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Neoclassical economics and labour migration theory : a Canadian perspective Olligschlaeger, Andreas Matthias 1986

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NEOCLASSICAL ECONOMICS AND L A B O U R MIGRATION THEORY: A CANADIAN P E R S P E C T I V E by  ANDREAS MATTHIAS O L L I G S C H L A E G E R B . A . , Concordia U n i v e r s i t y ,  1984  A THESIS S U B M I T T E D IN P A R T I A L F U L F I L L M E N T O F THE REQUIREMENTS FORTHE DEGREE OF MASTER OF ARTS in T H E F A C U L T Y OF G R A D U A T E STUDIES D e p a r t m e n t of Geography, U n i v e r s i t y of B r i t i s h C o l u m b i a  W e accept this thesis as conforming to the required standard  T H E UNIVERSITY  O F BRITISH C O L U M B I A  JULY  1986  (c) A n d r e a s M a t t h i a s Olligschlaeger,  1986  DE-6  In p r e s e n t i n g requirements of  British  it  freely  agree for  this  thesis  f o r an a d v a n c e d d e g r e e a t  Columbia, available  that  permission  that  that  for reference  d e p a r t m e n t o r by h i s for  I agree  (3/81)  Columbia  the make  further this  thesis  h e a d o f my It  this  s h a l l n o t be a l l o w e d w i t h o u t  of  ^ x f x ^  I  or her r e p r e s e n t a t i v e s .  The U n i v e r s i t y o f B r i t i s h 1956 Main Mall V a n c o u v e r , Canada V6T 1Y3  Date  shall  and s t u d y .  may be g r a n t e d by t h e  permission.  of  University  Library  copying or p u b l i c a t i o n of  f i n a n c i a l gain  Department  the  the  for extensive copying of  s c h o l a r l y purposes  understood  in partial fulfilment  is  thesis my w r i t t e n  ABSTRACT T h i s thesis examines the theoretical and empirical base of neoclassical migration analysis  in economic geography. It is shown that the key assumptions  of neoclassical  migration analysis stem from the broader m a r g i n a l equilibrium analysis and theory of resource allocation that defines  the neoclassical  school. Spefically, the hypothesis  that  neoclassical economics makes with respect to labour migration is that labour flows  from  low wage, high u n e m p l o y m e n t regions to regions with high wages and low unemployment, thus a r r i v i n g at a state of equilibrium. T h i s hypothesis is tested using C a n a d i a n labour migration data for 1976-1981. It is found that the hypothesis is unable to explain labour migration patterns i n C a n a d a because: first, the assumptions about h u m a n behaviour that the neoclassical model makes are both too simplistic and unrealistic, as are those about the nature of the economy, and second, migration seems to promote cumulative rather t h a n move the system towards equilibrium.  ii  causation  TABLE OF CONTENTS Abstract  ii  List of Tables  v  List of Figures  ix  Acknowledgement  x  1. Introduction  1  2. Neoclassical Economics and Economic Geography  3  2.1 The Advent of Neoclassicism  3  2.2 Major Characteristics of Neoclassical Economic Theory  7  2.3 Criticisms of Neoclassical Economic Theory  12  2.4 Geographical Applications of Neoclassical Economics  14  3. Neoclassical Economics and Labour Migration  20  3.1 The Foundations of Neoclassical Labour Migration Theory  20  3.2 Empirical Application of Neoclassical Labour Migration Theory  22  3.2.1 Assumptions of Labour Migration  23  3.2.2 Geographical Models of Labour Migration  24  3.2.3 Empirical Applications  27  3.2.3.1 Micro-Adjustment Models  27  3.2.3.2 Macro-Adjustment Models  28  4. Data and Methodology  32  4.1 Data  32  4.2 Methodology  35  4.2.1 Theoretical Considerations  35  4.2.2 Methodology  38  5. Data Analysis  43 iii  5.1 Gross M i g r a t i o n F l o w s  43  5.2 L a b o u r F o r c e Adjusted M i g r a t i o n Rates  45  5.3  Migration  Rates  Adjusted  for  Labour  Force,  Distance  and  Intervening  Opportunities  57  5.4 Wages, U n e m p l o y m e n t Rates and Adjusted M i g r a t i o n Rates  69  5.5 N e t M i g r a t i o n and Changes in W a g e and U n e m p l o y m e n t Rates  73  5.6 S u m m a r y of Findings  76  6. A c c o u n t i n g for F a i l u r e s of the Neoclassical M i g r a t i o n Model  77  6.1 M a x i m i z a t i o n  77  6.2 T e m p o r a l Considerations  84  6.3 Social Constraints to L a b o u r M i g r a t i o n  86  6.4 L a b o u r M a r k e t s  87  6.5 G o v e r n m e n t Intervention  88  6.6 Spatial E q u i l i b r i u m  93  7. S u m m a r y and Conclusion  96  8. Bibliography  .•  iv  98  LIST OF TABLES 4.1.1 A m a l g a m a t i o n of Occupational G r o u p s  34  5.1.1 Gross M i g r a t i o n , 1976-1981, A l l Occupations  44  5.1.2 N e t E x c h a n g e M a t r i x , 1976-1981, A l l Occupations  44  5.2.1 M i g r a t i o n Rates Adjusted  for Size of the L a b o u r Force,  1976-1981,  Managerial,  Administrative  46  5.2.2 Migration Rates Adjusted for Size of the L a b o u r Force, 1976-1981, N a t u r a l Sciences .'  46  5.2.3 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Social Sciences47 5.2.4 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Teachers 5.2.5  M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force,  47  1976-1981, Medicine &  Health 5.2.6  48 Migration  Rates  Adjusted  for  Size  of the  Labour  Force,  1976-1981,  Fine  Commercial Artists  & 48  5.2.7 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Clerical W o r k e r s 49 5.2.8  Migration  Rates  Adjusted  for  Size  of  the  Labour  Force,  1976-1981,  Sales  Occupations 5.2.9  Migration  49 Rates  Adjusted  for  Size  of the  Labour  Force,  1976-1981,  Service  Occupations  50  5.2.10 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, 5.2.11 M i g r a t i o n  Rates Adjusted  for Size of the L a b o u r Force,  Agriculture...50  1976-1981,  Primary  Occupations 5.2.12 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Processing  51  5.2.13 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, M a n u f a c t u r i n g 52 5.2.14 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Construction.52 5.2.15 M i g r a t i o n Rates Adjusted for Size of the L a b o u r F o r c e , 1976-1981, Transportation 53 5.2.16  Migration  Rates  Adjusted  for  Size  of the  Labour  Force,  1976-1981,  Occupations  Other 53  5.2.17 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, A l l Occupations 54 5.3.1 Regression of L a b o u r Force Adjusted M i g r a t i o n Rates with Distance and Intervening Opportunities, b y Province of O r i g i n  56  5.3.2 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities,  1976-1981, M a n a g e r i a l , Administrative  5.3.3 M i g r a t i o n Rates Adjusted Opportunities,  59  for Size of the L a b o u r Force, Distance and Intervening  1976-1981, N a t u r a l Sciences  59  5.3.4 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities,  1976-1981, Social Sciences  60  5.3.5 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities,  1976-1981, Teachers  60  5.3.6 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Medicine & H e a l t h  61  5.3.7 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities,  1976-1981, F i n e & C o m m e r c i a l A r t i s t s  5.3.8 M i g r a t i o n Rates Adjusted Opportunities,  61  for Size of the L a b o u r Force, Distance and Intervening  1976-1981, Clerical W o r k e r s  ;  vi  62  5.3.9 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Sales Occupations  62  5.3.10 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Service Occupations  63  5.3.11 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Agriculture  '.  63  5.3.12 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, P r i m a r y Occupations  64  5.3.13 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Processing  64  5.3.14 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, M a n u f a c t u r i n g  65  5.3.15 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Construction T r a d e s  65  5.3.16 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, T r a n s p o r t a t i o n  66  5.3.17 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1876-1981, Other Occupations 5.4.1  Significance of Interregional Differences  66 in W a g e  Residual M i g r a t i o n , b y Province of O r i g i n 5.4.2  and U n e m p l o y m e n t Rates on 70  Significance of Interregional Differences  Reisdual M i g r a t i o n , by Occupation  in W a g e  and U n e m p l o y m e n t Rates on 72  5.5.1 Significance of N e t M i g r a t i o n on Changes in W a g e a n d U n e m p l o y m e n t Rates, 19761981, by Province  74  vii  5.5.2 Significance of N e t M i g r a t i o n on Changes i n W a g e and U n e m p l o y m e n t Rates, 19761981, by Occupation  75  6.5.1 C M M P Generated M i g r a t i o n as C o m p a r e d to the Total Internal M i g r a t i o n in C a n a d a , 1966-1976 6.5.2  CMMP  90 Generated M i g r a t i o n as C o m p a r e d to the Total Internal  Migration, by  Province, 1976-77 a n d 1977-78  90  6.5.3 T h e Effects of Selected Changes in F i s c a l Structure on O u t - M i g r a t i o n Rates  From  the Atlantic Provinces Including Intra-Atlantic M o v e s , L o w e r Income C l a s s , 1968-1977..92  viii  LIST OF FIGURES 2.2.1 Feasible Resource Allocation as a n Intersection of Resource Constraints  10  2.4.1 Bid-Rent Functions a n d Locational E q u i l i b r i u m  15  2.4.2 Concentric Zone M o d e l of L a n d U s e  15  ix  ACKNOWLEDGEMENT T h e two past two years at the U n i v e r s i t y of B r i t i s h C o l u m b i a have been most enjoyable. In particular I would like to thank m y supervisor, D r . T r e v o r B a r n e s , for his support a n d patience during all phases of m y studies. T h a n k s also go to m y second- reader, D r . K e n Denike, for providing help with the methodology. I a m particularly indebted to D r . J a m e s W . Y o u n g , m y undergraduate supervisor at Concordia U n i v e r s i t y , for awakening my  interest in economic  geography  a n d - apart from giving me  the  occasional  well-  deserved kicks in the r e a r end - for being such a n outstanding teacher. A b o v e all, however, I would like to thank m y parents, Rudolf and Hildegard Olligschlaeger, who have sacrificed so  much  in  providing  for  their  childrens'  education,  for  their  affection,  love  and  understanding. It is to them that I dedicate this thesis. F i n a l l y , m y graduation from this university m a r k s the end of a six year stay in C a n a d a . D u r i n g those six years C a n a d i a n s have at all times made me feel welcome and at home. So, like thanks a lot, eh?  x  1. INTRODUCTION. E v e r since the departure from the descriptive type of economic geography (for some examples see D i c k e n , 1955  and Alexandersson & N o r s t r o e m , 1963) in the late 1950s and  early 1960s, neoclassical economics has played a major role in the field. T h i s is recognized by K i n g (1979, p.34), who characterizes most of current economic geography as: "positivistic, decidedly  neoclassical  in  its  economic  foundations,  and  only  weakly  spatial".  Whereas  neoclassical economics has been heavily criticized for quite some time by economists (Robinson, 1962;  Dobb,  1973;  Rowthorn, 1974), it is only within the  last  15  y e a r s that  economic  geographers have begun to question the neoclassical theoretical foundations of their own discipline (Massey, 1973; S a y e r , 1976; C l a r k , 1982,  1983; C l a r k & Gertler, 1983). T o this  date two alternative theories have been proposed: the M a r x i s t school of economic geography ( H a r v e y , 1982,  1985) a n d more recently the neo-Ricardian one (Barnes, 1984,  1985; B a r n e s  & S h e p p a r d , 1984). L a b o u r migration has been the focus of m u c h attention in economic geography and regional science. T h i s is largely due to the fact that it has traditionally played a n important role in regional development and in the spatial economy as a whole. While there are m a n y approaches to labour migration modelling, m u c h of contemporary migration analysis is based upon neoclassical economic theory. Specifically, the notions of utility a n d resource allocation which are crucial to the neoclassical scheme, are often k e y assumptions i n the analysis of labour migration. These assumptions, however, have come under h e a v y criticism in recent years (Greenwood, 1975; C l a r k & B a l l a r d ,  1979,  1980; C l a r k ,  1982,  1983; C u r r y ,  1985).  T h u s m a n y empirical studies have shown that such assumptions do not hold in the "real" world.  H o w e v e r , in spite  of the  emergence  of the M a r x i s t  and neo-Ricardian schools  of  economic geography, to date no rigorous alternative theory to neoclassical labour migration analysis has been proposed. T h i s thesis will focus on the neoclassical theory of labour migration and test it using C a n a d i a n interprovincial labour migration d a t a for the period 1976-1981. T h e second chapter  1  of the thesis will provide an overview of the development of the neoclassical school of thought and show how its principles have been applied in economic geography. T h e third chapter will establish the link between neoclassical economics and labour migration, a n d also outline two empirically testable hypotheses that stem from the neoclassical analysis. T h e fourth chapter will discuss the d a t a a n d methodology employed i n testing the two hypotheses. C h a p t e r five analyses the data, and concludes that the neoclassical hypotheses concerning labour migration are invalid at least for C a n a d a during this period. F i n a l l y , chapter six will critically examine the neoclassical contentions about labour migration and suggest w h y the theory does not hold.  2  2. N E O C L A S S I C A L E C O N O M I C S A N D E C O N O M I C G E O G R A P H Y . To understand neoclassical migration analysis, it is first necessary to be familiar with the roots of neoclassicism itself. T h i s introductory chapter consists of four sections. F i r s t , a brief history of neoclassical economics is presented. It will concentrate on those features of neoclassicism that particularly have been employed in economic geography. T h e second section will outline the major characteristics of neoclassical economic theory. T h e third section will critically  examine  these  characteristics.  Finally,  the  fourth  section  will  present  some  geographical applications of neoclassical economics.  2.1 T h e A d v e n t o f N e o c l a s s i c i s m . Neoclassical theory arose during the 1870's (Walsh & G r a m , 1980). A l t h o u g h the t e r m "neoclassicism" itself was not coined until the e a r l y twentieth century. T h r e e authors and their works are commonly associated with its origin: W i l l i a m Stanley Jevons Political  Economy",  1871), C a r l M e n g e r ("Grundsaetze  L e o n W a l r a s ("Elements of Pure Economics", essentially  1874)  der Volkswirtschaftslehre",  {"Theory of 1871)  and  (Dobb, 1973). These three works were  a reaction to the classical school of economic thought, as postulated by S m i t h ,  Ricardo and M a l t h u s (Walsh & G r a m , 1980). F o r classical economists the p r i m a r y concern was the reproduction of the economy and the m a x i m i z a t i o n of surplus, where surplus is defined as total output m i n u s those commodities that are used up i n the production of that output.  In turn the surplus is divided a m o n g three  social classes: workers, landlords and capitalists. T h e problem of classical economics was then to locate the mechanisms which determine what proportion of the surplus each class receives. A n o t h e r feature of the school was its emphasis on the conditions of production. D e m a n d does not p l a y a role because there are constant returns to scale, i.e., changes in output do not affect per unit costs. Neoclassical  economics,  on  the  other  hand,  emphasizes  exchange  rather  than  production. O n l y two sets of actors exist in the neoclassical world: producers and consumers. Prices are  set  through the d e m a n d a n d supply. While consumers  3  are motivated to buy  (demand) goods i n order to acquire utility, producers are motivated to sell (supply) goods i n order to acquire profits. T h r o u g h the action of supply and d e m a n d - the m a r k e t m e c h a n i s m resources are then allocated to the best possible uses. A s will be illustrated below, Jevons, W a l r a s and M e n g e r each made a unique contribution to this new line of thought, which has been more generally termed the "marginal revolution". W i l l i a m Stanley Jevons' (1835-1882) major work, the "Theory of Political Economy" published in 1871, was essentially  devoted to the determination of the mechanics of self-  interest and utility. T h e major novelty of Jevons' theory l a y in the singling out of the "final degree of utility" and the subsequent equating of this with the exchange value of commodity. In other words, the value (price) of a good depended on how m u c h pleasure ("utility") it would give to a n individual. G i v e n that the "utility" of a n individual a n d the value of a commodity are quantifiable factors, Jevons argued that a n y theory dealing with those variables should necessarily be mathematical (Dobb, 1973). These ideas were directly opposed to the beliefs of the classical economists who postulated that value was uniquely determined b y the costs of production, a n d those of M a r x , who implied that it was determined b y the value of labour (labour theory of value). T h i s was most likely one of the major reasons w h y economists at the time were so reluctant to accept Jevons' principles (Howey, 1973). In fact, Jevons w a s better known to his contemporaries as a n applied economist, rather t h a n as a theorist (Deane, 1978). In constructing a theory that deals  with the exchange  of commodities  in light of  consumers' wants and needs, Jevons used a partial equilibrium approach. T h e t e r m "partial equilibrium",  as  opposed  to  "general  equilibrium",  implies  that  onty  a  few  selected  relationships are examined i n detail, while other relationships are assumed to be constant (Hoover, 1978). F o r example, if we w a n t to identify the effect of substituting between various resources i n a production process, then the supply price of those resources is fixed at a constant level. G e n e r a l equilibrium theories,  on the other h a n d , simultaneously  take  into  consideration a l l interdependent variables such as cost schedules, demand functions a n d prices.  4  Carl  M e n g e r (1840-1921) was  economic  thought.  lifetime.  Menger's  U n l i k e , Jevons, theory,  put  the founder of the  he was  forward  Austrian  school of  widely recognized for his  in  his  "Grundsaetze  published in the same y e a r as Jevon's "Theory of Political  der  Economy",  neoclassical  writings during  his  Volkswirtschaftslehre",  was v e r y similar to that  of Jevons, except in that it was not mathematical . The  objective  of  Menger's 1973).  "Grundsaetze"  development  (Streissler,  The  main  development  is brought about b y increases  was  to  of  his  thrust  sketch  a  argument  in h u m a n welfare,  theory was  which is  of  economic  that  economic  defined  as  the  "constant widening of the range of goods and the improvement of their quality, i.e. changes in the productive output" (Streissler, 1973, pp. 164-165). In the process of constructing his theory of development, M e n g e r also constructed a theory of value which was v e r y close to that of J e v o n s . T h e value of a "first order" (consumer) good was derived from its power of satisfying h u m a n wants, whereas the value of a "higher order" (producer) good was determined by its contribution to the production of goods that cater directly to h u m a n wants (Dobb, 1973). In both cases the method used to derive the value was the so-called "loss principle", where the value of a good is defined as the loss of satisfaction a person experiences i f he or she has to do without it. In effect this is identical to the m a r g i n a l utility of a good: if a person is deprived of a good then the decrease in the overall utility of that person is equal to the m a r g i n a l utility times the quantity of the good that is lost. U n l i k e Jevons, M e n g e r ' s concern was always  out  of  equilibrium.  Menger  believed  the detailed study of a n economy which is that  because  of  information  uncertainty,  disequilibrium is the n o r m within a n economy. T h i s belief also accounts for Menger's rejection of the standard simplifying assumption of a single equilibrium price in a m a r k e t . F u r t h e r m o r e , it has also been judged to be the reason w h y he did not use mathematics. L e o n W a l r a s (1834-1910) was the third, a n d perhaps most influential, of the three founders of neoclassical economic theory. W a l r a s began work on his theory i n 1859, but did  5  not complete it until 1872 (Jaffe, 1973). H i s major work, "Elements of Pure Economics",  finally  was published in 1874. W a l r a s ' s theory was expressed in mathematics . One of his m a i n achievements,  in  fact, was the "synthesis of various aspects of the new approach into a m a t h e m a t i c a l system of m u t u a l dependence" (Dobb, 1973). T h e establishment of a "system of m u t u a l dependence" refers to a situation of general equilibrium, where all the central variables are considered simultaneously. T h i s is in direct contrast to Jevons and M e n g e r , with the former adopting a partial equilibrium approach and the latter a s s u m i n g that the system is constantly out of equilibrium. In  his  "Elements  of Pure  Economics"  Walras  assumed  that  given  first,  certain  predetermined quantities of productive services a n d , second, free competition, there will be three  so-called  "natural  effects"  (Jaffe,  1973):  (1)  certain definite  quantities  of various  products; (2) a definite price of each product at each moment in time; and, (3) a definite price of each productive service at each moment in time. T h e goal of his theory was  thus to  determine how these quantities and prices are arrived at. H i s answer to this was to solve a system of linear equations where the three "natural effects" appear as unknowns  (Jaffe,  1973). U n d e r these assumptions W a l r a s then proceeded to outline the two key concepts of his work: the theory of exchange and the theory of m a r g i n a l utility. B o t h theories were brought together at the m a r k e t place. E x c h a n g e will continue to occur until both sides can no longer gain any more utility from further trade, at which point the equilibrium is reached. In more general terms, the value of commodities is predetermined by their scarcity. T h e scarcer a good, the greater is its m a r g i n a l utility and hence the higher its price. E q u i l i b r i u m prices are then equal to the ratios of "raretes" (scarcities), where raretes are defined as the  "intensities  of the last wants satisfied for the holders of the commodities" (Dobb, 1973, p.204). A s mentioned above, W a l r a s is considered b y m a n y authors to be the most influential of the three founders of neoclassicism. I n fact, contemporary neoclassicism is often referred to as "post-Walrasian" (Walsh & G r a m , 1980). T h e reason for this is that W a l r a s was far more  6  successful  t h a n Jevons or M e n g e r in establishing a clearly defined analytical link between  m a r g i n a l utility and the m a r k e t price of a commodity (Jaffe, 1973).  2.2 M A J O R CHARACTERISTICS OF N E O C L A S S I C A L E C O N O M I C T H E O R Y  Perhaps  the  importance follows psychological  central feature  of  neoclassicism,  is  its  reliance  on  utility.  Utility's  from its role within the neoclassical theory of value. F o r utility is  entity  that  provides  a  good  with  value.  It  represents  the  the  fundamental  psychological satisfaction that is the motive behind any purchase. T w o features stem from the nation of utility: first, following Jevons et a l . , there is a systematic relationship between price (exchange value) and utility (use value). Second, because utility is what everyone wants, it follows that producers and consumers employ their resources in the most efficient w a y , that is, to realize as m u c h utility as possible given the available means. T h i s is termed "resource allocation".  Given  these  preliminary  remarks,  the  intention  of  this  section  is  first  to  summarize the general characteristics of neoclassicism, and second, to discuss the concepts of utility and resource allocation in detail. N o t only do the latter concepts play a pivotal role in neoclassical economics, but, by extension, in neoclassical economic geography as well. T h e r e are six major characteristics of neoclassical economic theory, all of which been applied i n economic geography and regional science  (King,  have  1979). F i r s t , the principal  focus of neoclassical economics is on equilibrium analysis, both general and partial. W i t h i n this context, the m a i n goal is to determine the conditions which m u s t exist if equilibrium is to be stable.  T h u s the tasks of neoclassical economics are twofold: first, to show that equilibrium  exists, and second, to prove that if at any point in time the s y s t e m is out of equilibrium, "forces exist that drive the system back to equilibrium" (King, 1979, p.37). Second,  it  is  consumers.  Each  consumers  display  assumed  of these the  that  only  groups act  same  two  in a  behaviour  groups  of individuals exist:  unified m a n n e r , in that both  and  make  identical  decisions  producers  and  producers and  under  the  same  circumstances. T h e a i m of both consumers and producers is to seek a state where they are as  7  well off as possible. T h i s leads to the third major characteristic: consumers seek to maximize utility, while producers seek to maximize p r o f i t . T h e fourth characteristic identifies the optimal state of a n economy once it has reached equilibrium. Such a state is defined b y the so-called "Pareto-optimality" criterion (King, 1979). A n equilibrium is considered to be Pareto optimal i f and only if there is no other point where at least one consumer would be better off and no other consumers worse off ( M y r d a l , 1953). T h u s in  Pareto-optimality  consumers'  utilities  are  maximized  thereby  allowing  the  "greatest  happiness for the greatest number". F i f t h , it is generally assumed that there are constant returns to scale in production. Production functions  are consequently  returns to scale, increases  all linear-homogeneous.  Because  there  are  constant  or decreases in the d e m a n d for a product will not lead to any  increases or decreases in its price. Prices are therefore supply inelastic. Finally,  it is  assumed  that both  the  producers  and the  consumers  have  perfect  knowledge of all prices. L e t us now first t u r n to the concept of "utilitj'". F r o m the previous discussion we have seen that utility is a key to the theories of all three founders of neoclassicism. F o r Jevons it was  the  amount of pleasure  a good provided;  for M e n g e r it represented  the amount of  displeasure an individual experienced i f he or she was deprived of that good (loss principle); and for W a l r a s the utility of a good was linked to its scarcity: the scarcer a good, the more satisfaction it provided to an individual. In general, however, all three were all referring to the same thing: the use-value of a good. T h e value of a good is directly derived from the utility it provides. J u s t as value can be expressed i n terms of prices (a physical quantity), the basis of a good's value, utility, can then be expressed in satisfaction (a psychological quantity). A l l individuals act to maximize their utility, i.e., they strive to obtain the m a x i m u m satisfaction. T h e neoclassical argument goes that in p u r s u i n g their own utility m a x i m i z a t i o n (see third characteristic above), individuals are also  collectively  maximizing  society's  utility.  When  8  all  individuals' utilities  have  been  maximized  the  point of equilibrium is reached,  i.e.  it is  not possible  to change  without  decreasing the collective utility. T h u s the greatest happiness for the greatest number (Paretooptimality) is achieved. Therefore, neoclassicists argue, because all individuals have the same goal, n a m e l y to m a x i m i z e their utilities, there is a n a t u r a l tendency towards a state of equilibrium. Consequently, it is in most cases not necessary to interfere with the economic process in order to maximize h u m a n welfare.  Therefore the argument is that political economists  should adopt a "laissez faire" type of attitude. Connected to the notion of utility is the concept of "marginal utility". T h e term was not coined until the e a r l y 1900's, when it was introduced as a n alternative t e r m for Jevons' "final utility" (Howey,  1973). T h e m a r g i n a l utility of a commodity is the change  in utility  an  individual receives f r o m consuming a n additional unit of a service or a good. T h u s the value of a good is directly derived from its m a r g i n a l utility. U n d e r the assumption of utility m a x i m i z a t i o n neoclassicists explain h u m a n behaviour. If it is possible for a person to gain additional utility b y obtaining a good or service, then, provided he or she has the funds to do so, it will be purchased. O n the other h a n d , if a n action will lead to disutility, i.e., a reduction in utility, a person will refrain from undertaking it. L e t us now t u r n to the issue of resource allocation. Resource allocation refers to the distribution of two or more given quantities of goods or services between two or more uses. Because consumers are utility m a x i m i z e r s a n d , b y extension, producers are profit maximizers, it is argued that these goods or services will be efficiently  distributed such that  Pareto  optimality is achieved. L e t us illustrate this principle by using a typical "post-Walrasian" example (see F i g u r e 2.2.1), where we have two input factors, land (T) a n d labour (L), and two commodities, wheat (W) and rice (R). T h e two  input factors  are constrained in that only a fixed amount  is  available. T h e a m o u n t of wheat and rice produced is shown on the y and z axes, respectively. A t point L y ^ all of the labour supply is used up for the production of wheat, so that  the  m a x i m u m a m o u n t of wheat possible is produced given the fixed supply of labour. S i m i l a r l y ,  9  1  F i g u r e 2.2.1: Feasible Resource A l l o c a t i o n as a n Intersection of Resource Constraints. I  Wheat-  Rice Source: W a l s h & G r a m (1980)  10  point L j ^ shows the m a x i m u m amount of rice that can be produced if all of the labour supply is used for rice production. T h u s any point on the line connecting L  w  and L - ^ (referred to as the  "production possibility frontier") represents a feasible allocation of labour between wheat and rice production, considering the  amount of land available. In the  same m a n n e r the  line  between T y ^ and T j ^ represents the production possibility frontier of land. Superimposed on the d i a g r a m are a number of points ( Y Q to Y g ) . A l l points, with the exception of Y g , Y y a n d Y g , are feasible locations. Point Y g exceeds both the land and the labour constraint, whereas at Y g the land constraint is exceeded and at Y y there is not enough labour available. T h e ideal location would be at Y g . H e r e both input factors are fully utilized and efficiency is at a m a x i m u m , i.e., all available resources are put to use. A l l other points are at levels of production where at least one of the resources is underutilized. It should be noted that although a simple case, the above example c a n be extended to any number of commodities and input factors, or resources. T h e difference between W a l r a s i a n and post-Walrasian neoclassical economics is that for the  former point Y g would be considered  the  only feasible  combination of  resource  allocation. T h i s is because it is assumed that all resources m u s t be fully utilized. Therefore any other point would constitute a "waste" of available resources. In post-Walrasian economics all feasible locations would be considered. F o r example, consumers in the model m a y all be wheat eaters, i n which case point Y-^ would be the ideal allocation. W a l r a s ' s assumption of fully utilized resources was the subject of considerable debate during the  1930's (Walsh &  G r a m , 1980). T h e most frequent a r g u m e n t was that it is not always possible to fully employ all resources, since, in a two factor - two commodity case, for example, the two production possibility frontiers m a y not intersect at a point where both outputs are non-negative. B o t h sides, however, agree that at point Y Q production would never occur. A t least one of the resources  must  always be fully utilized. T h i s happens because individuals wish  maximize their utility, i.e., get the most use (satisfaction) their wants and desires.  11  to  out of what is available in light of  T h e m a r g i n a l revolution h a d significant implications for orthodox economic theory. It provided theorists with a convenient set of analytical tools that could easily and effectively be applied to a wide range of uses. In particular, m a r g i n a l analysis provided a technique to identify the most efficient  allocation of a given set of competing resources. T h e o p t i m u m  allocation was at that point where m a r g i n a l values were equalized.  T h i s allocation principle  could also be applied to a number of different problems, be it the allocation of a fixed a m o u n t of income a m o n g a range of consumer goods or a set of production factors. In s u m m a r y , with techniques enabling the theorists to identify optimal allocations of resources neoclassicists  were able to derive a seemingly logically sound explanation of how  commodity and factor prices are determined in a m a r k e t system,  while at the same  time  m a x i m i z i n g consumers' satisfactions. T o economists at that time this new method represented substantial analytical power. T h u s it is no surprise that m a n y students of economics  were  attracted b y neoclassicism, and that neoclassical economics soon became the leading school of thought.  2.3 C R I T I C I S M S O F N E O C L A S S I C A L E C O N O M I C T H E O R Y .  T h e r e are numerous criticisms of the above characteristics that have been voiced b y economists,  regional  scientists and geographers  alike  (King,  1979;  Hollis & N e l l ,  1975;  Robinson, 1962; M y r d a l , 1953; B a r n e s , 1984, 1985; B l a u g , 1973; H o l l a n d , 1976; C l a r k ,  1982,  1983; C l a r k & Gertler, 1983). In particular, critics have tended to focus on utility (and utility maximizing  "economic  equilibrium)  and  hypotheses.  man"),  problems  of  resource dynamics  allocation in  the  (and  the  inevitable  formulation and  testing  pareto of  optimal  neoclassical  T h i s section will engage in a p r e l i m i n a r y discussion of some of these criticisms.  F u r t h e r criticisms, where appropriate, will be put f o r w a r d in later chapters. T h e concept of utility is one of the most heavily criticized aspects of neoclassical theory ( M y r d a l , 1953; Robinson, 1962,  1973; Dobb, 1973). O n e of the strongest arguments  utility has been that it is a circular concept (Robinson, 1962, p.48):  12  against  "Utility is a metaphysical concept of impregnable circularity; utility is the quality in commodities that makes individuals want to buy them, and the fact that individuals want to buy commodities shows that they have utility."  U t i l i t y and the m a x i m i z a t i o n assumption have been expressed in a concept that has come to dominate both the disciplines of economics a n d economic geography: "economic m a n " . Economic m a n , sometimes also referred to as "rational economic m a n " , is a person who essentially possesses no flaws. In s u m m a r y , economic m a n has the following characteristics (Hollis & N e l l ,  1975): (1)  he has  perfect knowledge of all factors involved in whatever  situation; (2) the principle applies to all organizations, including producers, consumers a n d landlords; (3) economic actors are m a x i m i z e r s , which implies that producers maximize profits, consumers maximize their utility, and landlords m a x i m i z e the amount of rent they can obtain under given circumstances; (4) rational economic m a n will always make a "rational" decision, i.e., he never makes a mistake. T h e r e are a n u m b e r of problems w i t h economic m a n . F i r s t , in using h i m it is a s s u m e d that everybody behaves i n the same w a y . T h u s a n y model based on economic m a n ignore diversity or cultural differences. Second, it has been argued that economic m a n is too simplistic an assumption (Pred, 1967, 1969; Hollis & N e l l , 1975). F o r example, A l l a n P r e d (1967), i n outlining his behavioural m a t r i x argues that economic m a n in possessing the ideal combination of perfect information a n d perfect computational skills is a special case that rarely, i f ever, occurs. F i n a l l y , it has been argued that economic m a n can never be tested (Kaldor, 1972). T h e a r g u m e n t here is that rational economic m a n is insulated against empirical falsification b y means of a ceteris paribus  clause. T h e problem is that i f in testing economic m a n we find that  he is disconfirmed, one never knows whether such disconfirmation is a result of h i m actually being falsified or whether things are not in fact equal. A final criticism of neoclassical theory is that its nature largely prohibits the use of d y n a m i c models. T h e economic s y s t e m is always considered to be at or near a state of equilibrium. If at any point i n time the s y s t e m falls out of equilibrium, then the perfectly  13  competitive system will ensure that m a r k e t forces will bring the system back to equilibrium. T h i s occurs because disequilibrium implies that w h e n some people experience disutility, utilitym a x i m i z i n g individuals will strive to m a k e themselves better off. In so doing they eventually b r i n g the  system  back in to equilibrium.  H o w e v e r , all other factors  are assumed  to be  exogenous to the s y s t e m and stable over time. T h u s the dynamics of exogenous factors are ignored. T h e emphasis on equilibrium analysis and the consequent neglect of dynamics, so the critics contend, is one of the major setbacks of neoclassicism (King, 1979).  2.4  GEOGRAPHICAL APPLICATIONS OFNEOCLASSICAL ECONOMICS.  Neoclassical economics have been applied i n numerous areas of economic geography, notably in theories of location analysis a n d the analysis of interregional flows, such as trade and migration, for example. In the process both partial and general equilibrium approaches to resource allocation have been adopted. T h e following discussion will outline some of the major theories within the partial and general equilibrium approaches. L e t us begin with partial equilibrium applications a n d some examples from the oldest b r a n c h of regional science and economic geography: location analysis (as we shall see later, however, location analysis is not restricted to the partial equilibrium approach). A v e r y well k n o w n location model u s i n g neoclassical resource allocation techniques is that developed b y Alonso (1964), which analyses the location of a firm within a city using the concept of a bid-rent function.  T h e purpose of the bid-rent function is to show how a firm's  willingness to p a y rent varies with increasing distance from the C B D while keeping profits constant regardless of location. Since it is assumed that the firm is a profit m a x i m i z e r , the objective is to find the location with the highest possible profit level and the lowest possible bidrent. T h i s is the case where the bid-rent function (the slope of which is given b y the size of the site, revenue and operating costs) is tangential to the rent gradient (Alonso, 1970). F i g u r e 2.4.1 illustrates this, where R is the actual rent charged with increasing distance from the city (assuming  that the  slope of the curve is negative),  14  and X-^ to X g are bid-rent functions  Figure 2.4.1 Bid-Rent Functions and Locational Equilibrium.  K  distance  Source: Richardson (1978)  Figure 2.4.2 Concentric Zone Model of Land Use.  distance  Source: Richardson (1978) 15  representing the amount of rent the firm is willing to p a y with increasing distance f r o m the C B D given a particular level of profits. T h e firm will then locate at the point of locational equilibrium, L , where the curve is tangential to the rent gradient. T h e amount of rent will be P at K distance from the C B D . T h i s example  can be extended  to a n y n u m b e r a n d type  of  firms  (Alonso,  1964),  resulting in a land use pattern centered around the C B D . Different firms producing different products (i.e. competing land uses) will have v a r y i n g bid-rent functions. T h u s , if competing land  uses  are  ranked  according to  the  steepness  of their  bid-rent functions,  each  will  monopolize a concentric a r e a around the C B D . In other words, each type of economic activity is "allocated" a particular zone of land. A n example  is shown in  figure  2.4.2, where four  competing land uses (a,b,c,d) are allocated to four zones of activity, resulting in a n "exclusive zoning" pattern (Richardson, 1978). T h e above model has been extended to a large variety of land uses, notably residential and commercial. H o w e v e r , there are two major weaknesses associated with its first,  only one rent is determined exogenously,  necessarily reflect reality.  assumptions:  so that the resulting land use patterns do not  T h e second problem lies with the explicit assumption that the slope  of the rent gradient is negative.  T h e advantage of this is, of course, that it enables a neat  solution to be derived. H o w e v e r , empirical studies have shown that the bid-rent functions for some industries have a different shape (Richardson, 1978). F o r example, some manufacturing industries,  although  initially attracted  to the  suburbs because of lower  land rents,  may  actually be willing to bid higher rents in peripheral locations t h a n at locations closer to the C B D due to other advantages, such as agglomeration economies a n d terminal locations. T h i s could i n t u r n i m p l y a positively sloped bid-rent function. A n o t h e r partial equilibrium approach is that of Weber's (1909) industrial location theory. T h e assumptions in his model are typical of neoclassical economic theory: producers are profit maximizers; they have perfect knowledge of all input factors and transportation costs (they are all rational); and, in the simple transport oriented model, all variables other  16  than distance are held constant. The argument is that under these assumptions the optimal location is uniquely determined at the site where total transport costs are minimized. In the case of m input factors (raw materials) and c markets, the optimum location will be determined by minimizing the sum of all transport costs (Richardson, 1978):  •  mm  „ TC =  m  m 1  i=l  1  t.r.q.  l l l  +  c T  .. ]=1  t.r.q. i i i  (2.4.1)  where: t is the transport rate per unit distance; r^ is the distance between the source of the raw material and the production site; and qj is the amount of material moved from the raw material source to the production site. The equation also implies that if there is more than one market, then the location of the optimal site will be sensitive to variations in demand among the different markets because it influences economies of scale (Richardson, 1978). The pull will be towards that market which shows the highest demand for a product because the per unit cost declines with increasing demand. For many years the major problem to be solved in location analysis was to find the minimum transport cost location under the assumption of profit maximization. Subsequent modifications to Weber's theory by Loesch shifted the attention to variations in demand under the  assumption  of uniform costs. However, this  still implies both revenue  and profit  maximization (Richardson, 1978). Alternative studies have focused on sales maximizing, as opposed to profit maximizing, which implies a different choice of an ideal location if costs change over space. As previously mentioned, most location models adopt the partial equilibrium approach, defined as an economic system is closed off to the rest of the world with all exogenous variables held constant.  A general equilibrium theory of location analysis, in contrast,  simultaneously considers all variables. Such general equilibrium models are extremely difficult 17  to develop, and although there have been numerous attempts at doing so (Henderson,  1958;  Lefeber, 1958; K u e n n e , 1963), all have thus far been unsuccessful (Richardson, 1978). One of the major obstacles is that even if a n initial equilibrium exists, it is almost impossible  to  determine the implications of a disturbance of that equilibrium as each disturbance would bring about a chain reaction of locational adjustments throughout the space economy. O n the other h a n d , for a variety of reasons, such as immobilities and spatial frictions, it is necessary to distinguish between those disturbances that create locational adjustments and those that do not. F u r t h e r m o r e , the prediction of the impact of a disturbance is complicated b y the fact that it takes time for certain factors, such as information, for example, to be transmitted over space. One of the earliest attempts at establishing a general equilibrium theory of location was that of Loesch (1954). T h e basic assumptions of the model are that producers m a x i m i z e profits and consumers maximize their utility b y b u y i n g the cheapest products. T h e competitive struggle  between producers results  in the elimination of excess profits  and thus  locational equilibrium. Specifically, the conditions for the existence of a general equilibrium are (Isard, 1956,  also i n  locational  1960): (1) all space is taken up by m a r k e t areas served b y  producers; (2) because prices are equal to average costs, all producers e a r n n o r m a l profits; (3) m a r k e t areas are of a m i n i m u m size; (4) all producers are located at the optimum site; and, (5) the m a r k e t a r e a boundaries are stable because all consumers are indifferent as to their choice between equidistant suppliers. T h e result of these conditions and assumptions is that regardless of their location all firms  producing a specific good have identical costs, m a r k e t areas, freight rates and f.o.b.  m a r k e t prices. A p a r t from the problems associated  assumptions,  the  Loeschian model is unrealistic in the sense that it neglects locational interdependencies  and  intraindustry  agglomeration  economies.  A  country  with its neoclassical  could thus  never  have  an  industrial  heartland in which, for example, most of the nation's automobile production takes place, as it is the case in C a n a d a . A l t h o u g h the model c a n deal with interindustry agglomerations,  18  the  resulting concentrations of population would negate the conditions for a locational equilibrium (Richardson, 1978). Other attempts at formulating a general equilibrium theory of location have been made b y G r e e n h u t (1956), Henderson (1958), Lefeber (1958) few  examples.  and Isard & Ostroff (1960, to name a  A l t h o u g h m a n y of these models have been more successful  in that  they  eliminate some of the problems associated with Loesch's model, none of them have been able to account for all aspects of the space economy. T h u s a working general equilibrium theory of location has yet to be established. A l t h o u g h the above discussion has not covered all aspects of neoclassicism and its impact on economic geography, it has nevertheless become clear that contemporary economic geography is indeed strongly rooted in neoclassical economics in that it v e r y m u c h reflects neoclassical  thought.  J u s t as  economists  were  attracted b y the  relative p a r s i m o n y a n d  analytical power of neoclassicism, so were geographers d r a w n towards the approach due to the apparent ease and efficiency with which it could be applied to a spatial context. T h e resulting theories and models proved to be extremely popular, illustrated b y the fact that, for the most part, they are still in use today, albeit in modified form. Consequently one m u s t ask the question whether neoclassical economics are really applicable to the "real" world, or whether they are j u s t a vision of an idealized "hypothetical" world.  19  3. N E O C L A S S I C A L E C O N O M I C S  In and  A N D L A B O U R  MIGRATION.  the previous chapter the central features of neoclassical economics were outlined  criticized.  It  was  demonstrated  how  traditional  economic  geography  is  rooted  in  neoclassicism. In the first p a r t of this chapter it will be shown how neoclassical migration theory is derived f r o m the broader neoclassical assumptions. T h i s is followed b y a discussion of several hypotheses  about the causes and effects of labour migration that stem  from  neoclassical f r a m e w o r k . T h e second part, of the chapter will show how these hypotheses  the have  dominated the theoretical and modeling literature of labour migration. In particular the two d o m i n a n t schools of thought within the neoclassical approach will be discussed: the "microadjustment approach" and the "macro-adjustment" approach. It will be argued that although the original models of these two  schools of thought  (Sjaastad (1962) developed the micro-  adjustment model a n d L o w r e y (1966) the macro-adjustment one), have been modified since their initial presentation, both the current literature on labour migration, and perhaps more significantly public policy, has, and continues to be, dominated by a neoclassical vision of the economy.  3.1 T H E F O U N D A T I O N S OF N E O C L A S S I C A L L A B O U R M I G R A T I O N T H E O R Y .  Not  s u r p r i s i n g l y , the key elements of neoclassical labour migration theory are the  same as those discussed in the previous chapter: utility, resource allocation determined b y the laws of d e m a n d and supply and equilibrium. In addition, like all neoclassical theory, it is also highly abstract m a k i n g a few simple assumptions about h u m a n behaviour and the nature of the economy. P e r h a p s the key assumption i n the neoclassical model which is transferred to labour m i g r a t i o n is  that  of utility m a x i m i z a t i o n . F r o m  neoclassical school of thought postulates  the  previous chapter we  know that  the  t h a t all individuals wish to m a x i m i z e their utility  (degree of satisfaction). It was also suggested that utility cannot be m e a s u r e d directly because it consists of a v a r i e t y of factors in t e r m s of which a n individuals determine their level of satisfaction. Consequently some surrogate for utility m u s t be found i n order to model labour  20  migration. W a g e a n d unemployment rates offer themselves intuitively because they are the only variables that v a r y with changes in the supply of labour. Clearly, however, there are other variables that individuals might want to m a x i m i z e , for example, climate or the quality of life. B u t climate is unresponsive to changes in economic variables, and therefore difficult to measure, and in the case of quality of life it is indirectly affected b y changes in wage and unemployment rates and thereby  already partly accounted for. T h u s although wage and  unemployment rates are not the only explanatory variables considered in neoclassical models, they nevertheless represent the key determinants of labour migration. T h i s is so because they are a n indicator of changes in utility at a given place. Perhaps the best w a y to exemplify how the broader principles of neoclassical economics are employed in neoclassical labour migration theory is to use the example of a hypothetical nation composed of two regions. In both regions we have perfectly competitive markets: there is no government intervention; there are no barriers to movement or entry to a n y market, thereby allowing each individual at a n y point in time to move freely from one region to the other; and, finally, information is homogeneous, u n i v e r s a l and complete, thus ensuring that all individuals  possess  perfect  knowledge  about  all  economic  indicators  (wages,  employment, etc.). A l s o , assume that initially the two regions are in perfectly  prices,  competitive  equilibrium, that is, there are no regional differences in a n y of the economic variables. N o w let us assume that for some reason, say, a shortage in the supply of labour, wage rates in one  of the  regions,  call it A , increase.  A s a result the  s y s t e m is no longer in  equilibrium. Because information is assumed to flow freely across space, workers in the other region, call it B , will learn of this wage increase and, because of their desire to maximize their utility, respond b y m o v i n g to region A . In t u r n , the migration from region B to region A will cause a n increase in the supply of labour in region A , while at there same time decreasing it in region B . T h e increase i n the supply of labour will, ceteris paribus,  through the law of demand  and supply, reduce wage rates in region A while the reduction in the pool of workers in B will  21  cause wage rates to rise in that region. W o r k e r s will migrate from region B to region A , and this process will continue until the s y s t e m is eventually brought back in to equilibrium. The  same argument can be made for unemployment rates: if unemployment is lower in  region A than in region B , the unemployed will move to A because of the greater probability of finding a job. In broader terms, labour migration can be viewed as a n "adjustment process" where labour is reallocated according to regional variations in the demand and supply of labour: workers respond to regional differences  in labour m a r k e t conditions b y m i g r a t i n g between  regions until the s y s t e m is back in equilibrium. T h u s , just as resources in the wider economy are efficiently  allocated between uses through the price system,  labour efficiently  "allocated" a m o n g regions  so too, ceteris paribus,  through the p u s h and pull of m a r k e t  is  forces,  namely changes in wage and unemployment rates. In  general then, two hypotheses c a n be derived from this simple model. T h e  first  concerns the causes of labour migration: all other things being equal, labour flow from regions of low wage and high unemployment rates to regions of high wage a n d low  unemployment  rates. T h e second hypotheses is that the effect of labour migration i n regions experiencing net outmigration will be for wage rates to rise and unemployment rates to fall, while in those areas experiencing net inmigration wage rates will fall and unemployment will rise. T h e net result is that the spatial economic s y s t e m will be driven back towards equilibrium, i.e., wage and  unemployment rates will be equal across the country.  3.2 E m p i r i c a l A p p l i c a t i o n s of N e o c l a s s i c a l L a b o u r M i g r a t i o n Theory The  neoclassical labour migration theory presented in the previous section is only a  simple version; it derives from H i c k s ' (1932) early work on wages and labour allocation. Since H i c k s ' pioneering study a number of modifications to the theory have been made. In part, such changes are a result of the realization that the assumptions of neoclassicism r a r e l y , if ever, apply.  Nevertheless,  despite  those  modifications 22  labour  migration  theory  remains  fundamentally neoclassical. T h i s part of the chapter will first present the m a i n assumptions of current labour migration literature, and then show some examples  of geographical  models  employing neoclassical labour migration theory.  3.2.1 Assumptions of Labour Migration. M c K a y & Whitelaw's (1977) work identifies  the six most common assumptions  in  current literature on labour migration. T h e first assumption is that the decision of when and where to migrate is made b y individuals who are free to do as they please. S u c h decisions, however, are influenced by prevailing economic conditions, spatially biased information flows and  existing  social  ties.  This  first  assumption  is  essentially  a modification of the  pure  neoclassical model a n d reflects the realization that the real world is more complicated t h a n the simplifying assumptions of neoclassicism. T h e second assumption is that individual decision m a k i n g takes place within a "free market" framework in which there is a wide range of alternatives. between as m a n y destinations  A person c a n choose  as there are regions within the spatial system. A l s o , once a  person has reached a destination, then he or she is free to compete with the local labour force for any job openings. T h i r d , an individual always has the alternative to r e m a i n in the same location. N o pressures exist that could force a person to move. T h e dislocation of workers due to plant closures, for example, could b y assumption never happen. Fourth,  although it is a n accepted  fact that mobility rates differ b y  socioeconomic  groups, it is assumed that all individuals are subject to a single migration process, albeit with different variables  intensities. influencing  T h i s implies labour  that  each  migration.  It  person responds is  recognized,  in the  however,  same w a y that  the  to  those  intensity  (probability) with which people respond does v a r y . T h i s leads us directly to the fifth most common assumption, which is that since a single  process is assumed,  highly aggregated  data is sufficient to test a migration model  23  because  everybody  behaves  (reacts)  to the  economic  environment  i n the  same  way.  If  everybody did not act in the same w a y the hypothesis on the causes of labour migration would not hold. F i n a l l y , and perhaps most importantly, migration is assumed to operate as a n efficient equilibrating m e c h a n i s m , reducing differences between regions: wage and unemployment rates will, through changes in the supply of labour resulting from migration, be equalized among regions.  3.2.2 Geographical Models of L a b o u r Migration. W i t h i n the r e a l m of neoclassical labour migration theory two distinct approaches have been adopted: the "micro-adjustment" approach (commonly also referred to as the "human investment" approach) and the more widely used "macro-adjustment" approach. W h e r e a s the former  approach reflects  the  highly  individualistic nature  of neoclassical  theory  and  is  theoretically more "pure" t h a n the other, the latter is more practical in that it can actually be applied empirically. In  our discussion  of the  two  approaches  let  us  begin with  the  micro-adjustment  approach and its ties to h u m a n capital or h u m a n investment theory. T h e origins of h u m a n capital theory go back to A d a m S m i t h (Carline et al, 1985). T h e theory is closely linked to the concepts of m a r g i n a l utility and m a r g i n a l product. N o t only has it been used in migration analysis, but also in a wide range of other areas. H u m a n capital theory is used to determine whether an individual will make a decision to "invest" in a n undertaking or not. F o r example, a s s u m i n g a wealth m a x i m i z i n g individual, if the m a r g i n a l increase i n future wages (discounted in terms of the r e m a i n i n g lifetime working horizon) is greater than the cost of such training that enables a person to earn those higher wages, then that person will decide to go ahead with the training. G e n e r a l l y speaking, if the m a r g i n a l increase i n utility or the m a r g i n a l product is greater t h a n the cost of a n undertaking, then, ceteris paribus, always choose such an undertaking.  24  a n individual will  This highly individualistic approach to decision making was first applied in migration analysis by Sjaastad (1962). His argument is that when an individual is considering moving from region A to region B, he or she computes the present value (PV ) of the move with t  respect to the following variables (Clark & Ballard, 1979): Potential earnings (Yg) in region B at time t; current earnings (Y^) in region A at time t; the individual's lifetime working horizon (T); the cost of moving from A to B (C); and a discount rate (r) which individuals apply to their earnings stream. Migration will only occur if the anticipated returns are greater than the cost of moving. In formal terms, define the present value of migrating as:  T  PV(t)  a  =  I t=0  YB  - YA  (1 + r )  - C  Z  (3.2.1)  T  1 where  = t+1. A present value can also be calculated for the decision not to migrate, call it  PV(t) . Therefore, migration will occur if and only if PV(t) is greater than PV(t) . In the case of multiple regions the individual will migrate to that region which promises the highest anticipated returns. The micro-adjustment model has a number of distinct advantages (Schwartz, 1976) which are linked to the significance it attaches to the attributes of individuals. Demographic characteristics such as age, occupation, and education are easily incorporated. Furthermore, contrary to the neoclassical assumption that migrants flow from low wage to high wage regions, it can account for the fact that there are also reverse flows: some people might be able to maximize their future earnings by migrating to a depressed region. However, there are two major problems with this model (Clark & Ballard, 1979). The most important one is that it is essentially untestable. Individual case histories would be necessary to test the propositions. Even if such data did exist, one would need a sufficiently large number of regionally stratified observations in order to make any general conclusions as to its validity. The second problem is the assumption that the individual will always go to that 25  region which promises the highest future gain. In real life the decision of when and where to migrate might well not be decided by a n individual. A person might be forced to move (because of a plant closure, for example; for a discussion of this see Gordus et a l . , 1981) even though the move will result in a net loss. O n the other h a n d , a move could be the result of a company transfer, in which case the decision is made by a higher authority, not the individual  (see  M c K a y & Whitelaw, 1977). L e t us now turn to the macro-adjustment approach. T h e assumptions it makes are typical  of  neoclassical  theory:  workers  have  perfect  knowledge  of  all factors  involved;  information is homogeneous, u n i v e r s a l and complete; there are no differences between regions other t h a n in terms of wage a n d unemployment rates; and there is no significant social or economic cost associated Lowrey  (1966).  In his  with the migration process. W o r k in this a r e a was model wage  and unemployment  pioneered by  characteristics at the origin and  destination points are assumed to be the determinants of migration. In its basic version, the model can be specified as:  u.  w.  L. L . i :  u.  w.  D. .  , 1*  1 *  where: Mjj is the gross migration from i to j ; U j and U j are the unemployment rates in i and j ; W j and Wj are the wage rates in i a n d j ; and L j , L j and Djj are the population and distance components of the gravity model. T h e major criticism of this model is that its assumptions conflict with reality: perfect information does not exist and there are numerous social and economic costs associated with the migration process. F u r t h e r m o r e , there has been v e r y little empirical evidence to support the L o w r e y model. C l a r k (1983) maintains that although it has been quite successful  for  prediction purposes, probably due to its gravity component, it is inadequate in explaining the labour migration process.  26  In s u m , both the micro- and the macro-adjustment models are representative of the first neoclassical hypothesis, n a m e l y that labour will migrate in accordance with the spatial pattern  of  demand  and  supply  as  reflected  in  interregional  differences  in  wage  and  unemployment rates. It is assumed that in the long r u n migration will tend to decline as the s y s t e m approaches equilibrium.  3.2.3 Empirical Applications. T h e r e are numerous examples of applications of neoclassical theory in labour migration modelling ( L a n s i n g and Mueller,  1967;  Renshaw,  1970;  Fields, 1976,  1978;  Milne,  1981;  S i m m o n s , 1982; Y o u n g , 1984). T h e first p a r t of this section will discuss applications of the micro-adjustment model, while the second will deal with examples of applications of the macroadjustment model.  3.2.3.1 Micro-Adjustment Models. E m p i r i c a l applications of the micro-adjustment approach to migration analysis are few and far between. T h i s is not surprising, considering the data requirements of the model. O f the few examples that do exist, most adopt the micro-adjustment (human investment) approach in their theoretical sections, but revert to a n aggregated  version when empirically testing  the  model. One example of this is V a n d e r k a m p ' s (1968) study of interregional mobility in C a n a d a . He  hypothesizes  that individuals are more likely to migrate  depending on the net advantage  they  differentials,  unemployment  aggregate  V a n d e r k a m p uses  variables).  He  found  that  from region A to region B  derive from migrating. A p a r t f r o m regional income  the  flow  and of  return  migration  migration  unemployment (as is predicted b y the neoclassical hypothesis)  is  as  variables  negatively  related  (all to  and that r e t u r n migration is  positively related to the unemployment variables. T h e positive relationship is explained by the push of the sending region's employment being stronger t h a n the pull of the region to which they return.  27  Other  examples  are  those  of B r e n n a n (1965),  Diehl  (1966),  Bodenhofer  (1967),  R a b i a n s k i (1970) and K o t t i s (1972). T y p i c a l l y , these studies relate the benefits of migration to factors such as variations in basic wage rates, opportunities for job t r a i n i n g and education, and economic rewards in alternative regions for attained skills (Shaw, 1975).  3.2.3.2 Macro-Adjustment Models. Far  more  popular t h a n  the  micro-adjustment  approach is  the  macro-adjustment  approach. T h e majority of past and current literature on labour migration has adopted it in one form or another. A s mentioned earlier it is essentially a n aggregated version of the microadjustment approach a n d reflects the neoclassical notion that labour flows from areas of low wages a n d high unemployment to high wage and low unemployment regions. G r a n t & V a n d e r k a m p (1976) examine the causes and effects of labour migration in C a n a d a d u r i n g different time periods. In a model almost identical to that of L o w r e y ' s , the significance  of wage  rates,  unemployment  rates  and job information were  examined  in  determining migration flows. T h e significance of all the variables was tested. T o allow for the fact that information about other provinces declines with increasing distance, a gravity type variables was also included. A l t h o u g h it was found that the standard linear equation did not satisfactorily explain the variation in mobility rates (both income and unemployment were insignificant as explanatory variables), a general observation was that income was a strong pull factor, but only a weak push factor. A s expected, distance played a major inhibiting role. U n e m p l o y m e n t had a strong push and a negative pull effect. T h e r e was, however, considerable variation in the significance of variables between time periods, suggesting that the migration pattern m a y be subject to cyclical fluctuations. A n o t h e r neoclassical study of labour migration is that b y R o s e m a n (1977) of changing migration patterns in the U n i t e d States. A g a i n the approach was identical to that of L o w r e y , w i t h one  major modification: the decision to move  and the decision where  to move  were  considered as two separate models (equations). T h e results were essentially commensurate to  28  those of G r a n t & V a n d e r k a m p ' s (1976), with the additional observation that there was also a considerable variation in mobility rates between age groups. Greenwood (1981) proposes a typical neoclassical model of metropolitan growth a n d migration. A r g u i n g along traditional lines, Greenwood maintains that outmigration of labour will put u p w a r d pressure on wage levels whereas inmigration will apply downward pressure. T h e magnitude of change in wages, however, depends on the relative magnitude of the change in the demand and suppty of labour. T h e same argument holds for unemployment rates. A l s o , the impact of migration on both variables is contingent upon a variety of other factors, such as the occupational composition of the inmigrating labour force visa-vis the occupational structure of the existing labour force. T h i s represents a departure from the n o r m a l assumption where the labour force is taken to be homogeneous, that is any labour can do a n y job. Y o u n g (1985) analysed changes in the significance of selected origin and destination characteristics on migration flows to W e s t e r n C a n a d a and on return migration f r o m W e s t e r n Canada  between  1971-1976 and  1976-1981 using  a model  along the  lines  of G r a n t  &  V a n d e r k a m p (1976) a n d Courchene (1970). These characteristics included a g r a v i t y t e r m , a n n u a l average employment in 1971 dollars (income), percentage growth in employment over the five y e a r census period, and a cultural variable (percentage  of the population of F r e n c h  mother tongue). It was found that the significance of origin and destination variables declined significantly between the two time periods under analysis. While for 1971-1976 almost all of the variables were statistically  significant at the  1% level, for 1976-1981 only two of the  variables were significant at 5%. A l t h o u g h the results of the analysis have to be interpreted with caution due to the five year census interval, they do suggest that there could be cyclical fluctuations in the sensitivity of migrants to interregional differences in economic variables. One of the most extensive reviews of migration literature is that conducted b y S h a w (1975).  H i s work m a r k s  the  beginning  of a  growing criticism of neoclassical  migration  analysis. H i s criticism, however, is limited to methodological rather than theoretical problems. T h u s he argues that aggregate migration measures do not permit the identification of non-  29  economic motives for migrants. F u r t h e r m o r e , r e t u r n migration a n d multiple moves are not accounted for in the neoclassical approach. In addition, even if crude economic measures  (such  as wages and unemployment) do seem significant in explaining migration patterns, the results are only rough indicators of the real forces at work in migration. Apart  from  the  methodological  criticisms  of  Shaw,  theoretical  failings  of  the  neoclassical approach have recently been identified. M o s t critiques have either focused on the assumptions of h u m a n capital theory (Greenwood, 1981; Peek & Standing, 1982) or on the effects of migration (Clark & B a l l a r d , 1979, 1980; C l a r k , 1982, 1983; C l a r k & Gertler, 1983). T h e r e is, however, a general consensus that migrants are not as sensitive to economic factors as neoclassical theory suggests. In addition, empirical evidence has shown that the broader framework that accounts for migration is one of cumulative causation ( C u r r y , 1985) t h a n a Pareto-optimal state of equilibrium (for a more detailed discussion see  rather  chapter  6).  Despite such criticisms, a complete alternative labour migration theory has yet to be proposed. These  methodological  and  modelling (for further examples  theoretical  criticisms  see K r i e s b e r g & V i n i n g ,  of  neoclassical  1978;  Stone,  labour 1978,  migration  1979;  Plane,  1981; Stock, 1981; Foot & M i l n e , 1982; Plane et a l . , 1984), are being increasingly recognized by neoclassicists themselves. T h e result is that a growing number of studies have  adopted  increasingly sophisticated methods, thereby recognizing, for example, that information is not homogeneous and universally available, people are not always free to move or to stay, and that the labour m a r k e t is not perfectly competitive. However, despite evidence to the contrary, most contemporary migration analysts hold on to the belief that interregional migration will eventually lead to a Pareto-optimal equilibrium. One of the  recent examples  of this  persistence  is a study b y C e b u l a (1979).  He  proposes two models of labour migration, one along the lines of the micro-adjustment approach and the other a n aggregate macro-adjustment model. S u r p r i s i n g l y , only v e r y few modifications are made to the s t a n d a r d L o w r e y a n d Sjaastad models. T h e point is, however, that a s s u m i n g perfectly competitive markets (!) and m a x i m i z i n g behaviour he argues that while a perfect  30  spatial equilibrium m a y never be reached, this is only because the m a r g i n a l interregional differences in economic benefits (marginal utility) do not outweigh the costs of moving. T h i s imperfect spatial equilibrium is thus only a reflection of rational decision m a k i n g b y utilitym a x i m i z i n g economic m a n : people will not make themselves better off b y m o v i n g because the costs are greater t h a n the benefits.  Therefore, while  wage equalization will never occur,  labour migration will nevertheless eventually result i n a Pareto-optimal equilbirium (nobodj  r  c a n make h i m or herself better off by moving).  In s u m m a r y , neoclassical economic theory as embodied in the micro-adjustment and the macro-adjustment approach to modelling labour migration is, despite a growing body of literature  critical of  its  assumptions  and  hypotheses,  still  very  much  alive.  Although  neoclassicists do recognize and allow for the inadequacies of the standard assumptions, continue  to argue  that labour migration will lead to a spatial equilibrium. T h e next  they two  chapters will examine the validity of the neoclassical h^potheses outlined in section 3.1 in a C a n a d i a n context.  31  4. D A T A  A N D  M E T H O D O L O G Y .  The objective of this chapter is to discuss the data and methodology used in testing the two neoclassical hypotheses presented i n chapter 3. Specifically, these are that (1) differences in unemployment a n d wage rates are directly related to migration rates, and (2) that  net  migration figures influence changes in u n e m p l o y m e n t and wage rates within a region. T h i s chapter is divided into two parts. T h e first discusses problems of data, while the  second  addresses methodological issues.  4.1  DATA.  D a t a availability and reliability have posed a problem to researchers in m a n y areas of migration  study.  While  the  micro-adjustment  model  probably  represents  the  purest  transformation of neoclassical theory, it requires unobtainable data. A s a result researchers have turned to aggregate data models, in particular the macro-adjustment approach. Despite the d a t a availability for aggregate modelling there are disadvantages to using gross flows. F o r example, return migration (individuals who return to their place of origin after h a v i n g moved to another place in search of a job) are almost impossible to  estimate.  However, studies have shown that this return migration can account for up to 40% of total migration flows ( V a n d e r k a m p , 1968). In  the  U n i t e d States a new  source of migration data has  recently become  more  available (Clark, 1983). It is the Continuuous W o r k H i s t o r y Sample ( C W H S ) compiled b y the Social Security A d m i n i s t r a t i o n a n d the  B u r e a u of Economic A n a l y s i s . T h i s data  source  provides micro-level migration estimates based on individual work histories (Clark & Gertler, 1983). T h e C W H S is recompiled each y e a r , m a k i n g it possible to conduct in-depth temporal analyses. U n f o r t u n a t e l y the data source does not extend to C a n a d a and thus the first p a r t of this analysis is forced to use gross  migration flows,  and hence a macro-adjustment model. In  particular, the analysis takes data from the 1981 C a n a d i a n Census (although estimates of net migration at the provincial level are available a n n u a l l y , complete figures are only available  32  every five years from the census). D a t a listed in the census volume dealing with population mobility are based on a 20% sample of private households. G r o s s migration flows are given for each province of origin a n d destination, broken down b y occupation. A s migration is defined in terms of the difference i n place of residence  (province) between 1976  and 1981,  multiple  moves during the five y e a r period are not accounted for. Multiple moves would also include return migration as well as "hypermobile" individuals who move more t h a n once every  five  years (particularly important in the white collar occupational groups; see Stone, 1978). A p a r t from this problem with the census figures, another difficulty is finding wage and unemployment data on which to regress the gross migration figures. A s the migration data refers to a five y e a r period, the decision to migrate could have been based on information obtained in a n y one of the five y e a r s , depending upon when that decision was made. . O n the other h a n d , information about wages and unemployment takes time to diffuse  over space  (Clark, 1986). F u r t h e r m o r e , there will be a time lag between the decision to migrate and the actual migration. Ideally, then, one would use annual migration flows and regress these on wage and unemployment rates of the previous year (if one assumed that the time lag was one year). Since this was assumed)  the  not possible,  error associated  1976  was  with the use  selected as the base year. E v e n if (as it is of 1976  data is constant,  the results of the  following analysis m u s t nontheless be interpreted with caution. W a g e and unemployment figures were compiled from original tapes of the 1976 and 1981 censi (the latter being used for the second part of the analysis). A s with the migration data, the tapes are based on a 20% sample.  A problem encountered  definitions of the occupational groups h a d changed between 1976  here was  that  and 1981. In 1876  the  there  were fewer groups t h a n i n 1981. T h u s the 1981 data (including the migration figures) h a d to be a m a l g a m a t e d in order to facilitate a direct comparison between the two years (see  table  4.1.1). A further problem is the availability of data. W h e r e a s in 1981 data were available for all provinces and territories, the 1976 tapes did not include Prince E d w a r d Island, the Y u k o n  33  Table 4.1.1 Amalgamations of Occupational Groups. Group #  Description (Census Occupational G r o u p #)  1  M a n a g e r i a l , A d m i n i s t r a t i v e and Related Occupations (11)  2  N a t u r a l Sciences, E n g i n e e r i n g and M a t h e m a t i c s  3  Social Sciences a n d Related Fields (23)  4  Teaching and Related Occupations (27)  5  Occupations i n Medicine and H e a l t h (31)  6  F i n e and C o m m e r c i a l A r t i s t s (33)  7  Clerical and Related Fields (41)  8  Sales Occupations (51)  9  Service Occupations (61)  10  F a r m i n g , H o r t i c u l t u r a l and A n i m a l H u s b a n d r y Occupations (71)  11  P r i m a r y Occupations:  (21)  - F i s h i n g , H u n t i n g and T r a p p i n g (73) - F o r e s t r y and L o g g i n g (75) - M i n i n g and Q u a r r y i n g (77) 12  Processing Occupations (81)  13  M a n u f a c t u r i n g Occupations (85)  14  Construction T r a d e s (87)  15  Transportation E q u i p m e n t Operators (91)  16  Other Occupations: - M a c h i n i n g a n d Related Occupations (85) - Materials H a n d l i n g Occupations (93) - Other Crafts a n d E q u i p m e n t O p e r a t i n g Occupations (95) - Occupations N o t Elsewhere Classified (99)  34  and the Northwest Territories. These regions were thus omitted from the analysis. In the case of the two territoties this omission is probably just as well, as the migration figures there are extremely high in some occupations. Inclusion of the Northwest Territories and the Yukon therefore would have distorted the results of the analysis. For the second part of the analysis (the test of the second neoclassical hypothesis) net mobility rates were used (calculated from the gross migration matrix). The 1976 and 1981 data were used to calculate changes in unemployment and wage rates.  4.2 Methodology. 4.2.1 Theoretical Considerations. In the previous discussion it was shown that most studies testing the first neoclassical hypothesis either use first, a gravity type model or, second, a model that directly relates migration rates (in the form of gross or net migration or mobility rates) to wages and unemployment. In particular, both models generally employ multiple regression techniques, where the independent variables include differences in unemployment and wage rates. In gravity type models population figures are often weighted by wage and/or unemployment o  rates. The r  and the partial regression coefficients are then deemed to be an indication of the  explanatory power of the hypothesis. This approach has been quite popular not only in migration analysis, but also in other studies of interregional flows, for example, the analysis of trade patterns. For quite some time now it has been realized that there are a number of problems associated with this approach (Olsson,  1965,  1970; Lycan,  1969; Curry,  1972; Johnston, 1973). While some  studies  recognize these problems and accordingly adjust their methodology, a surprisingly large number of studies  do not.  Significantly, these include the testing  of the  neoclassical  hypotheses. The first problem with the traditional approach concerns the use of unconstrained gravity models, especially those that incorporate wage and unemployment rates. Regressions 35  of gross migration rates with this  type  of model characteristically show extremely  high  correlations, usually greater than .8. W h i l e possessing a large degree of predictive power, gravity type models do not explain a n y of the variation. T h e resulting correlation coefficient is only a measure  of the  "goodness-of-fit"  of the model. E q u a l l y high r squares  could most  probably be achieved by simply using population or labour force figures. T h u s it is not possible to either reject or accept a hypothesis on the basis of a gravity model, because it is  not known  whether the high correlation is a result of wage and unemployment differentials or simply the friction of distance. T h e second problem is related to the regression of r a w gross migration figures on differences  in unemployment and wage rates and, in most cases, a distance variable. T h e  obvious implication here is that the n u m b e r of migrants depends on the size of the population (or the labour force if the concern is with labour migration). T h u s , the greater the population size of the region of origin, the greater  the number of migrants. In order to facilitate  a  comparison of migration rates between regions of v a r y i n g sizes, gross migration rates are usually transformed to mobility rates, i.e., the number of migrants per thousand population. However, this eliminates just one p a r t of the problem. Mobility rates to regions with large populations will still be greater t h a n to those with smaller populations. O n e of the reasons for this is that the larger a region's population base, the  larger the number of  employment  opportunities and, b y extension, the greater its attraction. N e l s o n (1959) has shown that a large part of total gross migration is a result of a "random" allocation process. In other words, migrants are randomly allocated according to the size of the regions of origin and destination. F o r example, if region j has 10% of the total population of a country, then, ceteris paribus, the number of migrants m o v i n g from i to j should be one tenth of all outmigrants from i. Conversely, if region i has a 5% share of the country's population, then, all other things being equal, the number of migrants from i to j should equal 5% of all inmigrants to j . W a g e rates, unemployment rates, or distance have nothing to do with this aspect of migration. In order to test the influence of these variables gross migration  36  rates thus have to be adjusted to allow for this factor b y removing the r a n d o m component of gross migration. Once the effects of the sizes of origins and destinations have been removed, the effects of spatial factors  have  to be  considered and also  removed before  the  influence  of  any  socioeconomic variables can be tested. Distance and intervening opportunities have been judged to be the most influential inhibitors to migration (Stouffer,  1960,  influence of distance is in itself a compound of two influences  1962; L y c a n ,  1969). T h e  (Johnston, 1973). F i r s t ,  the  friction of distance varies b y origin. In terms of migration this would m e a n that some regions experience outmigration to more distant destinations, whereas in others, m i g r a n t s tend to go to a more restricted portion of the system, concentrating on their "nearest neighbour". T h e second influence is that of the m a p pattern. S i m p l y because of the location of the region of origin in relation to the destination regions, the average distance m i g r a n t s have to travel varies. F o r example, O n t a r i a n s , being located in the middle of C a n a d a , do not have to travel as far on average as B r i t i s h Columbians to reach their desired destination. Therefore the influence of distance (degree of inhibition) will, all other things being equal, not be as high for migrants from Ontario as it will be for migrants from B r i t i s h C o l u m b i a . T h e implication is that aggregate estimates of the influence of distance (based on regressions that are not broken down b y origin) will be inaccurate for a n y kind of detailed analysis. A systemwide  regression  would result in a n overestimation of the influence of distance on migration from  regions  located i n the centre of a country, whereas it would be underestimated for peripheral regions. Therefore migration rates adjusted on the basis of a singular regression (not broken down b y origin) would include this error. The  other  major  spatial  factor  Intervening opportunity, like distance, variables,  such as  influencing  migration is  is in itself the  intervening opportunity.  result of a combination a  several  employment opportunities, and social and cultural considerations.  The  assumption is that intervening opportunities will have a n impeding effect on migration over space. While intervening opportunities are closely related to distance, they do tend to "de-  37  emphasize spatial separation across sparsely populated areas and to stimulate the absorptive effect of densely populated intervening areas" ( L y c a n , 1969, p.242). In other words, if, for example, a potential m i g r a n t has a choice between two alternate destinations, then the higher probability of m o v i n g to the closest one could be negated  b y the number of  employment  opportunities l y i n g in between (if that number is less for the further destination). A s with distance, the influence of intervening opportunities will v a r y by province of origin for m u c h the same reasons, i.e., the range of intervening opportunities will differ. W h a t this discussion suggests is that in order to test the neoclassical migration model we m u s t first remove both the spatial and population size-related influences from observed migration patterns. If we did not, we could not conclude m u c h from our analysis. F o r it would be not clear whether it was the spatial and population factors that were deterring migration, or the wage and unemployment rates that are the focus of the neoclassical model. So w h a t this chapter will do is to first account for observed migration patterns only in terms of spatial and population  size-related  factors.  Once this  has  been  done,  we  can test the  residuals  for  differences in the effect of wage and unemployment rates.  4.2.2 Methodology. T h e methodology used i n the first part of the statistical analysis closely follows that of N e l s o n (1959) and L y c a n (1969), albeit with some modifications. G r o s s occupational migration rates will be  adjusted  for the  size of the labour force  intervening opportunities. Interprovincial differences  in each occupation, distance  and  in wage and unemployment rates will  then be tested for their significance in exaplining the residual migration. F i r s t , census estimates of gross interprovincial migration are adjusted according to the size of the labour force in each occupation in each province. T h e rationale for this change is that the n u m b e r of m i g r a n t s in occupation k m o v i n g between two provinces should be directly proportional to the product of the provincial shares of the labour force in occupation k. T h e resulting adjusted migration rates (which are essentially ratios of expected to actual migration)  38  are defined as equal to 1.00 if the share of migrants m o v i n g from a given province of origin to a given province of destination is exactly proportional to the product of each of the provinces' share of the C a n a d i a n labour force in occupation k, less t h a n 1.00 if it is less, a n d greater than 1.00 if it is greater ( L y c a n , 1969). T h e formula used to arrive at the labour force adjusted migration rates is:  „ k  k £• * — I  • = - ^ - r / . . i l ij J  where my  k  h l  i,j  = 1  9  (4.2.1)  .i j u  i  J  is the labour force adjusted migration rates; M ^ is the gross number of migrants  between i and j in occupation k; a n d  and  is the size of the labour force in provinces i  and j in occupation k. Second, the influence of distance and intervening opportunities is estimated b y means of multiple regression. M i g r a t i o n rates are then adjusted a second time to account for this influence.  Distance  is measured  in the  n u m b e r of road kilometers  separating the  major  population centres of the provinces. Intervening opportunity is defined as the percentage of the total C a n a d i a n labour force in a particular occupation lying between the  two  provinces.  A l t h o u g h intervening opportunities are most likely related to wage and unemployment rates (the  higher  the  difference  opportunities), it is  in  assumed  wage  that  rates,  for  example,  the  greater  this relationship is equal across  the  the  intervening  country.  Because  C a n a d i a n migration is unique in the sense that almost all (with exception of the M a r i t i m e provinces)  of the  migration occurs in an easterly  N o r t h w e s t Territories are not included in the  or westerly  direction (the  analysis), it is possible  Yukon  and  to s i m p l y add the  percentage shares of the labour forces of the provinces lying between i and j . A  multiple  regression  will  be  performed on  assumption that:  ln(  k m i j  )  = f(ln(D ); I C ^ ) k  ij  (4.2.2)  39  each  province of  origin under  the  where:  v  j  k  10..  k  1  n=i +l  I  if  j  g.t.  i,  if  j  1. t .  i ;  or  L.  1=1  J  A n=j +l  L  i o . 1  k  v  D  *  i , j ,n = 1 , . . . , 9  (4.2.3)  j=l  10y  is the percentage of the C a n a d i a n labour force in occupation k l y i n g between i a n d j ; L j  and L j k is the size of the labour force in occupation k i n i and j , respectively; and D j j is the distance between i and j . L a b o u r force adjusted migration rates and distance were logged in order to normalize the distribution. B y conducting a separate regression for each province of origin, differential influences of  distance  and  intervening  opportunities  due  to  map  location  can  be  accounted  for.  F u r t h e r m o r e , intervening opportunities can also be broken down by occupation, thus reducing the problem of aggregation.  F o r both variables it is expected  that the p a r t i a l regression  coefficients will be negative. In formal terms,  to adjust migration rates in a m a n n e r  such that  distance  and  intervening opportunities are considered, one simply subtracts the migration due to distance and intervening opportunities from the adjusted total migration, to arrive at the residual migration (rm-). T h u s (following the example of L y c a n (1973)):  40  rm^  = lnCm^) - ((a + b (ln(D )) + b aOy )) 1  i  i  1  ij  k  2  (4.2.4)  where r m ^ is the residual migration; a* is the constant for province i; and b-^ and b2* are the regression parameters for province i. If the residual is less than zero, migration was less than expected based on labour force, distance and intervening opportunities. Conversely, if the residual is greater than zero, then migration was greater than expected. Spatial and labour force size related factors have now been removed as far as possible given the available data. However, some spatial biases still remain due to factors other than distance and intervening opportunities. For example, migration from the Maritime provinces will tend to be between Maritime provinces (in some occupations) due to the social welfare system in those provinces. Fishermen, for example, will tend to stay in the Maritimes, because it is easier for them to obtain unemployment benefits there than in other, non-Maritime provinces. This and other factors will be discussed in more detail in the next chapter. The final task (and a major objective of this part of the thesis) is to test the significance of differences in wage and unemployment rates in explaining the residual migration. This will again involve the use of multiple regression. The formula used is that:  u -u k  k  r m  ii  =  f { - J  nr * u  3  w -w  k  k  1 0 0 ;  K  1  k  - ~ir * J  w  K  1 0 0  >  (4.2.5)  1  where U j and U j are unemployment rates in provinces, j and i in occupation k, respectively; k  and Wjk and W j  k  k  are wage rates in occupation k in provinces j and i, respectively. According  to the neoclassical hypothesis stated in chapter 3, the expected sign of the partial regression coefficients would be positive for wage rates and negative for unemployment rates. This section of the analysis will consist of two parts. In the first a separate regresion will be run on each province of origin to test interregional differences, while in the second it will be broken down by occupational group.  41  T h e second neoclassical hypothesis concerning the effects of labour migration suggests that  positive  net  migration will  lower  wage  rates,  while  at  the  same  time  increasing  u n e m p l o y m e n t rates. T h u s :  Wj  k  = f(NETMOBj )  (4.2.6)  = f(NETMOBj )  (4.2.7)  k  and  Uj  k  k  where W j and U j are percent changes in wage and unemployment rates in province i k  k  between 1976 a n d 1981 in occupation k; a n d N E T M O B j  k  is the net loss (gain) per thousand of  the 1976 labour force in occupation k i n province i between 1976 and 1981. In keeping with the neoclassical hypothesis the expected sign of the correlation coefficient should be positive for u n e m p l o y m e n t rates and N E T M O B and negative for wage rates and N E T M O B .  42  5. DATA ANALYSIS. T h i s chapter will discuss the results of the data analysis as outlined in the previous chapter. T h e first section will provide a description of overall labour migration patterns in C a n a d a between 1976 and 1981, while the second section will concentrate on the labour force adjusted migration rates.  T h e third section  will examine  the residual migration rates not  accounted for by the size of the labour force, distance a n d intervening opportunities. In the fourth section the results of the test of the first hypothesis will be presented, while in the fifth those of the second hypothesis  will be discussed. F i n a l l y , this chapter will conclude with a  s u m m a r y of the findings. W h e r e appropriate, comparisons will be made to a similar study conducted b y L y c a n (1969) on C a n a d i a n migration patterns between 1955 and 1961.  5.1 Gross Migration Flows. Table 5.1.1 1976 and 1981. sufficient  shows gross migration figures within C a n a d a for all occupations between  Prince E d w a r d Island, the Y u k o n and Northwest Territories are included, as  data were available for this stage of the analysis. A l s o included are flows from  outside C a n a d a . By  far the most popular destination for migrants from outside C a n a d a was  Ontario,  followed b y B r i t i s h C o l u m b i a , A l b e r t a and Quebec. Considering the population size of Quebec, the inflow of foreigners  is somewhat  lower t h a n expected.  However, this relative lack of  attractivity could i n part well be attributed to the fact that the official language of Quebec is F r e n c h , creating a cultural barrier for overseas or A m e r i c a n immigrants. F u r t h e r m o r e , the Quebec  Department  of Immigration  (a separate  entity  from the  federal  Department  of  Immigration with veto rights) tends to favour i m m i g r a n t s from F r e n c h speaking countries such as F r a n c e , H a i t i a n d some A f r i c a n nations. I m m i g r a n t s from these countries constitute a minority i n the total immigration to C a n a d a . In order to interpret migration patterns within C a n a d a , the gross migration matrix was converted into a net exchange matrix for all occupations (see table 5.1.2; the table does  43  Table 5.1.1 Gross Migration, 1976-1981, A l l Occupations. From/to FOREIGN  NFLD 1225  P.E.I.  N.S.  N.B.  610  4195  3595  QUEBEC  ONT.  44715 136570  MAN.  SASK.  ALTA.  B.C.  YUKON N.• W.T.  14260  6365  45310  50880  265  380  27565  320  3905  1350  750  8810  895  490  6100  1940  90  365  PEI  165  5770  1485  795  105  1535  135  145  1935  455  25  35  NS  1820  1135  43790  4915  1660  12425  1260  940  10920  5205  105  350  NB  725  965  5435  33855  3950  8630  905  625  8455  2580  65  175  524 5 592165  73250  2715  1485  22025  13935  235  415  1015  1820  NFLD  Quebec Ontar io Man i t .  760  500  3475  4960  1705  11865  7230  385  50  1015  485  Sask.  70  115  Alta.  425  375  B.C.  345  Yukon N.W.T.  24015 753955  13615  8135  92 45 49810  8170  49510  8005  22930  14880  225  560  180  450  1105  290  525  3855  4275  69135  23840  9510  2280  1050  1895  15105  4650  11195 168775  41785  680  1155  310  2175  915  2890  16750  3900  5755  43310 267275  1645  800  15  20  65  30  45  345  70  180  1220  2225  820  95  105  20  115  40  285  725  285  410  2960  1245  340  1925  4 60  Note: Exchange between same province is internal migration  Source: Statistics C a n a d a (1981)  Table 5.1.2 Net E x c h a n g e Matrix, 1976-1981, A l l Occupations. From/to NFLD PEI NS NB Quebec  NFLD ******  P.E.I. 155  -155 ****** -2085  N.S. 2085  -10  ONT. 3850  MAN. 510  SASK.  ALTA.  420  5675  B.C.  YUKON  N.W.T.  1595  75  260  5  15  -170  -395  -170  85  30  1560  145  -350 ******  -520  -1815  560  245  480  8640  3030  40  235 135  -625  170  10  395  520 ****** 1815  Ontario  -3850  170  -560  -510  -85  -245  Sask.  -420  -30  -480  Alta.  -5675  -1560  -8640  Yukon  625  QUEBEC  350  Manit.  B.C.  N.B.  -1595  -145  -75  -5  N.W.T.  -260  -15  NET IN  -15240  -1300  -3030  335  7405  1665  35  1610  960  20130  11045  190  130  5445 -5445 ******  4280  77140  33060  670  1095  3730  18280  10980  155  275  12645  3755  0  40  -7405 -20130 -77140 -18280 -12645 ******  -1525  -540  -1805  1525 ******  -580  -445  580 ******  -245  -1295  1400  420  1295 ******  49235  -1400 -49235 * * * * * * -420 -335  r960  -4280  -3730 ******  -1665 -110 4 5-33060 -10980  -40' -235  -1610  -35 -135  -190 -130  -670 -1095  -155 -275  -8460 -10165 -86815 -66815 -25105  Source: Statistics C a n a d a (1981)  44  -3755 0  5*0 1805  445  -6205 155345  64745  -40  245 ****** 295  -310  not include inmigrants from outside  Canada). H e r e the migration pattern is more readily  apparent t h a n in the previous table. In terms of total net inmigration f r o m all provinces, A l b e r t a was able to attract 155,345 more migrants t h a n it lost to other provinces. T h e only other  province  tremendous  that  experienced  positive  net  migration  was  B . C . , with  64,775.  This  gain for A l b e r t a is no doubt related to the boom of the oil i n d u s t r y and the  resulting economic spinoffs. The  m a s s exodus from Quebec is again not surprising, considering that the Partie  Quebecois came to power i n 1976. T h e subsequent introduction of B i l l 101, the controversial language law requiring all business transactions to be conducted i n F r e n c h and prohibiting advertising in E n g l i s h , is most likely to be one of the major determinants of the net loss. W i t h the exception of Newfoundland, Quebec was the only province to lose m i g r a n t s to very other province. P e r h a p s a bit surprising is the relatively large loss for O n t a r i o (66,815). F o r the Maritimes  the  loss was  to be  expected.  Newfoundland, Prince E d w a r d  Island and  New  B r u n s w i c k have traditionally been areas of low employment opportunities. O f the opportunities that do exist, m a n y are seasonal jobs, particularly in fisheries and related occupations. O v e r a l l , there was a pronounced east to west movement between 1976 a n d 1981  (see  table 5.1.2). T h i s is indicated b y the fact that, again with the exception of Quebec, almost all of the values above the diagonal in the m a t r i x are positive, whereas below they are negative. From  Ontario westwards,  provinces.  Clearly  the  provinces  pole  gained  of attraction  from eastern  was  Alberta,  provinces  obtaining a  a n d lost to net  gain  western  even  from  neighbouring B r i t i s h C o l u m b i a which, like A l b e r t a , gained from all other provinces.  5.2 L a b o u r Force Adjusted M i g r a t i o n Rates. L a b o u r force adjusted migration rates according to formula (4.2.1) display a more detailed pattern. Tables 5.2.1  to 5.2.16 show migration rates broken down by occupation.  Tables 5.2.17 shows migration rates for all occupations. F o r reasons discussed above Prince E d w a r d Island, the Y u k o n and the N o r t h w e s t Territories are not included in the tables. T h e  45  Table 5.2.1 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Managerial, Administrative. s.  FROM/TO  NFLD  NEWFOUNDLAND  0 0  16 36  NOVA SCOTIA  12 70  NEW BRUNSWICK  N  N B.  QUEBEC  ONT .  MAN.  SASK.  ALTA .  B C.  6 24  O 31  1 06  1 01  O 94  2 86  0 49  0 0  22 97  0 39  1 82  1 04  2 26  5 45  1 76  4, 52  20 75  0 O  0 90  1 09  0 77  1 40  4 32  1 08  QUEBEC  0 28  0 86  1 21  0 0  1 50  0 27  0 18  1 56  0 75  ONTARIO  0 79  1 59  1 03  0 38  0 0  1 00  0 96  3 75  1 58  MANITOBA  0 51  0 90  0 28  0 15  1 12  0 0  12 13  10 24  4 55  SASKATCHEWAN  0 16  0 97  0 43  O 07  0 58  5 76  0 0  14  3 94  ALBERTA  0 43  1 05  0 84  0 10  0 83  2 01  8 41  0 0  7 62  BRITISH COLUMBIA  0 25  1 08  0 30  0 15  0 72  1 22  3 22  8 22  0 0  1 1  Table 5.2.2 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, N a t u r a l Sciences.  N  s.  FROM/TO  NFLD  N B.  ONT..  MAN.  SASK.  ALTA .  B C.  NEWFOUNDLAND  0 o  15 66  3 48  0 84  1 34  1 63  0 95  8 89  1 08  NOVA SCOTIA  12 05  0 0  10 44  0 49  2 06  0 94  0 82  1 1 96  3 90  NEW BRUNSWICK  4 17  8 63  0 0  0 54  0 88  0 63  2 69  4 32  0 72  QUEBEC  0 63  1 12  0 63  0 0  1 40  0 45  0 58  2 23  0 94  ONTARIO  0 79  1 65  0 49  0 38  0 0  0 96  0 96  4 78  1 49  MANITOBA  1 36  0 94  0 81  0 26  1 01  0 0  1 1 25  9 78  3 63  SASKATCHEWAN  0 48  1 10  0 32  0 12  0 46  4 95  0 0  16 29  3 02  ALBERTA  0 73  1 43  O 29  0 20  0 61  0 91  5 19  0 0  5 10  BRITISH COLUMBIA  0 0  0 90  0 28  0 22  0 47  0 69  1 70  7 01  0 0  QUEBEC  46  Table 5.2.3 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, S o c i a l Sciences. FROM/TO  NFLD  NEWFOUNDLAND  0. .0  10 . 38  19 .. 28  NOVA SCOTIA  QUEBEC  ONT .  MAN .  2.91  0. . 12  1 . 75  0. .0  8 .. 73  0. . 73  N., S .  N,,B.  SASK .  ALTA .  B ,C.  3 .7 1  1 .80  2 . 65  0 . 30  2 . 10  1 . 18  1 . 43  9 . 13  2 . 73  NEW BRUNSWICK  8 .. 73  9 .. 75  0. .0  0. .64  0 . 98  0 .51  0 . 93  3 . 98  1 . 16  QUEBEC  0. .46  0. . 73  0. .96  0. 0  1 .07 .  0. .55  0 .4 1  1 .. 15  0. .83  ONTARIO  0. .99  2 ..02  0. .69  0. .44  0. .0  1. . 4 1  1, . 25  4 ..85  2 . 19  MANITOBA  O. 74  1 .57  0. 51  0. 12  1 .. 55  0. .0  7 . 63  10. . 19  5 ..07  SASKATCHEWAN  0. 0  1 .91 .  0. 62  0. 04  0. 51  4 . 05  0. O  9 . 10  2 ..83  ALBERTA  0. 88  1 .64  0. 46  0. 13  0. 82  2 ..93  5 .. 26  0. .0  6 .. 38  BRITISH COLUMBIA  0. 30  1 .45'  0. 1 1  0. 1.3  0. .77  1 .69  3 . 32  4 .84  0. .0  Table 5.2.4 M i g r a t i o n Rates Adjusted for S i z e of the L a b o u r Force, 1976-1981, Teachers FROM/TO  NFLD  N. S .  N.B .  QUEBEC  NEWFOUNDLAND  O..0  6 . 75  1 . 87  NOVA SCOTIA  10. . 29  0 .0  NEW BRUNSWICK  0. 70  QUEBEC  ONT .  MAN.  SASK .  ALTA .  B.C .  0 . 34  0 .84  1 . 67  0 .47  2 . 37  1 . 59  8 .63  0 . 50  1 . 54  1 . 44  2 .02  6 . 72  2 .56  9 .00  0, ,0  0 .83  0 .60  0 . 67  1 .07  2 .96  0. . 57  0. 47  0 .98  1 .02  0. .0  1.2 1  0 . 48  0 .31  1 .07  0. .91  ONTARIO  1 .00  1. 7 1  0. 61  0. 62  0. .0  1 .. 22  1 .. 35  2 .97  2 ..13  MANITOBA  0. 84  1 .31 .  0. 29  0. 33  0. .94  0. O  5 .. 35  4 . 37  3 ..88  SASKATCHEWAN  0. 23  0. 37  0. 0  0. 08  0. 63  3 . 54  0. 0  9. 53  3 . 91  ALBERTA  1 . 13  2 . 03  0. 77  0. 18  0. 86  1 .47  5. 92  0. 0  6 . 65  BRITISH COLUMBIA  0. 59  1 .94  0. 06  0. 28  0. 89  1 .09  2 . 49  5 . 34  0. 0  47  Table 5.2.5 M i g r a t i o n Rates Adjusted f o r Size of the L a b o u r Force, 1976-1981, Medicine & Health.  FROM/TO  NFLD  NEWFOUNDLAND  0 .0  23 . 54  2 . 16  13 . 70  O .0  NEW BRUNSWICK  3 .40  14 . 27  QUEBEC  0. , 28  ONTARIO  ONT .  MAN.  SASK.  ALTA .  B .C.  0. . 24  1 .64  3 .02  0 ,65  4 .62  4 . 27  16 .. 74  0. 47  2 . 10  2 . 10  1 ,. 2 1  6 . 26  5 .02  0. .0  0. 68  1 . 16  0 .63  0. ,48  3 . 39  0 .99  0. . 92  1 . 14  0. .0  0 . 86  0. . 38  0. , 24  0 . 93  0 . 77  1 .. 10  2 .. 23  0. 72  0. 35  0 .0  1 .. 12  0. 94  2 .84  2 ,. 32  MANITOBA  0. ,40  2. . 72  0. 63  0. 13  1 .03  0. .0  6 . 44  7 .. 58  6 ,01  SASKATCHEWAN  0. . 22  1 .48  0. 10  0. 05  0. . 53  2 ..97  0. 0  10. . 1 1  5 ., 24  ALBERTA  0. 35  1 .78  0. 4 1  O. 16  0. . 70  1 .. 74  3 .,73  0. .0  6 .,90  BRITISH COLUMBIA  0. 68  1 .97  0. 56  0. 13  0. . 56  1 .29  1 .83  4 ..34  0. ,0  NOVA SCOTIA  N.. S .  N..B.  QUEBEC  '  Table 5.2.6 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, F i n e & C o m m e r c i a l Artists. FROM/TO  NFLD  NEWFOUNDLAND  0, .0  NOVA SCOTIA  1 ,, 68  NEW BRUNSWICK  O,,0  QUEBEC  0, . 26  ONTARIO  N.S .  N.,B .  QUEBEC  ONT .  MAN.  SASK.  ALTA .  B ., C .  1 1 .76 ,  1 ,59 .  0. ,52  2 . 23  2 .. 52  3 ..56  2 , 70.  0. , 79  0, .0  9 . 28  0. 65  1 .99 ,  2 ,. 94  2 ,.77  3 , 15  2 ..44  10 . 52  0. ,0  1 ,00 .  1 ., 17  0. .46  1 .31 ,  2 .. 39  1 ,, 30  1 .01  0. 90  0. ,0  1 . 10  0. . 57  0 . 32  0 .99  0. . 73  0, , 74  1 .92  0. 96  0. .60  0 .0  1. . 74  1 .76  3 .52  2 .,06  MANITOBA  3 ., 78  0 .98  0. 46  0. , 4 1  1 .66 ,  0 ,0  16 ,.08  13 .. 23  3 ,.89  SASKATCHEWAN  0, ,0  0. .0  0. 0  0. 43  0 .84  10 .90  0, .0  16. .01  3 ,.88  ALBERTA  O., 54  3 . 15  0, 80  0. , 27  1 .06  2 . 21  10, .01  0 .O  7 .90  BRITISH COLUMBIA  0, . 39  2 .90  0. . 29  0, , 25  0 .95  1 . 37  3 .07  6 . 53  0 .0  48  Table 5.2.7 M i g r a t i o n Rates Adjusted for S i z e of the L a b o u r Force, 1976-1981, C l e r i c a l Workers. FROM/TO  NFLD  NEWFOUNDLAND  0 .0  NOVA SCOT IA  N .S.  N,.B.  SASK.  ALTA .  B .C .  15 . 74  4 . 95  1 . 54  1 . 84  9 . 84  1 .67  6 . 12  0 .0  1 .76  1 .88  1 .40  9 .31  2 .94  NEW BRUNSWICK  2 . 42  0. . 78  1 .07  0 . 94  0 . 99  5 . 84  1 . 44  QUEBEC  0. .81  0. 0  1 . 18  0. . 34  0. . 16  1 .85 .  0 .85  1 .. 27  0. .69  0. . 35  0 •0  0 .86  0 . 75  4.41  1 .61  0. .58  1 ,48 .  0. 29  0. . 10  0. .67  0. ,0  7 .. 13  9, , 22  4 . 26  SASKATCHEWAN  0. 32  0. .73  0. 35  0. .09  0. . 39  4 ..69  0. .0  ALBERTA  0. 50  1 .61  0. 79  0. 14  0. .64  1 .81 .  BRITISH COLUMBIA  0. 24  0. 82  0. 42  0. 14  0. 56  1 .00  QUEBEC  ONT .  MAN.  O.. 24  2 .07  8 .92  0 . 43  1 1. 29  0. .0  0. , 32  0. .69  ONTARIO  0, ,95  MANITOBA  17 ..38  4 ,.91  7 . 27  0. .0  7 .,93  2 . 35  9 . 58  0. .0  Table 5.2.8 M i g r a t i o n Rates Adjusted for S i z e of the L a b o u r Force, 1976-1981, Sales Occupations. FROM/TO  NFLD  NEWFOUNDLAND  0 .0  NOVA SCOT IA  4 .51  NEW BRUNSWICK  N.  s.  N.B .  QUEBEC  ONT .  MAN.  SASK.  ALTA .  B .C .  10 .59  2 . 75  0 . 23  0 .98  0 . 58  0 . 12  5 .63  0 . 50  0 .0  8 .38  0 .33  1 .37  1 .08  0, .80  5 .63  1 . 88  1 ., 13  10. . 43  0. .0  0 . 72  0. . 73  0 .42  0. 49  3 .48  0. .80  QUEBEC  0. , 12  0. 8 1  0. 85  0 .0  1 .. 28  0 . 28  0. 10  1 .41 .  0, ,68  ONTARIO  0. . 94  1 .61 .  0. 72  0 . 34  0. 0  1 .06  0. 61  3 .93  1 .. 5 1  MANITOBA  0. .69  1 .02  0. 31  0. . 16  0. 79  0. ,0  7 . 30  10. . 74  4 .,44  SASKATCHEWAN  0. 36  0. 20  0. 22  0. .06  0. 26  3 . 01  0. 0  10. .05  2 . 64  ALBERTA  0. 26  0. 90  0. 57  0. .08  0. 66  1 ,83 .  4 . 60  0. 0  7 . 54  BRITISH COLUMBIA  0. 32  0. 58  0. 23  0. 14  0. 55  1 .00  1 .46  7 . 34  0. 0  49  T a b l e 5.2.9 M i g r a t i o n R a t e s A d j u s t e d f o r S i z e o f t h e L a b o u r F o r c e , 1976-1981, S e r v i c e Occupations.  SASK.  ALTA .  B ,C.  1 .. 73  1 .69 .  5 ..88  2 ..09  o 38  2 .24  2 . 05  7 • 3.1  3 ., 18  0. .69  0. .92  1 .01  0. .62  2 .92  0. ,83  0 .98  0. 0  0. .93  0. .42  0. , 40  1 .. 48  0. .80  2 . 49  o  . 90  0. . 33  O. ,0  1 . 33  0. . 82  3 . 48  1 .58 .  0, .72  1 .60 ,  0. . 68  0. . 10  0. .86  0 .0  3. . 72  5 .88  3 . 29  SASKATCHEWAN  0. . 29  1 .. 30  0. . 55  0. . 14  0. . 40  2 .80  o:.0  7 . 77  2 . 91  ALBERTA  0. .55  2 .. 33  0 .63  0. , 22  0. ,75  1 .87  4 .01  0 .0  5 .82  B R I T I S H COLUMBIA  0, .29  1 .96 .  0. .49  0. . 20  0. ,59  1 .36  1 .88  5 .81  0. .0  QUEBEC  ONT .  MAN.  4 . 91  0. .21  2 . 46  0. .0  6 . 12  0. .47  1 .64 .  6. .98  0, .0  QUEBEC  0. . 25  1 ,. 39  ONTARIO  1 .09 .  MANITOBA  FROM/TO  NFLD  NEWFOUNDLAND  0. .0  NOVA SCOTIA  7 . 18  NEW BRUNSWICK  N.. S . 25 .  18  N. B.  T a b l e 5.2.10 M i g r a t i o n R a t e s A d j u s t e d f o r S i z e o f t h e L a b o u r F o r c e , 1976-1981, Agriculture.  FROM/TO  NFLD  NEWFOUNDLAND  0 .0  NOVA SCOTIA  8 . 25  NEW BRUNSWICK  N.S .  N .B.  QUEBEC  ONT .  MAN.  SASK.  ALTA .  8 . 17  2 .51  2 .53  7 .08  9 . 19  0. .0  0 .28  4 .43  7 .20  B .C.  49 .52  28 .95  0. .0  0 .0  21 . 59  0 . 76  0 .0  28 ..06  0. .0  2 ,.67  2 . 47  0. .66  0 .33  4 .07  4 .21  QUEBEC  0 .0  0 . .95  1 .. 78  0. .0  1 .81  0. . 14  0 .07  0 .82  2 . 23  ONTARIO  1 ., 72  3 . 08  1 ,. 24  0. 44  0 •0  0 . 83  0. ,21  2 , 49  3, .94  MANITOBA  0, ,0  O. 28  0. 0  0 . 03  0, . 44  0. 0  1 ,37 .  1 ,. 59  4 ,,06  SASKATCHEWAN  0 . .0  O. 42  0 . 17  O. 0  O, . 1 1  o . 58  0. 0  2 . OO  1 ,93 .  ALBERTA  0. 0  1 .1 1  0 . 37  0 . 05  0 . 44  0 . 87  1 .84  0. 0  7 ., 19  B R I T I S H COLUMBIA  0. O  5 . 14  2 . 40  0 . 58  1 .26  1. 87  2 . 56  7 . 36  O. O  50  • 2 .02  Table 5.2.11 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, P r i m a r y Occupations.  FROM/TO  NFLD  N..  s.  NEWFOUNDLAND  0..0  1 .82  0.. 29  NOVA SCOTIA  0 .87  0 .0  NEW BRUNSWICK  0.. 18  QUEBEC  ONT .  MAN.  SASK.  0..09  0..64  5 .15  0. 90  5.. 10  0.. 30  0.. 48  0..03  0..42  1 .27  1 .05  5 .94  0.. 78  0.. 82  0..0  0..31  0. 35  0. 95  0. 15  2 .91  0..50  0..07  0 . 15  0.. 74  0.0  0. 98  0. 54  0. 34  2 .04  0..67  ONTARIO  1 ,45 ,  1 . 37  0.. 7 1  0. 38  0..0  2 .65  1 .93 .  8 .. 73  1 ,73 .  MANITOBA  1 .09 .  1..09  0.. 32  0.. 12  1 .96 .  0..0  10,.51  22 . 39  3 .67 .  SASKATCHEWAN  0..0  0..0  0.. 15  0.0  0. 39  5 . 66  0..0  30 . 15  2, . 30  ALBERTA  0,, 5G  1.. 1 1  0..40  0.03  0. 53  2 .15  10..94  0 .0  5 , 55  BRITISH COLUMBIA  0.. 12 . 0.. 32  0.,05  0.02  0. 26  0. 53  0..96  6 . 57  0.,0  N.,B.  QUEBEC  ALTA .  B. ,C.  Table 5.2.12 M i g r a t i o n Rates Adjusted f o r Size of the L a b o u r Force, 1976-1981, Processing.  FROM/TO  NFLD  N .S.  N .B .  NEWFOUNDLAND  0 .0  8 . 14  1 .44  NOVA SCOTIA  1 . 68  0 .0  NEW BRUNSWICK  0 . 29  QUEBEC  QUEBEC  ONT .  MAN .  SASK.  0 .21  2 .67  3 . 48  3 . 55  •O. 20  1 . 56  5 .68  0 .0  0 . 78  0 . 17  0..31  1 .. 47  ONTARIO  1 .84 ,  1 .99 .  MANITOBA  0..87  SASKATCHEWAN  ALTA .  B .C .  4 .77  10 . 58  1 . 70  1. 9 1  0 .0  6 .96  2 .42  1 . 28  3 .42  0..0  7 . 73  1 .30  0..0  0.. 73  0 . 29  0,. 24  1 .72 .  0..68  1 .. 16  0..31  0..0  1 .30  1 .08 ,  7 .. 13  1 ,86 .  0..48  0. 49  0.06  1.. 17  0.,0  10. 53  17 .98  5..65  0. 0  0. 0  0. 40  0. 14  0. 52  5 .67 .  0. 0  32 .52  7 .89  ALBERTA  0. 24  2 .32  0. 79  0. 17  1. 03  4, . 20  9 .53  0. 0  1 1 56 .  BRITISH COLUMBIA  0.08  0. 38  o. 52  0.05  0. 39  1 .05  1 .62  9 .16  0.0  51  Table 5.2.13 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Manufacturing.  FROM/TO  NFLD  N.S .  N.B .  QUEBEC  ONT .  MAN .  SASK .  ALTA .  B .C.  NEWFOUNDLAND  0 .0  29 ., 64  8 . 27  0. .61  6 .. 37  4 .66  2 . 34  27 . 75  6 . 33  NOVA  6 . 59  0 .0  14 . 64  0. . 38  2 . 52  2 . 23  4 . 44  19 . 56  4 . 44  i.  . 76  16 ..04  0. .0  0. .81  1 .30  1 .66  1 . 73  13 . 6 0  2 . 13  QUEBEC  0. . 14  0. . 56  1 .09 .  0. .0  0. . 63  0. . 35  0. . 33  2 .46  0 , 75  ONTARIO  1 .48 .  1 .76  0. 89  0. 24  0. 0  1 .02 .  1 .. 22  6 . 26  1 .97 .  MANITOBA  0. . 74  1 .. 24  0. 62  0. . 17  0. 57  0. .0  12 . 16  15 .96  7 . 30  SASKATCHEWAN  0. 0  0 . 89  1 .73 .  0. 13  0. 4 1  6 ..87  0. .0  30 .99  7 .45 .  ALBERTA  1 . 19  2 . 51  1 .43  0 . 17  0 . 98  3 . 36  15 ..92  0. .0  15 . 27  0 . 26  0 . 98  0 . 49  0 . 22  0 . 63  1 .46 .  4 .59 .  15 .32  0. .0  NEW  SCOTIA BRUNSWICK  BRITISH  COLUMBIA  Table 5.2.14 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Construction.  FROM/TO  NFLD  N. S .  N . B.  QUEBEC  ONT .  MAN .  SASK .  ALTA .  B .C.  NEWFOUNDLAND  0 .0  1 . 50  0 .89  0 . 14  0 .98  0 .66  1 . 68  7 .69  0 .68  NOVA  1 . 15  0. .0  1 . 69  0 . 1 1  0. . 72  0 . 59  1 . 34  9 .93  1 .65 .  0 . 53  2 . 19  0 .0  0 . 23  0. . 46  0 . 27  0 . 39  6 .80  0 .70  QUEBEC  0. .05  0 . 21  0. . 43  0. .0  0. 40  0. .07  0. . 22  2.71  0. .53  ONTARIO  0 . 60  0 . 73  0. 5 1  0. . 17  0. 0  0. . 37  0. .68  6 . 36  1. 51  MANITOBA  0 . 37  0 . 29  0. 14  0. 03  0 . 38  0. O  6 .. 5 1  10.. 82  3 . 61  SASKATCHEWAN  0. 0  0 . 17  0 . 06  0 . 05  0 . 15  1. 33  0. 0  15..04  2. 97  ALBERTA  0 . 12  1 .38  0 . 20  0 . 09  0 . 35  1. 07  5 . 82  0. 0  6 . 42  0 . 06  0 . 27  0 . 23  0 . 06  O. 28  o . 46  2 . 20  7 . 68  0. 0  NEW  SCOTIA BRUNSWICK  BRITISH  COLUMBIA  52  Table 5.2.15 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Transportation. SASK.  ALTA .  B.C.  FROM/TO  NFLD  N., s.  N . B . QUEBEC  ONT .  MAN.  NEWFOUNDLAND  0..0  5 .31 .  1 .95 .  0., 20  0..97  0 . 65  0.0  4 .73  0 .89  NOVA SCOTIA  4 .85 .  0..0  4 .05 .  0., 20  1 .14  1 .. 17  0. 49  6 . 84  2 . 28  NEW BRUNSWICK  o"..97  5..07  0..0  0. 23  0. 59  0..51  0. 23  4 . 15  0 . 44  QUEBEC  0..45  0..40  0..58  0..0  0. 76  0 .34  0\ 16  2 .08  0..51  ONTARIO  1 .. 32  1 .49 .  0,.66  0,, 27  0..0  1 .. 53  0. 95  6 . 43  1 .. 37  MANITOBA  0. 65  1 .31 .  0..41  0.. 23  0..68  0 .0  5. 77  1 1.86  3 .82  SASKATCHEWAN  0..0  0..49  0.. 1 1  0..10  0..23  3 .81 .  0.0  14 .42  2 . 89  ALBERTA  0..21  1 ,50 .  0.,40  0. 19  0. 86  2, . 78  4 .76  0 .0  9 ,.1 1  BRITISH COLUMBIA  0.. 13  0..80  0,. 28  0.. 12  0..46  1 .05  1 .7 1  10 .69  0 .0  Table 5.2.16 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, Other Occupations.  FROM/TO  NFLD  N . s.  N .B .  NEWFOUNDLAND  0 .0  9 .4 1  5 .97  NOVA SCOTIA  3 . 76  0 .0  NEW BRUNSWICK  1 .66  QUEBEC  QUEBEC  ONT .  MAN.  SASK.  ALTA .  B .C .  0 .04  4 .82  2 .87  1 .03  8 .89  2 . 56  9 . 46  0.. 39  1 . 77  1 .28  1 . 38  7 .93  2 . 26  1 1.04  0..0  0 . 59  1 .41  1 . 20  0 .65  8 .71  1 . 50  O . 25  O .67  0. 75  0 .0  0 .71  0 . 23  0,. 25  1 .67 .  0 . 58  ONTARIO  1 ,, 64  1 .. 56  1 .00  0. 25  0 .0  1 ., 12  0,.87  4 . 58  1 . 70  MANITOBA  1 ., 9 1  1 .00  0. 75  0. 15  0 . 88  0, 0  7 ,72  1 1.. 75  5 .05  SASKATCHEWAN  O.0 •  0. 77  0. 49  0.09  0.,6 1  6 .20  0. 0  13 .17  3 .63 .  ALBERTA  0. 52  1 .56  0. 66  0.06  0. 84  2, . 55  5 .69  0.0  8 .. 57  BRITISH COLUMBIA  0. 44  1 .10  0. 39  0.08  0. 49  1 .76  2 .55  7 .96  0..0  53  Table 5.2.17 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, 1976-1981, A l l Occupations.  Newfoundland  * * * * * 15. 08  4.91  .29  2. 44  2. 32  1. 58  7. 33  2. 15  7. 17 * * ** *  9.73  .42  1. 70  1. 46  1. 48  7. 91  2. 97  2. 07 10. 66 * * * * *  . 78  1. 04  • 91  • 84  5. 10  1. 23  1. 03  • 37  • 27  1. 64  • 84  1. 22  1. 02  4. 78  1. 91  8. 23 10. 85  4 .51  4. 55 * * * * * 15. 54  3. 93 7. 84  New  Scotia Brunswick  Quebec  NS  QUEB. ONT  .96 * * * * *  SASK. ALTA.  BC  NFLD  Nova  NB  MAN •  From/to  • 26  • 74  1. 15  1. 78  .81  . 37 * * * * *  Manitoba  • 95  1. 15  .43  .16  • 98  Saskatchewan  • 13  .  68  . 36  . 10  • 43  Alberta  • 51  1. 74  .61  .14  75  2. 11  6. 81 *****  26  1. 48  .44  .17  61  1. 22  2. 34  Ontar i o  British  Columbia  54  * * ** *  7. 73 ** * * *  following section will first describe the overall C a n a d i a n pattern of migration and then look at the pattern for individual occupations. A number of generalizations c a n be made from the tables. F i r s t , with one  exception  (agriculture) Quebec experienced far less inmigration t h a n expected. T h e adjusted migration rates are in most cases well below Quebec was  1.00.  A t the same time, however,  also g e n e r a l ^ less than expected.  T h i s reasons  outmigration from  for this are the cultural and  political explained above. T h u s F r e n c h speaking Quebecers are likely to have a m u c h lower tendency to migrate, whereas of those that do migrate to another province the majority will in all probability be E n g l i s h speaking. T h e destination of most of the migrants from Quebec is either N e w B r u n s w i c k (also bilingual), Ontario or A l b e r t a , although inmigration from Quebec to A l b e r t a was not as high as for the other provinces. Second, there was a great deal of interaction within the M a r i t i m e provinces. A l t h o u g h the propensity to migrate was the highest i n the M a r i t i m e s , migrants from those provinces do tend to stay within the M a r i t i m e s , i.e., move to another M a r i t i m e province. T h e major nonm a r i t i m e destination for the Atlantic provinces was A l b e r t a . N o v a Scotia seemed to be the M a r i t i m e pole of attraction. In m a n y cases inmigration was greater t h a n expected. M o s t of the migrants likely moved to H a l i f a x , the major growth centre in the M a r i t i m e s between 1976 and 1981. T h i r d , the attractivity of A l b e r t a was more readily apparent in the adjusted migration rates. In only three cases was inmigration less t h a n expected on the basis of Alberta's share of the C a n a d i a n labour force. F i n a l l y , migration rates tend to be greater than 1.00  between  neighbouring provinces and A l b e r t a , and less t h a n 1.00 for other provinces. T h e above  findings are similar in two instances with those of L y c a n (1969). T h e  Quebec pattern a n d the greater propensity to migrate within the M a r i t i m e provinces also existed between  1956  a n d 1961.  H o w e v e r , A l b e r t a was  not as popular a destination.  In  addition, the variation in migration rates was also not as great as it was between 1976 a n d 1981. Increased mobility leading to higher migration rates appears to be a national trend.  55  Table 5.3.1 Regression of Labour Force Adjusted Migration Rates with Distance and Intervening Opportunities, by Province of Origin.  ln(D)  IO  Province  R  R  Newfoundland  .578"  .334  -.577*  .553*  Nova Scotia  .313"  .098  -.306*  .304*  New Brunswick  .460 '  .211  -.444*  .350*  Quebec  .317"  .101  -.317*  .252^  Ontario  .695 *  .483  .693*  -.048  Manitoba  .591  .349  -.221*  -.163*  Saskatchewan  .746 '  .557  -.432*  -.009  Alberta  .734 '  .539  -.485*  .155  British Columbia  .787*  .619  -.559*  .211  Canada*  .333"  .111  -.234*  .043  :  :  :  z  : significant at 10% **  : significant at 5% *** : significant at 1% x  : does not include Prince Edward Island, Yukon and Northwest Territories  56  :l  Although Alberta was the major region of attraction for every occupation, this attractivity was more pronounced in the blue collar and resource-related occupations such as primary occupations, processing and manufacturing. In general, however, blue collar workers do not seem to have as high a propensity to migrate as white collar workers. The reason for this is likely to be found in the social and cultural characteristics of blue collar workers. One of these is that they are more conservative and thus more deeply rooted to their region of origin. Nova Scotia tends to attract migrants from white collar occupational groups. Again, this is most likely related to the development of Halifax as the gateway to eastern Canada. Halifax's fastest growing industry, the port, requires a large number of service industries. These service industries have in turn been able to attract many other, non port-related activities. Apart from the above observations, labour force adjusted migration rates do not show any notable variation between occupational groups.  5.3 Migration Rates Adjusted for Labour Force, Distance and Intervening Opportunities. The next step in the analysis is to determine the influence of spatial factors (distance and intervening opportunities) on the adjusted migration rates, and in turn adjust the rates according to equation (4.2.4). Table 5.3.1  shows the results  of the multiple regression.  Overall distance  and  intervening opportunities explained 11.1% of the variation in migration rates, significant at 1%. This is very much lower than the result of Lycan's (1969) study, where the multiple r showed that 49.8% of the variation was explained by spatial factors. As was to be'expected, however,  the explanatory powers of the two spatial factors vary considerably between  provinces of origin, and are, in most cases (Nova Scotia and Quebec excepted), higher than the coefficient based on all provinces. Generally the multiple R tends to increase in an east to west direction. In all cases the sign of distance was negative, except for Ontario where there was a highly significant positive relationship (62.7% of migrating Ontarians moved to Alberta or 57  B r i t i s h Columbia). H o w e v e r , intervening opportunities h a d a positive sign in all provinces save Ontario, M a n i t o b a and Saskatchewan. For  the  eastern  provinces  the  relationship  between  distance  and  intervening  opportunities is one of a m i r r o r image. In addition, the partial regression coefficients almost  equal  to  the  multiple  regression  coefficient.  The  major reason  that  are  intervening  opportunities show a positive correlation is that, as mentioned earlier, migrants from the M a r i t i m e provinces tend to go to A l b e r t a and B r i t i s h C o l u m b i a i f they do not stay within the M a r i t i m e s . A s the majority of the n o n - M a r i t i m e moves are therefore destined to provinces west of Ontario, it is not surprising that the  sign is positive.  T h e largest  proportion of  C a n a d a ' s labour force is in the industrial heartland of Ontario and Quebec, which tends to be "skipped" b y migrants f r o m the M a r i t i m e s , thus explaining the positive partial correlation coefficient.  O v e r a l l the amount of variation explained by spatial factors for migration to the  M a r i t i m e s was relatively low, compared to the rest of C a n a d a . A g a i n , this is accounted for by the fact that there are only two major destinations: neighbouring provinces or A l b e r t a . F o r Quebec the coefficients were comparatively low. T h i s c a n be explained by the same reasons as above: the small amount of migration that does occur is either to N e w B r u n s w i c k , Ontario or A l b e r t a .  F o r Ontario the  partial correlation of intervening opportunities  was  negative, but totally insignificant. T h i s was to be expected as Ontario itself is the industrial heartland of C a n a d a (along with Quebec). T h e strong positive relationship with distance c a n be explained b y the fact that a good proportion of the moves are over long distances. T h e multiple r  for the western provinces is relatively high compared to the rest of  C a n a d a , r a n g i n g from a low of .349 (Manitoba) to a high of .619 (British Columbia). While distance is highly significant in all cases (greater t h a n 1%), intervening opportunities do not account for as m u c h of the variation a n d are generally not as significant. The equation  results  would  of the  lead  to  multiple regression errors.  The  confirm that  explanatory  power  the of  considerably, as do the signs of the partial correlation coefficients.  58  use  spatial  of a n factors  economy-wide vary  quite  Table 5.3.2 M i g r a t i o n Rates Adjusted f o r Size of the L a b o u r Force, Distance a n d Intervening Opportunities, 1976-1981, Managerial, Administrative.  FROM/TO  NFLD  N .s.  N .8 .  QUEBEC  ONT .  MAN .  SASK .  ALTA .  B .C.  NEWFOUNDLAND  0 .0  1 .01  0. . 68  - 0 . 29  - 0 .31  - 1 .46  - 1 . 32  0 . 24  - 1 .21  NOVA  2 . 29  0 .0  1 .60 .  - 1 .40  - 0 . 15  - 1 .04  - 0 . 23  0 . 75  - 0 . 34  1 .91 .  1 . 53  0 . .0  - 0 . .47  -0,, 4 1  - 0 .84  - 0 , . 14  1 ., 16  -0.. 1 1 0 . 34  NEW  SCOTIA BRUNSWICK  QUEBEC  -o,,  19  0, .50  0 . 67  0. ,0  0. ,49  - 0 .95  - 1.26 ,  1 .00 ,  ONTARIO  -o.,  75  0 . .43  0 . 17  0. .02  0 . ,0  - 0 , .20  - 0 , .44  0, .70  0 . 26  0 . 55  - 0 . 74  -2 .,02  - 0 . 68  0, .0  - 0 . 13  1. 24  0 . 29  - 1 98 .  - 0 . 14  0 . 07  0 . 55  0 . 23  - 1 96 .  - 0 . 07  0 . 95  - 0 . 43  - 1 .15  MANITOBA SASKATCHEWAN ALBERTA BRITISH NOTE: BASED  COLUMBIA  - 0 , ,42  0. .62  1 .. 20  1 ,02 .  - 0 , 38  0. 0  0. 97  1 .27  0 . 51  - 0 . 29  0. 14  0. 0  0 . 89  0 . 95  0 . 03  0 . 40  0 . 22  0. 0  P O S I T I V E VALUES INDICATE THAT MIGRATION IS GREATER THAN ON P O P U L A T I O N , DISTANCE AND INTERVENING OPPORTUNITY  EXPECTED  Table 5.3.3 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, N a t u r a l Sciences  ONT .  MAN.  SASK.  ALTA .  0.61  O. . 27  - 0 .98  -1 ,.29  1 .42  -0,. 4 1  0. .81  - 1 .20  0. .07  - 1• .  ^  - 1. ,24  1 . 55  0, ,45  0. . 66  0. .0  -0.97  - 1.00 .  0, . 55  1 .21  O, .60  0 . . 74  0. 02  - 0 . 76  O. 46  MANITOBA  1 .24  SASKATCHEWAN ALBERTA  FROM/TO  NFLD  N .S.  N..B .  NEWFOUNDLAND  0, .0  0 .97  0. . 10  NOVA  2 ,. 24  0. .0  1 ., 83  QUEBEC ONTARIO  NEW  SCOTIA BRUNSWICK  BRITISH NOTE: BASED  COLUMBIA  QUEBEC  - 0 . . 48  1  B .C.  - 0 . ,48  0.0  0. . 4 1  - 0 , ,49  - 0 . . 17 .  1 . 30  0. , 50  - 0 . 59  0.02  0. 0  - 0 . . 23  - 0 . , 44  0 . 94  - 0 . , 47  0 . 59  0 . 32  -1.41  - 0 . 79  0. 0  0. ,55  1 . 15  0. 80  0.. 99.  1 .37  - 0 . 02  - 1 . 49  - 0 . 37  - 0 . 54  0. 0  1 ., 12  1 ,01 .  o. 6 1  O. 87  - 0 . 81  - 1 . 35  0 . 20  - 1 07 .  - 0 . 34  0. .0  0 . , 49  0. 0  0 . 77  - 0 . 49  -0.82  0 . 51  - 0 . 54  - 0 . 24  0, .06  0. 0  P O S I T I V E VALUES INDICATE THAT MIGRATION IS GREATER THAN ON P O P U L A T I O N , DISTANCE AND INTERVENING OPPORTUNITY  59  EXPECTED  Table 5.3.4 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Social Sciences. FROM/TO NEWFOUNDLAND NOVA SCOTIA NEW BRUNSWICK QUEBEC ONTARIO MANITOBA SASKATCHEWAN ALBERTA BRITISH COLUMBIA  NFLD  N,,S.  0..0 0.. 55 2, . 7 1 0..0 2.., 57 O., 78 0.. 29 0,, 32 -0., 52 O,,67 1 ,09 . 0.,63 1 ,92 . 0..0 1 ,01 . 0.,80 0., 15 1 .25  N,,B.  QUEBEC  - 1..38 -o,, 78 -0,,81 0.,0 -0. 24 0,, 17 . 24 -0.. 15 -2 , . 0. 66 -2 ,67 , -0. 35 - 1.73 -1.^46 - 1,31 . -o,,09 0.,63 O.,0 0..44  ONT .  MAN.  SASK .  -0,.09 -0..59 -0..90 -o. 66 - 1,,18 -0. 48 -0., 20 -0. 42 0.. 15 -0. 18 0.,0 0,,0 0. 16 -0. 35 -0., 26 -0.. 74 0. 0 0.,08 -0. 33 0. 49 1. 01 0,. 35 0. 44 0,. 13 -0,,03 -0..51 0., 14  ALTA .  0..20 1 ,, 28 1 ,, 12 0., 7 1  ,C . B.  - 1.62 . 0.. 12 0 .01 0 . 46  0,,96 -0..09 1 ,.20 1 .. 13 0,. 54 0 .94 0.,0 0.. 72 -0.. 30 0.,0  NOTE: POSITIVE VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON POPULATION, DISTANCE AND INTERVENING OPPORTUNITY  Table 5.3.5 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Teachers FROM/TO NEWFOUNDLAND NOVA SCOTIA NEW BRUNSWICK QUEBEC ONTARIO MANITOBA SASKATCHEWAN ALBERTA BRITISH COLUMBIA  NFLD  N.. S .  0 .0 2,.08 0,,03 0..29 -0.. 5 1 0.. 7 1 0,. 27 1 .06 . 0..83  0.. 12 0..0 O,, 70 0.. 59 0,.51 0..86 0.. 27 1. 25 1 .56 .  N. ,B .  QUEBEC  -0., 59 -0.43 0.,62 -1.18 -0.55 0..0 0,, 50 0.0 -0.. 34 0.52 -0. 80 -1.31 - 1 . 94 0. 0 0. 21 - 1 . 36 -2 .05 -0. 48  ONT .  MAN .  SASK.  ALTA .  -0.. 78 -0.. 37 - 1.01 . 0.. 27 0..0 -0. 85 -0,.06 0. 52 1. 1 1  -0..61 -0..60 -0.. 79 -0. 24'  - 1 77 . -0. 25 -0. 25 -0. 63 -0. 10 -0. 20 0. 0 -0. 21 0. 13  0.. 20 0..05 1 ,02 , 0 .08 0..90 -0..66 0.. 70 0.. 59 0.. 47 -0.. 1 1 0.. 36 0..89 0.. 58 1 .. 27 0'..0 0.. 76 -0..21 0. 0  0. 00 0. O -0. 87 -0. 61 -0. 1 1  NOTE: POSITIVE VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON POPULATION, DISTANCE AND INTERVENING OPPORTUNITY  60  B ,C .  T a b l e 5.3.6 M i g r a t i o n R a t e s A d j u s t e d f o r S i z e o f t h e L a b o u r F o r c e , D i s t a n c e a n d I n t e r v e n i n g O p p o r t u n i t i e s , 1976-1981, M e d i c i n e a n d  Health.  N .B . QUEBEC  ONT .  MAN .  SASK .  ALTA .  B ,c.  - 0 , . 67  0 . 20  0 .04  - 1. 33  0..92  1 .06  1 , 28  - 1. 23  0..02  - 0 . . 22  - 0 . . 74  0..96  0 . 74  1. .16  0 ,.0  - o . 75  - 0 . . 28  - 0 . . 87  - 1.04 .  1.02 .  - 0 . . 13  FROM/TO  NFLD  N .S.  NEWFOUNDLAND  0 .. 0  1 . 37  NOVA SCOTIA  2 . 37  0 .0  NEW BRUNSWICK  1 ,62 .  - 0 , .40  QUEBEC  - 0 . .21  0 ,. 54  0 .,61  0 .,0  - 0 . ,07  - 0 . . 52  - 0 . .93  0 . 51  0 .. 37  ONTARIO  - 0 , ,42  0.. 77  - 0 , . 19  - 0 . .06  0 ., 0  - 0 . .08  - 0 . .46  0 ..43  - 0 . ,02  MANITOBA  - 0 . .03  1..59  - 0 , ,01  - 2 ., 22  - 0 . . 77  0 ..0  - 0 . .01  0 . 92  1. .34  0 . , 20  1..66  -1 ,. 20  - 2 .. 37  - 0 . , 23  - 1 . 05  0 ..0  0 . 64  1 .56 .  -0. 1 1  1. 12  - 0 . 43  - 1 50 .  0 . 31  - 0 . 45  - 0 . 67  0. 0  0 . 80  0 . 97  1.,57  0 , ,23  - 1.30 ,  0 . .64  0 . .04  - 0 . 19  - 0 . 42  SASKATCHEWAN ALBERTA BRITISH COLUMBIA  0. 0  NOTE: POSITIVE VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON POPULATION, DISTANCE AND INTERVENING OPPORTUNITY  T a b l e 5.3.7 M i g r a t i o n R a t e s A d j u s t e d f o r S i z e o f t h e L a b o u r F o r c e , D i s t a n c e a n d I n t e r v e n i n g O p p o r t u n i t i e s , 1976-1981, F i n e a n d C o m m e r c i a l  Artists.  FROM/TO  NFLD  N.s.  N .B.  QUEBEC  ONT .  MAN .  SASK.  ALTA .  B .C.  NEWFOUNDLAND  0 .0  0 .68  - o .71  0 . 17  0 . 18  - 0 . 72  - 0 .05  0 . 17  - 0 .73  NOVA SCOTIA  0 . 27  0 .0  0 . 69  - 0 . . 88  - 0 . 13  - 0 .05  - 0 .04  0 . 20  - 0 .00  NEW BRUNSWICK  0 .0  0 .85  0 .0  - 0 . 36  -0 . 4 1  - 1. 38  - 0 .21  0 . 58  0 .09  QUEBEC  - 0 . . 28  0 .64  0 . 38  0 ..0  0 .. 18  - o . . 18  - 0 . .66  0 . 59  o .. 36  ONTARIO  - 0 . .80  0 . 63  0. 1 1  0 . 49  0 . .0  0 . 36  0 . 16  0 ..63  - 0 . ,15-  MANITOBA  2 . 30  0 . 66  - 0 . 20  - 1 01 .  - 0 . 29  0. 0  0 . 90  1. .44  0 . 86  SASKATCHEWAN  0. 0  0. 0  0. 0  - 0 . 23  0 . 23  0 . 25  0. 0  1 .10  1 26 .  ALBERTA  O. 30  1. 66  0 . 18  - 0 . 94  0 . 78  - 0 . 18  0 . 32  0. 0  0 . 93  BRITISH COLUMBIA  0 . 40  1. 94  - 0 . 47  -0. 6 1  1. 26  0 . 17  0 . 36  - 0 . 01  NOTE: POSITIVE VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON POPULATION, DISTANCE AND INTERVENING OPPORTUNITY  61  0. 0  Table 5.3.8 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1876-1981, C l e r i c a l Workers.  FROM/TO  NFLD  N S.  N B.  QUEBEC  ONT .  NEWFOUNDLAND  O 0  0 97  O 43  -0 62  0 49  NOVA SCOTIA  1 5G  0 0  0 65  - 1 32  1 28  O 93  0 O  QUEBEC  -0 08  0 26  ONTARIO  -0 56  MANITOBA  MAN.  SASK .  ALTA .  B C.  -0 98  -0 6 1  1 52  0 07  -0 14  -o  43  -0 69  1 30  0 20  -0 61  -0 36  -0 59  -0 44  1 50  0 22  0 27  0 0  0 25  -0 72  - 1 40  1 16  0 45  0 20  -0 24  -0 04  0 0  -0 34  -0 69  0 86  -0 39  0 38  1 03  -0 71  -2 42  - 1 19  0 0  0 09  1 09  0 96  SASKATCHEWAN  0 60  0 96  0 07  - 1 77  -0 55  -0 59  0 0  1 18  1 49  ALBERTA  0 23  0 99  0 19  - 1 64  0 25  -o  0 0  0 93  -0 07  0 69  -0 09  - 1 26  0 70  -0 17  0 38  0 0  NEW BRUNSWICK  BRITISH COLUMBIA  1  39  -o  00  0 09  NOTE: POSITIVE VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON POPULATION. DISTANCE AND INTERVENING OPPORTUNITY  Table 5.3.9 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Sales Occupations.  i  FROM/TO  NFLD  N  s.  N B.  QUEBEC  NEWFOUNDLAND  0 0  0 58  -0 20  -0 76  -0 23  - 1 55  NOVA SCOTIA  1 26  0 0  0 59  - 1 59  -0 37  NEW BRUNSWICK  0 51  0 85  0 0  -0 69  0 42  0 31  0 0  ONT .  MAN.  ALTA .  B c.  -2 93  1 23  -0 95  -0 85  - 1 12  0 89  -0 19  -0 70  - 1 23  -0 98  1 10  -0 28  0 32  -0 82  - 1 79  0 93  0 26  -0 90  0 75  -0 45  0 1 1  1 27  1 03  0 0  0 63  0 88  -0 46  0 0  0 88  -0 41  0 1 1  0 0  | QUEBEC  -1  I  ONTARIO  -0 58  0 44  -0 19  -0 09  0 0  -0 13  MANITOBA  0 50  0 59  -0 7 1  -2 02  -1 03  0 0  SASKATCHEWAN  0 70  -0 35  -0 39  -2 16  -0 96  -1 03  -o  09  -2 18  o  -0 64  - 1 22  0 63  ALBERTA BRITISH COLUMBIA  1 1  -0 37 0 23  o  46  0 38  SASK .  25  -o  40  -0 2 1  NOTE: POSITIVE VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON POPULATION, DISTANCE AND INTERVENING OPPORTUNITY  62  Table 5.3.10 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Service Occupations.  s.  FROM/TO  NFLD  N  NEWFOUNDLAND  0 0  1 44  0  38  -0  NOVA  1 72  0 0  0  27  - 1 27  0  0 0  74  SCOTIA  N B.  QUEBEC  ONT .  95  0 61  -0  42  0  16  -0  -0  46  0 00  MAN .  SASK.  ALTA .  B C.  -0  29  1 29  0 54  1 1  -0  18  1 16  0  35  -0  31  -0  71  0 97  -0  19  -0  42  -0  39  1 00  0 09  -0  60  0 63  -0  40  0 0  -0  56  0 66  0  72  I  NEW  BRUNSWICK  O 87  44  -0  QUEBEC  -0  35  0 93  0 46  ONTARIO  -0  42  0 88  O 02  -0  1 1  MANITOBA  0  52  1 03  0 04  -2  46  -0  95  SASKATCHEWAN  0  50  1 53  0  - 1 34  -0  52  - 1  •1 1  ALBERTA  0  37  1 41  0 04  - 1  14  0  38  -0  38  -0  60  0  16  1 61  0  17  -0  85  0  70  0  1 1  -0  15  BRITISH  COLUMBIA  52  0 0  0 0  0 0  38  0  0 0 -0  12  0 44  0 97 0 62 0 0  N O T E : P O S I T I V E VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON P O P U L A T I O N , DISTANCE AND INTERVENING OPPORTUNITY  Table 6.3.11 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance a n d Intervening Opportunities, 1976-1981, A g r i c u l t u r e . FROM/TO  NFLD  N S.  N B.  NEWFOUNDLAND  0 0  2  2 26  NOVA  1 86  0 0  1 53  0 0  1 84  0 0  0 62  0 76  -0  0 0  o 61  1 06  0 O  1 05  0  0 -3  NEW  SCOTIA BRUNSWICK  QUEBEC ONTARIO  -0  01  12  32  QUEBEC  1 50  1 58  1 32  - 1 79  0 66  0 94  27  -1  01  1 2 1  1 08  0 67  - 1 34  -2  04  0  21  1 12  17  0 0  -0  38  -1  93  0  36  0 60  84  - 1 62  - 1 56  -0  44  1 27  0 0  -0  98  0 57  70  -0  98  SASKATCHEWAN  O 0  0  40  -0  69  ALBERTA  0 0  o 67  -0  54  -2  82  0 0  2 42  1 54  -0  1 1  COLUMBIA  1 74  B C.  0 0  BRITISH  2 90  ALTA .  MANITOBA  O 0  MAN.  SASK.  0 0 -0  ONT .  0 0  0  28  - 1 80  0 0  0 O -2  68  42  - 1 34  38  0 97  0 02  0 00  -0  N O T E : P O S I T I V E VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON P O P U L A T I O N , DISTANCE AND INTERVENING OPPORTUNITY  63  0 0 0  1 1  0 84 0 0  Table 5.3.12 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance a n d Intervening Opportunities, 1976-1981, P r i m a r y Occupations.  FROM/TO  NFLD  NEWFOUNDLAND  N.S.  N..B.  QUEBEC  ONT .  0 .0  - 1. 19  -2 . .80  -2 .47  - 1. 27  NOVA SCOTIA  -0 . 38  0..0  -2 . 28  -4 . 26  NEW BRUNSWICK  - i ..47  - 1.70 .  0..0  QUEBEC  - 1 ,81 .  - 1 .,33  0., 18  ONTARIO  -0. 12  0.. 28  MANITOBA  0..83  SASKATCHEWAN ALBERTA BRITISH COLUMBIA  MAN.  SASK .  1 . 38  -0..05  2. 1 1  -0,.31  - 1.62  -0.. 37  -0..49  1 . 34  -0,.62  - 1.52  - 1.40  0..08  - 1.62 .  1 .49  -0,. 1 1  0 .0  0..06  0.,07  -0.. 28  1 .61  0..59  -0. 21  0..03  0,,0  0.. 78  0. 25  1 . 54  0. 48  -0. 95  -2 . .51  0. 0  0. 48  1 .98  0,.79  0. 0  0. 0  -0. 77  0..0  -0..55  -0. 40  0. 0  1 . 73  0. 74  0. 54  0. 88  -0. 16  -2 . .91  0. 07  -0. 22  0. 41  0..0  0. 58  -0. 48  0.08  -1 . 77  -2 ..86  -0. 02  -0. 78  -0. 79  0,,00  0. 0  -0.. 12  ALTA .  B .C.  -0,, 33  NOTE: POSITIVE VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON POPULATION, DISTANCE AND INTERVENING OPPORTUNITY  Table 5.3.13 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance a n d Intervening Opportunities, 1976-1981, Processing. FROM/TO  NFLD  N.S.  NEWFOUNDLAND  0..0  NOVA SCOTIA  0.. 27  N .B.  QUEBEC  ONT .  0 .31  -0 .92  -0 .96  0 . 14  0.,0  -0 . 27  -2 . 1 1  -0..40  -o..31  NEW BRUNSWICK  -0..89  0.. 24  0,.0  -0..61  QUEBEC  -0. 73  -0., 55  0,.87  0..0 -0.. 17  MAN .  -o .  13  SASK .  ALTA .  B ,C.  0 .47  1 . 76  O .51  0..0  1 . 10  0.. 15  0.. 77  0..0  1 .90  Oi.31  -0.. 75  1 .23  0..42  1 . 34  -0,. 27  -o.. 37  0.0  0..07  -0..86 -0.. 32  -3. 05  -0. 63  0. O  0..48  1 . 75  1.. 19  0. 22  - 1 .32 .  -0. 25  -0. 40  0. 0  1 .81 .  1. 97  ONTARIO  0. 12  0. 67  0..30  MANITOBA  0. 79  -0. 12  -0. 23  SASKATCHEWAN  0. 0  0. 0  -0.. 24  ALBERTA  -0. 49  1 .40  0. 25  - 1 38 .  0. 74  0. 46  0. 27  0 .0  1. 31  BRITISH COLUMBIA  - 1 .13  0.03  0. 25  -1 .99  0. 4 1  -0. 06  -0. 24  0..33  0. 0  NOTE: POSITIVE VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON POPULATION. DISTANCE AND INTERVENING OPPORTUNITY  64  Table 5.3.14 M i g r a t i o n Rates Adjusted f o r Size of the L a b o u r Force, Distance a n d Intervening Opportunities, 1976-1981, Manufacturing. FROM/TO  NFLD  N. S .  N .B.  NEWFOUNDLAND  0 .0  1.60  0 . 98  NOVA  1 . 64  0 .0  1 . 15  1 .42  1 . 28  0 .0  NEW  SCOTIA BRUNSWICK  QUEBEC  ONT .  MAN.  SASK .  ALTA .  0 . 38  1 . 37  - 0 . 37  - 0 .83  2 . 18  1 .21  - 1.42 .  0. . 13  -0.. 4 1  0. .32  1 .93  0 . 54  - 0 . . 57  - 0 . . 27  - 0 . .21  - 0 . .06  2 . 19  0 . . 52  B .c.  QUEBEC  - 0 . .87  0 .06  0 . 56  0 , ,0  - 0 . . 38  - 0 . .75  - 0 . . 73  1 .41  0 . . 33  ONTARIO  -0.. 1 1  0 . . 54  0. .03  - 0 . .44  0. 0  - 0 . 17  - 0 . .21  1 .21 .  - 0 . . 20  MANITOBA  0 . . 70  0 . .94  0. . 14  - 1 84 .  - 1 36 . .  0. 0  0 . 62  1 .63 .  1 .45 .  SASKATCHEWAN  0. 0  1. 16  1..69  - 1 38 .  - 0 . 50  - 0 . 21  0. 0  1 ,, 76  1 .91  ALBERTA  1 .04  1. 37  0. 7 1  - 1 50 .  O. 69  0 . 24  0 . 78  0 . .0  1 .59  - 0 . 05  0 . 82  0 . 02  - 0 . 80  0 . 87  0 . 27  0 . 79  0 . .85  0. 0  BRITISH  COLUMBIA  N O T E : P O S I T I V E VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON P O P U L A T I O N , DISTANCE AND INTERVENING OPPORTUNITY  Table 5.3.15 M i g r a t i o n Rates Adjusted f o r Size of the L a b o u r Force, Distance a n d Intervening Opportunities, 1976-1981, C o n s t r u c t i o n Trades. N.. s .  N ,B.  O .0  - 1.38 .  - 1 . 38  - 0 . . 10  0. O  - 0 . , 27  QUEBEC  FROM/TO  NFLD  NEWFOUNDLAND  ONT .  MAN.  SASK.  - 1 . 37  - 0 . 20  - 1 . 23  - 0 , . 16  1 . 75  - 0 . , 52  - 1.01 .  - 2 . 68  - 1 .00  - 1 . 40  - 0 . .55  1 .53  - 0 . 27  - o . . 72  0 . .0  - 1 . 84  -1. 1 1  - 1 . 57  - 1. ,14  ' 1 . 88  - 0 . 33  - 1.91 .  - o . 94  - 0 . . 36  0 .0  - 0 , .84  - 2 . 17  - 1.00 ,  1 .62  0 . 02  ONTARIO  - 1 03 .  - o . 35  - 0 . .54  - 0 . . 79  0 .0  - 1. ,18  - 0 . . 78  1 . 23  - 0 . 45  MANITOBA  - 0 . 16  - 0 . 70  -1. 6 1  - 3 ..80  - 1 . , 75  0 .0  - 0 . ,00  1 . 26  0 . 83  0. 0  - o . 52  - 1 . 62  -2 . 35  - 1 . .49  - 1.85 .  0 . ,0  1 .04 '  0 . 99  - 1 09 .  0 . 92  - 1 . 07  - 2 ..09  - 0 . , 37  - 0 . , 93  - 0 . 23  0, .0  0 . 72  - 1 38 .  - 0 . 34  - 0 . 59  - 2 ,,03  - 0 . 05  - 0 . 99  - 0 . 01  0 , . 16  0. 0  NOVA NEW  SCOTIA BRUNSWICK  SASKATCHEWAN ALBERTA BRITISH  COLUMBIA  QUEBEC  N O T E : P O S I T I V E VALUES INDICATE THAT MIGRATION IS GREATER THAN EXPECTED BASED ON P O P U L A T I O N , DISTANCE AND INTERVENING OPPORTUNITY  65  ALTA .  B ., C .  Table 5.3.16 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Transportation.  . s.  FROM/TO  NFLD  NEWFOUNDLAND  0 .0  NOVA  1 .. 33  0. .0  o!', 34  0 . 12  0 . . 23  - 0 . 31  - 0 . 23  MANITOBA SASKATCHEWAN  NEW  SCOTIA BRUNSWICK  QUEBEC ONTARIO  ALBERTA BRITISH NOTE: BASED  COLUMBIA  N.  N.. B .  QUEBEC  ONT .  MAN.  - 0 .58  - 1 .04  - 0 .59  - 1 .52  0 .0  1 .02  - 0 . 30  -o .  -2 . 1 1  - 0 . .•65  - 0 . . 79  - 1.62 .  1 .08  0 .03  0. .0  - 1 .84  - 0 . .98  - 1.02 .  - 1. .72  1 .30  - 0 .81  - 0 .06  0. .0  - 0 . 20  - 0 . .60  - 1 28 .  1 . 38  0 .06  0 . 37  - 0 . . 28  - 0 . . 32  0. .0  0. 23  - 0 . 45  1 . 24  - 0 . . 56  0 . 45  0 . 85  - 0 . .46  - 1.67 .  - 1 .18  0 . .0  - 0 . 12  1 . 36  0. .86  0. 0  0 . 55  - 1 04 .  - 1.69 .  - 1 05 .  - 0 . 80  0. 0  1 .00  0. .96  - 0 . 60  0 . 97  - 0 . 44  - 1 26 .  0 . 53  0 . 02  -o. 43  0.0  1. .07  - 0 . 66  0 . 72  - 0 . 39  - 1.30 .  0 . 48  - 0 . 14  - 0 . 22  0 . 49  0. 0  - 0 . 12  14  P O S I T I V E VALUES INDICATE THAT MIGRATION IS GREATER THAN ON P O P U L A T I O N , DISTANCE AND INTERVENING OPPORTUNITY  SASK.  ALTA .  B .C .  EXPECTED  Table 5.3.17 M i g r a t i o n Rates Adjusted for Size of the L a b o u r Force, Distance and Intervening Opportunities, 1976-1981, Other Occupations FROM/TO  NFLD  N.S .  N .B.  QUEBEC  ONT .  MAN.  SASK.  ALTA .  B .C.  NEWFOUNDLAND  0 .0  0 .46  0 .56  -2 . 57  1 .. 24  - 0 . . 30  -1 ..07  1 . 47  O .58  NOVA  1 .08 .  0 0  0 .7 1  - 1.41  - 0 . . 15  - 0 . .78  - 0 . .65  1 . 18  - 0 . .03  0. . 88  0 .90  0 .0  - 0 .88  - 0 . . 10  -0.. 3 1  - 0 . .81  1 .93  0. 30  NEW  SCOTIA BRUNSWICK  QUEBEC  -0.. 3 1  0 . 23  0 . 20  0. .0  - 0 . . 26  - 1.08 .  - 0 . 92  1 .08  0. 10  ONTARIO  - 0 . 02  0. . 4 1  0. . 14  - 0 . ,40  0. 0  - 0 . .08  - 0 . 54  0 .90  - 0 . 34  MANITOBA  1. 57  0. .62  0. . 22  -2 ..04  - 0 . .93  0 . .0  SASKATCHEWAN  0. 0  1 .00 .  0. .4 1  - 1,80 .  - 0 . 10  ALBERTA  0 . 29  0 . 98  0 . 02  -2 . 44  0 . 54  1 .01  - 0 . 13  - 1 78 .  BRITISH NOTE: BASED  COLUMBIA  0. 17  1 . 34  1 . 13  - 0 . 31  0. 0  0 .90  1 . 19  0 . 51  - o . 06  - 0 . 25  0. .0  1 .01  0 . 57  0 . 39  0 . 17  0. . 19  0. 0  P O S I T I V E VALUES INDICATE THAT MIGRATION IS GREATER THAN ON P O P U L A T I O N , DISTANCE AND INTERVENING OPPORTUNITY  66  EXPECTED  Tables 5.3.2  to 5.3.17 show migration rates b y occupation adjusted for labour force  size, distance and intervening opportunities, which are simply the residuals of the multiple regression as given in equation (4.2.2). T h e question is whether the explanations for the above patterns still hold, or whether the patterns were removed and accounted for b y distance and intervening opportunities. T h e tables show that the removal of the influence of distance and intervening  opportunities  has  resulted  in both the  emergence  of new  patterns  and  the  enhancement and/or r e m o v a l of old ones. A l b e r t a still shows the highest inmigration rates.  N o v a Scotia now has the  second  highest rates, followed b y British C o l u m b i a , which has lost m u c h of its original attractivity. In the M a r i t i m e s m u c h of the increased interaction between other M a r i t i m e provinces has been removed (although one can still see  a pattern), whereas in some occupations it has  been  reversed, that is migration is less t h a n expected. Some examples of these negative residuals are p r i m a r y , processing and construction occupations. F o r Newfoundland a n d N e w B r u n s w i c k the residuals are also in most cases positive, i.e., inmigration is greater than expected, for most most occupations, but not quite as pronounced as N o v a Scotia. In general the M a r i t i m e s do not do as badly as one would have otherwise  expected.  In fact inmigration rates are  generally higher than those of Ontario. O u t m i g r a t i o n rates, on the other h a n d , tend to average out to zero. T h e fact that the M a r i t i m e s performed comparably well can be explained by three factors: (1) m u c h of this inmigration is most likely to be r e t u r n migration; (2) social security benefits are in some cases probably easier to obtain than in other provinces; and (3), explanation already mentioned  an  in the discussion of labour force adjusted migration rates,  H a l i f a x ' s role as a growth pole. T h e tendency found above to migrate to a neighbouring province has now largely been removed. Instead, a new pattern has emerged where migration rates to the eastern neighbours are generally negative, whereas to western neighbours they are usually positive, indicating a "pull" to the west. Quebec, Ontario, M a n i t o b a and Saskatchewan all p e r f o r m quite poorly in  67  attracting migrants due to other t h a n spatial or labour force related factors compared to the rest of C a n a d a . The  above  results  are again quite different  to those of L y c a n  (1969). F i r s t ,  the  variation in the size of the residual was m u c h lower (the correlation was also greater). Second, no significant east to west movement was found. Quebec and Saskatchewan, however, were also poor attractors of migrants between 1956 and 1961. F r o m a n occupational point of view three distinct groups appear when observing the signs of the residuals: (1) occupations that are relatively reluctant to migrate (mostly negative residuals),  (2) occupations  that show a tendency  towards  "hypermobility" (mostly  positive  residuals), and (3) occupations which do not show a tendency in either direction. T h e first group of occupations is comprised of sales (58% of the residuals are negative),  construction  (81%) and transportation (60%). Salespeople, although they do travel quite frequently, are not required to move in order to gain access to jobs. T h e c o m p a n y a salesperson works for can be located anywhere in C a n a d a (or the U n i t e d States). Companies prefer to assign regions to people that are on their "home turf". Construction- and transport-related occupations  are  highly unionized, as mentioned earlier, which would p a r t l y explain the reluctance to move. Hypermobile occupations are fine and commercial artists (63% of the residuals are positive), service occupations (60%), agriculture (67%)  and m a n u f a c t u r i n g (65%). F o r artists  m a n y jobs are short t e r m contracts, thus often requiring a move w h e n a new contract is won. In the agricultural sector of the economy (this concerns not so m u c h the f a r m e r s , but more the agricultural consequently  workers) not  as  there stable  are constant as  in  other  up- and downswings, occupations.  Thus  and job opportunities agricultural workers  are have  traditionally been nomadic people. In the service related occupations we find the hypermobile "Yuppies". F o r m a n u f a c t u r i n g it is difficult to find a n explanation for the relatively high tendency  to  migrate,  especially  considering the  heavy  unionization in those  occupations.  P e r h a p s increased automation and the resulting relative instability of jobs could provide a partial explanation.  68  5 . 4 Wages, Unemployment and Adjusted M i g r a t i o n Rates. The  purpose of this  section of the chapter  is to test the  influence  of wage and  unemployment rates on the residual migration not explained b y the size of the labour force and spatial factors. According to the neoclassical hypothesis we should thus find that if the wage rate  is  higher in the  province of destination  than  it is  in the  province of origin,  and  unemployment rates are lower, then the residual should be positive. Consequently, as stated earlier,  the  partial  coefficient  should then  be  positive  for wage rates  and negative  for  unemployment rates. Table 5.4.1  shows the results of the multiple regression broken down by province of  origin. In general the  correlation coefficients  insignificant. Differences  are not v e r y high and in most cases quite  in wage and unemployment rates explained between 0.7%' (New  B r u n s w i c k and Ontario) and 8.1% (British Columbia) of the variation. O v e r a l l (Canada) the r was 0.5%. T h e partial regression coefficients were in most cases not of the expected sign: for unemployment rates only in three out of nine cases was the sign negative, whereas for wage rates  only  four  out  of  nine  were  positive.  Intuitively  this  suggests  that  wage  and  unemployment rates do not influence migration rates in the m a n n e r they are expected  to  according to the neoclassical hypothesis. H o w e v e r , before such a judgement can be made, data problems and individual cases (provinces and occupations) have to be considered. The  negative partial correlation coefficients for wage rates in the M a r i t i m e s indicate  that individuals from those provinces tend to go to low wage regions, in this case other M a r i t i m e provinces (although a large portion of the i n t r a - M a r i t i m e migration pattern was removed  after  migration  rates  were  adjusted  for  spatial  factors).  For  Ontario  and  Saskatchewan the multiple correlation coefficients (.082 and .100, respectively) were also v e r y low. T o explain this phenomenon it is necessary to go back to the labour force and spatiallyadjusted migration rates tables. F o r Saskatchewan the residuals (in terms of outmigration) are generally positive  for the  M a r i t i m e s and A l b e r t a , a n d negative  69  for the remainder of the  Table 5.4.1 Significance of Interregional Differences i n Wage and Unemployment Rates on Residual Migration, by P r o v i n c e of O r i g i n .  Unempl.  Wages  Province  R  R  Newfoundland  .137  .019  -.083  -.126  N o v a Scotia  .122  .015  .079  -.079  New Brunswick  .081  .007  -.024  -.081  Quebec  .214*  .046  .089  .213**  Ontario  .082  .007  .077  .054  Manitoba  .247  .061  .053  .245  Saskatchewan  .100  .010  -.100  -.039  Alberta  .102  .010  .055  .100  British Columbia  .285  .081  .145  Canada  .068*  .005  .066  x  **  ***  2  **  * * * *  : significant at 10%  * : significant at 5%  ** : significant at 1% : does not include Prince E d w a r d Island, Y u k o n and N o r t h w e s t Territories.  70  ** -.188 . .036  country. T h u s it is possible to make the same kind of arguments above with respect to the low r squares i n the M a r i t i m e s (note that the partial correlation coefficient for wage rates is also negative). F o r migrants from Ontario the residuals seem to be r a n d o m l y distributed. W i t h the exception of A l b e r t a , O n t a r i a n s do not seem to favour a n y particular destination. B r i t i s h C o l u m b i a was  the only province of origin where  residual migration  rates  showed a significant correlation with wage and unemployment rates, although in both cases the partials were of the wrong sign. A g a i n , it is necessary to refer to the residual migration tables to provide a partial explanation for this finding. T h e residuals tended to be positive for Ontario, N o v a Scotia, and to certain extent also for N e w B r u n s w i c k (all r a n k i n g lower t h a n British  Columbia  on  the  wage  and  unemployment  rates  scale),  and r a n d o m for  other  destinations (including Alberta). Return migration could again partially account for the positive residuals for M a r i t i m e destinations and Ontario. Manitoba  had  the  second  highest  correlation  (.247, significant  at  the  5%  level).  Residuals tended to be positive for western destinations and negative for eastern destinations. In the provinces to the west of M a n i t o b a wage rates are relatively low (positive partial). F o r Quebecers the two variables explained the third highest proportion of the variation. While unemployment  rates  were  insignificant,  wage rates  showed  a positive  relationship  with  shows the results of the regression of wage and unemployment  rates  residual migration (significant at the 5% level). Table 5.4.2  broken down by occupation. O v e r a l l the multiple correlation coefficients were slightly higher t h a n obtained i n the previous regression, but still insignificant. White collar occupational groups tended to have a slightly higher r squared t h a n the blue collar groups, although the lowest was in m a n a g e r i a l and administrative occupations (0.4%). In only one case (teachers) the partial correlation coefficients of unemployment rates was of the expected sign. F o r wage rates the signs tended to be negative for the white collar groups a n d positive for the blue collar occupations. A s with the previous regression, the results show that the residual migration pattern does not seem to fit the neoclassical hypothesis.  71  Table 5.4.2 Significance of Interregional Differences in Wage and Unemployment Rates on Residual Migration, by Occupation.  Unempl.  Wages  Occupation  R  R  Managerial  .063  .004  .062  N a t u r a l Sciences  .250  .063  .213*  Social Sciences  .202  .041  .024  -.202*  Teachers  .252  .064  -.076  -.229*  Medicine & H e a l t h  .272*  .074  .211*  -.070  Artists  .227  .052  .165  -.204  Clerical W o r k e r s  .159  .025  .063  -.126  Sales  .282*  .080  .234  -.000  Service  .163  .027  .162  .009  Agriculture  .146  .021  .024  .136  Primary  .143  .021  .103  .129  Processing  .214  .046  .170  .212*  Manufacturing  .172  .030  .042  .172  Construction  .219  .048  .088  .197*  Transportation  .162  .026  .160  .043  O t h e r Occupations  .188  .035  .186  .051  A l l Occupations  .068  .005  .066  *  : significant at 10% : significant at 5%  72  2  -.014 .131  *  **  **  .036  5.5 Net M i g r a t i o n and Changes i n Wage and Unemployment Rates. This final part of the analysis will examine the effects of migration on wage and unemployment rates between 1976 and 1981. The neoclassical hypothesis here is that net inmigration will increase unemployment rates while reducing  wage rates, whereas net  outmigration will reduce unemployment rates and increase wage rates. It is assumed that these changes will bring the system back to a state of equilibrium. Table  5.5.1  shows  the relationship between  net migration  and  wage  and  unemployment rates broken down by province. While net migration did have an effect on changes in wage and unemployment rates between 1976 and 1981 (although significant only in a few cases), in most cases the direction of the sign was not as expected. The relationships were strongest in Quebec, Alberta and New Brunswick. The reversed signs suggest a process of cumulative causation rather than an equilibrating process, particularly in Alberta, where, as we know, net inmigration was the highest in Canada. Broken down by occupation the relationship becomes clearer (see table 5.5.2). The correlation coefficients are generally higher for wage rates and lower for unemployment rates. In all but one case the signs are reversed. For unemployment rates we find that net migration had a stronger and more significant effect in the upper occupational groups, while for wage rates there was little variation. Only in two cases (fine and commercial artists and other occupations) there was a significantly strong relationship. This latter regression suggests more strongly that net inmigration promotes a. process of cumulative causation. This implies that, rather than increasing unemployment and reducing wage rates, net inmigration causes the opposite effects. Thus the neoclassical hypothesis on the effects of labour migration can not be substantiated.  73  Table 5.5.1 Significance of Net Migration on Changes in Wage and Unemployment Rates, 1976-1981, by Province.  Unemployment  Wages R  R  .006  .414  .171  .028  .239  .057  .286  .314  .098  Province  R  R  Newfoundland  .076  N o v a Scotia  .168  New Brunswick  ** -.535  **  2  2  Quebec  .524  .274  .465*  .216  Ontario  -.153  .023  -.463*  .215  Manitoba  -.083  .007  .321  .103  .108  .021  .489*  .239  Saskatchewan  **  Alberta  -.498  .248  .408  .167  British Columbia  -.012  .000  -.277  .077  Canada  -.529  .280  .140  x  ***  a  * : significant at 10% : significant at 5%  *** : significant at 1%  x  : does not include Prince E d w a r d s Island, Y u k o n a n d Northwest Territories  74  .019  Table 5.5.2 Significance of Net M i g r a t i o n on Changes i n Wage and Unemployment Rates, 1976-1981, by Occupation.  Wages  Unemployment Occupation  R  R  *  2  R  R  2  Managerial  -.666  .443  .046  .002  N a t u r a l Sciences  -.572  .328  .273  .074  Social Sciences  -.661*  .437  .205  .042  Teachers  -.574  .666  .000  .000  Medicine & H e a l t h  -.816  .666  .008  .000  Artists  -.635  .403  .672  .451  Clerical W o r k e r s  -.565  .319  .250  .063  Sales  -.697  .486  .370  .137  Service  -.489  .239  .117  .014  Agriculture  -.457  .209  -.071  .005  Primary  -.546  .298  .144  .021  Processing  -.560  .314  .297  .088  Manufacturing  -.328  .108  .312  .098  Construction  -.538  .290  .013  .000  Transportation  -.539  .291  .123  .015  O t h e r Occupations  -.513  .263  .599*  .358  A l l Occupations  -.529  .280  .140  ** *** **  **  ***  : significant at 10%  * : significant at 5% : significant at 1%  75  **  *  .019  5.6 Summary of Findings. Once the effects of the size of the labour force and spatial factors have been removed from the gross migration data, we find that A l b e r t a and N o v a Scotia seem to attract the largest proportion of the residual migration. While wage and unemployment rates in general perform poorly in explaining migration rates,  it is not possible  to conclusively  reject  the  neoclassical hypothesis. T h e argument might be made that the factors affecting an individual's decision to migrate consist of more than just wage and unemployment rates. T h e y might include climate, political factors, and other such considerations. If this is the case a n individual m a y still maximize their utility even though the destination province has lower wage rates and higher unemployment rates than the province of origin. Nonetheless it still can be argued that the  standard notion that  wage a n d unemployment rates  are the  major determinants  of  migration patterns is highly questionable, at least in the case of C a n a d a . A stronger case can be made against the neoclassical assumption about the effects of migration. H e r e we  do not have  the d a t a problems encountered i n the  first  p a r t of the  analysis. F u r t h e r m o r e , in almost every single case the outcome was the exact opposite of the predicted  result.  Instead  of  reducing  regional  disparities  u n e m p l o y m e n t rates), migration seems to have increased them.  76  (by  equalizing  wage  and  6. ACCOUNTING FOR FAILURES OF T H E NEOCLASSICAL MIGRATION MODEL. The previous discussion has thus far raised three different kinds of doubts about the neoclassical approach to migration analysis: (1) there is considerable concern about the validity of some of the basic assumptions of neoclassical migration theory; (2) the methodologies employed in neoclassical migration models are questionable; and, (3) the above data analysis, while not disproving the neoclassical hypotheses, has at least raised some serious questions about their validity. This final chapter will try to account for some of the ostensible problems with the neoclassical scheme. Specifically, it will be argued that the major reason why the neoclassical model fails is that the neoclassical assumptions are often too simplistic and do not reflect reality. In doing so we will discuss the maximization principle, temporal considerations, social constraints, labour markets, government intervention and the notion of spatial equilibrium.  6.1 Maximization. This section of the chapter will deal with the maximization principle, more specifically with the associated concepts of utility, the ceteris paribus principle and the assumption of perfect information flows. In chapter 2 we saw that the concept of utility is a key pivot around which much of neoclassical theory revolves. In chapter 3 it was further shown that neoclassical theory contends that individuals' utilities are the reason why people move from one place to another: if for any reason it is possible to increase one's utility by migrating, then such a move will always occur. Having already discussed the theoretical aspects of utility above we now turn to the practical issue of empirically testing the utility-maximization thesis. We have seen that in neoclassical labour migration theory peoples' utilities are frequently measured in terms of wage and unemployment rates. What we have not been able to prove, however, is that these socioeconomic variables are the only significant measures of utility. Such a proof, though, is  77  necessary to demonstrate that the neoclassical model is invalid. F o r i f it cannot be proved that wage a n d u n e m p l o y m e n t rates are the only variables affecting utility, then it could be argued by a neoclassicist that people are still m a x i m i z i n g utility, but they are m a x i m i z i n g variables other t h a n wage a n d unemployment rates, for example, climate, cost of living or quality of life. T h e problem with this counterargument is that if each person measures his or her utility i n terms  of different  variables,  then,  in order  to test the hypothesis,  psychological profiles of each m i g r a n t would be needed.  case  histories a n d  T h u s , in light of the absence of  sufficient data (i.e. individual case histories) a n d the fact that the notion of utility is a crucial ingredient i n the neoclassical  theory on labour migration, the entire hypothesis  would be  untestable. T h u s the crux of the problem is that if neoclassical economic geographers reject the claim that utility c a n be measured b y wages a n d unemployment, then they are left with a theory that cannot be empirically tested. A further fundamental aspect of neoclassical labour migration theory a n d the utility maximization principle that underlies it is the so-called  "ceteris paribus" principle, or the  premise of "all other things being equal". N o t only is its existence crucial i n that without this condition the neoclassical theory would not hold, but it is also used to show that a neoclassical world is in fact a desirable one. F o r only i f all things are equal in all regions is it possible for all individuals to m a x i m i z e their utilities. If, for example, there were barriers to movement i n one  region,  then individuals living in that region  would not be able  to maximize  their  satisfaction b y m i g r a t i n g . Therefore, the argument goes, it is desirable to move the real world closer to the neoclassical one so that all individuals are able to maximize. T h u s we encounter the t e r m i n m a n y neoclassical arguments. W i t h i n the context of labour migration, we learn that i f i n a n y region wage rates are higher and unemployment rates are lower t h a n i n other regions, then, ceteris paribus, it will experience inmigration which in t u r n through the law of supply a n d demand will bring wage and unemployment  rates back to equilibrium levels.  "Ceteris paribus" c a n in this sense be interpreted as presupposing that all of the neoclassical assumptions  (perfectly  competitive  market,  perfect  78  information, maximization  of utility,  freedom of movement, etc.) apply. If a n y one of these conditions does not exist, then the theory does not hold. Neoclassicists  thus argue that i f the results of a n empirical test of a  neoclassical  hypothesis prove to be inconclusive, then initial (real life) conditions m a y not be the same as the  initial  assumptions.  equilibrium  -  which  Therefore, because  would occur only  it is  if the  desirable to bring  initial  conditions  are  the  system  equal  to  back  the  to  initial  assumptions - something is wrong with the system. O n e should design policies that bring the real world closer to a neoclassical one. A n o t h e r element of the m a x i m i z a t i o n thesis upon which the neoclassical theory of labour migration is based is the assumption that information flows freely across space. T h e r e are no n a t u r a l or artificial barriers to the flow of information. Inherent in this assumption is that all individuals have equal access and ability to process that information. If they did not, then all individuals would not be able to m a x i m i z e their utilities. T h u s at a n y given point in time each and every person has perfect knowledge. T h i s has v e r y important implications not only for the efficiency of the labour adjustment process, but also for the resulting tendency for the spatial economic system to move back towards a state of equilibrium. A s soon as a n individual receives information that he or she can make h i m or herself better off by moving to another region (taking into consideration the cost a n d the friction of distance), then they will do so. T h i s move will then be destined to a region where the net gain i n satisfaction will be m a x i m i z e d . If, however, a n y one of the assumptions about information (flow, access and ability to process) does not hold, then the neoclassical theory will not work because people make wrong decisions. T h e subject of information has been the subject of m u c h research, notably within the general field of job search theory (for some examples see Pissarides, 1975; A z a r i a d i s , Clark  &  W h i t e m a n , 1983).  Like  many  other  areas  of regional analysis  and  1981;  economic  geography, research in job search theory has also been dominated by neoclassical economic conceptions of individual behaviour and macro-equilibrium-oriented adjustment (Clark, 1986).  79  T h i s dominant school of thought recognizes the existence of imperfect information and uses it to explain inefficiencies in the allocation of labour (Holt, 1970; Phelps, 1970). Phelps' (1970) "island parable" is a typical example of a neoclassical explanation of this problem. In it the author likens the spatial economic entity to a s y s t e m of islands between which information flows are costly, i.e., workers m u s t forgo wages b y travelling to other islands to learn of the wages there. A s s u m i n g a constant labour supply, homogeneous labour with respect to the techniques of production and perfect inter-island competition, then, if for some reason relative wages fall on the local island, the worker will be induced to search for a better wage offer, either locally or on some other island. Because searching costs money (in terms of lost wages), there is a constraint on the number of searches and the geographical pattern of search (Clark, 1986). N o worker could afford to visit all islands, which results in few workers reaching peripheral islands. H o w e v e r , as the existence of a n inter-island equilibrium depends on the efficiency of workers' searches (which in turn depends on the flow of a n d efficiency with which workers process the information), a limited number of searches and a n inefficient information transfer  will  lead  to  an  inefficient  labour  market  adjustment  and  thus  a  persistent  disequilibrium. T h e neoclassical argument concludes that workers' search efficiency should therefore be improved by training and education, while the flow of information should be improved b y some government sponsored information gathering and dissemination agency. Holt (1970), for example,  argues  that  a  national computer  m a t c h i n g network  could greatly  improve  the  efficiency of the labour adjustment process. C l a r k (1986) maintains that this is in fact the logic behind the C a n a d i a n federal labour m a r k e t information system and the U n i t e d States job search p r o g r a m . T h e r e are m a n y examples within the geographic literature of alternative views on the subject  of job search theory  a n d the  spatial inefficiency  of labour markets. W h i l e m a n y  economists believe that information is distinctly aspatial (for some examples see  Pissarides,  1985 a n d E v e r s & V a n der V e e n , 1985), geographers have argued that information on job and  80  wage offers  is in fact systematically  differentiation of the economy  (Clark,  dispersed  among regions  as  a result of the  1986). Greenwood (1981), for example,  spatial  argues  that  empirical evidence suggests that not only are workers' searches subject to a friction factor of distance, as the Phelps island parable suggests, but also that migrants tend to have specific search paths which are directly linked with their origin. T h i s is in accordance with the findings of this thesis. It was  shown that there is a wide range among provinces of origin in the  sensitivity of m i g r a n t s to the influence of distance a n d intervening opportunities. E v e n after these influences  are removed, distinct interaction patterns can still be observed. Recall, for  example, the tendency for migrants from a M a r i t i m e province to stay within the M a r i t i m e s . One of the reasons for this observation could be that M a r i t i m e r s limit their area of job search to other M a r i t i m e provinces. T h e importance of imperfect information and its impact on the spatial economic s y s t e m is  shown  by M a i e r  (1985). H e recognizes  that the  standard neoclassical  job search  and  migration models based on the assumption of perfect information are too restrictive to permit insights into the migration decision process. M a n y hypotheses derived from these assumptions in fact  contradict empirical observations.  Once the  assumption  of perfect  information is  dropped the task of modelling job search behaviour becomes more complex. H e goes on to argue that under the assumption of imperfect information, strategies which seem absurd or suboptimal under conditions of perfect information c a n actually be preferable. H e constructs a model  which  distribution.  analyses job  search  T h e information is  strategies based  imperfect  and  on information about  accumulated  through the  the  wage  search  rate  process.  Individuals "buy" information about wage offers in other regions. T h e decision to migrate thus depends on four key variables: each person's knowledge about the wage offer distribution; the cost of searching for the information; the actual cost of the information; and the cost of m i g r a t i n g to another region. Although the model is essentially  neoclassical  with modified  assumptions, M a i e r argues that it can explain m a n y phenomena used in polarization theory,  81  most  notably  effects  of  cumulative  causation  caused  by  past  migration.  This  directly  contradicts the neoclassical hypothesis on the effects of migration. While at first glance M a i e r ' s model seems to offer a relatively elegant solution to the problem of imperfect information, it still does not get around some of the other fundamental problems  of  neoclassical  migration  models.  In  chapter  3  it  was  mentioned  that  most  contemporary migration models do not consider time as a variable, yet it has been shown that time can be a vital factor (Clark & B a l l a r d , 1980;  a more detailed discussion of temporal  considerations will follow in a subsequent section of this chapter). A further drawback of his model is that wage offers constitute the sole source of information on the basis of which a potential m i g r a n t will base his or her decision to move. F i n a l l y , M a i e r offers no empirical evidence to support his contentions. C u r r y (1985) suggests a different (non-neoclassical)  approach to handling the problem  of information flows in determining migration. H e strongly questions the standard neoclassical notions on how the spatial economy is supposed to work. F u r t h e r m o r e , he argues that past attempts at ameliorating spatial inefficiencies in the operation of labour m a r k e t s have more often t h a n not produced the opposite of the desired results. T h e reason for this, he argues, is that workers do not exploit opportunities in a n o p t i m u m m a n n e r because they are in m a n y cases ignorant of them. T h i s ignorance can drastically affect the economic landscape. Because information is acquired locally, and there are large regional differences i n the quantity and quality of information available (which in t u r n is a result of the spatial differentiation of the economy),  each  region  and  occupation  has  unique  expectations  and  specific  degrees  of  sensitivity and selectivity with regards to jobs and wage offers. Therefore, because each region will react differently to changes in wages or other variables, central policies cannot work and in fact often produce adverse results.  Decentralized policy instruments,  specifically  geared  towards individual regions, would on the other h a n d serve to decrease inefficiencies  in the  labour m a r k e t .  82  A further alternative approach to dealing with information is that of "indeterminate information"  (Clark,  1986),  as  opposed  to  imperfect  information.  It  is  argued  information is indeed indeterminate, i.e., it is heterogeneous, incomplete, and/or upon other postulates,  factors, lead  then  the  likelihood that information will,  to a n efficient  as  the  reallocation of labour would appear  that  contingent  neoclassical  to be  if  theory  remote.  Clark  maintains that in the extreme case indeterminate information might mead to a total collapse of the spatial labour m a r k e t . Clark  recognizes,  however,  that  not  all circumstances  need  be  characterized  by  indeterminate information. In some cases well defined, albeit spatially contingent information channels do exist. O n e example is the rather well developed and very reliable information network between the upper midwest of the U n i t e d States and California, which is based on previous migrants' experiences and growth trends in the two areas. In most cases, however, reliable information channels do not exist. F o r example, empirical evidence suggests that as a result of their inability to develop reliable information channels about employment prospects in other parts of the country, m a n y midwest auto workers preferred to r e m a i n unemployed d u r i n g the recession rather than risking their r e m a i n i n g assets (Clark, 1986). T h i s i n t u r n suggests that the influence of information is far more complex than Phelps made it out to be. C l a r k argues that it is not possible to circumvent the existence of uncertainty by simply putting a price tag on information. Neoclassicists  frequently  contend  that  while  indeterminacy  of information is  well  within the realm of possibilities, its source is government policy (intervention), rather than problems with the  internal logic of the  neoclassical  model (Clark,  1986). Note  that  the  implication of this, as has previously been argued and will be argued i n subsequent sections, is for policy m a k e r s to change reality to suit the neoclassical model, as opposed to respecifying the model to accomodate reality. A typical example of this philosophy is the notion of rational expectations based  on available  information (Lucas,  1981). L u c a s argues  that  while  all  individuals essentially m a k e correct (rational) decisions, spatial disequilibrium persists because  83  of misinformation about other regions originating from government policy. In addition, local policies such as unemployment benefits  and m i n i m u m wages prevent the labour allocation  process from working efficiently. A final alternative approach to job search theory that is closely linked to the notion of indeterminate information are contract models (Clark, 1986). W i t h i n these models information is believed to be inherently indeterminate for two reasons: first, m a n y events can not be anticipated, and second, it is impossible to completely rely on a n unanticipated event, no matter how high the likelihood of its occurrence. Consequently there will always be a degree of uncertainty. In order to reduce the level of uncertainty and to protect the worker (and the firm)  from  unanticipated events, contracts  are d r a w n between employers  and  employees  (Clark, 1986). These can be of a n explicit nature (union - labour) or implicit (company policies). A l t h o u g h obviously not every worker has a contract (such as the self-employed), contracts will in  the  aggregate  because  hinder short t e r m adjustments  of labour to changing m a r k e t conditions  of their long t e r m rigidity. B o t h workers and management  will not  immediately  renegotiate contracts in response to fluctuations in the space economy, rather they will gather as m u c h information as possible  about both inter a n d intra-regional differences  until  the  contract expires. In  s u m m a r y , utility maximization, the ceteris paribus principle and the neoclassical  assumption labour information flows are all conditions that have been highly criticized, for the most p a r t because they are never met in reality. If this is the case (in fact if only one of the conditions does not hold), then the neoclassical hypotheses on labour migration will not hold.  6.2 Temporal Considerations. It temporal  has  been  aspects  argued repeatedly  of the  that  migration process.  neoclassical Adjustments  migration models are  usually  largely  assumed  to  ignore occur  instantaneously. C l a r k (1982) has argued that the structure of the neoclassical model itself cannot deal with the dynamics of migration, despite the fact that migration is perceived as a  84  flow - a t e r m that in itself implies change over time. Because temporal  factors,  neoclassical  models  thus  essentially  of the failure to consider  analyze  migration  in  terms  of  comparative statics, rather than dynamics. B u t s i m p l y c o m p a r i n g the economy between one point i n time to another could lead to the failure to recognize migration cycles and to the overor underestimation of the sensitivity because  of migrants to origin and destination  of the neglect of time lags in the decision-making process. C l a r k  characteristics  (1982), C l a r k &  B a l l a r d (1979) and Greenwood (1970, 1981) have proposed models that do incorporate time as a variable. In order to illustrate the significance of time we will review some literature that does account for the temporal dimension. Greenwood (1970) analyzed lagged responses in the decision to migrate. H e  argues  that migration from one place to another increases geometrically. T h e reason for this is that the more people migrate from i to j , the more information is available: friends and family who have m o v e d to j will send back information about the success of their move. T h u s the flow of migrants f r o m  i to j during  a particular time period is not only  a function of current  socioeconomic indicators, but also related to the cumulative number of migrants that have moved  from  i to j in the  previous  periods.  Consequently parameter estimates of  most  socioeconomic variables tend to obscure the true relationship with migration because they also indirectly influence migration through their effect on past migrants. B u t these past migrants will in t u r n affect future migration by relating their experiences, for example. T h i s hypothesis was  tested on inter-state  migration in the  U n i t e d States between  1955  and  1960  and  compared to a s t a n d a r d model not considering past migration as a n independent variable. T h e results of the analysis showed that the explanatory power of the model was greatly increased when incorporating time (the average r  increased from .77 to .93), while at the same time  individual (socioeconomic) variables showed a decline in significance. Greenwood atemporal  (1981)  approaches  to  puts  forth a  further  migration modelling,  argument  concerning the  p a r t i c u l a r l y with  respect  problems to  with  employment  opportunities. T h e d i l e m m a is that migration m u s t be m e a s u r e d over some finite time interval.  85  D u r i n g this time interval, however, migration is itself influencing the observed growth of employment opportunities. T h i s could lead to a bias in the parameter estimates of single equation, multiple regression models of migration over one extended time period. C l a r k (1982) maintains that neoclassical economists present labour migration as a static process. T h e question for neoclassicists is how to allocate labour between regions given the current labour supply so that spatial equilibrium m a y be reached. T h u s the issue is allocative efficiency from one point in time to the next. T h e two points in time are analyzed in terms of comparative statics, not by modelling the process of adjustment from one time period to the other (this is one of the reasons that net migration flows are generally preferred to gross flows in neoclassical models; while net migration fits the comparative statics framework, the adjustment properties of gross migration do not (Clark,  1982)). H o w e v e r , while it is  possible to evaluate the effects of migration on m a r g i n a l changes in independent variables, typical neoclassical models employing a comparative statics framework (such as the popular L o w r e y model) cannot analyse the temporal sequence of adjustment. C l a r k & B a l l a r d (1979) have shown that gross flows of both in- and outmigration are indeed quite  sensitive  unemployment  rates).  to  short-run fluctuations  They  conclude  that  in economic  factors  labour' migration,  like  (including wage a n d many  other  regional  processes, is a cyclical phenomenon. T h e implication of this is that as the economy moves through a sequence of fluctuations, migration patterns will also v a r y in a similar fashion. G i v e n that these temporal fluctuations can be quite significant, macro-adjustment models using census data compiled at five year intervals will miss the true pattern of migration.  6.3 Social Constraints to Labour Migration. One of the assumptions of the basic neoclassical hypothesis is that people are free to move anywhere a n d anytime. It has been shown, however, that i n reality there are m a n y barriers to migration. In the data analysis section, for example, it was argued that only few people migrated to a n d from Quebec because of social and cultural (language) barriers. O t h e r  86  impediments are family ties and, although more of a short run hindrance, job contracts (see Clark, 1986). Housing is considered to be a further important barrier to labour mobility (Cullingworth, 1969; Johnson et al, 1975). Although there is a general agreement on the connection between housing and labour mobility, the nature of the relationship has been highly debated. Housing is in itself a complex phenomenon when regional differences, preferences of various social classes and their accessibility to housing finance are considered (Johnson et al, 1975). The white collar occupational groups, for example, will, because of higher wages, have easier access to owned housing  and  mortgages than the blue collar groups. Thus the  availability and type of housing is in turn related to other socioeconomic variables. The most popular view, however, is that workers owning houses show the highest mobility rates and tend to migrate further. Publicly owned and rented housing is generally associated with much lower levels of mobility and shorter moves (Cullingworth, 1969).  6.4 Labour Markets. A further argument for barriers to labour migration is provided by the dual labour market theory (Sloane, 1985). The basic version of the dual labour market theory suggests that there are two distinct sectors: a primary market where "good" jobs and majority workers predominate, and a secondary market where "bad" jobs and minority workers are dominant. While Sloane argues that the existence of these two markets hinders inter-market mobility, it can also be argued that it hinders interregional mobility. In contrast to the primary labour market, wages are generally low, unemployment high, and the often hazardous jobs in the secondary labour market are mostly occupied by minority groups (blacks, hispanics, etc.). If, for example, a country has two regions that traditionally offer most employment opportunities in the secondary labour market (such as the southern United States), then a move to a region other than those two would thus often also involve moving up the occupational hierarchy, i.e., a promotion into the primary labour market. Empirical studies have shown, however, that, because of racial discrimination, lack of education and training and other factors this is  87  extremely difficult (Sloane, 1985). Therefore m i n o r i t y groups and workers in the secondary labour m a r k e t in general are faced with fewer choices of destinations when deciding to move. McKay  & Whitelaw's  (1977) study  of the  role of large  private and  government  organizations in generating interregional migration is one example of the dual labour m a r k e t approach to constrained choices of destinations w i t h i n the spatial labour m a r k e t . T h e y point out that there are a multitude of formal and unwritten rules of entry into m a n y occupations imposed b y both employers and trade unions. It is argued that occupations in the p r i m a r y labour m a r k e t are more mobile due to the fact that  an increasingly large proportion of  interregional moves are a result of company policy, i.e., a transfer from b r a n c h to another (this in m a n y cases also applies to government employees, in particular teachers and health workers). Individuals in the secondary labour m a r k e t , on the other h a n d , were found to be considerably less mobile, in part because local trade unions make entry into the job m a r k e t extremely difficult for newly arrived migrants.  6.5 Government Intervention. A s was shown in chapter 2, neoclassicists generally argue for a "laissez faire" type of approach to public policy. T h i s implies that, because n a t u r a l forces exist that drive the spatial economic system back to equilibrium, governments should desist from enacting policies that serve to reduce regional disparities. T h e neoclassical hypothesis on labour migration assumes that a perfectly competitive  m a r k e t exists: there  are no outside  influences  on migration  patterns. A number of recent studies have shown, however, that government action such as fiscal policy does in fact have a pronounced effect on m i g r a t i o n patterns (Riew, 1975; K o s i n s k i , 1981; Peek & Standing, 1982; W i n e r & G a u t h i e r , 1982; C l a r k , 1983). T h u s migration is no longer just a function of individuals' choices and motivations, as it is assumed i n neoclassical or " h u m a n capital" type of models, rather a highly significant proportion of interregional migration is directly and indirectly caused by government policies.  88  One  of the best examples of a federal p r o g r a m directly affecting migration is to be  found in C a n a d a (Kosinski, 1981). T h e D e p a r t m e n t of E m p l o y m e n t and Immigration (DEI) administers a number of programs, the most important of which is the C a n a d a M a n p o w e r Mobility P r o g r a m ( C M M P ) .  T h e following grants  are made  available under this p r o g r a m  (Kosinski, 1981): - exploratory grants to search for jobs elsewhere; - relocation grants for workers and their families; - special travel grants to obtain manpower services not offered locally; - travel grants for temporary employment; - travel grants to temporary employment; and - travel grants to attend training courses offered under the C a n a d a training p r o g r a m . Although boundaries,  their  only  some  of  the  grants  provide  impact is nevertheless quite  funds  significant.  for  moves  T a b l e 6.4.1  across  provincial  shows the  size of  migration flows generated b y C M M P grants between 1966 and 1979 and their share of total interprovincial migration in C a n a d a . W h e r e a s overall the impact is not v e r y significant  (the  range is from 1.6% to 15.3% of total interprovincial migration), its importance does differ quite considerably between provinces of origin (see table 6.4.2). Between 1976 and 1978 34.7% of all outmigration f r o m Newfoundland was generated (20%)  by C M M P grants, followed b y Quebec  a n d Ontario (19.4%). T h e lowest share was in A l b e r t a (1.2%) and in Prince E d w a r d  Island (1.6%). D a t a for the destinations of C M M P  migrants  were not available. A l t h o u g h  C M M P is the most important p r o g r a m affecting labour mobility, it is not the only one. O t h e r s include the C a n a d a M a n p o w e r Consultive Service, the L o c a l E m p l o y m e n t Assistance P r o g r a m , the C a n a d a W o r k s P r o g r a m and the Opportunities for Y o u t h P r o g r a m (Kosinski, 1981). W i n e r & G a u t h i e r (1982) analyzed the indirect impact of the C a n a d i a n fiscal structure on interprovincial migration (in terms of both in- and outmigration) between 1968 a n d 1977). The  independent  variables  were  provincial changes  in  the  total  sum  of  unemployment  insurance benefits paid (Ul), unconditional grants ( G U : comprised of the s u m of equalization  89  Table 6.5.1  Table 3. CMMP generated migration as compared to the total internal migration in Canada, 1966-1976. Financial year  1 Number of relocation grants  1966-67 1967-68 1968-69 1969-70 1970-71 1971-72 1972-73 1973-74 1974-75  2,138 5,757 6,591 7,460 6,382 9,026 10,653 11,019 11,361 12,786 20,338 10,206 12,302  1975-76 1976-77 1977-78 1978-79 i Notes: ; '  a  .  2  3 Estimate of the total Total interprovincial flow supported by CMMP^ migration in Canada 6,400 17,300 19,800 22,400 19,100 • 27,100 32,000 33,000 34,100 38,400 61,000 30,600 36,900  406,000 382,000 365,000 414,000 404,000 399,000 390,000 436,000 417,000 375,000 398,000 405,000 n.a.  4 Proportion of CMMP migration 1.6 4.5 5.4 5.4 4.7 6.8 8.2 7.6 8.2 10.2 15.3 7.6  -  a Including 1 287 grants and 851 loans; b Based on an assumption that one worker supports two dependents (see CMCS program). Assumption that one-third are singles and two-thirds support three dependents would yield similar results; c Based on assumption that all CMMP supported moves are interprovincial.  Table 6.5.2 Table 4. CMMP generated migrations as compared to the total internal migration by provinces, 1976-77 and 1977-78. —  -- • •  Estimate of total flows by provinces  Newfoundland • 2,821 42 Prince Edward Island Nova Scotia 1,162 New Brunswick 1,378 Quebec 8,425 Ontario 12,790 Manitoba 490 Saskatchewan 354 Alberta 485 British Columbia 2,497 Yukon & the N.W. Territories 100  8,500 120 3,500 4,100 25,300 38,400 1,500 1,100 1,500 7,500 300  24,500 7,700 46,400 36,800 126,700 197,600 64,600 49,500 ' 122,300 112,300 13,300  34.7. 1.6 7.5 11.1 20.0 19.4 2.3 2.2 1.2 6.7 2.3  Total  91,600  802,800  11.4  Provinces  Notes  30,544 a b  2  4 Percentage of CMMP generated migration as compared to the total flow  3 Total interprovincial outmigration by provinces 1976-77 and 1977-78  1 Relocation grants authorized in 1976-77 & 1977-78 by provinces  Based on an assumption that one worker supports two dependents; Based on an assumption that all CMMP supported moves are interprovincial  Source: Kosinski (1981) 90  payments, subsidies, adjustment grants, and revenue guaranteed by the federal government to the provinces) a n d n a t u r a l resource revenues (NRR). A l l dependent variables were measured in terms of changes from 1971 to 1977. T h e model was tested on high, middle a n d low income groups of individuals. It was found that the fiscal structure indeed did have a significant impact on both in- and outmigration, although it varied systematically with the geographical composition of the migration flow and was generally more significant (as is intuitively to be expected) in the lower income class. T h e fiscal variables performed considerably better on outmigration from the A t l a n t i c provinces and on inmigration to A l b e r t a and B r i t i s h Columbia. Recall that in the d a t a analysis (chapter 5) it was found that M a r i t i m e r s tended to either  migrate  to  another  Atlantic province  or  move  to  Alberta  or B r i t i s h  Columbia.  F u r t h e r m o r e , A l b e r t a was b y far the greatest pole of attraction for migrants from all C a n a d a . C o m p a r e these findings to table 6.4.3, which shows W i n e r & Gauthier's (1982) results for outmigration from the Atlantic provinces in the lower income class. Changes i n the total s u m of unemployment insurenace benefits  paid out h a d a positive influence  on i n t r a - M a r i t i m e  moves, whereas they tended to be negative for other destinations (with only few  exceptions).  F o r example, outmigration from Newfoundland to N e w B r u n s w i c k was 52.9% higher t h a n it would have been in the absence  of any changes  to the unemployment insurence  system.  Unconditional grants, on the other hand, tended to have a negative impact on outmigration, i.e., induce potential movers to stay, although the impact was generally not as pronounced as for unemployment insurance benefits. Changes in n a t u r a l resource revenues h a d virtually no impact on outmigration save  for the  destinations  of A l b e r t a ,  Saskatchewan  and  British  C o l u m b i a . F o r all three A t l a n t i c provinces migration to A l b e r t a was about 63% higher than it would have been h a d A l b e r t a n n a t u r a l resource revenues remained at the 1971 level. T h i s variables  also  h a d the  most  important impact on inmigration from  other, n o n - M a r i t i m e  provinces, for both A l b e r t a a n d B r i t i s h Columbia. These results v e r y concur with our findings in chapter 5 in that they in m a n y w a y s fit the description of the residual migration patterns shown in tables 5.3.2 to 5.3.17.  91  Table 6.5.3 T h e Effects of Selected Changes i n F i s c a l Structure o n Out-Migration Rates F r o m the Atlantic P r o v i n c e s Including Intra-Atlantic M o v e s , L o w e r Income C l a s s , 1968-1977.  Origin  Destination  Ul  GU  NRR  0.095 0.041  0.000 0.000  -0.045 0.109 -0.045 -0.045  0.000 0.000 0.632  British Columbia  0.385 0.529 0.021 -0.091 -0.131 0.116  Newfoundland New Brunswick Quebec Ontario Manitoba Saskatchewan Alberta British Columbia  0.438 0.555 0.459 0.038 -0.076 -0.189 -0.116 0.134  -0.083 -0.044 -0.063 -0.125 0.017 -0.228 -0.125 -0.125  0.000 0.000 0.000 0.000 0.000 0.592 0.631 0.106  Newfoundland N o v a Scotia Quebec Ontario Manitoba Saskatchewan Alberta British Columbia  0.325 0.297 0.344 -0.043 -0.149 -0.253 -0.186 0.045  -0.037 0.054 -0.017 -0.081 0.068 -0.189 -0.081 -0.081  0.000 0.000 0.000 0.000 0.000 0.591 0.630 0.105  Newfoundland N o v a Scotia New Brunswick Ontario Manitoba Alberta  0.106  N o v a Scotia  New Brunswick  Source: W i n e r & G a u t h i e r (1982)  92  The  above  empirical evidence  directly contradicts the  contention that interregional migration patterns  "conservative"  (neoclassical)  are dominated b y long r u n trends which  cannot be directly manipulated b y government policy (Clark, 1983). G o v e r n m e n t action, by providing for the existence of the neoclassical  assumptions,  can only indirectly  influence  migration. A s we have seen, however, government policy indeed can have quite a profound direct influence on migration, not only in the long r u n , but also in the short r u n . In the long run  changes  to the  social welfare  system,  such as regional increases  or decreases in the  amount of u n e m p l o y m e n t insurance benefits paid out, will induce or inhibit migration. O n the other h a n d , manpower travel grants c a n induce a worker to search for a job i n another region in the short r u n , which he or she could not afford to do in the absence of such policy.  6.6 Spatial E q u i l i b r i u m . The  neoclassical notion that the p r i m a r y effect of labour migration is to lead the spatial  economic s y s t e m back to a state of equilibrium has been strongly questioned, even b y some neoclassical theorists (for an example see M a i e r , 1985). T h e consensus seems to be that rather than leading to equilibrium, labour migration has a cumulative causatory effect. H o w e v e r , there are also m a n y other aspects of the consequences of migration not normalty considered by neoclassicists.  This  section  of the  chapter  will  concentrate  first  on  alternative  theories  advocating cumulative causation, and then proceed to look at other alternative notions about the effects of migration. The  hypothesis  causation, was  that  interregional migration promotes  put forward as e a r l y as  1957  by Myrdal.  polarization, or cumulative  H i s argument was  that  since  migration is a selective phenomenon, it is usually the most productive and educated people that are attracted a w a y from declining regions. T h u s , because the inflow of skilled workers increases the attractivity of growth regions a n d the outflow of skilled workers from the poorer regions decreases their attractivity, cumulative causation will result. A similar argument is made b y Webber (1972), when he suggests that where agglomeration economies are strong,  93  skilled labour is more likely to be attracted to growth centres because of the wider range in wage differentials  that are likely to exist there. K a l d o r (1970) maintained that while  the  neoclassical model predicts equilibrium i n the long r u n , in reality regional economic disparities are  generally  reinforced and  argument was later extended  that  divergence  rather  than  convergence  is  the  rule.  His  and interpreted as the "Verdoorn effect" (Clark, 1983). T h e  Verdoorn effect basically implies that regions are able to m a i n t a i n their dominant positions through increasing returns to scale. G i v e n that there are increasing returns to scale in high wage regions, inmigration from low wage areas reinforces the dominance of those regions. Clark  & Ballard  (1981) tested the  neoclassical  assumptions  about  the  effects  of  migration on U n i t e d States data in a short t e r m time-series model, taking into consideration both the demand a n d the supply of labour. It was found that the effect of migration on wages was mixed: while in some cases it increased them, in others it caused them to decline or h a d no effect at all. While it is commonly thought that migration in one w a y or another affect wage rates, it is frequently not realized that migration also results in redistributions of income, both in the region of origin a n d the region of destination (Greenwood, 1981). T h i s implies that in both areas some individuals are made better off, while others find themselves in a worse situation. F o r example, in a depressed region outmigration in the short r u n will result in less competition for the few job opportunities that do exist, so that people who would otherwise be unemployed now e a r n those wages that the migrants formerly earned. O n the other h a n d , older workers in the receiving region will find it more difficult to gain employment as y o u n g immigrants enter the local job m a r k e t . A l s o , if outmigration leads to a significant decline in the population base of a depressed region, then the average tax burden of the r e m a i n i n g population could increase or, because of the smaller tax base and the declining economy of scale, the government might have to practice constraint and cut back on existing programs, thereby reducing overall social welfare.  94  F r o m the above discussion it can be seen that m a n y authors believe, and furthermore back up such beliefs with empirical evidence, that the standard neoclassical assumptions and determinants of labour migration do not hold. H o w e v e r , it cannot be said that migrants, particularly those from depressed regions, do not react to economic opportunities. Rather, the w a y i n which they react to those variables is different: there is little evidence that migrants maximize their utilities in terms of economic variables, they rarely, if ever, have equal and perfect information about t h e m , and they do not always have the freedom to move to the destination of their choice.  95  7.SUMMARY AND CONCLUSION. The  task of this thesis was  to empirically test the neoclassical  theory of labour  migration in light of C a n a d a ' s experience d u r i n g the period 1976-1981. I n c a r r y i n g out this task, it was argued in chapter 2  that m u c h of contemporary economic geography stems from  neoclassical economic theory, and, specifically the concepts of utility and resource allocation. The six major characteristics of neoclassical theory were then outlined and their applications illustrated using some examples of geographic models. C h a p t e r 3 linked the broader neoclassical theory to labour migration. It was how neoclassical principles and assumptions  shown  are applied in formulating the two standard  neoclassical migration models: the micro- a n d macro-adjustment approaches. F u r t h e r m o r e , it was argued that two central hypotheses stem from these two neoclassical approaches: first, that labour will flow from regions of low wages and high unemployment to areas of high wages and low unemployment; and second, that the effect of this migration will be to reduce interregional differences in wage and u n e m p l o y m e n t rates. F i n a l l y , it was argued that despite a growing body of literature critical of the two approaches and neoclassical assumptions and hypotheses, neoclassical migration modelling is still v e r y m u c h alive. Chapter neoclassical  4  presented  hypotheses.  the  Chapter  data  and  methodology  5 interpreted the  results  employed of the  in  testing  analysis  the  two  arguing that  C a n a d i a n patterns of labour migration between 1976 a n d 1981, as well as provincial changes in  wage  and u n e m p l o y m e n t rates,  do not fit either one  of the  neoclassical  hypotheses.  Specifically, there is no uniformity in the direction of the flow of migrants in relation to interprovincial  differences  in wage  and unemployment  rates.  Furthermore,  rather than  reducing regional differences in those variables, labour migration seems to have increased them. While the findings of this thesis do not entirely justify a rejection of the hypotheses (in p a r t because of d a t a problems), they do raise doubts as to their validity. F i n a l l y , chapter 6 attempted to account for the failures of the neoclassical model. It was  argued that the m a i n reason for its failure are the overly simplistic and unrealistic  96  assumptions of neoclassicism. The real world is far more complex than the neoclassical one. All other things are not always equal. A n additional oversimplifying assumption is that of the utility-maximizing individual and, by extension, the argument that all individuals behave and act in the same way. It is usually recognized by neoclassicists themselves that wage and unemployment rates are not the only variables that people maximize. Even so, it must be strongly questioned whether it is at all possible to measure utility. If this is not the case, then, because they are based on the assumption of the utility-maximizing individual, it is also impossible to empirically test the neoclassical hypotheses about labour migration. It is perhaps time to rethink migration theory. Although much work has been done on individual aspects of the migration process, a comprehensive model - one that is flexible, less rigid, more realistic in its assumptions and that encompasses the entire migration process has yet to be formulated. Thus, future research should focus more closely on the causes and effects of migration. While it has been established that migrants are sensitive to regional variations in socioeconomic variables and that migration does have an effect on the spatial economy, it is still unclear how the actual process works. Before a comprehensive alternative theory of labour migration can be put forward, it is thus necessary to learn more about individual decision-making behaviour and the dynamics of the adjustment of socioeconomic variables to migration (and vice versa). Clearly,  my  thesis  has  not  provided  that  comprehensive  alternative  theory.  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