice of T will have on the performance of all previously established franchisees. Without a type of contract that offers the upstream firm with the right incentives, T will not be chosen optimally in the eyes of the franchisees. Unless they can get some form of assurance that the value of the tradename will be upheld, franchisees will not agree to a fixed-rent contract. Note that a franchisor can show he has incentives to maintain the value of the tradename either by operating a certain proportion of outlets himself, and/or by using share contracts. We now have a bilateral moral-hazard problem. In these circumstances, both the franchisees and the franchisors will need contracts that give them incentives to cooperate and self-monitor. As in Eswaran and Kotwal (1985), share contracts may be chosen by franchisors depending on the importance of l{, T, and possibly the managerial assistance given by franchisors in the downstream demand equation (or production process). This of course will vary according to the kind of product sold. For example, some types of goods require much more personalized services (computer sales for example) than others (fast food). This affects the importance of l{. The choice of contract will also depend on how costly it is to monitor l{ and T . 2 2 For example the buy backs of the early 70's, which occurred mainly in urban areas, could be due to the decrease in monitoring costs associated with an increase in the density of stores in.those areas. The trend towards more franchised units in recent years could be the result of increased distance between outlets which would increase If U can easily be monitored, then the franchisor becomes as efficient as the franchisee in providing it through a hired manager. 21 monitoring cost. Better established reputations could also explain this tendency to franchise more: they reduce the need for the franchisor to guarantee his performance by operating his own stores.2\"' This kind of model has the advantage of being able to account for two stylized facts one finds in the context of franchising. The first is the very infrequent use of fixed-rent contracts. The second is the fact that franchisors only offer two out of the three types of contracts at any point in time. More precisely, they have a single franchise contract that is usually a share contract, although in some cases it is a fixed-rent one, and then they operate some of their stores directly under a fixed-wage contract. The argument in both cases hinges on the input of the franchisor, T. In Eswaran and Kotwal (1985), under a fixed-rent contract, the tenant must provide both unmar-keted inputs (supervision and management in their case). But here, the franchisee can never provide the tradename component of T. The franchisor can provide both li and T if he hires a manager for an outlet. In that case, a fixed-wage agreement is used. Or the franchisor provides T and the franchisee l{, in which case a share contract arises. Since T necessarily comes from the franchisor, as long as it is unob-servable, the contract must give the franchisor incentives to maintain its value. This makes fixed-rent contracts costly. Thus, these contracts will tend to be observed only when the provision of T can easily be monitored. Since that will not be the case in general, one will find mainly share and fixed-wage contracts in franchising. In addition, for a given franchise system, either T is or it is not easily monitored. If it isn't, this firm will have to design its franchise contract as a share contract, while if it is, its franchise contract should be a fixed-rent agreement. Thus we will find each franchisor using a franchise agreement that is either a share or a fixed-rent contract, but never both at the same time.2'* 23 24 The U.S. Department of Commerce establishes these trends in \"Franchising in the Economy\". A question that arises then is why would a firm that opts for a fixed-rent contract ever want to operate stores directly, i.e. under a fixed-wage contract, if its choice of contract reflects the fact that there are no incentive problems on the franchisor's side ? Do they in fact operate significantly less stores than other franchisors do? Results from Chapter 5 suggest that they do. 22 3.4 Capital-Market-Imperfection Arguments The traditional explanation put forward to explain the existence and the use of franchising has to do with franchisors facing a binding capital constraint, and resorting to franchising as a means of obtaining capital. For example, Caves and Murphy (1976) argue that before the tradename is well established or at times of rapid expansion, it is difficult for a franchisor to raise all the capital he needs.2^ Thus he recruits franchisees who invest their own capital in their outlet. Jaynes (1984) puts forth a similar argument in the case of cropsharing: \"The landowner who finds a tenant with a plow and possibly his own team of bullocks may find that offering a share tenancy to this agent is a cheaper way of obtaining this capital than having to risk some portion of his own property as collateral for a loan that would allow him to lease or purchase all the necessary capital inputs himself and to hire wage labor.\" (p. 60) There are several difficulties with such an explanation for franchising. First, if the franchisor's need for capital was the main explanation for the existence of franchising, one should not observe well-established firms using franchising with their new outlets, except perhaps during rapid expansions. According to Caves and Murphy (1976), as the company matures, one would find a trend toward more company operation. It has also been suggested that if capital constraints were the main reason for the existence of franchising, franchisors should ultimately buy back all of their outlets.26 Franchising would simply be a transitional state. But while a tendency towards more company-owned outlets seems to have been observed in the early 70's, according to the U.S. Department of Commerce this trend has reversed itself since the mid 70's. A second problem with this explanation for franchising is that franchisors often provide financing to their franchisees.27 This of course is not consistent with an 2 ^ In the Ozanne and Hunt survey, this need for capital, and the fact that franchisees who own their businesses would manage the outlets better, were the two reasons generally given by franchisors for choosing this arrangement. The fact that 18% of them said they would ultimately prefer to have no franchised outlets is consistent with a binding capital constraint argument. 2 6 See for ex. Hunt (1973), Martin (1987), and Scott (1987). 2 7 In the Entrepreneur's 1986 survey, 228 out of the 968 franchisors who responded said they provide direct financing. 23 explanation for franchising that relies on a binding capital constraint for franchisors. Finally, as Rubin(1978) points out, investing in a single outlet is clearly much riskier than investing in a portfolio of shares from all outlets in a chain. Hence a risk-averse franchisee would require a higher return on his investment in a single outlet, implying that the franchisor could obtain cheaper capital by offering shares of all its outlets to its store managers. Brickley and Dark (1987) use the same argument. However, this ignores the possibility of moral hazard on the part of these managers. If there is an incentive problem at the downstream level, with a portfolio of shares from all stores, we get a standard prisoner's dilemma. Every retailer benefits only marginally from increasing his own /{, so they all set it too low. Knowing this, retailers might well demand a higher rate of return on portfolios, even if they are less risky, than they would for capital invested in a single store that they operate themselves. Hence it is possible that the upstream firm would benefit from cheaper capital through franchising. This would be especially valuable to those firms facing a binding capital constraint. Note however that the existence of a non-observable l{ is central to the argument. In general then, if it allows franchisors to get cheaper capital during periods of expansion, franchising may be more attractive than company-operation at those times and hence firms may use it more. But their need for capital is not necessary to get franchises. It is worth pointing out that an explanation of franchising based on franchisors' capital requirements should lead to fixed-rent contracts since that would guarantee more capital to franchisors faster. In addition, so far, the incentive problems are only on the franchisees' side, and by themselves, those lead to fixed-rent contracts. For share contracts to emerge, incentive problems on both sides, or risk-aversion of the franchisees combined with non-observable are still necessary. With respect to the terms of the share contract, a binding capital constraint for the franchisor should increase the probability that the contract stipulates a large fixed payment and low royalties. 3.5 Self-Selection and Screening Models The fifth class of explanations for share contracts is based on asymmetric infor-mation concerning labor quality and the resulting need for the principal to screen 24 potential agents. The latter have differing abilities with respect to the provision of their input. Thus there is a hidden characteristic problem. Examples of such mod-els in the case of sharecropping include Hallagan (1978) and Newbery and Stiglitz (1979). The existence of different types of contracts in these models forces down-stream operators to reveal information about themselves. The most capable choose a fixed-rent contract and the least capable, a wage contract. Those in between opt for a share contract. An advantage of this kind of model is that it naturally leads to the coexistence of the three types of contracts. In the context of franchising, this would imply that store operators have differ-ential abilities with respect to the provision of Assume that their ability level is in the closed interval [0,L]. If each operator devotes all his or her time to this activity, and there are no additional costs associated with l{, the amount of /{ will vary directly with these people's ability level. Assuming that the franchisees are risk-neutral, they care about their expected revenue. If C(/(T,/;)) \u00E2\u0080\u0094 c \u00E2\u0080\u00A2 f(T,l{) -f FC, the franchisee's expected revenue under the three types of contracts would be given by E{Rf) = w (2.21) E(R?) = {p-c)f(T,li)-FC-FR (2.22) E(R?) = (1 - a)(p - c)f(T,li) - F C - F s (2.23) where w stands for fixed-wage, R stands for fixed-rent and S stands for share contract. Naturally, the fixed fee associated with the fixed-rent contract would be larger than that of the share contract, i.e. FR > Fs- The resulting revenue functions, assuming that / ( T , 0) = 0, are illustrated in Figure l . 2 8 Both Rf and Rf are concave in for all 0 < a < 1, given that / is concave in Zi. Individuals with the ability to provide l{ < A will opt for a fixed-wage contract since their revenues under that scheme are greater than under any of the other arrangements. With U = A, they are indifferent between a fixed-wage or a share arrangement. With the ability to give A < l{ < B, an individual prefers a share contract and naturally for l{ > B, one chooses a fixed rent contract. A more realistic screening model in the case of franchising would have to take into account the unobservability of the value of the franchise as well as that of the potential 2 8 See Hallagan (1978). 25 l<=0 l.=L Figure 1: Contractual Choices as Self-selection Mechanisms franchisee. Most members of this \"industry\" emphasize the need for prospective franchisees to shop around before getting involved with a particular franchisor. The information asymmetry is two-sided. Allen (1982) proposes a model where both land quality and tenants' abilities are unobservable. An adaptation of this model might be more appropriate for the study of franchising. While such self-selection models are interesting, it is difficult to believe that they capture the whole story. For one thing, these models, like those discussed in the previous sections, imply that each franchisor should use a variety of share contracts. Indeed, one would think that franchisors should offer a whole array of contracts, i.e. many share contracts, from those with low royalty rates and high franchise fees all the way to contracts with high royalty rates and low franchise fees, in addition to fixed-wage and fixed-rent contracts. This would allow downstream operators to self-select as finely as possible. Yet, as was mentioned earlier, franchisors offer two types of contracts only, a franchise and a fixed-wage contract. 26 Given the average length of franchise contracts, it is also difficult to believe that a franchisor's goal in offering them is to screen potential franchisees. According to the U.S. Department of Commerce, franchise contracts last for almost 15 years on average. If the various contracts were used so that franchisees would reveal information about their types, one would not expect them to last for such long periods of time. Another problem with self-selection models is that the proportion of franchised stores in a given chain is not the result of a decision the franchisor makes. Instead, it is determined exogenously and depends simply on the distribution of abilities in the population and the random draw of \"potential franchisees\" of this firm. Assuming that n is large enough and that ability levels are uniformly distributed on [0,L], one would find a number of fixed-wage contracts proportional to the distance OA in the diagram, while the quantity of share contracts would be proportional to AB and that of fixed-rent contracts, to BL. The only thing that could affect these proportions across firms would be differences in technology, i.e. in general, differences in the type of activity the firms are involved in. These would affect the importance of k in the production process and thus shift the revenue curves depicted in Figure 1. But the direction in which the proportions of the three types of contracts would vary given a change in the importance of l{ is undetermined. Self-selection models are not very satisfactory when it comes to explaining tem-poral and spatial variations in the contractual mix. Similarly, they can not explain variations in the actual terms of the share contract since these are exogenously given in such models. In the empirical analysis, both the contract mix (i.e. the proportion of franchised stores) and the terms of the share contract (royalty rates and franchise fees) are assumed to be chosen optimally by each franchisor. Thus the empirical work concentrates on the first four types of models and not on the latter. 4. C o n c l u s i o n The aim of this chapter was to provide a general description of franchising. It was also meant to establish the fact that models developed to explain the existence of sharecropping have natural extensions to other types of share contracts, notably fran-chising. Because the models were developed in the context of single principal-agent pairs, they all lead to a single dominant contract, a result that remains unchanged if these models are modified to incorporate multiple principal-agent pairs. As was 27 noted, this was the case for the standard versions of the pure risk-sharing and the one-sided hidden-action models. It was necessary to extend the models in order to get the result that franchisors can operate some of their outlets directly and franchise others. In addition, in theoretical work authors tend to isolate those factors they feel are most relevant to the problem at hand and they abstract from the others. This is generally done for tractability. But in reality, there is no reason for a single explanation of share contracts to dominate all others. While incentive issues might be very important, how much a firm decides to rely on franchising may also depend on its financial constraints and on the amount of uncertainty it faces. The various explanations of the existence of share contracts are not mutually exclusive and thus should not be treated as such empirically. By allowing interactions among the various factors suggested by the theories, it is possible to develop a framework to analyse firms' propensity to franchise. Optimal risk-sharing models and principal-agent models based on \"hidden action\" rather than \"hidden characteristics\" can all be used to explain variations in the contract mix chosen by franchisors. So can imperfect-capital-market arguments. Similarly, all of these have implications concerning the terms of the share contract. They are therefore the models on which the empirical model and analysis will be based. In the next Chapter, I provide a brief review of the existing empirical literature on share contracts, followed by a description of the empirical model. 28 C H A P T E R III A n Empirical Model of Franchising 1. Introduction The purpose of this Chapter is to develop an empirical model for franchising that will allow testing of some implications of the theoretical models just discussed. In the next section, I briefly review some of the existing empirical literature on share contracts. I begin with those empirical papers that have been written in the area of sharecropping. Then I discuss the few papers that have examined some aspects of franchising. . In Section 3, I develop a model aimed at explaining firms' tendency to use franchising which combines the first four types of models discussed in Chapter 2. Next, the model is extended to take into account the fact that franchisors not only choose the contract mix, but also the terms of the franchise contract, i.e. the royalty rate and franchise fee. Section 4 contains a few concluding remarks. 2. A n Overview of the Empirical Literature on Share Contracts 2.1 The Empirical Literature on Sharecropping There exists a relatively large body of empirical literature on the subject of sharecropping. One issue that has received a certain amount of attention at the empirical level is that of the allocative efficiency of sharecropping contracts. In other words, do they lead to different input/output intensities than those that are observed under fixed-rent and fixed-wage contracts?1 Since I am interested in those circumstances under which share contracts arise as the more efficient, albeit second best, arrangement, I will not discuss this literature. A number of other empirical papers have focused on the contract mix and the contractual terms in agriculture. The aim of the following discussion is to provide a general idea of the questions that authors have addressed in such studies as well 1 See for example Shaban (1987) and the references therein. 29 as the problems they encountered. In general, it is worth mentioning that authors have not tried to discriminate among precisely specified models in their empirical work. They have tended to insist on the complementarity of various explanations of sharecropping, rather than seeing them as mutually exclusive models. Thus they mainly searched for patterns that would be consistent with these explanations. The first question that has been addressed empirically in this area concerns the effect of risk on landlords' tendency to use sharecropping. According to the argument suggested by Cheung (1969), there should be a positive relationship between the extent of sharecropping, as a proportion of all contract types, and the amount of exogenous risk in production. Under the pure risk-sharing argument presented in this thesis, it was noted that share contracts should prevail irrespective of the amount of risk present when all potential tenants have the same preferences with respect to risk, and/or when landlords are able to modify r in those cases where tenants' attitudes vis-a-vis risk are allowed to differ. Thus no systematic positive relation between risk and sharecropping is to be expected in either of these two cases. If potential tenants' attitudes with respect to risk are heterogeneous, but landlords are constrained to use a single share contract, then increases in risk, assuming the landlord is less risk-averse than the tenant, would increase the tenant's relative insurance need. This would lead to a shift away from fixed-rent contracts and toward more share and more fixed-wage contracts. Reductions in uncertainty would mean less fixed-wage contracts, and more fixed-rent and more share contracts. Thus no clear correlation, either positive or negative, should be expected between the extent of sharecropping as a proportion of all three types of contracts and the amount of risk in this case either. As was mentioned in Chapter 1, the empirical evidence on the subject remains inconclusive. Cheung (1969), Higgs (1973), Huang (1974), and Bardhan (1977) present evidence of a positive correlation between risk and the use of sharecropping, while Rao (1971), Reid (1973) and Chao (1983) for example find no such support for Cheung's hypothesis. One must however exercise some caution in interpreting these results. Early studies on the effect of risk, for example, Cheung (1969), Higgs (1973), Reid (1973) and Huang (1974), compared the extent of sharecropping in some geographical regions or for different crops to some measure of riskiness, either the variance or the coefficient 30 of variation of yields. Rao (1971) used the variance of profits rather than that of yields. Given the paucity of the data, they could only observe these aggregate measures and were not able to control for other possible effects. Hence, as Huang (1974) points out, Rao's measure of riskiness is more likely to embody \"risk associated with decision-making\" by the tenant and not just exogenous risk. Thus the negative correlation he observes between uncertainty and the extent of sharecropping as opposed to fixed-rent contracts should not necessarily be interpreted in the context of an explanation for share contracts based on risk. Rather it provides evidence that the use of fixed-rent contracts as opposed to sharecropping increases when the managerial talents of tenants become more important. This is clearly consistent with those models that involve some hidden action problem on the part of tenants. Under the risk-sharing argument used in this thesis, if one concentrates on the extent of share contracts as a proportion of fixed-rent and share arrangements only, as Higgs (1973) does, increases in risk should lead to a greater incidence of share contracts. And this is indeed what he finds. Reid's (1973) result of no significant correlation is consistent with this given that he observes acreage under sharecropping as a proportion of total acreage. For the same reason, Bardhan's (1977) result is also consistent with the risk-sharing argument used here. In addition, contrary to earlier studies where authors were unable to control for other effects due to the lack of data, Bardhan (1977) controls for the labor-intensity of crops, the wage level of laborers, and the extent of credit provided by landlords to tenants in his regressions. Chao's (1983) result, hoAvever, which is based on micro-level data, contradicts both Cheung's hypothesis and the pure risk-sharing model described in this thesis. He obtains his result by calculating the average coefficient of variation of rents actually collected over 20 to 30 years by landlords who had two different types of contracts that they used simultaneously on different plots of land. Those were \"pure sharecropping\" contracts, where landlords and tenants each received 50% of the yields, and \"modified sharecropping\". The latter was a transitive type of contract between a pure-share and a fixed-rent contract since it involved a nominal rent, fixed at the level of 50% of the yields in the good years, which the landlord could reduce during \"less-than-perfect\" years. Chao (1983) found that these average coefficients of variation were not different enough to suggest that there existed differences in risk between the two types of plots. 31 Other issues that have been addressed in the empirical literature on sharecrop-ping include the effect of changes in the tenants' exogenous wage rate, the effect of technological change and the effect of supervision costs on contractual choice. In terms of the effect of the exogenous wage rate, as Binswanger and Rosenzweig (1984) point out, there is some consensus to the effect that declining real wages should lead to changes in the contract mix and/or the contract terms that yield either a lower income, or more risk, or more work for the tenants. This is true given the production technology, and the amount of labor used. Thus Clay (1976) reports a case in which declining real wages lead to a shift from harvest share payments for the tenants to payment in cash. There was a shift away from share contracts toward fixed-wage contract. More importantly, this shift resulted in lower real incomes for the tenants. However, in his study of the evolution of the contractual structure in China, Chao (1983) finds that decreases in real wages resulted in a shift from sharecropping to fixed-rent contracts. In his general equilibrium framework, this is explained by the use of more labor-intensive techniques in agriculture as wages fall. More labor-intensive technologies imply more supervision costs, and thus a greater need to provide tenants with contracts that incite them to work, hence a greater tendency to use fixed-rent contracts. Thus, holding the technology fixed, decreases in real wages tend to shift contractual choices toward more fixed-wage contracts. But if one allows for changes in the method of production, the resulting increases in supervision costs would lead to a greater reliance on fixed-rent contracts. With respect to technological change, the empirical consensus seems to be that land-augmenting technological change such as irrigation, and the use of High Yielding Varieties of grains (HYV), generally lead to a shift away from fixed-rent contracts and toward fixed-wage ones. Thus Rao (1975) reports that as a result of the introduction of H Y V and other technological advances, the total area under tenancy, and especially that under share tenancy, declined substantially in the sixties in India. Similarly, Day (1967) finds that sharecropping contracts were replaced by fixed-wage contracts in the post-bellum South as a result of mechanization. These results (as well as Chao's result) are consistent with an explanation of contractual choices based on transactions costs in general, and on supervision costs in particular. By reducing the need for labor and/or labor supervision relative to other inputs such as know-how and capital, mechanization and land-augmenting technological change reduce the importance of supervision costs. Thus they diminish 32 the need to provide tenants with contracts that give them incentives to work: This explanation for contractual choices can also account for the observed tendency of absentee landlords to lease out their land under fixed-rent contracts.2 Since they are not in a position to supervise their tenants, they must provide them with contracts that give them incentives to work. Some empirical studies on sharecropping have focused on the effect of supervision costs directly. These include Alston and Higgs (1982), Alston, Datta and Nugent (1984), and Datta, O'Hara and Nugent (1985). In the first two, the authors use a data set based on a survey of 22 cotton plantations in Georgia undertaken by the U.S. Census Bureau in 1911. Because of the homogeneous nature of the sample, risk and technology can be assumed to be constant across these plantations. Since information about the number of supervisors was collected, the effect of supervision costs can be tested directly. Their results, although inconclusive in some cases, are consistent with the hypothesized relations between supervision costs and contractual choice. In general then, the empirical studies give some support to the notion that as the role of the tenant becomes more important, or harder to supervise, there is a shift towards contracts that give more incentives to work to the tenant. As is illustrated by the discussion thus far, authors of empirical work on share-cropping have focused on explaining the contract mix. The contractual design, i.e. the determination of the sharing rule, has received little attention in the empirical literature. Yet the theoretical models have implications for the terms of the share contract as well as for the contractual structure, if not more so. Because they focus on a single principal-agent pair, most of these models must concentrate of the share parameter as the principal's or the landlord's main control variable. Thus this issue should also be addressed empirically. A major reason for the lack of empirical work on the sharing rule is that it has been found to remain relatively constant, at 50% of gross output, within and across regions, as well as through time. Chao (1983), for example, reports that the division of output was done on a 50-50 basis for more than 2000 years in China, and that, despite a steady increase in population and the corresponding decrease in real wages. In fact, this constancy of the share parameter around one half is one of the four stylized facts Newbery and Stiglitz (1979) suggested theories concerning sharecropping should be See for example Jodha (1984). 33 able to explain. But if the terms of the share contract do not vary, one can not find factors that determine them. Hence the lack of attention in the empirical literature. But while 50-50 splits are common, contract terms do vary within some regions. With the advent of more detailed data sets, and more precisely information on individual plots or contracts, authors have begun to observe these differences. For example, Roumasset (1984) observes that landowners' shares vary substantially in the Philippines. He also finds that these shares are positively correlated with land quality, and negatively related to the relative price of labour. In semiarid tropical India, Jodha (1984) found that the terms of tenancy contracts were fairly flexible. The tenant's share varied between 50 to 75 %. In addition, the rules governing the sharing of input costs and the allocation of by-products varied widely. Thus the common 50-50 split of output can hide many differences in the final shares attributable to each party. Because detailed information concerning individual contract terms is not easy to come by, there are only a few such studies. Similarly, with respect to the contract mix, most of the work has been done on the basis of aggregate data due to the unavailability of micro-level data. Wrhile some micro data sets have now become available (see for example Alston and Higgs (1982) and Chao (1983)), they remain too rare (and often too small) to permit a thorough empirical investigation of the abundant theoretical literature on sharecropping. It therefore appears natural to broaden the scope of these theories to other types of share contracts, as was done in Chapter 2 in the case of franchising, and then test them within these new contexts. If share contracts do exist for similar reasons in different sectors of the economy, these tests should prove useful in enhancing our understanding of these types of contracts in general. While this approach has not been used before, some empirical work has been done on franchising. I now turn to a discussion of these papers. 2.2 Some Empirical Papers on Franchising The main issue that has been addressed in the empirical literature on franchising is whether or not this is just a transitional stage for firms on their way to becoming fully-vertically-integrated chains. This question was first posed by Oxenfeldt and Kelly (1969). In a sense, this has also been an issue in the sharecropping literature. Many have argued that as markets develop, sharecropping becomes unnecessary, and so with time, it should disappear. 34 Hunt (1973) first examined this issue at an empirical level. Based on the data collected in the Ozanne and Hunt (1971) survey, he was able to show that at an aggre-gate level, the proportion of company-operated outlets in fast-food chains increased between 1960 and 1971. In addition, on the basis of chi-square tests on disaggregated data, he found that large chains were more likely than small ones to be increasing the proportion of units they operate directly. He found the same kind of pattern relative to the age of the franchise, i.e. older chains tended to increase their proportion of company-operated stores. Caves and Murphy (1976) also examined this issue. Using aggregate data pub-lished in Franchising in the Economy, they found a trend toward more company-ownership in franchising as a whole. They also noted that reversions to company-ownership, i.e. franchisors buying back franchised outlets to operate them directly, were important numerically. Finally, two recent empirical papers on franchising also investigate the long-term trend in the proportion of outlets franchisors choose to operate. These are Martin (1987) and Scott (1987). Martin (1987) uses data on 772 franchisors classified among sixteen different sectors. Within each of these sixteen sectors, using a logit model, he calculates a franchising lifecycle function, i.e. how the proportion of company-owned outlets varies as a function of the number of years since the firms began franchising. Using these, he derives long-run proportions of company operated outlets for firms in each sector. He then uses these to test alternative explanations for franchising, including the capital-market-imperfection argument. His test in this case is based on the notion that ultimately, this explanation leads to 100% company-operated chains. On the other hand, he suggests that if franchising is used because it provides a better incentive system, then mature chains should be 100% franchised. Finally, he contends that under a portfolio hypothesis, firms should choose an interior solution. As was shown in Chapter 2 however, this statement is mistaken.^ His results indicate that none of the proportions of company-owned outlets converge to one. Thus he rejects the capital-market-imperfection argument and the notion that franchising is a transitory phenomenon. He can not reject his other two hypotheses, i.e. the notions that the chains will ultimately become lOOor that they will converge to some interior solution. ^ See the discussion pp. 13 to 15. 35 Scott (1987) also argues that under the capital-market explanation, firms should reduce their reliance on franchise contracts as they grow and become more mature, but that if franchising is used because it is an efficient incentive device, there should be no such trend toward company-operation as the firm matures. He uses aggregate data from the U.S. Department of Commerce to estimate, using generalized least squares, how the proportion of franchised units varies across sectors as a function of, among other things, the average age and size (number of outlets) of firms in the industry, as well as the average start-up cash and the total investment required. He finds positive coefficients for both the age and size variables (although the coefficient of size was insignificant), and negative signs for the cash and investment requirement, all of which go against the capital-market explanation for franchising. Three other empirical studies, i.e. Goldberg (1982), Brickley and Dark (1987) and Norton (1988), have examined conditions under which firms choose to use fran-chising. They address this problem in a transactions or an agency-costs framework. In his thesis, Goldberg (1982) uses data on 25 companies involved in the restau-rant business between 1960 and 1979.4 Using a logit model, he relates the proportion of company-operated stores to two measures of the extent of the externality outlets impose on each other in a chain by free-riding on the value of the trademark. The higher the value of the tradename, the higher the gains from free-riding and the more costly franchising should be. These two measures of the value of the tradename, i.e. the company's age and the number of outlets, are expected to increase the proportion of company-operated stores. He finds that firms' tendency to own stores increases with their age given the number of outlets, but decreases with the number of stores given the age. Thus depending on which measure of \"maturity\" is preferred, the re-sults are consistent or not with the hypothesis he proposed. He also finds that firms tend to increase the proportion of stores they operate themselves after going public, a result which is consistent with a capital-shortage explanation for franchising. He how-ever cautions against this interpretation stating that the causality is unclear in that case. Firm-specific effects are found to be an important determinant of franchisors' tendency to own stores. In addition, a dummy variable that was given a value of one when the restaurant was classified as a \"coffee shop\" and zero otherwise had a signif-icant positive effect on the proportion of company-owned stores. He interprets this 4 For those companies in the sample that were not in existence in 1960, the data start later. In no cases did it start later than 1969. 36 as an indication that when repeat sales are rare, the externality outlets can impose on each other is greater, and thus company operation becomes preferable. Finally he finds some support for the notion that increased government legislation affects firms' choices with respect to franchising. Norton's (1988) analysis of the benefits of franchising focuses on the differences in agency costs between franchised and vertically-integrated stores. He tests his hypotheses about the circumstances that favor franchising by estimating a logit model where the dependent variable measures the incidence of franchising in three sectors of the U.S. economy, notably Restaurants and Lunchrooms, Refreshment Places and Motels and Tourists Courts. The data he uses are those published in the 1977 U.S. Census of Retailing and in the 1977 Census of Service Industries on an aggregate basis for each State in 1977. There is however a problem with the way he calculates his dependent variable. It is described as the number of franchise holders as a proportion of the total number of establishments in the sector in each State. Given this dependent variable, many of the theoretical arguments he presents have no a priori reason to hold. This is because factors that favor franchising in his discussion also favor the existence and the number of independent retailers in an industry. He argues for example that increased labor intensity leads to greater monitoring costs, so that firms will find it in their best interest to hire someone who specializes in monitoring in each outlet. To prevent this monitor from shirking, they will want to make his revenues depend on his performance. This is what a franchise contract does. Thus he expects to find a higher proportion of franchised outlets in those industries and States where the ratio of employees to sales is greater. But independent retailers also qualify as an efficient way to organize production in these circumstances. If their number grows faster than that of franchised outlets, then the proportion of franchised outlets overall in the industry in the State would be reduced.^ Consequently, the interpretation he gives of his empirical results is problematic. Finally, Brickley and Dark (1987) concentrate their empirical work on the effect of monitoring costs, repeat business and initial capital requirements on franchisors' decision to operate or franchise each individual outlet. They obtained information from 36 franchisors concerning, for each outlet, whether it is franchised or owned, and ^ While most of the arguments he gives would tend to favor both franchising and independent operators simultaneously, his argument concerning the value of the trademark would tend to favor chains in general, i.e. both franchised and vertically integrated ones. 37 the distance to the nearest headquarters. They found that on average, outlets that were controlled by the franchisor were significantly closer to headquarters than those that were franchised. If distance increases monitoring costs, this result supports the notion that firms opt for franchise contracts, i.e. contracts that provide more incentives to the outlet operator and thus reduce the need for monitoring, in those cases where monitoring costs are high. The authors also partition a larger sample of firms (143) into two groups on the basis of whether or not they operate in an industry characterized by repeat business. They define nonrepeat sectors as those that serve mainly transient populations, i.e. Restaurants, which are mainly fast-food outlets, Car Rental stores, and finally Motels and Hotels. They find that the average proportion of franchised stores is significantly greater for the group of firms that operate in the repeat business sectors than for the other group, thus confirming their hypothesis. In addition, they test the notion that due to inefficient risk-bearing, franchising should be used less when the initial capital requirement is high. They also find some support for this argument. In general, these empirical studies on franchising, like those that have been done on sharecropping, have been constrained by a lack of available data. In most cases, authors have used aggregate data, and in those cases where information concerning individual franchisors was collected, the number of firms and/or the type of infor-mation was quite limited. In some cases, the hypotheses being tested, and the way in which they related to the theoretical literature, were not well defined. Finally, these papers have all addressed the question of the contractual mix. None has inves-tigated the terms of the franchise contract. In the next section, I present a model of franchising, based on profit maximisation, that relates franchisors' choices concerning the contract mix and the terms of the franchise contract to the theoretical literature discussed in Chapter 2. 3. The Empirical Model In this section, I develop the empirical model that will allow me to test predictions from the first four types of theories of share contracts presented in Chapter 2. This is done first with respect to firms' decisions about the contractual mix, and is then extended to take into account their choices concerning the design of the franchise contract. 38 In developing their models, theorists can choose those aspects of a problem they feel are most relevant, and abstract from other considerations they think are not as important. This makes their problems more tractable. Empirical work can contribute to this process by indicating which factors may be relevant and what questions deserve some further attention. As was seen in the previous chapter, many different types of models of share contracts are found in the theoretical literature. They all point to different factors that should influence the incidence of share contracts. As Singh (1987) points out in his review of the literature on sharecropping: \"Having gone through the various models (...), we do not \"pick a winner\". This is because we do not think that there is a single explanation, no matter how ingenious or complicated, of the exis-tence of share contracts or sharecropping.\" (p. 4) Similarly, the goal of this empirical analysis is not to \"pick a winner\". Rather its purpose is to examine whether the various factors theorists have examined as potential reasons for the existence of share contracts seem to be relevant when it comes to explaining the use of a particular type of share contract, namely the franchise contract. There is no reason to expect these explanations to be mutually exclusive. Thus whereas in the theoretical literature these factors are treated in isolation, I want to allow interactions among them to see whether their effects on firms' tendency to use franchising, and on the way they design their franchise contracts, is consistent with the various theories. For that reason, the empirical model will embody simultaneously all the factors suggested by the first four types of theories discussed in Chapter 2. In this way, other effects will be controlled for when the empirical results are contrasted with predictions from the various models. It is important to point out again that while franchise arrangements are mainly share contracts, some franchisors choose to use a fixed-rent contract, so that the roy-alty rate r is nil in some cases. No firm ever employs the three types of contracts simultaneously. Empirically then, fixed-wage contracts (company-operated outlets) will be compared to a spectrum of share arrangements that include fixed-rent con-tracts as a special case.6 Any of these gives more incentives to the franchisee, and A test will be performed to determine whether or not franchisors that opt for a fixed-rent contract rather than a share contract should be treated separately from the others. 39 less so for the franchisor, than a fixed-wage contract would be. They also reduce the amount of risk faced by the franchisor. 3.1 Franchisors' Choices of Contractual Mix One of the peculiarities of franchising exploited here is that the majority of franchisors operate \"mixed systems\", i.e. both company-operated and franchised units. As noted by Caves and Murphy (1976), the fact that franchisors were willing to give their views on the optimal number of company-operated outlets in the Ozanne and Hunt (1971) survey indicates that they consider this to be a choice variable. This proportion of franchised outlets varies significantly across franchisors. Consider an upstream firm that produces a homogeneous product under a trade-name. As a consequence, this firm possesses some market power. It can distribute units of this good either through company-operated or through franchised stores. Consumers do not differentiate the two types of outlets so there is a single demand for this firm's product, given by the sum of the individual demands at the outlet level. It will depend on the price at which the good is sold, p, which is assumed to be the same across all outlets of a given franchisor, on the value of the tradename T, and on the provision of local inputs Z{. Franchised outlets all operate under the same linear contract with a share parameter equal to r, and a franchise fee of F? In other words, the franchisees pay an amount given by vp-Xi+F = r-P-(f(T,h) + 6l) + F (3.1) to the franchisor. The upstream firm is the one who chooses F and r. Given that the two types of contractual arrangements lead to differences in the amount of risk the franchisor faces, in the amount of supervision he must perform, in the cost of capital, etc., the sale of one unit of the good will contribute differently to the franchisor's profits (or utility) depending on the contractual arrangement under which it is sold. One can think in terms of a shadow price pc associated with each of the qc units sold through company-operated outlets, where qc = ^ \" I j A'j. There would be a different shadow price p/ for the qj units sold through franchised outlets, 7 Again, since the fixed fee is for the duration of the contract, which lasts for almost 14 years on average, if Xi is interpreted as yearly sales for example, F would refer only to that portion of the fixed fee that is attributable to a year. 40 where 0, and the fixed-wage contract to r = 1, F < 0. If they were, the two-stage procedure would not be justified. But with their fixed-wage contract, the landlord provides both unmarketed inputs and in the fixed-rent contract, the tenant does. Hence they are not simply special cases of the share contract, the latter having both the tenant and the landlord specializing in the activity for which they have a comparative advantage. In the data on franchising however, fixed-rent contracts are taken to be a special case of franchise contracts, with r = 0. 46 have the following reduced form equations for the two fees: r = r(Iu,Ii,IT,IK) (3.19) and F = F(Iu,It,IT,IK). Substituting (3.19) into (3.16) and (3.17) gives (3.20) GF(IU,IHIT,lK) (3.21) GC(IU,II,ITJK) (3.22) so that Qf[h,Il,lT,lK)- (3.23) Q* In this case, we have equations (3.19) and (3.20) to estimate together with (3.23). Since the few theoretical papers that have been written on franchising, i.e. Rubin (1978), Blair and Kaserman (1982), and Mathewson and Winter (1985), do treat r and F as decision variables of the franchisor, some of their results concerning the choice of contractual parameters can be tested here. For example, Blair and Kaserman (1982) argue that a greater value of the brand name implies that future demand relies heavily on the franchisor's future behavior. Their model predicts that the optimal level of the variable fee should be larger, and thus the fixed fee lower, for these franchisors than for those whose brand name is not as valuable. In fact, anything that increases the franchisor's tendency to shirk is expected to lead to more reliance on the variable fee, and a correspondingly lesser reliance on the fixed fee. Anything that increases the probability that the franchisee will cheat would have the opposite effect. This is consistent with Rubin (1978) and Eswaran and Kotwal (1985). Since Ji and IT are meant to capture exactly those factors that affect both parties's incentives, the estimation of (3.19) and (3.20) provides an empirical test of these results. The estimation of (3.20) also provides an implicit test of the assumption that is maintained in deriving it, i.e. the idea that no rents are left downstream and that franchisees are held at their opportunity level of utility. It is important to notice again that the theoretical models on which the construc-tion of (3.19)and (3.20) is based generally imply a different optimal share contract for each principal and agent pair. This is clear for example in the risk-sharing argument 47 since the optimal share is a function of the principal and agent's risk-aversion parame-ters.1^* It is also quite obvious in the Eswaran and Kotwal (1985) model. The optimal share contract is chosen as a function of the individuals' abilities, the importance of their inputs, etc. Thus a different optimal share contract would obtain whenever the individuals under consideration differ. Yet this is not what is observed in franchising. Each franchisor establishes a single franchise contract, and uses it with all of its fran-chisees.11 As was mentioned in Chapter 2, one of the puzzles authors have tried to address in the sharecropping literature has been the relative constancy of the share parameter around 50%. Here, share contracts vary across franchise chains, but the same contract is used for all the franchisees of a given franchisor. One way to explain this, given existing theories, would be to assume that the outlets and outlet operators a firm faces are similar enough that different share contracts are not necessary. This is clearly unsatisfactory. The use of a single share contract by franchisors could also be rationalized if differences in the parameters of the problem tended to give relatively similar results in terms of optimal share, as in Eswaran and Kotwal (1985). The fact that firms belonging to the same franchise sector offer different share contracts goes against both of these arguments. Another way to explain this behavior would be to suppose that the development of a franchise contract is not costless. So while franchisors may feel it worthwhile to develop different contracts for very different types or sizes of businesses, it is easily conceivable that it may not be worth doing for each franchisee. Thus the franchisor chooses an \"average\" optimal share contract for all of its franchisees, and a fixed-wage contract. As was noted in the context of the pure risk-sharing and the one-sided hidden-action models in Chapter 2, the fact that each franchisor's franchise contract would be an \"averaged\" one would in general affect the value of selling units through franchises, pf, and would alter the optimal choice of contract mix. In other words, some of the adjustments for differences among outlets or among outlet operators would then be done through the company-own or franchise decision rather 1 0 See Stiglitz (1974) and Rees(1985). 1 1 There are some exceptions, i.e. some franchisors offer various contracts to franchisees. These are usually associated with different types or sizes of businesses. For example, restaurant franchisors may offer a different type of contract to a franchisee for a full fledged restaurant than for a small satellite operation. These are referred to as \"different franchise packages\". When this happened in the data, the average royalty rate or franchise fee demanded was used on the basis that these should apply to the average type of outlet. 48 Figure 2: The Trade-Off Between the Two Decision Variables, r and q//Q than modifications of the terms of the contract. If one takes for granted the notion that F is determined as a residual, given r, the franchisor controls two major variables with respect to his contractual relations with his franchisees: the proportion of franchised stores and the share parameter, r. Since the same explanatory variables are found in (3.19) and (3.23), it is clear that in response to differences in any of these variables, either r and/or the proportion of franchised stores can be modified. Thus franchisors can trade off one for the other. This is illustrated in Figure 2. Assuming, for example, that all outlets are equally risky, the total amount of risk the franchisor faces will be proportional to the shaded area, given that he has chosen r* and q*f/Q* on the graph. A franchisor that would find a higher degree of risk more profitable to him could achieve it by choosing a higher royalty rate with q*j/Q* the same, or by reducing q//Q for the same r*, or through any combination of the two. Hence any movement in the directions shown by the arrows would achieve this goal.12 12 This assumes that starting from a given point, r* and q~f/Qa firm that would now want to bear more of the risk, will not choose to move in a direction that will decrease this risk on one 49 In terms of individual franchisees, of course, changes in r are not equivalent to changes in qf/Q- But in terms of the amount of risk the franchisor must contend with, there is clearly a trade-off. And the franchisor is the one who chooses the contract mix as well as the terms of the contracts here. Similarly, from the point of view of the franchisor, the amount of incentives provided to downstream operators in the chain is proportional to the unshaded area. In order to increase this \"total amount of incentives\" downstream, movements in any direction opposite to the arrows will be sufficient, i.e. an increase in qf/Q and/or a decrease in r. If the former is chosen, a greater number of store operators will have a kind of contract that incites them to work more. In the latter case, those who were already getting a share of the output will now get an even larger share, which means their contract will incite them to work even more than before. This relationship between contract mix and contract terms has also been noticed in the study of sharecropping. For example, Binswanger and Rosenzweig (1984) remark that \"It is not known why, for example, in certain areas adjustments typically take the form of changes in contract terms whereas else-where terms remain unaltered but there are shifts in the relative importance of different types of contracts.\"(p.31) Also, Chao's (1983) explanation for the constancy of the terms of the sharecropping contract, at 50-50 for over 2000 years in China, was based on the argument that landlords and tenants adjusted to change by modifying the amount of land and labour they provided under share contract, rather than by changing the contract itself. Table 3.1 summarizes the expected effect of each of the indices on qf/Q under the various theoretical models discussed in Chapter 2. It is important to point out again that the various explanations for share contracts put forth in the literature are not mutually exclusive. This can be seen here in the fact that there are no conflicts among the signs of the various indices across models. The effects of the same indices on r and F are readily inferred from the table. The previous discussion implies that with endogenous fees, increases in r and reductions in of the two instruments and then move in the direction that increases the risk it faces using the other instrument in such a way as to more than compensate for the reduction in risk induced by the first movement. In any case, this would not be possible in a context where r and qf jQ were treated independently. 50 Table 3.1 Expected Effects of Indices on qf/Q in the Various Models Model In h IT IK Pure Risk-sharing One-sided Hidden-action \u00E2\u0080\u0094 + Two-sided Hidden-action + \u00E2\u0080\u0094 Capital-market Imperfection (-) + (-) + * Assuming the franchisee is the more risk-averse party. Note: Parentheses indicate that one and/or the other effect should occur. q//Q are to some extent equivalent ways for the franchisors to deal with differences in the indices. Thus those things that would tend to increase qf/Q should reduce r, and vice versa. In addition, F is taken to be a residual given r, so that those circumstances that would lead to a lower royalty rate should also increase the optimal value of F. Consequently, the effects of the indices are expected to be in the same direction for qf/Q and F, and in the opposite direction for r. 4. Conclusion From the brief review of the existing empirical literature on share contracts presented here, it is clear that there is still much to be done in terms of evaluating the abundant theoretical literature on this subject. Firstly, theoretical models have tended to focus on single principal-agent pairs and as a result, the comparative statics results that arise from this literature concern mainly the variable fee, r, and, by extension, the fixed fee F. Due to the unavailability of data on contract terms, empirical work on the other hand has focused on the observed contract mix. In reality, franchisors make decisions with respect to both the terms of the share contract, and the extent to which they want to utilize share contracts. This should be taken into account in the theoretical as well as the empirical literature. In addition, it was seen that the way in which the hypotheses being tested relate to the theoretical literature was not always well defined. The intention behind the 51 development of the empirical model in the second part of this Chapter was to provide a more systematic framework with which one could interpret the estimation results to come. Finally, it is clear that the limited amount of data that have been available has imposed major constraints on empirical work in this area. Thus one of the tasks involved in this thesis was the construction of a new micro level data set. In other words, information on individual franchisor's proportion of franchised outlets, royalty rate and franchise fee, as well as data on factors that are likely to affect these according to the theories, had to be gathered. Given that this type of data set has not been available before, I provide a fairly detailed description of it in the next Chapter. 52 C H A P T E R TV The Data: Sources and Characteristics 1. Introduction The first part of this Chapter is concerned with the way in which the final sample of 548 U.S. franchisors to be studied in the empirical analysis was arrived at. It also describes the main sources of data that were used. The next section contains a rather detailed statistical summary of the data. Both the type of information that has been obtained at the level of the individual franchisor, and the relevant data that are only available on a sectoral level from the U.S. Department of Commerce, are discussed. This is intended to provide information on the sample of franchisors studied here, as well as some stylized facts about franchising in general. Concluding remarks are found in Section 4. 2. The Sample of Franchisors Traditional product franchising, such as auto and truck dealerships, gasoline stations and soft-drink bottlers, in which the franchisor-franchisee relationship is limited to the sale of a given product under the franchisor's tradename, is still very widespread. According to the U.S. Department of Commerce, it accounted for 74% of all sales done through franchising in 1985 (but only 26% of all franchising employment). However most of the growth that has occurred since the 1950's has been attributable to business-format franchising, i.e. those franchises in which franchisors offer a complete system of operation and ongoing support to franchisees. This is probably why most surveys on franchising focus on format franchising. The following data having been compiled from such surveys, they are also restricted to business-format franchising. Because traditional product franchises do not in general involve the payment of a franchise fee up front or the payment of royalties, they could not have been included in this study in any event.1 1 Instead, as was discussed previously, the franchisor is the sole supplier to his franchisees, so he can rely on input mark-ups as a source of revenue. Franchisees are not capable to substitute away from these inputs, therefore no distortions result from mark-ups in this case. 53 The data set used here in fact consists of a cross-section of business-format franchisors in 1986. The main source of these data was Entrepreneur Magazine's \"1986 Franchise 500\" survey which was published in January 1987. It provides data on 1110 franchisors.2 Exclusions from this data base were made as follows. Seven firms were excluded because they reported no outlets in 1986. Further, 40 reported only one outlet, either company-operated or franchised. Since such firms did not really qualify as \"chains\", they were removed from the sample. An additional 23 firms were discarded because of inconsistencies in the reported data on the number of outlets, the fees, etc. Three more companies were excluded because they were not really engaged in franchising as defined here.\"* Of the remaining 1037 franchisors, 22 based their royalties on something other than their outlets' sales or gross revenues. Since I was interested in analysing contractual design using precisely these data, all such firms were eliminated: . they do not have a royalty rate that can be compared to that of the other firms in the sample. There remained 1015 firms of the original 1110 after these exclusions. It is worth noting that 15 of the 22 firms just mentioned extracted royalties on a per unit of output basis. As was mentioned previously, this is equivalent to levying royalties on sales if the price of output at the downstream level is controlled by the franchisor. Assuming a per unit fee of \u00C2\u00A3 dollars, and a fixed price of p, the equivalent royalty rate is simply tjp. Thus these firms calculate their royalties on something which is similar to sales. Only the remaining 7 franchisors based their royalties on a notion of profits. That such an overwhelming majority of firms, i.e. 1001 out of 1008, ask for a percentage of sales or a royalty based on output rather than a proportion of profits is an interesting empirical fact. A survey published in 1985 by the Association of Canadian Franchisors found a similar regularity. 87% of the franchisors in their sample assessed royalties on the basis of outlets' sales; less than 9% based them on profits; the others calculated royalties on the basis of commissions (i.e. another notion of total revenues), purchases (i.e. input sales), or on the number of stores operated by the franchisee. The theoretical models discussed previously cannot account for ^ This number excludes the four companies which were surveyed but were subsidiaries of other surveyed firms. Their outlets were already accounted for by the parent company. They are Sunshine Polishing Systems, MicroAge Canada, Baskin-Robbins Ice Cream Silcorp and Minimaid/Minimenage. ^ Those were USBL, a sports franchise, Western Temporaries and Foremost Liquor Stores. 54 such constancy in franchisors' behavior: royalties on sales and royalties on profits are equivalent in the models. Firms that reported no franchised outlets in 1986, i.e. those that were wholly company-operated chains, were excluded as well. Only 29 of those were included in the survey, 6 of which would have remained in the final sample once additional information had been gathered. So even though it would have been interesting to have fully-company-operated firms in the sample, they were very underrepresented here and I felt it best to exclude them altogether. Two firms were also added to the sample.4 These firms were not seeking franchisees in 1986 and so did not respond to Entrepreneur's survey. They were put back in the sample since data were available for them in the \"1985 Franchise 500\" and other sources. Complete information concerning royalty rates, franchise fees, advertising fees and franchised and company-operated outlets in 1984, 1985 and 1986 was available for 913 of the resulting 988 franchisors.5 For each of these 913 firms, the survey also provided information about the year the}' had begun their operations and the year they had begun franchising. Whether or not franchisees are required to have previous experience in the business and whether the franchisor provides financing to his franchisees was indicated as well. However, 23 of those 913 firms were found to have no franchise fee and no royalty rate, even taking into account future fixed payments and advertising fees. Some of these were contacted by phone. At Lindal Cedar Homes for example, I was told that the company was not really involved in franchising. They were looking for dealers and franchise surveys were a good way to get exposure. They added that in order to be able to demand either a franchise fee or royalties, they would have to go through the paper work required by the various State laws on franchising in the U.S. and they did not feel it was worth it. In other words, there are costs associated with becoming a franchisor. At Champion Auto Stores, I was told the firm made money by selling inputs to its franchisees who were not, however, required to buy from it. Antitrust laws in general do not allow such requirements.6 Assuming that these firms get all of their revenues from dealers through the use of 4 These were Burger King and Ken's Pizza. 5 The 1986 and 1987 Franchise Annuals were used to get some of this information when it was missing in the survey. 6 See Brickley and Dark (1987). 55 input mark-ups, do they belong in the sample of franchisors studied here? Under the conditions discussed in Chapter 2, the sale of inputs at a price higher than marginal cost can be equivalent to royalties on sales. However these conditions are rather stringent. In particular, it is necessary for the downstream firm to produce with a fixed-proportions technology or for the upstream firm to control 100% of the inputs used at the downstream level. Any possibility of substitution at the downstream level would lead to distortions that would make input mark-ups less efficient than royalties on sales or profits.7 Consequently one would expect royalties on sales to be preferred by upstream firms. In addition, to get the equivalence between royalties based on output and roy-alties on sales, it is necessary that the price at the downstream level be controlled by the franchisor. In his analysis of 172 franchise agreements, 60% of which were for fast-food franchises, Udell (1972) found that 28% of contracts contained a clause stipulating that the \"franchisor controls the prices franchisee may charge\". Ozanne and Hunt (1971) found direct price control clauses in only 14% of the 121 fast-food agreements they examined. However, Caves and Murphy (1976) discuss the possi-bility that franchisors often control franchisees' prices through the price information they include in their advertising. Thus the conditions that are necessary for input mark-ups to be equivalent to royalties on sales may hold in some cases, but in general, input mark-ups will not be equivalent to royalties on sales.8 Consequently, it is not clear whether these firms' franchisees can be considered to be operating under a share contract, and if they are, what the parameters of that contract would be. Since the purpose of this study is to analyse the use and design of share (or fixed-rent) contracts as opposed to fixed-wage contracts, it was decided to exclude them from the sample. Finally, additional information on the number of States in which each franchisor has outlets, the number of outlets outside the home country, and the length of the initial training period was found in Entrepreneur Magazine's 1987 Franchise Yearbook 7 See J.M. Vernon and D.A. Graham (1971), R. Schmalensee (1973) and F.R. Warren-Boulton (1974) among others on the related question of the variable proportions incentive for vertical integration. R 0 Of course, if there is a cost involved in the use of royalties, as indicated by Mr. Lindal of Lindal Cedar Homes, this inefficiency may not be sufficient to insure that we do not observe input mark-ups rather than royalties. Champion Auto Stores is a case in point. 56 and the United States Department of Commerce's Franchise Opportunities Handbook for 1985 and 1986. Because of coverage problems, this further reduced the sample size from 890 to 548 franchisors. Table 4.1 gives a general idea of the coverage of this final sample of 548 fran-chisors. To produce its yearly publication, Franchising in the Economy, the U.S. De-partment of Commerce mails questionnaires to all known American business-format franchisors. In 1984 they received replies from 1942 franchisors. In 1985, 2090 fran-chisors responded. In both cases it was estimated that these franchisors accounted for 99% of all business-format franchising sales and establishments in the U.S. The distribution of all the franchisors surveyed, by sector and number of establishments, is published in Franchising in the Economy. Using the 1985 numbers as a descrip-tion of the whole U.S. franchisor population, it is therefore possible to calculate the proportion of this population that is accounted for in the final sample of 548 firms. The first column in Table 4.1 presents the number of franchisors included in the sample (N). The sectors, numbered 1 to 14, are those defined by the U.S. Department of Commerce in Franchising in the Economy. All franchisors in the sample were classified by the author in one of these 14 sectors; the Department of Commerce does not provide lists of the firms included in each of its sector. The total number of franchisors in the U.S., and the proportion of U.S. franchisors included in this sample are found in the second and third column respectively. Note that fewer size cohorts are found in some sectors than in others. In a few cases this is due to the way the data were published in Franchising in the Economy. In other cases size cohorts were combined by the author in order to eliminate those for which the number of franchisors in the sample was nil. Table 4.1 establishes clearly that the sample of firms studied here is biased towards large firms in the sense that a higher proportion of those are included in the sample. In fact, the proportion of firms in the sample tends to grow steadily as the size of the chain increases. This is not too surprising given the sources of the data. The probability that Entrepreneur is aware of the existence of a franchisor, and the probability that firms will respond to such a survey could easily grow with the size of the firm. The same is true for the ancillary sources of information that were used to complement the data set. The fact that firms with only one outlet were eliminated from the sample certainly contributed to this bias as well. 57 Sectors and s i z e cohorts Total U.S. N Franch. % 1- AUTOMOTIVE PRODUCTS 45 172 26, .2 0 - 10 OUTLETS 6 57 10. ,5 11 - 50 OUTLETS 19 57 33 .3 51 - 150 OUTLETS 12 30 40. .0 151 - 500 OUTLETS 5 15 33. .3 501 - 1000 OUTLETS 1 4 25. .0 10O1 + OUTLETS 2 9 22. .2 2- BUSINESS AIDS AND SERVICES 96 421 22. .8 0 - 10 OUTLETS 16 166 9 .6 11 - 50 OUTLETS 36 150 24. .0 51 + OUTLETS 44 105 41 . 9 3- CONSTRUCTION & MAINTENANCE 50 183 27, .3 0 - 10 OUTLETS 12 50 24 ,0 11 - 50 OUTLETS 12 80 15. .0 51 - 150 OUTLETS 7 28 25. .0 151 - 500 OUTLETS 11 16 68. 8 501 + OUTLETS 8 9 88. .9 4- CONVENIENCE STORES 8 27 29. .6 o - 50 OUTLETS 2 11 18. .2 51 - 150 OUTLETS 3 5 60. .0 151 - 1000 OUTLETS 2 8 25. ,0 1001 + OUTLETS 1 3 33. .3 5- EOUC PRODUCTS & SERVICES 29 75 38. ,7 0 - 10 OUTLETS 8 30 26. 7 11 - 50 OUTLETS 12 25 48. 0 51 - 150 OUTLETS 2 12 16. ,7 151 - 500 OUTLETS 5 5 100. 0 501 + OUTLETS 2 3 66. 7 6- RESTAURANTS 121 470 25. 7 0 - 10 OUTLETS 13 141 9. 2 11 - 50 OUTLETS 39 191 20. 4 51 - 150 OUTLETS 28 68 41. 2 151 - 500 OUTLETS 19 40 47. 5 501 - 1000 OUTLETS 13 17 76. 5 1001 + OUTLETS 9 13 69. 2 7- HOTELS. MOTELS & CAMPGROUNDS 10 43 23. 3 0 - 150 OUTLETS 2 30 6. 7 151 - 500 OUTLETS 5 8 62. 5 501 + OUTLETS 3 5 60. 0 Sectors and si z e cohorts Total U.S. N Franch. % 8- LAUNDRY & DRY CLEANING 3 18 16 .7 0 - 150 OUTLETS 1 14 7 . 1 151 + OUTLETS 2 4 50 .0 9- RECREATION AND TRAVEL 11 43 25 .6 0 - lO OUTLETS 2 14 14 .3 11 - 150 OUTLETS 5 19 26 .3 151 + OUTLETS 4 10 40 .O 10- AUTO & TRUCK RENTALS 6 26 23 . 1 0 - ISO OUTLETS 2 12 16 .7 151 - 1000 OUTLETS 2 9 22 .2 1001 + OUTLETS 2 5 40 .0 11- EQUIPMENT & TOOL RENTAL 1 31 3 .2 12- NON-FOOD RETAILING 99 329 30 . 1 0 - lO OUTLETS 13 108 12 .0 11 - 50 OUTLETS 33 1 10 30 .0 51 - 150 OUTLETS 25 62 40 .3 151 - 500 OUTLETS 20 30 66 .7 501 - 1000 OUTLETS 5 lO 50 .0 1001 + OUTLETS 3 9 33 .3 13- FOOD RETAILING - NON-CONV. 52 177 29 .4 0 - 10 OUTLETS 9 62 14 .5 11 - 50 OUTLETS 20 61 32 .8 51 - 150 OUTLETS 11 28 39, .3 151 - 500 OUTLETS 6 17 35 .3 501 \u00E2\u0080\u00A2 OUTLETS 6 9 66. .7 14- MISCELLANEOUS 17 75 22. .7 0 - 10 OUTLETS 1 34 2. .9 11 - 50 OUTLETS 7 26 26. .9 51 - 150 OUTLETS 2 6 33, .3 151 - 500 OUTLETS 6 6 100. .0 501 - 1000 OUTLETS 1 3 33. 3 ALL SECTORS 548 2090 26. .2 0 - 10 OUTLETS 80 686 11. ,7 11 - 50 OUTLETS 186 761 24. .4 51 - 150 OUTLETS 117 319 36. ,7 151 - 500 OUTLETS 99 204 48. .5 501 - 1000 OUTLETS 36 67 53. ,7 1001 + OUTLETS 30 53 56. .6 There is no reason to expect this bias in the sample to affect in a systematic way the distribution of any of the main variables of interest here, i.e. the proportion of franchised outlets, the royalty rate and the franchise fee. The observed stratification is in terms of exogenous variables only. The descriptive statistics that follow however are dependent upon the sample itself, which with 548 firms, represents 26% of the whole population of franchisors. 3. Some Interesting Descriptive Statistics This section contains a statistical summary of all the data used in this research. First, the data available for each franchisor in the sample of 548 firms are described with the aid of Tables 4.2 to 4.7. For all these tables, except Table 4.6, individ-ual franchisors were again grouped into the 14 major franchising sectors denned in Franchising in the Economy. Information for subsectors with a reasonable number of firms is provided as well. However these subsectors are not meant to account for all the firms in the original main sector. Data that could only be obtained on a sectoral basis from the U.S. Department of Commerce, and that were found to be relevant to this study, are presented in Tables 4.8 and 4.9. 3.1 The Number of Outlets Table 4.2 gives a description of the distribution of the total number of outlets, either company-operated or franchised, among franchisors in the various sectors. It also indicates the total number of outlets and franchisors (N) covered by the sample. Not surprisingly, the franchisor with the most outlets is found in the Hamburger category, and it is McDonald's. This is also the category with the largest average number of outlets. The smallest average numbers of outlets per franchisor are found in the sectors of Tune-up and Educational and Training programs.9 On average, franchisors in the sample had about 273 outlets in 1986. This is rather large and clearly affected by the presence of very large chains in the sample. The median number of outlets is about 54. This table also provides information on how long, on average, these firms have been in business (column 7) and how long they have been franchising (column 8). 9 As was previously discussed, all firms with only one outlet were eliminated from the sample, which explains why the minimum number of outlets is two. 59 Table 4.2 : Number of O u t l e t s f o r the 54B F r a n c h i s o r s Sectors TOTAL OUTLETS OUTLETS OUTLETS OUTLETS YEARS YEARS % TIME OUTLETS in 1986 In 1986 In 1986 In 1986 In BUS. FRANC. Not N i n 1986 Mini mum Maximum Mean St. Dav. Mean Mean FRANC. 1- AUTOMOTIVE PRODUCTS 45 7407 3 20O6 164 .6 392 .2 19 .7 11 .5 0.321 PARTS AND SERVICES 10 2462 3 1706 246 .2 521 .3 34 .6 14 .5 0.422 BRAKES, MUFFLERS ft SHOCKS 7 2957 5 2006 422 .4 742 . 1 15 .9 13 .7 0. 199 TRANSMISSION 6 44 1 7 142 73 .5 55 .9 18 .8 14 .5 O. 189 TUNE-UP 1 1 670 9 322 60 .9 90 . 1 9 .8 7 . 7 0.225 2- BUSINESS AIDS ft SERVICES 96 19593 3 6597 204 . 1 705 .4 14 .9 9 .5 0. 336 ACCOUNTING AND COLLECTION 19 2354 4 885 123 .9 212 .5 15 .7 10 .5 0.324 EMPLOYMENT SERVICES 20 1396 3 439 69 .8 1 10 .5 20 .6 13 . 4 0.390 PRINTING AND COPYING 14 4126 17 1081 294 .7 373 .2 14 .7 1 1 . 1 0.271 REAL ESTATE 8 9285 13 6597 1160 .6 2255 .8 14 .5 9 . 1 0.226 3- CONSTRUCTION ft MAINTENANCE 50 12922 2 3365 258 .4 530 .8 14 .8 9 .8 O. 294 MAID SERVICES 8 811 4 320 101 . 4 115 O 9 .0 6 .4 0.292 CONSTRUCTION 13 1253 9 4O0 96 .4 124 .4 13 .8 7 8 0.322 HOME IMPROVEMENT ft REPAIRS 11 1036 2 810 94 .2 238 .3 8 .8 6 .2 0.283 CARPET CLEANING 9 7948 150 3365 883 . 1 986 .3 27 . 1 19 . 1 0.249 4- CONVENIENCE STORES 8 2682 29 1276 335 .2 453 .6 25 .2 22 .4 0. 174 5- EDUCATIONAL PRODUCTS ft SERVICES 29 5727 3 3319 197 .5 618 . 1 14 .9 7 .6 0.389 EDUCATIONAL ft TRAINING PROGRAMS 12 773 4 273 64 4 88 .8 17 .6 9. 4 0.416 HEALTH AIDS ft SERVICES 17 4954 3 3319 291 4 800 .3 12 .9 6 4 0.370 6- RESTAURANTS 121 54295 3 9060 448 . 7 1273 . 1 19 .8 13 . 3 0.299 FAST FOOD 84 48143 3 9060 573 . 1 1507 .0 19 .9 13 0 O. 307 - CHICKEN 1 1 1 1334 4 8200 1030 .4 2419. 6 21 .6 12. 8 0.363 - MEXICAN 10 3158 10 2292 315 8 704 .6 17 .4 12 8 0.251 - HAMBURGER 9 18970 39 9060 2107 8 3097. .2 30 .2 20 8 0.266 - PIZZA 22 6236 11 340O 283 .4 726. 3 18 . 1 1 1 . 4 0.328 - SUBMARINES 13 1730 5 BOO 133 . 1 213. .3 17 3 12. 2 0.300 TABLE SERVICE 37 6152 5 915 166 3 221 . 6 19 .7 14 . 1 0.280 - STEAKHOUSES 6 2102 44 623 350. 3 267. 2 23 3 2 1 . 8 0.067 - ITALIAN 6 637 10 320 106 2 1 13. 8 20 .2 13. 3 0.298 - FULL MENU 11 2118 5 915 192. 5 288. 4 17. .9 13. 1 0.347 7- HOTELS, MOTELS ft CAMPGROUNDS 10 5298 63 1672 529. 8 456. 1 27. 5 21 . 9 0. 181 8- LAUNDRY ft DRY CLEANING 3 1281 46 1084 427. 0 57 1 . 4 23 .0 17 . O 0. 338 9- RECREATION ft TRAVEL 1 1 1097 6 34 1 99. 7 119. 1 1 1 . 5 9 . 0 0.282 TRAVEL AGENCIES 4 627 21 273 156. 7 104. 3 9. 7 8. 7 0.098 lO- AUTO ft TRUCK RENTALS 6 5905 58 3320 984 . 2 1240. 8 14 . 5 12 . 2 0.204 11- EOUIPMENT ft TOOL RENTAL 1 373 373 373 373. 0 0. 0 42. 0 24. 0 0.429 12- NON FOOD RETAILING 99 14635 2 1283 147 . 8 229. 1 17. 8 10. 0 0.345 CLOTHING ft SHOES 16 2019 6 486 126. 2 151 4 19. 6 12. 6 0.304 FURNITURE ft ACCESSORIES 9 1106 24 313 122. 9 126. 1 17. .7 10. 6 0. 350 ART SUPPLIES 8 869 6 323 108. 6 106 . 5 18. 6 10. 5 0.272 COMPUTER PROOUCTS 8 1403 7 576 175. ,4 187 . 2 6 .5 4 . 9 0.261 VIDEO RENTAL 7 1569 14 703 224. 1 286. 1 5 4 4. 6 0. 134 13- FOOD RETAILING - NON CONVENIENCE 52 15323 2 4894 294 . 7 825. 5 21 . 3 13. 4 0.326 DONUT SHOPS io 3201 23 1512 320. 1 496. 6 29. .4 18. 5 0.382 ICE CREAM PARLORS 17 10373 9 4894 610. 2 1351 . 5 25 5 17 . 9 0.258 SPECIALTY FOOD SHOPS 9 737 2 495 81 . 9 158. 8 19. 0 1 1 . 4 0.399 14- MISCELLANEOUS 17 3246 7 863 190. 9 234 . 8 12 2 8. 7 0.231 BEAUTY SALONS 12 3084 7 863 257. 0 252. 7 14 .7 10. 5 0.202 ALL SECTORS 548 149780 2 9060 273. 3 784. 2 17 .8 11 . 4 0.316 Firms in Parts and Services, those in the Hamburger sector as well as the only firm involved in Equipment and Tool Rental have been in existence for more than 30 years on average. The oldest firm in the sample has been in business for 110 years; it is called Ben Franklin. The sectors in which firms have been involved in franchising for more than 20 years on average include Convenience stores, Hamburger Restaurants, Steakhouses, Hotels, Motels and Campgrounds and Equipment and Tool Rentals. The newcomers to franchising, Video Rental and Computer Product stores, are also the \"youngest\" in terms of years in business. In most cases, firms were in business for quite a few years before they got involved in franchising. The last column of Table 4.2 gives the proportion of total time in business during which the firms have not been involved in franchising. It may be interpreted as an indicator of the difficulty or ease with which firms are able to adapt their operations to franchising. The smaller this proportion is, the faster the firms in the sector began to use franchising, which would imply that there was not much of a cost involved in adapting the business to franchising. When this proportion is large, it could indicate for example that it took more time to develop the concept or the franchise package, suggesting that the adaptation of this firm to franchising was more costly. On average, firms in the sample did not franchise for the first 31.6% years that they have been in business. This proportion is lowest for Travel Agencies and Steakhouses (9.8% and 6.7% respectively) and highest for Educational Products and Services (41.6%), Parts and Services (42.2%) and again for the firm in Equipment and Tool Rental (42.9%). The previous discussion would imply that the latter are harder to franchise than the former. It is worth pointing out however that 31.6% on average seems quite high. This goes against the notion that firms use franchising as a means to obtain capital. If this were the case, one would expect firms to start using franchising as soon as possible. As just noted, the delay may be explained at least in part by the need to develop the \"system\". But a lag of 6.4 years on average seems long in the context of an explanation of franchising as a response to capital constraints on the part of franchisors. Firms would be expected to be more \"anxious\" than that to get involved in franchising if they were waiting for this to expand their operations. The main purpose of Tables 4.3, 4.4, and 4.5 will be to show how the percentage of franchised outlets, the royalty rates and the franchise fees, which are the main variables of interest here, vary across and within the franchising sectors defined by 61 the U.S. Department of Commerce. 3.2 The Use of Franchising Table 4.3 is mainly concerned with franchisors' propensity to use franchising. From it, one finds that although the average proportion of franchised outlets is always quite high in these chains,, it still varies significantly from 56% in the Fast-Food Restaurants that specialize in serving chicken to 98.3% in the Carpet Cleaning and the Travel Agency businesses. On average, franchisors in this sample franchised 82.7% of all their outlets in 1986. According to the U.S. Department of Commerce's survey, 78.8% of all outlets in the same sectors (i.e. excluding traditional franchise sectors) were franchised in 1985. The lowest proportion of franchised outlets in this sample is found in the sector of Non-Convenience Food Retailing. More precisely, this record is held by a firm called Winchell's Donut House. The maximum proportion of franchised outlets is 100% in a majority of sectors. In fact, 117 of the 548 franchisors in this sample franchise all of their outlets. In the initial sample of 890 firms, 199 were wholly franchised. This contradicts the finding of Martin (1987). He obtained data on company-owned and franchised outlets for 772 franchisors from The 1985 Franchise Annual and found that only three of these firms had no company-owned outlets. This discrepancy can be explained, I believe, by the way in which he selected his 772 firms from the 3000 plus surveyed by The 1985 Franchise Annual. It appears that the Franchise Annual , in its description of franchise chains, does not indicate the number of company-operated outlets when this number is zero. Since he needed data for each firm on the number of franchised and company-owned outlets, as well as years in business and years involved in franchising, he would have eliminated all of those for which this information was not available. If this is correct, then most of the wholly-franchised chains would have been excluded from Martin's sample.1^ !0 This was verified by comparing data for wholly-franchised chains in the Entrepreneur survey with that from the Franchise Annual. More precisely, firms that operate both types of outlets will usually have the following information: Number of Units: Company Owned: x, Franchised: y. Those that have only franchised outlets either have: Number of Units: z or Number of Units: Franchised: z and nothing else. It is worth pointing out that some of the franchisors included in my sample are quite proud of the fact that they are 100% franchised: Century 21, for example, requires that franchisees advertise the fact that \"Each office is independently owned and operated\". 62 Table 4.3 : P r o p o r t i o n of F r a n c h i s e d O u t l e t s f o r the 548 F r a n c h i s o r s S e c t o r s 1- AUTOMOTIVE PRODUCTS PARTS ANO SERVICES BRAKES, MUFFLERS ft SHOCKS TRANSMISSION TUNE-UP 2- BUSINESS AIDS ft SERVICES ACCOUNTING AND COLLECTION EMPLOYMENT SERVICES PRINTING AND COPYING REAL ESTATE 3- CONSTRUCTION & MAINTENANCE MAID SERVICES CONSTRUCTION HOME IMPROVEMENT ft REPAIRS CARPET CLEANING 4- CONVENIENCE STORES 5- EDUCATIONAL PRODUCTS ft SERVICES EOUCATIONAL ft TRAINING PROGRAMS HEALTH AIDS ft SERVICES 6- RESTAURANTS FAST FOOD - CHICKEN - MEXICAN - HAMBURGER - PIZZA - SUBMARINES TABLE SERVICE - STEAKHOUSES - ITALIAN - FULL MENU 7- HOTELS. MOTELS * CAMPGROUNDS 8- LAUNDRY ft DRY CLEANING 9- RECREATION S TRAVEL TRAVEL AGENCIES 10- AUTO ft TRUCK RENTALS 11- EQUIPMENT & TOOL RENTAL 12- NON FOOD RETAILING CLOTHING * SHOES FURNITURE ft ACCESSORIES ART SUPPLIES COMPUTER PRODUCTS VIDEO RENTAL 13- FOOD RETAILING - NON CONVENIENCE DONUT SHOPS ICE CREAM PARLORS SPECIALTY FOOD SHOPS 14- MISCELLANEOUS BEAUTY SALONS ALL SECTORS % FRANC. % FRANC. % FRANC. % FRANC. X EXP. % FIN. N Minimum Max 1mum Mean St. Dev. Mean Mean 45 0 .368 1 .000 0 .837 0 . 198 0 . 133 0 .200 10 0 .368 1 .000 0 .846 0 .211 0 .000 0 .200 7 0 .400 1 .000 0 . 749 0 .243 0 .286 0 . 143 6 0 .857 1 .000 0 .962 0 .053 0 . 167 0 .000 1 1 0 .444 1 .000 0 .791 0 .234 0 . 182 0 . 182 96 o .088 1 .000 0 .899 0 . 187 0 .406 0 .437 19 0 .500 1 .coo 0 .929 0 . 127 0 .737 0 .474 20 0 .088 1 coo 0 .780 O .311 O .200 0 . 500 14 0 .672 1 .000 0 .947 0 .095 0 .071 0 .429 8 0 .824 1 .ooo 0 .978 0 .062 0 .750 0 .750 50 0 .444 1 coo 0 .924 O . 134 0 . 180 0 . 320 8 0 .750 1 .coo 0 .913 0 . 107 0 . 125 0 .250 13 0 .444 1 .coo 0 .918 0 . 151 0 .385 0 . 154 1 1 0 .500 1 .ooo 0 .880 0 . 194 0 .273 0 .364 9 0 .921 1 .ooo 0 .983 0 .032 0 .000 0 .667 8 0 .688 O .992 0 840 0 .094 0 . 125 0 250 29 0 .345 1 ooo 0. 817 0. . 176 0 .414 0 .207 12 O .345 1 .ooo 0. .762 0. .234 0 .250 0 333 17 0 .667 1 ooo 0. 855 0. . 114 0 .529 0 . 118 121 0. . 158 1 .000 0. 719 0. .239 0 .421 0 .058 84 0. , 158 1 .000 0. 715 0. 243 0 393 0. 036 1 1 0. 225 0 .992 0. 559 0. 259 0. 636 0. OOO 10 0 185 1 ooo 0. 737 0. 279 0. 500 0. OOO 9 0. . 158 0 .981 0. 677 0. 284 0. .556 0 OOO 22 0. 200 1 .000 0. 732 0. 226 0. .364 0. ,045 13 0 596 1. .000 0. 886 0. 149 0. 077 0. 154 37 0. 159 0 995 0. 727 0. 233 0. 486 0. 108 6 0. 159 0 .995 0. 719 0. 366 0. 500 0. 167 6 0. 572 0 992 0. 834 0. 169 0. 333 0. 167 11 0. 263 0 .944 0. 658 0. 174 0 636 0. OOO 10 0. 421 1 .000 0. 835 0. 190 0. 500 0. 2CO 3 0. 689 1 .000 0. 846 0. 156 0. 333 0 COO 1 1 0. 300 1, OOO 0. 860 0. 212 0. 091 0. 182 4 0. 952 1. COO 0. 983 0. 021 0. 000 0. 250 6 0. 948 1, OOO 0. 982 0. 021 0. 167 0. 667 1 0. 815 0 .815 0. 815 0. OOO 0. COO 0. 000 99 0. 103 1. 000 0. 834 0. 216 0. 242 0. 152 16 0. 103 1. COO 0. 787 0. 272 0 062 0. 062 9 0. 167 1. OOO 0. 718 0. 302 0. 444 0. 111 8 0. 825 1. OOO 0. 909 0. 070 0. COO 0 250 8 0. 714 1 COO 0. 936 0. 094 0. 625 0. OOO 7 0. 583 1. OOO 0. 902 0. 161 0 143 0. 143 52 0. 016 1 000 0. 800 0. 251 0. 250 0 077 10 0. 016 1. OOO 0. 820 0. 306 0. 10O 0. 300 17 0. 633 1. ooo 0. 907 0. 117 0. 235 0. 059 9 0. 111 0. 983 0. 6CO 0. 299 0. .222 0. OOO 17 0. 429 1 000 0. 866 0. 165 0. 000 0. 353 12 0. 429 1. 000 0. 895 0. 161 0. 000 0. 417 548 0. 016 1. 000 0. 827 0. 215 0. 297 0. 210 When asked what the ideal proportion of company-operated outlets would be, fast-food franchisors gave an average response of 42% in the Ozanne and Hunt (1971) survey [p.82]. Here, fast-food franchisors operate only 28% of their outlets. Either franchisors in this sample are quite far from what they consider ideal, or more likely, this preferred proportion has decreased since 1971. Still, fast-food franchisors tend to control directly more outlets than franchisors in other sectors do. In addition, Table 4.3 contains information on the proportion of franchisors that require their franchisees to have previous experience in the business (%EXP, column 6). 30% of the firms in the sample require such experience. This is especially frequent in sectors that demand special expertise, such as Accounting and Collection, and Real Estate. There are quite a few sectors, notably Parts and Services, Carpet Cleaning, Travel Agencies, Art Supplies stores and Beauty Salons, for which experience is not required by any of the franchisors.11 The last column, entitled %FIN, indicates the proportion of franchisors that provide direct financing to their franchisees, as opposed to simply aiding them in obtaining financing from other sources or giving them no assistance at all. Direct financing is found mostly in the Business Aids and Services sectors, and in such things as Carpet Cleaning, Auto and Truck Rental and Beauty Salons. However it is quite rare in the Restaurant sectors and subsectors among others. In total, 21% or 115 of the 548 franchisors offered financial assistance to their franchisees. Ozanne and Hunt (1971) found that a majority of the fast-food franchisors they studied preferred to enroll franchisees who had no previous experience in the business [p.124-125]. 3.3 About the Contractual Design: Royalty Rates and Franchise Fees A description of royalty rates in each sector is found in Table 4.4. Royalty rates here are meant to capture all those fees that represent the sharing component of the contract. Advertising fees stated separately as a certain percentage of sales were therefore added to reported royalties to generate the royalty rates used in this study.12 The highest royalty rate for this sample is found in the Health Aids and Services sector: it is that of Jazzercise, at 25%. In general however, the highest royalty rates are found in the sector of Automotive Products, where average royalties are at 9.2%, with two subsectors, Brakes, Mufflers, and Shocks, and Tune-up, with average rates over 10%. On the other hand a minimum rate of 0% is found in many sectors. The \"% fixed\" column indicates the proportion of franchisors that do not require their franchisees to pay any percentage of their sales. The next column gives the number of firms with royalty rates greater than 0. The last column indicates what the average royalty rate per sector becomes when only these last firms are included in the calculation. The exclusion of fixed-fee contracts for the calculation of average royalties is justified in the Eswaran and Kotwal (1985) model. Depending on whether a fixed-fee or a share contract is chosen, the tenant and the landlord provide different inputs. Therefore, in this model, fixed-fee contracts are not simply a special case of share contracts where the variable payments would be nil. Consequently, they should be separated from \"real\" share contracts. ^ In all, there are only 37 franchisors out of the 548 that have a zero royalty rate. Consequently, on the whole sample, the average royalty rate is not much affected by whether or not these firms are included in the calculation: it goes from 6.5% to 7.0%. But some sectors are more affected by this than others. In particular, while these In addition, royalty rates for travel agencies presented some problem. Some reported them on the basis of total commission. This is the relevant notion of total revenues for the outlets in this industry, and it is also used as the basis for royalties in the real estate industry. Others it seems, including International Tours, which is in the final sample, and Uniglobe, which is not, stated their royalty rate on the basis of total \"Travel Sales\" in the Entrepreneur survey. I found from a few articles that commissions in this industry are approximately 10% of sales value. And indeed, the royalty rate reported directly by Uniglobe when they were contacted was 10 times that given in the Entrepreneur Survey, and so was the rate they reported in Retailing & Services Guide 87. For these reasons, the royalty rate used for these firms was 10 times the rate indicated in the Entrepreneur Survey. Whether firms that use a fixed-fee contract in this sample behave differently from those that opt for a share contract will be tested later. 65 Table 4.4 : Royalty Rates for the 548 Franchisors ROYALTY ROYALTY ROYALTY ROYALTY X FIXED N ROYALTY Sectors exc. exc. fixed N Mini mum Maximum Mean St. Dev. Mean fixed Mean 1- AUTOMOTIVE PRODUCTS 45 0.0 19.0 9.2 3.5 0.022 44 9.4 PARTS AND SERVICES 10 3.0 10.0 6.9 2.5 0.000 10 6.9 BRAKES, MUFFLERS ft SHOCKS 7 9.0 19.0 11.9 3.5 0.000 7 11.9 TRANSMISSION 6 6.0 13.0 9. 1 2.3 0.000 6 9. 1 TUNE-UP 11 7.0 16.5 10.7 2.9 0.000 11 10.7 2- BUSINESS AIDS & SERVICES 96 O.O 18.0 6.6 3.9 0. 125 84 7.5 ACCOUNTING AND COLLECTION 19 0.0 17.0 6.3 4.6 0. 158 16 7.5 EMPLOYMENT SERVICES 20 0.0 10.0 7.2 2.4 0.050 19 7.6 PRINTING AND COPYING 14 4.5 8.0 6.5 1.3 0.000 14 6.5 REAL ESTATE 8 0.0 14.0 5.4 4.8 0. 125 7 6.2 3- CONSTRUCTION ft MAINTENANCE 50 0.0 20.0 6.2 4.4 0.200 40 7.8 MAID SERVICES 8 0.0 10.0 6.2 2.9 0. 125 7 7. 1 CONSTRUCTION 13 0.0 10.0 4.2 3.4 0.308 9 6.0 HOME IMPROVEMENT ft REPAIRS 11 0.0 10.0 5. 1 3.8 0. 182 9 6.2 CARPET CLEANING 9 0.0 17.0 6.6 5.0 0.222 7 8.4 4- CONVENIENCE STORES 8 0.0 15.0 5.9 5.4 0. 125 7 6.8 5- EDUCATIONAL PRODUCTS 8 SERVICES 29 0.0 25.0 7.5 4.5 0.069 27 8.0 EDUCATIONAL & TRAINING PROGRAMS 12 2.0 11.0 8.5 2.6 o.ooo 12 8.5 HEALTH AIDS ft SERVICES 17 0.0 25.0 6.8 5.4 0. 118 15 7.7 6- RESTAURANTS 121 1.0 15.5 6.6 2.2 0.000 121 6.6 FAST FOOD 84 2.0 15.5 7.0 2.2 0.000 84 7.0 - CHICKEN 11 4.0 10.0 7.6 1.8 0.000 11 7.6 - MEXICAN 10 2.0 10.0 5.7 2.8 O.OOO 10 5.7 - HAMBURGER 9 3.0 15.5 B.2 3.2 0.000 9 8.2 - PIZZA 22 4.0 10.0 6.7 1 .B 0.000 22 6.7 - SUBMARINES 13 5.0 13.0 7.4 2.3 o.ooo 13 7.4 TABLE SERVICE 37 1.0 10.0 5.7 1.9 0.000 37 5.7 - STEAKHOUSES 6 2.0 6.8 4.5 1.8 0.000 6 4.5 - ITALIAN 6 5.0 10.0 6.7 2.1 0.000 6 6.7 - FULL MENU 11 3.5 8.0 6.4 1.6 0.000 11 6.4 7- HOTELS, MOTELS ft CAMPGROUNDS 10 4.0 10.0 6.3 1.6 0.000 10 6.3 8- LAUNDRY ft DRY CLEANING 3 0.0 1.0 0.3 0.6 0.667 1 1.0 9- RECREATION & TRAVEL 11 0.0 10.0 5.8 2.9 0.091 10 6.4 TRAVEL AGENCIES 4 0.0 9.0 5.5 3.9 0.250 3 7.4 10- AUTO ft TRUCK RENTALS 6 3.5 9.0 6.8 1.9 0.000 6 6.8 11- EQUIPMENT ft TOOL RENTAL 1 2.7 2.7 2.7 0.0 0.000 1 2.7 12- NON FOOO RETAILING 99 O.O 16.5 5.7 3.0 0.040 95 5.9 CLOTHING ft SHOES 16 2.5 11 .0 5.6 3.0 0.000 16 5.6 FURNITURE ft ACCESSORIES 9 2.0 8.0 5.3 1.8 0.000 9 5.3 ART SUPPLIES a 1 .0 8.0 5.7 2.9 0.000 8 5.7 COMPUTER PRODUCTS 8 0.0 9.0 6.1 3.0 0. 125 7 6.9 VIDEO RENTAL 7 3.5 8.0 5.4 1.8 0.000 7 5.4 13- FOOD RETAILING - NON CONVENIENCE 52 0.0 9.9 6.0 2.4 0.038 50 6.2 DONUT SHOPS 10 0.0 9.9 7.4 2.9 0. 100 9 8.2 ICE CREAM PARLORS 17 0.0 9.0 5.2 2.6 0.059 16 5.6 SPECIALTY FOOD SHOPS 9 2.0 8.0 5.4 2.0 0.000 9 5.4 14- MISCELLANEOUS 17 0.0 15.0 6.9 3.7 0. 118 15 7.8 BEAUTY SALONS 12 0.0 15.0 7. 1 3.7 0.083 11 7.8 ALL SECTORS 548 0.0 25.0 6.5 3.4 0.066 511 7.0 Note: Royalty rates include the a d v e r t i s i n g fee franchisees pay to franchisors when this fee i s spe c i f i e d as a % of sales or gross revenues. Averages were used when ranges were given. \"fixed-fee\" contracts are relatively frequent in the Business Aids and Services and the Construction and Maintenance sectors, it is interesting to see that none of the 121 restaurants in the sample use this type of contract. In fact, none of the firms that operate with such a fixed-fee contract are found in those sectors that Brickley and Dark (1987) classify as \"non-repeat\" types of activities, i.e. Restaurants, Hotels and Motels, and Auto and Truck Rentals. This is consistent with the fact that the downstream operator's role is not as important in these kinds of non-repeat businesses. Franchise fees are the main focus of Table 4.5. In this case, as these fees must represent the \"fixed\" component of the contract, the present value of all future fixed payments specified in the contract was added to the initial franchise fee to generate the actual measure of franchise fee used in this thesis. In order to calculate the present value of such future payments, it was necessary to know what time horizon was covered by the contract. Individual data on the length of contracts were not available for all of the 548 franchisors. However the U.S. Department of Commerce publishes information from which the average duration of contracts in each of the franchising sectors can be calculated (see Table 4.8). Consequently, the discounting was done over the calculated average length of franchise agreements in the sector in which the individual firm was classified. A nominal discount rate of 10% was used since there was no indication in the data that the amounts of future fixed payments are adjusted to account for inflation.14 This computation was performed only 31 times, since only 31 of the 548 franchisors asked for future fixed pa3rments. The average fixed payment was $464. per month. Franchise fees in this sample vary from 0 to as much as 286.2 thousand dollars, with the latter found in the \"Health Aids and Services\" category,1^ as the highest royalty rate was. Only 7 firms in the sample have no franchise fee. The average franchise fee is largest in the \"Laundry and Dry Cleaning\" and \"Travel Agencies\" categories. The former is also the one with the smallest average royalty rate (with 2 out of 3 firms having no royalties at all). Since franchise fees and royalty rates are two means by which the franchisor can extract rent from its franchisees, one would 1 4 The resulting franchise fees were almost the same whether a 10% or a 5% discount rate was used. ^ This fee of 286.2 is for a company called MedStop. It is generated by adding up a franchise fee of $55,000 and future payments of $2,500 per month discounted at a rate of 10% for the average duration of contracts issued in 1985 in this sector (14.5 years, see Table 4.8). Clearly the actual number obtained is sensitive to this procedure and the numbers used. 67 Table 4,5 : Franchise Fees for the 54B Franchisors F. Fee F. Fee F. Fee F. Fee Cor. Spearman Cor. Spearman Sectors N Minimum Maxlmum Mean St. Dev. (F.r) Rank Cor. (F'.r') Rank Cor 1- AUTOMOTIVE PRODUCTS 45 0.0 79.5 19.7 15.0 -0.05 0.08 -0.05 -0.02 PARTS AND SERVICES 10 0.5 52.9 15.5 14.3 0.44 0.33 0.41 0.35 BRAKES. MUFFLERS & SHOCKS 7 10.0 22.5 15.8 5.3 0.30 -0.04 0.32 0. 11 TRANSMISSION S 15.0 25.0 21.1 3.8 0.20 0.03 0.24 0. 14 TUNE-UP 11 15.0 79.5 24.2 IB.9 0.00 -0.39 -0.27 -0.32 2- BUSINESS AIDS & SERVICES 96 0. 1 136.0 21.7 17.9 0. 11 0. 12 0. 11 0. 12 ACCOUNTING AND COLLECTION 19 0. 1 71.0 20.9 18.8 0.42 0.33 0.45 0.39 EMPLOYMENT SERVICES 20 5.0 50.0 21.5 12.8 0.24 0.07 0.25 0. 15 PRINTING AND COPYING 14 7.5 42.5 28.9 11.5 0.48 0.54* 0.47 0.51 + REAL ESTATE 8 5.0 19. 1 10.5 4.6 0. 15 0.26 0. 10 0. 14 3- CONSTRUCTION & MAINTENANCE 50 0.0 69.0 16.3 12. 1 -0.21 -0. 10 -0. 18 -0. 1 1 MAID SERVICES 8 7.5 31.1 13.4 7.6 -0.73 -0.02 -0.80 -0.76* CONSTRUCTION 13 5.0 69.0 19.5 16.7 -0.37 -0.34 0.30 0.27 HOME IMPROVEMENT & REPAIRS 1 1 3.4 56.9 18.3 14.8 0. 17 0.37 0.27 0.35 CARPET CLEANING 9 5.8 18.0 12.8 4.1 0.42 0.58+ 0.72 0.70* 4- CONVENIENCE STORES 8 5.0 25.0 12.8 7.3 -0.24 -0.26 0.08 0. 17 5- EDUCATIONAL PRODUCTS tt SERVICES 29 0.5 . 286.2 32.9 50.6 -0. 12 -0.08 -0.04 -0.01 EDUCATIONAL & TRAINING PROGRAMS 12 7.5 35.0 22.7 8.4 0.28 0. 17 0.33 0. 17 HEALTH AIDS & SERVICES 17 0.5 286.2 40. 1 65.6 -0. 11 -0. 12 0.09 -0.23 6- RESTAURANTS 121 5.0 87.5 21.2 12.2 -0.02 0. 11 -0.01 0. 12 FAST FOOD 84 5.0 87.5 18.9 10.6 0. 15 0.27* 0. 16 0.25* - CHICKEN 11 10.0 30.0 21.4 6.7 0.04 -0. 16 -0.03 -0.02 - MEXICAN lO 6.0 35.0 16.4 7.8 0.67 0.81**' 0.52 0.44 - HAMBURGER 9 10.0 87.5 31.9 22.9 -0. 18 -0.33 0.03 -0. 15 - PIZZA 22 5.5 25.0 15.6 5.0 -0.01 -0.22 0.40 0.26 - SUBMARINES 13 5.0 39.0 15.8 8.6 0. 18 0.35 0.21 0.30 TABLE SERVICE 37 7.5 64.5 26.4 14. 1 -0. 14 -0.02 -0. 15 -0.06 - STEAKHOUSES 6 15.0 50.0 26.3 13.0 0.73 0.54 0.90 0.77 + - ITALIAN 6 10.0 25.0 14.6 5.6 0.94 0.94* 0.97 0.94* - FULL MENU 11 18.0 50.0 32.3 10.2 -0.27 -0.27 -0.28 -0.47 7- HOTELS. MOTELS & CAMPGROUNDS 10 12.5 50.0 24.7 10.6 -0.23 -0.45 -0.32 -0.42 8- LAUNDRY & DRY CLEANING 3 42.2 66.5 52.5 12.6 0.96 1.00 n.a. n.a. 9- RECREATION & TRAVEL 11 6.0 127.5 34.3 37 .O -0.61 -0.30 -0.77 -0.71* TRAVEL AGENCIES 4 20.5 127.5 49. 1 52.3 -0.96 -0.80 n.a. n.a. 10- AUTO & TRUCK RENTALS 6 5.0 28.3 IB.7 10.2 -0. 15 0.31 -0.19 -0.37 11- EQUIPMENT & TOOL RENTAL 1 20.0 20.0 20.0 n.a. n.a. n.a. n.a. n.a. 12- NON FOOD RETAILING 99 0.0 112.5 19.9 16.9 0.21 0.32** 0.22 0.32** CLOTHING 8 SHOES 16 0.0 35.0 13.6 9.8 -0.01 0.00 0. 13 0. 10 FURNITURE a ACCESSORIES 9 0.0 50.0 23.5 17.3 0. 14 0.33 0.33 0.30 ART SUPPLIES 8 6.0 34 .0 17.2 10.5 0.74 0.67+ 0.77 0.86** COMPUTER PRODUCTS 8 5.0 45.0 24.9 13.8 0.87 0.90** 0.83 0.71 + VIDEO RENTAL 7 0.0 29.9 15.3 8.9 0.77 0.82* 0.69 0.39 13- FOOD RETAILING - NON CONVENIENCE 52 0.0 164.5 20.0 21.9 -0. 19 0.30* -0. IB 0. 11 DONUT SHOPS 10 5.0 40.0 22.0 10.9 0.50 0.35 -0. 19 -0.02 ICE CREAM PARLORS 17 0.0 164.5 24.8 36.8 -0.49 -0.07 -0.51 -0.31 SPECIALTY FOOD SHOPS 9 7.5 30.0 15.2 7.4 0.55 0.68* 0.63 0.83** 14- MISCELLANEOUS 17 5.0 99.0 26.0 23.2 -0.25 0. 17 -0. 19 -0. 19 BEAUTY SALONS 12 12.5 99.0 29.7 24.4 -0.63 -0.42 -0.69 -0.76** ALL SECTORS 548 0.0 286.2 21.5 20.3 -0.04 0. 10* -0.04 0. 10* oo Note: Franchise fees are In thousands of U.S. d o l l a r s . They Include the present value of a l l future payments s p e c i f i e d for the duration of the contract (using the average length of agreements In Table 4.8). The discount rate used Is 10%. Averages were used when ranges were given. F' and r' are error terms from regressions of F and r on number of outlets and number of years in business. Two-sided tes t s : ** : .01 l e v e l . * : .05 l e v e l , + :.10 le v e l . expect this kind of negative correlation between the two. However the average royalty rate for \"Travel Agencies\", at 5%, is below the overall average of 6.6%, but not as much as one could have expected it to be. Similarly the lowest average franchise fee of $10,500 is found in the \"Real Estate\" sector which does not have a high average royalty rate. In fact at 5.4%, it is below the overall average. A positive correlation between franchise fees and royalty rates could be observed in some cases. This is because a franchisor may be able to require higher fees in general when the value of his tradename is greater than that of another franchisor. In particular, if the brandname is more valuable, one expects the terms of the contract or the contract mix to be adjusted so that the franchisor is given more incentives to uphold its value. Thus r may increase. But a more valuable tradename would also make individual stores more profitable. Consequently, the franchisor could also increase F. In such a case, both r and F could be larger for one firm than for the other, and a positive relationship between the fees would be observed. Note that if the franchisor with a more valuable tradename chose a larger value for only one of the two fees, then one would find no correlation between F and r. The last four columns of Table 4.5 were compiled to investigate this correlation further. The simple correlation coefficient between the franchise fee and the royalty rate is presented in the first of those columns. The second column gives the Spearman rank correlation coefficient between the two fees. The advantage of the latter is that it is possible to test whether or not this correlation coefficient is significantly different from zero without having to make any assumptions on the distribution of the two variables. ^ For the whole sample, the simple correlation coefficient is negative but very small. Given the size of the sample, one may assume that the two fees are jointly normally distributed. Under that assumption, it is possible to test whether this correlation coefficient is significantly different from zero, and it is not. 1 7 The rank correlation on the other hand is positive and although quite small, given the size of the sample, it is significantly different from zero at the 0.05 level using a two-tail test. Correlation coefficients could be calculated for only 13 of the 14 main sectors. 1 ^ For n < 30, Spearman rank correlation tables are available for example in Gibbons (1976). For n > 30, we have that z = Ry/n \u00E2\u0080\u0094 1 ~ iV(0,1), where R is the rank correlation coefficient. 1 7 Given normality, under H(,:p \u00E2\u0080\u0094 0, we have ry/N \u00E2\u0080\u0094 2/y/\ \u00E2\u0080\u0094 r2 ~ tjv-2 where r refers to the correlation coefficient. The calculated t-statistic in this case was 0.93, which is not significant. 69 It is interesting to see that the simple correlation coefficients are positive for only 3 of those sectors, while the rank correlations are positive for 8 of them. Only Non-Food Retailing and Non-Convenience Food Retailing have significant rank correlation coefficients on the basis of two-sided tests. In both cases the association between the two fees is positive. Similarly, in all the subsectors for which a significant association is observed between the two fees, it is a positive one. Because the explanation for a positive relation, or a lack of relation, between the fees depends on some notion of growth in the value of the tradename, it was thought that if this effect was taken out of the data, the negative correlation might be observed. Consequently, both the franchise fees and the royalty rates were regressed on the two variables that can serve as proxies for the value of the tradename, i.e. the number of outlets and the number of years since each firm started its operations. The correlation coefficients reported in the last two columns of Table 4.5 were calculated using the error terms from these regressions. Since three degrees of freedom were necessary in order to estimate these regressions, and because there are only three observations in the Laundry and Dry Cleaning sector, these new correlation coefficients could not be estimated for that sector. As a result of this procedure, both the simple and rank correlation coefficient for the whole sample remain unchanged. The simple correlation coefficients are reduced or made more negative in 17 of the 45 sectors for which all coefficients were calculable. In most cases though, the change is minimal. Only two coefficients go from positive to negative, while six go from negative to positive. Similarly, four rank correlation coefficients go from positive to negative, but another four go the other way. Significant negative rank correlations can now be found in one main sector, Recreation and Travel, and two subsectors. But in general, this attempt to take the effect of growth out of the two fees in order to uncover the negative relationship one expects to find between them was not very successful. The regressions fared so badly that this result is not too surprising.181 also tried controlling for the amount of inputs sold by franchisors, in addition to years in business and number of outlets, and also separately, and again found no correlation. Thus no clear relationship between franchise fees and royalty rates emerges from all this.1 9 The F-statistics were generally insignificant so that the hypothesis that both slope coefficients were nil could not be rejected in most cases. 1 9 The same results were obtained when the fixed fee that was used was divided by the duration of 70 It could be argued that this lack of correlation is simply a reflection of the little importance of the fixed fee as a proportion of total revenues collected by the franchisor from each franchised store. However, using aggregate data on average sales per outlet and on the average duration of franchise contracts, as published by the U.S. Department of Commerce, one can estimate the proportion of the franchisor's revenues that is attributable to the fixed fee. Total revenues to the franchisor over the duration of the contract are given by the franchise fee plus the variable fee multiplied by average sales and by the number of years contracted for. The franchise fee represents 13.7% of these total revenues and is therefore clearly not negligible.2^* Consequently, this argument can not explain the observed lack of correlation between the two fees. A final attempt was made to elucidate this relationship in Table 4.6. Instead of separating firms on a sectoral basis, size cohorts were generated. The 548 observations were sorted by the number of outlets they had, and the cutoff points for each decile were located. Because many firms often had an identical number of outlets, it was not possible to generate cohorts of 55 firms each, but the size cohorts in Table 4.6 were chosen to get as close as possible to that. As usual, N indicates the number of franchisors in each category. Because the value of the tradename can also be associated with the number of years a firm has been in business, age cohorts were generated as well. In this case however, the number of firms with the same number of years was too large. It made it impossible to get 10 age cohorts of similar size. For that reason, only 6 of them, with about 90 franchisors each, were constructed. The second column of Table 4.6 describes how the proportion of franchised stores varies across cohorts. For both size and age cohorts, this proportion seems to go up, reach a maximum around the median, and then maybe go down again. With respect to the fees, what transpires from this table is that royalty rates do seem to grow as the size of the chain, and possibly the number of years in business, increases. As both the size of the chain and the number of years in business can be used as proxies for the value of the tradename, this is consistent with predictions from the contract given in Table 4.8, to give a measure of the yearly fixed fee. This is not surprising since these durations do not vary much across sectors. 9ft The average sales figures used for this computation actually represent average yearly sales per outlet whether franchised or company-operated. Average sales per franchised outlet tend to be smaller than the overall average. Thus the proportion of revenues attributable to the fixed fee as calculated here may underestimate the true value. 71 Table 4.6 : Royalty Rates and Franchise Fees Within Size and Age Cohorts Size cohorts % Franc. Royalty Royalty F . Fee F . Fee Cor(F.r) Spearman Rank Cor N Mean Mean St. Dev. Mean St . Dev. (F.r) 1- 1 < OUTLETS < 8 58 0.697 6.6 2.9 16. 1 8.4 0.34 0.32* 2- 9 < OUTLETS < 15 51 0.730 6.6 2.8 25.9 40. 3 0.12 0.24+ 3- 16 < OUTLETS < 24 56 0.830 6. 1 3.0 20.9 15.4 0. 15 0. 11 4- 25 < OUTLETS < 35 52 0.791 6.4 3.2 19.2 13.5 0.00 0. 17 5- 36 < OUTLETS < 54 58 0.870 6.0 3.3 23.4 20.0 -0.03 0. 19 G- 55 < OUTLETS < 85 56 0.885 6.2 3.4 22.3 19.5 0.00 0.26+ 7- 86 < OUTLETS < 151 54 0.874 6.0 3.4 20.2 14.3 -0.02 -0.06 8- 152 < OUTLETS < 299 55 0.884 7.2 3.8 20.9 17.6 -0.35 -0.24+ 9- 300 < OUTLETS < 620 55 0.860 7. 1 3.2 23.3 13.4 0.01 O.05 10- 621 < OUTLETS < 9060 53 0.849 7.4 4.7 23. 1 25.5 -0.28 -0.06 Age cohorts 1- 1 < YEARS IN BUS. < 6 87 0. .841 6 .2 3 . 1 20. ,5 19 .4 0. .07 0. 18+ 2- 7 < YEARS IN BUS. < 9 91 0. ,827 6 .4 3. .2 23. 7 32. .4 -0. 13 -0. 09 3- 10 < YEARS IN BUS. < 13 91 O. .832 6 .5 3. .2 21 . 9 14. .2 -0. 05 0. 21* 4- 14 < YEARS IN BUS. < 17 83 0 .888 6 .9 4 .5 20. . 1 13 .5 -0, .08 -0. .00 5- 18 < YEARS IN BUS. < 27 lOO 0, .794 6 .5 3. . 1 20. . 1 13 .9 -O. .04 0. .05 6- 28 < YEARS IN BUS. < 170 96 0. .794 6. .7 3. .4 22. .5 21 . 9 0. .01 0. .22* Note: Two-sided test s : ** sign, at the .01 l e v e l . * sign, at the .05 l e v e l , + sign, at the .10 l e v e l . the two-sided hidden action models. Franchise fees seem to remain about the same, or grow a little as the number of outlets in the chain gets larger. The variability of royalty rates increases a little with the number of outlets, as one would expect. However this is not the case for franchise fees. As the number of years in business increases, neither fee's standard deviation goes up. Turning our attention to the correlation between the two fees, it is interesting to find that it is positive for small size chains, and then it becomes negative for chains with a large number of outlets. The way in which mean fees vary across size cohorts tends to indicate that both fees could grow simultaneously. However the simple correlation coefficients suggest that large chains must trade off one type of fee for the other, while small chains do not have to. According to the Spearman rank correlations there is a significant positive relationship between the two fees for small and medium sized firms. The relationship is negative and significant in one of the larger size cohort. The others show no relationship at all. The pattern is somewhat different for age cohorts. A significant positive rela-tionship between royalty rates and franchise fees is found in both the \"youngest\" and \"oldest\" age cohort. No age cohort shows a significant negative correlation. There is therefore no trade off between the fees even for firms that have been in business for a very long time. The average fees found for each age cohort seem relatively constant, indicating that on average firms do not tend to increase either fee as the number of years in business increases. This can be taken to mean that years in business do not provide a good proxy to the value of the tradename. Within each age cohort firms with relatively \"stronger\" tradenames are still able to demand higher fixed and variable fees. In general, one can only conclude that there is no simple relationship between the two fees. In most sectors and in many of the size and age cohorts, no significant relation was found at all. In a majority of the cases where there was a significant association between the two fees, it was a positive, not a negative one. However, within size classes there was some indication, from the simple correlation coefficient, of a trade off between franchise fees and royalty rates for large but not for small chains. Royalty rates did seem to increase with the size of the chain. In fact, the pattern may be U-shaped. Franchise fees remained relatively constant as the number of outlets gets larger. Neither fee really increased with the number of years in business. 73 In their model, Mathewson and Winter found that \"Monitoring increases for an established firm in response to the increased temptation for the franchisee to free ride on the brand name\" [p. 520]. They argued that this result was consistent with 01 observed buy-backs in North America. If we allow for a certain \"critical\" size or years in business for a firm to be defined as established in their model, their result is also consistent with what we observe here, i.e. the fact that the average proportion of franchised outlets goes down slightly once firms have reached the median size or age. Rubin's explanation of buy-backs was based on the notion that monitoring costs per outlet go down as density increases. To make this consistent with what is found in Table 4.6, one would also have to invoke a notion of \"critical density\" from which monitoring costs would start decreasing. Otherwise, given that density increases with the number of outlets, one would expect the average proportion of franchised outlets to decrease monotonically with the size of the chains. 3.4 A Comparison of the Two Samples For comparison purposes, Tables A . l to A.5 in appendix A show the same statistics for the same variables as Tables 4.2 to 4.6, but for the sample of 890 franchisors. As one would expect, the main difference between the two sets of tables shows up in the total number of outlets covered and in the number of outlets per chain. The latter goes up in the sample of 548 firms: many small franchisors were ehminated because they were not covered in the other surveys from which the additional data were obtained. The average number of years in business and years franchising are also slightly larger in the sample of 548 for the same reason. Most of the other numbers are quite similar across the two sets of tables. It was the need for additional data that resulted in the exclusion of firms, most of them relatively small, and the reduction of the sample size from 890 to 548 firms. This does not seem to have introduced any systematic bias, especially for the dependent variables. In particular it is worth noting that the average proportions of franchised outlets in most sectors in Table A.2 are very similar to those found in Table 4.3. Similarly, according to Tables 4.3 and 4.4, the average franchise contract was given by r = 6.5% and F = 21,500. In Tables A.2 and A.3, one finds an average r of 2 1 As was mentioned previously, this trend seems to have reversed itself. 74 6.5% and an average F of 21,700. The two are almost the same. In their survey, the Association of Canadian Franchisors (ACF) found an average royalty rate of 5% and an average advertising fee of 2%, resulting in an average r of about 7%. Since the survey of the A C F was done using data for 1984, and is restricted to a sample of Canadian franchisors that accounts for only about 10% of all franchised sales in Canada, it is interesting that the numbers are so similar. 3.5 M e a s u r e s o f G e o g r a p h i c a l D i s p e r s i o n a n d o f F r a n c h i s o r s ' C o n t r i b u t i o n As was discussed previously, additional data were collected for the sample of 548 franchisors. These include measures of geographical dispersion of outlets, which make the monitoring of franchisees more costly, as well as the amount of training provided by each franchisor. The latter serves as a measure of franchisors' contribution. These were available for 1985 only.2** They are described in Table 4.7. Here, States refers to the number of States each franchisor has outlets in. Excluding Equipment and Tool Rental which contains only one observation, the average number of States covered by franchisors is highest in the Carpet Cleaning category, and then for Hotels, Motels and Campgrounds. The smallest average number of States, 5.5, is found in the category of Italian Restaurants. The next two columns provide information on the number and the proportion of foreign outlets in each chain. Both the number of states and the proportion of foreign outlets are meant to capture the degree of geographical dispersion of each franchise chain. However establishing the proportion of foreign outlets was not as straightforward as one would expect. The survey produced by Entrepreneur asks franchisors for the number of franchised and company-operated outlets they have worldwide. But in many cases, the American corporation is legally distinct from its foreign counterparts and does not report foreign outlets as its own. The empirical model used here requires each data point to represent the decision-maker, i.e. the entity that chooses the optimal combination of company operated and franchised outlets as well as the optimal contract. If the foreign firms are distinct in the sense that they can make these decisions with respect to outlets in their jurisdiction, then The standard error of F however is larger for the sample of 890 than that of 548, which is not surprising. n o The existence of a lag between these variables and my dependent variables has the advantage of getting around some possible simultaneity. 75 Table 4.7 : Measures of Geographical Dispersion and of Franchisors' Contribution Sectors STATES FOREIGN ^FOREIGN TRAINING GROWTH CAPITAL OUTLETS OUTLETS In In NEEDED WEEKS OUTLETS ($000) N Mean Mean Mean Mean Mean Mean 1- AUTOMOTIVE PRODUCTS 45 12.2 13.0 0.019 3.0 0.231 60.8 PARTS AND SERVICES 10 16.4 9.5 0.006 3. 1 0.252 48.5 BRAKES, MUFFLERS S SHOCKS 7 16.9 68.9 0.036 3.6 0.090 84.4 TRANSMISSION 6 17.0 0.3 0.002 3.8 0.077 77.9 TUNE-UP 11 7.3 0.0 0.000 2.B 0.224 66.3 2- BUSINESS AIDS 8 SERVICES 96 17.7 12.5 0.022 2.2 0.300 38.3 ACCOUNTING AND COLLECTION 19 14.3 0.7 0.013 2. 1 0.332 16. 1 EMPLOYMENT SERVICES 20 15.3 0.2 0.002 3. 1 0. 184 32.5 PRINTING AND COPYING 14 21.5 23.5 0.028 3.7 0.364 75.0 REAL ESTATE 8 22.5 93.5 0.065 0.7 0.320 24.9 3- CONSTRUCTION & MAINTENANCE 50 19.8 26.9 0.062 1.8 0.292 21.8 MAID SERVICES 8 10.4 18.5 0. 124 2. 1 0.421 15.2 CONSTRUCTION 13 22.0 3.8 0.060 1.9 0.369 33.3 HOME IMPROVEMENT 8 REPAIRS 11 \u00E2\u0080\u00A2 11.5 11.1 0.04B 2.0 0.360 18.9 CARPET CLEANING 9 40.4 112.7 0.083 1.6 0.083 14.5 4- CONVENIENCE STORES 8 10.9 1.9 0.002 2.7 0.040 49.5 5- EDUCATIONAL PRODUCTS & SERVICES 29 12.0 11.2 0.054 2.0 0.312 39.8 EDUCATIONAL 8 TRAINING PROGRAMS 12 10.5 2.8 0.068 2.4 0.270 32.3 HEALTH AIDS & SERVICES 17 13. 1 17. 1 0.043 1.6 0.342 45. 1 6- RESTAURANTS 121 13.3 40.3 0.024 5.5 0. 138 202. 1 FAST FOOD 84 13.2 56. 1 0.022 4.8 0. 143 170.0 - CHICKEN 11 16.0 171.4 0.027 5.1 0. 164 258.7 - MEXICAN 10 11.7 5.0 0.037 3.3 0.149 135.4 - HAMBURGER 9 24.7 279.8 0.089 7.6 0. 147 339.2 - PIZZA 22 9.4 3.5 0.009 5.0 0.159 148.7 - SUBMARINES 13 8.2 0.2 o.ooo 3.4 0. 126 59.3 TABLE SERVICE 37 13.5 4.5 0.028 6.9 0. 128 275.0 - STEAKHOUSES 6 25.2 13.8 0.033 7.9 0.016 300.2 - ITALIAN 6 5.5 O.O O.OOO 4.5 0. 109 156.7 - FULL MENU 11 12.8 6.3 0.033 10. 1 0. 162 429.7 7- HOTELS. MOTELS & CAMPGROUNDS 10 38.6 40.6 0,077 1.4 0. 135 444.9 8- LAUNDRY 8 DRY CLEANING 3 23.0 0.0 o.ooo 4.0 0.291 86.7 9- RECREATION & TRAVEL 11 19.6 4.2 0.041 1.6 0.345 108.7 TRAVEL AGENCIES 4 27.7 0.7 0.033 1.7 0.216 41.2 10- AUTO 8 TRUCK RENTALS 6 37.0 545.7 0.255 1.1 0. 167 45.5 11- EQUIPMENT & TOOL RENTAL 1 48.0 0.0 0.000 2.4 -0.111 255.0 12- NON FOOD RETAILING 99 16.3 8.2 0.035 2. 1 0.257 84 .6 CLOTHING & SHOES 16 17.3 8.0 0.026 2.1 0. 146 87.5 FURNITURE & ACCESSORIES 9 16. 1 21.6 0.082 2.2 0.201 110.6 ART SUPPLIES 8 19.0 3.2 0.020 3.3 0. 176 52. 1 COMPUTER PRODUCTS 8 30.0 27 .4 0.069 2. 1 0.477 93.9 VIDEO RENTAL 7 13.7 0.0 0.000 1.5 0.476 80.2 13- FOOD RETAILING - NON CONVENIENCE 52 12.5 38.5 0.026 2.9 0.263 84.4 DONUT SHOPS 10 11.5 41.5 0.048 4.9 0.084 98.2 ICE CREAM PARLORS 17 15. 1 93.0 0.052 2. 1 0.294 79.6 SPECIALTY FOOD SHOPS 9 13.8 0.9 0.002 3.7 0.093 75.2 14- MISCELLANEOUS 17 15.2 6.8 0.019 1.4 0.384 40.9 BEAUTY SALONS 12 18.2 9.6 0.023 1.4 0.222 42.8 ALL SECTORS 548 15.9 27.4 0.034 2.9 0.242 97.4 one should treat these firms as separate entities and not consolidate the outlets. Assuming that whether or not a firm claims the outlets as its own indicates something about the amount of control it feels it has over them, I have used the data as given in the survey. In cases where it was clear that all foreign outlets had been excluded from the reported number of franchised and company-operated units, and consequently the American firm only was the data point, the number of foreign outlets was given a value of zero. Not surprisingly, Auto and Truck Rental and then Hamburger franchisors are found to have the largest average number of foreign outlets. However, franchisors in the Auto and Truck Rental and then those in Maid Services are the ones that have the largest proportion of foreign outlets. On average, franchisors in this sample operated 27 outlets outside of the U.S., representing 3.4% of all their outlets. Training, in the fifth column, stands for the length of the initial training period and is given in number of weeks. It also varies a lot on average, from a low of 0.7 weeks in the Real Estate business to a high of 10.1 weeks for Full Menu Restaurants. Overall, franchisors provide around 3 weeks of training to their franchisees. Two other variables were obtained for the sample of 548 firms and are presented in Table 4.7. First, there is a measure of growth of the chain, given by half the difference in the logarithm of the number of outlets in 1986 and in 1984. The mean value for this variable in the various sectors is found in the sixth column.2 5 Not too surprisingly, the fastest growing sectors during this period are those of Video and Computer stores. Excluding Equipment and Tool Rental, which contains a single firm that experienced negative growth between 1984 and 1986, one finds that there has been growth in all franchising sectors. The slowest growth is found in the Steakhouses sector. At the firm level, in total, 62 of the 548 firms experienced negative growth between 1984 and 1986. Another 34 firms had zero growth during that period. All 94 For example, A & W clearly indicates that its Canadian counterpart is a distinct entity and so it does not report any Canadian outlets. And while the American firm franchises almost all its outlets (620 out of 630), A & W Canada operates 28% of its stores, i.e. 82 out of 295. The franchise fees and the royalty rates (not counting the advertising rate which is unavailable for the Canadian company) are also different for the two franchisors: F = 20000 and r \u00E2\u0080\u0094 4% for the American corporation, F = 25000 and r is between 2 and 2.75% for the Canadian Company. 2 5 Firms that had no outlets in 1984 were eliminated in the construction of the sample of 548 firms because this variable was not well defined in those cases. 77 the other chains show positive growth. The resulting average growth rate for all the firms in the sample is estimated to be around 25%, which is very high. When it was calculated on the basis of actual percentage changes in the number of outlets between 1984 and 1985, and then between 1985 and 1986, the average of these two gave an estimated growth rate of 45%. The fact that this number is large is probably due to the presence of small firms in the sample for which the addition of one or two outlets represents a very high increase in proportion to the size of the chain. The last variable presented in Table 4.7 represents the amount of capital needed to start one of their franchises according to each franchisor. Whenever a range was given in the survey, the lower bound was used as it represents the minimum amount required to start the business. It is an indication of the minimum capital constraint the firm faces when it seeks to expand. As can be seen in Table 4.7, Hotels, Motels and Campgrounds, as well as Restaurants, tend to require much more capital on average than the other types of franchised businesses. Over the whole sample, franchisors estimated the minimum capital requirement to be around $100,000. 3.6 Some Relevant Sectoral Data Useful data were found on an aggregate basis in the U.S. Department of Com-merce's \"Franchising in the Economy\". Again, the most recent available data were for 1985. Some of these are presented in Table 4.8. The first column, entitled Total Outlets, mainly serves to give some notion of the coverage of the samples of fran-chisors used in this paper. This is done here in terms of outlets as opposed to number of franchisors as in Table 4.1. However, the numbers are not directly comparable to those found in the first columns of Tables 4.2 and A l . One reason for this are the different years: data in Table 4.8 are for 1985, whereas all previous tables contained 1986 data. More importantly, total outlets in the U.S. Department of Commerce's publication seem to refer to U.S. outlets only. Tables 4.2 and A l were compiled using worldwide outlets. The second column presents total sales in the U.S. for each sector in millions of dollars. Restaurants remain the most important business-format franchising sector both in terms of outlets and in terms of sales. This accounts for the fact that 121 out of the 548 franchisors studied here operate in this sector. Column 3 gives the amount of average sales per outlets; this is a proxy for the average size of outlets 78 Table 4.8 Some Relevant S e c t o r a l Data T o t a l Total Average Mean Franchisees Franchisees' Discontinued O u t l e t s {%) O u t l e t s Sales Sales Agreement purchases purchases Average 1984- 1985 (5) (1) (1) per Length per o u t l e t per o u t l e t Total Co--Owned Franc. o u t l e t (In years) V A ^ =*x/N- (4-6) Given an estimate of the variance of average sales per outlet obtained using time series data, S2t, one could then get an estimate for a2^, i.e. N S\ = Vn^Xi/N) \u00E2\u0080\u00A2 N = S2e< \u00E2\u0080\u00A2 N. (4.7) t=i But TV varies over time, so that the correction implied by (4.7) isn't that straigth-forward. Note that the same problem would have arisen in the calculation of (4.4). The most appealing way to handle this here would be to use the average value of N over the time period, N. If the A'j's are not independent from each other, i.e. if the sales level of one outlet in a sector is dependent upon the sales level of other outlets in the sector, we are back to (4.5). In this case, if all the correlations can be assumed to be positive, we have that P2x S*t \u00E2\u0080\u00A2 N (4.10) and we cannot, think of S% \u00E2\u0080\u00A2 N as an upper bound anymore. Since the A*,'s refer to all outlets in the sector in the U.S., I will assume that overall, the sum of the correlations would be positive. 84 ( sales are perfectly correlated across all outlets, which, as was mentioned in Chapter 2, is not very consistent with the fact that franchise contracts are independent contracts, then from (4.5), Si = V a r ( ^ k ^ i ) = _ L [N . 4 + { N _ 1 ) N . A 2 X ] = *x (4-11) i.e. the variance of average sales would be the same as the variance of each outlet's sales. Since correlation coefficients cannot go beyond 1, S2 clearly gives a lower bound on o\. The interpretation of measures of risk based on aggregate data, as we have here, thus depends critically on the assumptions one makes about correlations. If the average number of outlets, N, was similar across sectors, the difference between (4.7) and (4.11) would vanish. Using either one of these, one would obtain the same ordering of sectors' risk, and in fact, relative magnitudes would be the same. If N varies a lot between sectors, as is the case here, then if the A\"'s are independent, i.e. (4.7) is correct, but o\ is estimated using (4.11), the \"riskiness\" of sectors with a large number of outlets is underestimated. If the correlations are positive and large but (4.7) is used, the riskiness of sectors with a large number of outlets on average is overestimated. Finally, for any intermediate scenario in terms of correlations, which are the most realistic, differences in N between sectors will not be the only thing influencing the bias of the measures. The \"amount of correlation\" between outlets' sales will also tend to vary across sectors and this will affect the validity or the bias of any measure that is actually used. In these circumstances, the best strategy is to do some sensitivity analysis. Since we can obtain upper and lower bounds for