mum... M . I: . . . -35:33}szTIA-73113253219w. ; . - MIGRATION SELECTIVITY BY AGE. SEX AND COLOR, AND THE RELATIONSHIP. BETWEEN THESE PATTERNS OF SELECT IVITY AND METROPOLITAN AREA CHARACTERISTICS. MICHIGAN STANDARD METROPOLITAN STATISTICAL AREAS Thesis for the Degree of M. A. MICHIGAN STATE UNIVERSITY UTAKO OZAKI 197 l W P. “MM; 1’ . Uchmty IIIIIIIIZIIIIIUIINIIIIIIIIIU{MW .: ABSTRACT MIGRATION SELECTIVITY BY AGE, SEX AND COLOR, AND THE RELATIONSHIP BETWEEN THESE PATTERNS OF SELECTIVITY AND METROPOLITAN AREA CHARACTERISTICS, MICHIGAN STANDARD METROPOLITAN STATISTICAL AREAS by Utako Ozaki In the first part of this study the migration patterns of the Standard MetrOpolitan Statistical Areas of Michigan are analyzed by age, sex, and color. Net migration between I950 and 1960, and between 1955 and 1960, and in- and out-migration between 1955 and T960 were the data used. It was fOund that certain Standard Metro- politan Statistical Areas (SMASA‘s) shared similar migration patterns; others were fbund to have unique migration patterns. Four groups comprising the ten SMSA's in Michigan were fbrmed based on the simi- lar or unique migration patterns exhibited. The second part of this study considers why the migration patterns of SMSA's are similar or unique. The following hypothesis was examined: that SMSA's having similar social and economic char- acteristics will exhibit similar migration patterns: those having unique characteristics will exhibit unique migration patterns. It was found that migration patterns of the communities were related to selected social and economic characteristics of the communities. These characteristics were educational attainment, the proportions employed in manufacturing and in white collar occupations. the pro- portions of establishments of nondurable goods industries and of durable goods industries. and the income of families. MIGRATION SELECTIVITY BY AGE, SEX AND COLOR, AND THE RELATIONSHIP BETWEEN THESE PATTERNS OF SELECTIVITY AND METROPOLITAN AREA CHARACTERISTICS, MICHIGAN STANDARD METROPOLITAN STATISTICAL AREAS By Utako Ozaki A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF ARTS Department of Sociology 1971 ACKNOWLEDGEMENTS It is a great pleasure to acknowledge my debt to the members of my guidance committee, Dr. J. Allan Beegle. Chair- man, Dr. Kevin D. Kelly, and Dr. Richard D. Rodefeld, for their interest in the development of demography and their readiness to advise and assist. My sincere acknowledgement is particularly due to my advisor, Dr. J. Allan Beegle. Without his guidance and en- couragement this thesis could not have been completed. I am indebted also to him fbr providing much useful data. I wish to thank my old friends, Dr. and Mrs. John F. Tinker, fbr their cooperation in correcting the thesis. ii TABLE OF CONTENTS Chapter I. INTRODUCTION ...................... The Aim of the Thesis and Its Organization ..... Some Studies of Migration Selectivity by Age, Sex, and Color ................ Some Studies of Migration Patterns and the Characteristics of Communities .......... Sources of Data and Methods of Analysis ...... . II. AN ANALYSIS CE NET MIGRATION: 1950-60 AND 1955-60, AND IN- AND OUT-MIGRATION: 1955-60 BY AGE, SEX, AND COLOR ...................... Net Migration by Age: 1950-60 and 1955-60 . . Net Migration by Sex: 1950-60 and 1955-60 ..... Net Migration by Age-Sex Composition: 1950-60 and I955-60 ................ Net Migration by Age-Sex-Color Composition: 1950-60 ............... . ...... In-migration and Out-migration by Age: 1955-60. . . In-migration and Out-migration by Sex: l955-60. . . In-migration and Out-migration by Age-Sex Composition: 1955-60 ........ g ..... III. THE RELATIONSHIP BETWEEN MIGRATION PATTERNS AND THE CHARACTERISTICS OF THE SMSA'S OF MICHIGAN. . . LITERATURE CITED ........................ APPENDIX ....................... IV. SUMMARY AND CONCLUSIONS ................. Page 12 I4 16 21 24 28 32 36 37 46 50 53 LIST OF APPENDIX TABLES Table Page 1. Net migration and p0puIation of Michigan SMSA's by age groups: I950-60 . . . . . . . . ........ 53 2. Per cent distribution of residence in 1955 for Michigan SMSA's: I960 ........... . ..... 54 3. Per cent distribution of residence in 1955 of white population for Michigan SMSA's: I955-I960. . . . 55 4. Per cent distribution of residence in 1955 of non-white p0puIation for Michigan SMSA's: 1955-1960. . 56 5. Number and proportion of in-migrants to and of out-migrants from Michigan SMSA's by distance migrated: 1955-1960 ...................... . 57 6. Net migration rate of Michigan SMSA's by age groups and sex: I955-1960 .................. 58 7. Net migration rate of Michigan SMSA's by age: 1950-1960. 59 8a. Male net migration and male population of Michigan SMSA's by age groups: 1950-1960 ............. . . 60 8b. Female net migration and female p0puIation of Michigan SMSA's by age groups: 1950-1960. . ........ . . 61 9. Net migration rate of Michigan SMSA's by age and sex: I950-1960 ..................... . . 62 10. Net migration of white population for seven SMSA's of Michigan by age groups and sex: 1950-1960. . . . . . . 64 11. Net migration of non-white population for seven SMSA's of Michigan by age groups and sex: 1950-1960 . . . . . 65 12. Net migration rate of male population for seven SMSA's of Michigan by age and color: 1950-1960 ..... . . . 67 I3. Net migration rate of female population for seven SMSA's of Michigan by age and color: 1950-1960 ..... . . . 69 iv List of Appendix Tables (cont.) Table I4. 15. 16. 17. Number and proportion of in-migrants to and of out- migrants from Michigan SMSA's by age groups: I955-I960 . . . Sex-ratio of in-migrants to and of out-migrants from Michigan SMSA's by age groups: 1955-1960 . . . . . . . Characteristics of Michigan SMSA's: 1960 . . . . . . . . Per cent distribution of occupation groups for Michigan SMSA's by sex: I960 .................. Page 71 72 73 77 Map I. Figure I. 2. 3. LIST OF ILLUSTRATIONS Standard MetropoIitan Statistical Area of Michigan . . . Net migration of male population for Michigan SMSA's: I950-60 and 1955-60 ................. . Net migration of female p0puIation for Michigan SMSA's: 1950-60 and 1955-60 .................. Per cent distribution of in- and out-migrants by age 1955-60 9 0 groups fbr Michigan SMSA's: vi Page 26 27 35 CHAPTER I INTRODUCTION The Aim of the Thesis and Its Organization: Migration is a basic component in the demographic equation. Together with mortality and fertility, migration plays a role in the rate of p0pu1ation growth as well as population composition. There can be little doubt that spatial mobility has played an important rule in the history of man. Today with economic and technological progress. the rate of migration has greatly increased. The automo- bile. airplane. and other means of transportation. of course. have facilitated such movement. It is known that spatial mobility in the United States is greater than in any other nation. An American who lives in the same house all of his-life would be considered unique. In fact, about one-quarter of the population of the United States does not live in the state in which they were born. And every year one out of five persons changes his residence. However. an average American changes his place of residence as many as ten times during his lifetime.1 1William Peterson, Population (New York: The Macmillan Company, 1961), p. 169. However, in this spatially mobile nation, a great majority has always moved short distances, that is, within a single county. In 1950, persons who were living in a “different house" within the United States, were classified into two categories by the Bureau of the Census: inter- and intra-county migrants. The fbrmer are those who moved within the county, and the latter indicates those who crossed a county line. Thus, "migrants" were distinguished from "movers" according to whether they had crossed a county line or not. Migrants were further divided into those who moved within the same state, those who moved from or to a contiguous state, and those who moved from or to a non-contiguous state. Migrants are called in- migrants when they arrive, and out-migrants when they leave. It must be pointed out here, that migration is not universal. We are all born and are destined to die, while some persons migrate and others remain where they are. Migrants do not represent a ran- dom distribution in their biological, socio-economic, and cultural characteristics. They have some characteristics that differentiate them from non-migrants. Migration is usually selective in terms of age, sex, and certain other characteristics. Moreover, migration differentials vary with type of community. A partial aim of this thesis is to see whether or not generalizations concerning selectivity are applicable to Michigan metropolitan area migrants.2 2The metropolitan areas presented in this thesis are those officially defined as Standard MetrOpoIitan Statistical Areas (SMSA's) by the Bureau of the Census. An SMSA consists of a single county or a group of adjacent counties which contains at least one Michigan metropolitan areas were selected mainly because most migrants are concentrated in those areas. In addition, the metropolitan areas of Michigan differ in size and exhibit different social, economic, and cultural characteristics. Another purpose of this thesis is to find what characteristics of the metropolitan areas relate to the migration patterns exhibited in the analysis of migration selectivity. Therefore, the thesis consists of two sections. The first section is devoted to an analysis of migration and selectivity with respect to age, sex, and color. Other differentials such as educa- tion and occupation were not given in the data used. Net migration data for the period 1950 to 1960, and for the period 1955 to 1960, and data for in- and out-migration between 1955 and 1960 for the Standard Metropolitan Statistical Areas (SMSA's) of Michigan will be used. The second section of the thesis will be devoted to observ- ' ing the relationship between the results of the analysis in the first section and selected characteristics of the SMSA's. The fol- lowing characteristics will be examined: 1. Land area. 2. Distance between central cities. 3. Size of central city. central city of 50,000 or more inhabitants, or two or more cities with a combined p0pu1ation of at least 50,000 persons, and which are essentially metropolitan in character and economically and so- cially integrated with the central city. Michigan has 10 SMSA's: Ann Arbor, Bay City, Detroit, Flint, Grand Rapids, Jackson, Kalama- zoo, Lansing, Muskegon-Muskegon Heights, and Saginaw SMSA's. See Map I. f Map 1. Atoa of Michigan flue-O IL“ Munkogon-Munko n Note: Ottawa County has been added to the Grand Rapid: SMSA and Lapoor County to the Flint SMSA since 1967 '4 ightn rj d W Ra I an... (In! ______ an at allude LLA Il‘hc , '1) sun. 0 lint Standard Metropolitan Statintical LILAC U I. Afll Detroi IO. II. Geographic features. Total p0pu1ation. Population change: Total Net migration Natural increase. Population characteristics: Urban population Black population Population of 65 years old and over. Education of persons 25 years old and over: Median school years completed Completed less than 5 years of school Completed high school or more. Employment: In manufacturing In white collar occupations. Establishments with 20 or more employees: Nondurable goods industries Durable goods industries. Income of families: Median income Under 3,000 dollars 10,000 dollars and over. This thesis, therefbre, has two major purposes, namely, to identify the nature of selectivity among migrants and to ascertain the relationship between selectivity and the character of the metro- politan communities. There would seem to be little need to justify the importance of investigating selectivity among migrants. Studies exist in abundance showing that all p0pu1ation movements are selec- tive in some respects, that migrants do not represent a cross-section of the population from which they are drawn. It may be important, however, to provide a rationale fer the relationship between selec- tivity and the characteristics of SMSA's. It is well known that no two metropolitan areas are identi- cal in all respects. They differ with respect to the degree of dif- ferentiation or the extent to which they are functionally special- ized. They also differ in size, extent to which they are indepen- dent or linked to a network of cities, and in numerous other ways. It should be clear, then, that there should be a clear relationship between the social and economic structure of an SMSA and migrant selectivity. If the metropolitan area is specialized in heavy in- dustry, we would expect migrants to that area to be disproportion- ately young, economically productive males. If the metropolitan area is specialized in insurance and clerical occupations, we would expect in-migrants to be disproportionately young females. Many other factors of course may play a role, such as availability of health and medical services, facilities for the aged, quality of educational facilities, and others. Thus, the two parts of the thesis are closely linked. We hope to identify patterns of migration selectivity for the several Michigan SMSA's and group the SMSA's having similar (or unique) patterns. Then we want to explore the extent to which the SMSA's possess social and economic characteristics that are responsible, at least in part, fer the migration patterns found. Some Studies of Migration Selectivity by Age, SexJ and'Color In the many studies of migration selectivity, demographers have tried to establish universal migration differentials which would be applicable to any place and to any time. The laws of migra- tion presented in 1885 by Ravenstein were one example.3 His broad generalizations have been supported by several studies. However, up to date, the only differential which might be considered near- universal irrespective of Space and time, is that persons between 20 and 34 years old are more likely to migrate than other age groups. This has been shown in many studies. According to the annual report of "Mobility of the P0pulation of the United States,“ young adults have been the most mobile, especially in their twenties, and with advancing age, the mobility rate declines.4 The study of "Migration within Ohio, l935-40" by Thompson, showed that among the migrants to metropolitan areas, those aged between 20 and 34 constituted a larger proportion than the resident p0pu1ation of these ages, and the pro- portions of migrants under 20 and 45 and over were smaller than those of the resident population of these age groups.5 Bogue and Hagood 3Ernest G. Ravenstein, "The Laws of Migration," Journal of the Royal Statistical Society, No. 48, June 1885, pp. 16 - . 4U.S., Bureau of the Census, Current Population Reports, "Mo- bility of the Population of the U.S.," Population Characteristics, Series P-20, 1950-60. 5Warren S. Thompson, Migration within Ohio, 1935-40, Scripps Foundation Studies in Population Distribution,’l951, pp.lll-125. found, in their research on differential migration in the Corn and Cotton belts, positive indexes of differential migration as high as 300 for young adults, and negative indexes as low as 50 for young children and older adults.6 Similar findings have also been reported for areas outside the United States. For example, in a sample survey of the migrants to the metropolitan area of San Salvador in 1960, a heavy concentra- tion of the migrant p0pu1ation was found in the young adult ages; 46 per cent were in the age group between 20 and 39, and 57 per cent were in the 15-39 age group.7 While it is widely recognized that young adults are over represented among migrants, several studies have reported refine- ments in the generalization. Sanfbrd, for example, reported an age difference between the in-migrants and the out-migrants in a rural Alabama commanity. While out-migration was selective of young adults, in-migration was more evenly distributed from infancy to the 65-69 year age group.8 Differences in the age selectivity between in- migrants and out-migrants were also reported in Hobb's study of migrants in Plymouth, a town in the Anthracite Region. While 6Donald J. Bogue and Margaret J. Hagood, Differential Mi ra- tion in the Corn and Cotton Belts, Subregional Migration Tn the . . 1935-40, V01. II, Scripps Foundation Studies in Population Distribu- tion No. 6, 1953, pp. 10-15. The computation of the indexes were illustrated as follows: [(migration rate fbr the articular age group)-—(migration rate for the general population?] 4 (migration rate for the general p0pu1ation), times 100. 7C1iffbrd J. Jansen, Readings in the Sociology of Migration (New York: Pergamon Press, 1970), pp. 390-39T) 8Gilbert A. Sanford, "Selective Migration in a Rural Alabama Commgglty," American Journal of Sociology, Vol. 5, Oct. 1940, pp. 763- . out-migration was highly selective of the age group 15-29, in- migration was selective of the same age group only to a slight degree. A large proportion of the in-migrants were in the age groups 30 to 44 and 45 years old and over.9 Thornthwaite found age selectivity in rural to urban migra- tion. More than 40% of the migrants from farms to cities were be- tween 10 and 20 years of age, and only 9% of those moving from ‘0 Freedman in his farms to the cities were 50 years old or over. study of "Recent Migration to Chicago" found that The more rural the background of the (white) migrants, the younger was the average and the greater was the excess in the years of late adolescence and early adulthood.1 'Although Freedman agreed with the generalization that all types of migrants were concentrated in the late adolescent and early adult ages irrespective of sex, race and region of origin, he emphasized that Negro migrants were not related to variations of rural-urban cultural characteristics. [In a special study of the people of the Muskegon County area of Michigan, it was observed that non-white net in-migration occurred at every life stage, but older children between,10 and 20 9Aibert H. Hobbs, Differentials in Internal Migration (Phila- delphia: University of Pennsylvania, 1942), pp. 56-7. 10Warren C. Thornthwaite, Internal Mi ration in the United States (Philadelphia: University of PennsyIvania Press, 1934), p. 32. 1‘.Ronald Freedman, Recent Mi ration to Chicago (Chicago: The University of Chicago Press, I950}, pp. 31-41. I0 years old, youth between 20 and 29, and young middle-aged persons between 30 and 44 were over-represented]12 According to the 1950 Census, among whites every age group over 30 had more than 30% living outside their state of birth, and a peak of 38% was reached for the age group over 70. 6?. the other hand, among non-whites, the peak was already observed in the 40-49 year age group; for every age group over 20 more than a third were living outside their state of birthtj/3 Thus, migration of the non- whites tends to occur at earlier ages than among the whites. This suggests that family group migration may be more characteristic of non-whites than whites j ' Very little support can be found for a universal principle with respect to the sex composition of migrants. Patterns feund in the more deve10ped nations are not often applicable to all less de- veloped nations. Freedman found that migrants to Chicago had a lower sex- ]4 This was consistent with Goldstein's ratio than non-migrants. study of migrants in Norristown, Pennsylvania between 1910 and 1950. He observed that the sex-ratio of the migrants was 77 males fbr 100 12Civic Affairs Research, Inc., Anatomy of a Community: Characteristics of the People of the Muskegon County Area, 1968, p.1T6. I3 14 Jansen, op. cit., pp. 7-8. Freedman, loc. cit. II females, while that of the non-migrants was 91 males for 100 fe- males.15 On the other hand, according to a paper presented at the 1961 International P0pulation Conference 6y Dandekar, the sex-ratio of net migrants in Japan between 1950 and 1955 was 110 males for 100 females in 35 cities of over 200,000 population. Also in Cey-. lon, males were more likely to be migratory than females in all age groups between 1946 and 1953.16 In the United States, in general, through a review of cur- rent mobility data, rates for males and females are not very dif- ferent, but the tendency to move has been slightly favorable for males.17 However, the factor of time, or stage of development, appears to exert an influence on migration differentials by sex. Thornthwaite discovered that between 1910 and 1920 the number of the male in-migrants to Detroit exceeded the female in-migrants, but in the following decade the situation was reversed.18 Hobbs explained this reversal of migration pattern as due to changing socio-economic conditions, specifically the decline of industry. According to his report, in the first period when good jobs were 15Sidney Goldstein, Patterns of Mobility: 1910-1950 (Phila- delphia: Philadelphia University Press, 1958), p. 48. 16Jansen, o . cit., p. 17. See 0. P. Dandekar, "Internal Migration in Some Countries of the East,“ International Population Conference, 1961, Paper 111. 17U.S., Bureau of the Census, op. cit., No. 61, Oct. 1955, 18Thornthwaite, Op. cit., p. 35. 12 still available outside the Anthracite Region in spite of decline in economic opportunity in Plymouth, the male out-migrants were domin- ant. Later, as the depression became more severe, and when jobs were very few elsewhere, the percentage of the male out-migrants decreased.19 1 Thus, the sex selectivity among migrants is diverse in time and space. It appears unlikely that any universal law can be ex- pected.20 Some Studies of Migration Patterns and the Characteristics of CommunitTES ' There are relatively few studies of migration patterns as re- lated to the characteristics of communities, although a considerable number of studies concerning migration patterns as related to the characteristics of the migrants may be found. In the study of migration to Stockholm, Moore attempted to show the significance of the type of industrial development in the migration patterns. The study was done, based on the following two assumptions: 1. The behavior patterns of the types of communities of birth reveal a lag for those who were born in the dif- ferent communities in degree of industrial development. 19 20Donald J. Bogue, Technigues and Hypotheses for the Study of Differential Migration, International Population Conference, Paperll4. Hobbs, og. cit., pp. 57-58. I3 2. Different types of community of birth produce different behavior patterns by a comparison of the following feur types of distributions; education, occupation, income, and civil status. She divided migrants by type of communities of birth into agricul- tural-, industrial-, and town-born persons. She, then, found that migrants to a city had lived last in a town more often than in any other type of community. Moreover, it was shown that the behavior patterns of migrants differed according to the type of community of birth as measured by their education, occupation, and civil status. However, income distributions did not reveal any signifi- cant differences. Probably because, she explains, "there was a con- siderable overlapping in the range of incomes fer a particular occu- pational class," finding that the average income for each type of community of birth was same.2] Oyler studied migration patterns by constructing indexes of population fertility, income, communication, and education in Ken- tucky fer the period 1920 to 1940. These indexes for the 120 coun- ties of Kentucky were analyzed using correlation procedures. One of his hypotheses was that the net out-migration of youth 15-19 years old was associated directly with population fertility, income, com- munication and education. He found that low income was the strongest factor influencing outward migration among young people. The next most important factor was education. Favorable communication 2‘Jane Moore, Cityward Migration (Chicago: The Univer- sity of Chicago Press, 1938). I4 networks and high fertility were influential in stimulating outward migration, but the fbrmer was countered by the accompanying effect of high income and the latter by the accompanying effect of low income.22 Sources of Data and Methods of Analysis The data for this thesis were derived principally from the Census. The quality of data on migration is usually poor as com- pared with other demographic data. Statistics on internal migra- tion are especially limited in most countries. There are two major measurements for internal migration, that is, by comparison of two consecutive censuses, either by the "vital statistics method," or by the "survival ratio method." A third measure sometimes used is a comparison of state-of-birth sta- tistics with present residence. The vital statistics method is also called the residual method. This method estimates net migration, that is, total net. gain or loss from total p0pu1ations at the beginning and end of a decade after subtracting natural increase during the period. The fbrmula is often expressed as fellows: (I -- O) = (P1 -- Po) -- (B -- 0), when I, O, P1, Po’ 8, and 0 indicate number of in-migrants, 22Merton D. Oyler, Fertility Rates and Migration of Ken- tucky ngulation 1920 to 1940, as Relatetho Communicationg_Income, and Ecfllcafion, Ph.D. thesis, University oFChicago, 1943. 15 number of out-migrants, p0pu1ation at the end of the period, popula- tion at the beginning of the period, number of births, and number of deaths, respectively. The survival ratio method estimates the proportion of the p0pu1ation which should be expected to survive at the second census and differences between the expected p0pu1ation and the actual p0pu- 1ation may be attributed to migration. In the United States, beginning with the 1850 Census, native- born persons have been asked to name their state of birth, and since 1940 additional information has been collected: people were asked where they were living 5 years, or one year, earlier. Even with this information, we still see that it is not possible to reveal intermediate migration or to distinguish deaths of migrants from deaths of natives. Despite such disadvantages, it is possible to know the total volume of the movement, the type of migration, and the streams of migration through the use of the present data. The data used in this thesis were gathered through the "vital statistics method," and census questions concerning place of residence 5 years earlier. In order to analyze the data, several methods have been used. I have used simple demographic indexes and proportions. The sex- ratios were recorded in the number of male migrants per thousand female migrants. Migration rates were computed as the ratio of net migrants for each SMSA of Michigan during the decade l950-1960 to the population as of 1960. CHAPTER II AN ANALYSIS OF NET MIGRATION: 1950-60 AND 1955-60, AND IN- AND OUT-MIGRATION: 1955-60 BY AGE, SEX, AND COLOR This chapter is devoted to analyzing the data. The data presented in this chapter are mostly those of net migration during the decade 1950-60, and the last five years of the decade, and those of in- and out-migration during the period 1955-60, for the SMSA's of Michigan. The data are analyzed by sex, age, and color, and com- binations of these characteristics. The following sections, then, will be presented: 1. Net migration by age: 1950-60 and I955-6O 2. Net migration by sex: 1950-60 and 1955-60 3. Net migration by age-sex composition: 1950-60 and I955-60 4. Net migration by age-sex-color composition: 1950-60 and I955-60 5. In-migration and out-migration by age: I955-60 6. In-migration and out-migration by sex: 1955-60 7. In-migration and out-migration by age-sex composition: I955-60. BefOre I deal with migration data by age, sex, and color, I will describe migration without controlling fer these characteris- tics. That is, the total volume of net migration as well as in- and out-migration will be considered for the SMSA's in Michigan. 16 17 Net migration represents the difference between the number of migrants who moved into and out of a given area during a speci- fied period of time. Net migration is a residual and tells us whether the area gained or lost pe0ple through migration. During the period between 1950 and 1960, the SMSA's of Michigan gained a total of 166,146 persons through migration. About 94 per cent of the total net migration in Michigan was concentrated in the SMSA's. Migration accounted fbr an increase of 3 per cent of the total p0pu1ation of the SMSA's of Michigan. Over half the gain (55 per cent) occurred in the Detroit SMSA, the largest SMSA of Michigan. The next largest gain through migration was in the Flint SMSA (16 per cent). The Bay City and Muskegon-Muskegon Heights SMSA's each had small net in-migrations. The volume of net migra- tion was more or less pr0portional to the population of the State's SMSA's, with the exception of the Kalamazoo and Lansing SMSA's. In the Kalamazoo SMSA, migration accounted fer 10 per cent of the total population. This was the highest percentage found fbr any SMSA in Michigan. The Lansing SMSA, in spite of a high rank (fourth) in p0pu1ation, ranked eighth in net migration (See Appendix Table l). The net migration during the period between 1955 and 1960 was obtained directly by subtracting the number of out-migrants from the number of in-migrants. I would like to emphasize here that data for those under 5 years of age have been omitted, since children under five years old were not born April 1, 1955 when the 1960 Cen- sus was taken. Besides these limitations, some data fbr the Muskegon-Muskegon Heights SMSA were not available, and since data 18 for non-whites were collected for the Detroit and Flint SMSA's only, the analysis by color was omitted for the period 1955-1960. Although the net migration available here applies to the population five years old and over between 1955 and 1960, some as- pects are quite different from the net migration fer the decade. Some of the differences will be mentioned here. One characteristic finding was a half of all Michigan SMSA's experienced net out-migration which was not found fer the decade. This suggests that the net in-migration which was fbund in all SMSA's between 1950 and 1960, was due to the supposed large net in-migration which occurred during the first 5 years of the decade. It was interesting to notice that the big three SMSA's of Michigan all had net losses. These three SMSA's--Detroit, Flint, and Grand Rapids--rely in large measure on the automobile industry. There- fOre, it seems quite reasonable to suppose that net out-migration in these SMSA's during the last part of the decade may reflect changing economic conditions in the automobile industry. On the other hand, net in-migration between 1955 and 1960 was fbund in the Ann Arbor, Jackson, Kalamazoo, and Lansing SMSA's. It should be remembered that, except fbr the Jackson SMSA, the SMSAts mentioned above surround expanding university towns. Unlike net migration, the direct data of in-migration and out-migration reveal how many migrants came in to the SMSA's and how many went out from the SMSA's. Moreover, we shall notice some differences in the migration pattern between in-migrants, which are not apparent in the net migration data. 19 According to the Census report, more than half of those who lived in the SMSA's of Michigan in 1955 still lived in the same house in 1960. The Ann Arbor and Kalamazoo SMSA's were exceptional. In these two SMSA's, many more mobile persons were found than per- sons who did not change their residences. Especially in the Ann Arbor SMSA's only 40% of the total p0pu1ation (5 years old and over) lived in the same house. On the contrary, the most stable was the Bay City SMSA, in which only 61% of the total population (5 years old and over) did not change their houses. Of persons who lived in different houses, more than half moved within the same county. This was true of all SMSA's except the Ann Arbor SMSA. The Saginaw, Muskegon-Muskegon Heights, and Flint SMSA's showed very high rates (79.5%, 78.2%, 78.2%, respec- tively) of movement within the county. On the other hand, the Ann Arbor, Lansing, and Kalamazoo SMSA's showed higher out-migration rates than the other SMSA's of Michigan (See Appendix Table 2).* Over half of the migrants in all SMSA's of Michigan moved within the state. The Bay City, Jackson, and Lansing SMSA‘s showed especially high rates of within-state migration. However, a con- siderable number of migrants from different states were observed in the Flint and Ann Arbor SMSA's. This was true fer out-migrants. *Note: Detroit SMSA and Lansing SMSA consist of three counties re- spectively, while the other SMSA's consist of only one county. Therefore, we have migrants who crossed the county line within the Detroit and LanSing SMSA's. Appendix Table 2 counts such migrants who moved to different counties in these two SMSA's. However, in- migrants and out-migrants fer the SMSA's do not count migrations within the SMSA's, if there is no special indication. 20 Also out-migrants from most of the SMSA's moved within the state, but in the Ann Arbor and Flint SMSA's many more migrants moved to different states than to the same state. In addition to these two SMSA's, Detroit SMSA showed the lowest rate (24.4%) of out-migrants who moved within the state. As we see Appendix Tables 3 and 4, the non-white population was more mobile than white p0pu1ation. Although the non-white pop- ulation was more mobile than the white population in absolute num- bers, it was found that the rate of migration of the white p0pu1a- tion was higher than that of the non-white p0pu1ation. In other words, among the non-white mobile population we find a greater num- ber who had changed residence within the same county, but a smaller proportion of the white population. This was true of all SMSA's of Michigan except the Jackson and Bay City SMSA's. However, if we consider migration fer both whites and non-whites, the non-white migrants had the tendency to move to the SMSA's from greater dis- tances than the whites. More than 55% of the white migrants to the SMSA's of Michigan were from within the state, while the greater proportion of non-white migrants was from different states. The Ann Arbor and Jackson SMSA's were exceptional; that is, in these two SMSA's many more non-white migrants came from the state. Also out-migration from the area was more likely to occur within the state. However, unlike in-migrants, out-migrants had the tendency to move longer distance. And yet in the two big SMSA's of Michigan, Detroit and Flint, migrants to non-contiguous states 21 outnumbered migrants to the state. This was observed also in the Ann Arbor SMSA. It was interesting to note that the proportions of both in- migrants from contiguous states and out-migrants to contiguous states were very small in all SMSA's of Michigan (See Appendix Table 5). Net Migration by Age: 1950-1960 and 1955-1960 All ages were classified into four groups: young people from age 0 to 14, younger adults from 15 to 34, older adults from 35 to 64, and old people of 65 years old and over. During the period between 1950 and 1960, total net in- migration in all SMSA's of Michigan were largely due to net in- migration of the young adult age group. All SMSA's of Michigan experienced net out-migration of old pe0ple. These findings might be explained by the fact that metropolitan areas have many social, economic, and cultural attributes which are attractive to young groups, while environmental factors are more important for old people. However, when we examine each SMSA, we see some variations in age groups. Although net in-migration occurred largely in the younger adult group, the Bay City, Muskegon-Muskegon Heights, and Saginaw SMSA's lost this age group through migration. It is inter- esting that these three SMSA's showed similar migration patterns in 22 many respects. Other SMSA's of Michigan also had some similarities in migration patterns. As another aim of this thesis, the following chapter will treat this subject more thoroughly. This chapter de- scribes only the differentials by age, sex, and color of migrants. The Ann Arbor and Lansing SMSA's were characteristic of the pattern in which net in-migration was seen only in the young adult age group. In all other age groups out-migrants exceeded in-migrants. Since Ann Arbor and Lansing have state universities, the great excess of in-migration over out-migration in the younger adult age group is nostly due to the inflow of students. These two SMSA's, in fact, have large proportions of young people and younger adults; however, the Lansing SMSA has considerable proportions in the older adult age group because it is a governmental center employing many people in the older age group (See Appendix Tables 1 and 6). In addition to the Ann Arbor and and Lansing SMSA's, the Jackson SMSA also had net out-migration among older adults. This is due to the fact that in the Jackson SMSA the continuous excess of out-migrants over in- migrants started at an earlier age than in any other SMSA's of Michigan, except the Detroit SMSA. In the Jackson and Detroit SMSA's, age 50 is the beginning as opposed to age 60 in others. In all SMSA's of Michigan, the highest migration rate occurred in the younger adult age group, particularly in the age group between 20 and 34. The highest net in-migration rates were observed at the early 20's in the Ann Arbor, Kalamazoo, and Lansing SMSA's, the main reason being college students. The Bay City, Muskegon-Muskegon Heights, and Saginaw SMSA's had something in common: the highest 23 net in-migration rates were in the early 30's, while the highest net out-migration rates were in the early 20's. In all other SMSA's of Michigan, the highest net in-migration rates were shown in the late 20's and the highest net out-migration rates were feund among old people (See Appendix Table 7). Net migration during the period, 1955 to 1960, was quite different from net migration during the decade, 1950 to 1960. It is very striking that all age groups experienced net out-migration in the Detroit, Flint, Grand Rapids, and Saginaw SMSA'S. And yet, the outflow was concentrated particularly in the age group of younger adults. This was in contrast with the migration pattern of the decade, since that same age group experienced the highest net in-migration during the decade. The Ann Arbor and Lansing SMSA's showed the same pattern of net migration, that is, net in-migration occurred only among younger adults. The Kalamazoo SMSA was the only SMSA that experienced net in-migration in all age groups. In the Jackson SMSA, net out-migration of the older adult age group, which was observed for the decade, would be due to the outflow of that age group during the first five years of the decade, since a con- siderable net in-migration was shown in the same age group during the last five years of the decade (See Appendix Table 6). 24 Net Migration by Sex: 1950-1960 and 1955-1960 In the decade, 1950 to 1960, total female net migration in all SMSA'S of Michigan outnumbered total male net migration by 37%. This was due to a greater net in-migration of female younger adults, and to a considerable outflow of male old pe0ple. This seems to be true also in the total population in all SMSA's. The female popula- tion of younger adults and of old people exceeded the male popula- tion of younger adults and of old people. Net out-migration of females took place in the Bay City and Muskegon-Muskegon Heights SMSA's, while that of males was found only in the Lansing SMSA. In all SMSA's in which net in-migration occurred, the female net in-migration exceeded greatly the male net in-migration. However, only the Jackson SMSA was exceptional; that is, male net in-migration slightly exceeded female net in-migration (See Appendix Tables 8a and 8b). Female migration rates were higher than male migration rates~ in all SMSA's except: I) the Bay City and Muskegon-Muskegon Heights SMSA's in which net out-migration of females occurred and 2) the Jackson SMSA in which male net migration outnumbered female net migration. The highest migration rate was found for both sexes in the Kalamazoo SMSA (10.5 for males and 11.3 fbr females). Flint SMSA came next (7.5 for males and 7.9 for females). The lowest migration rate of males was found in the Lansing SMSA, and that fer females was found in the Bay City SMSA. In most SMSA's the differ- ence between migration rates for males and those for females was 25 small, but Ann Arbor SMSA showed a great difference (2.6 fer males and 6.0 fer females) (See Appendix Table 9). The Detroit, Flint, Grand Rapids, and Saginaw SMSA's which experienced net in-migration for both sexes during the decade, 1950 to 1960, showed net out-migration for both sexes in the period be- tween 1955 and 1960. For the period between 1955 and 1960 these SMSA's had net losses in which males outnumbered females, while fer the decade, 1950 to 1960, they had net gains in which females outnumbered males. Net in-migration for both sexes, on the other hand, was shown in the Ann Arbor, Kalamazoo, and Lansing SMSA's. In the Lansing SMSA female net in-migration constituted 98% of the total net in-migration of the SMSA. The other two SMSA's showed nearly equal male and fe- male net in-migration. Net out-migration of males and net in-migration of females was found in the Bay City SMSA, while net in-migration of males and net out-migration of females was found in the Jackson SMSA. Through the observation of net migration between 1950 and 1960, and between 1955 and 1960, it seems clear that the net loss during the last 5 years of the decade required a large net gain during the first 5 years in order to yield a net gain for the decade as a whole. Data, however, were lacking for the Muskegon-Muskegon Heights SMSA, and the decade data included ages under 5 years (See' Figures 1 and 2). 26 Figure 1. let aigratien et nale pepulatien for Michigan SMSA'e: 1950-60 and 1955-60( Muekegen-Mnekegen Height- SMBA ie excluded ). /,¢¢ / gain: 1950-60 gain: 1955-6O gain: 1950-60 loee: 1955-60 ______r oar-nu Iowa ukv‘Yll at 00.0 lone: 1950-60 8‘13: 1955‘60 MASON LI" 0:: a unit an In W m ”qu60 u A unit LA ru , anal We: our 7 LA!!! A“ A teem \ de .x. D... } '\.;\ \ ‘.'.'n . . \ ‘ : \ .. . I ’1 . ' 2‘.“ ‘F . 'I e . y . ‘ I I. ' f, l ‘I ' .II ' I I Ka ' i“ I‘ . .Ia. J ‘ ' I I e .N 7 O! .9 .nnucu 27 Figure 2. Net nigratien e: fenale pepulatien for Michigan SMSA'e: 1950-60 and 1955-60( Mnekegen-Mnahegen Height. SMSA ie excluded ). 1955-60 "t I III] ”a. st gain: 1950-60 10": 1955-60 «can: a A (:1— 7 nuts": fluoeo a we I emcee-non IM' leee: 1950-60 Gain: 1955-60 W" W o . m m... A Wish LLA "earthly our 7 ‘ l ,1. . . o ' e I . . fl . ‘ l I I -— I . | I _. '- 1“ “‘l ”he 28 Net Migration by Age-Sex Composition: 1950-1960 an311955-l960 Net out-migration of old people was found for both sexes in all SMSA's in the decade data. Net out-migration of female old peOple exceeded that of male old pe0ple only in the Bay City SMSA. In the Kalamazoo SMSA net out-migration of old males was about four times that of old females. This proportion was remarkable since the male and female population of old people was not unbalanced. As we have seen, the Ann Arbor and Lansing SMSA's showed the same pattern in the net migration of total population. They also show the same pattern in the net migration of male and female popu- lation. Net in-migration was observed only in the younger adult group for both sexes in these two SMSA's. Since a great number of. younger adults came in, many more than the number of people of other age groups who went out, these SMSA's had net in-migration in total population. However, the Lansing SMSA experienced net out-migration of male population. The Bay City, Muskegon-Muskegon Heights, and Saginaw SMSA's resembled each other in net migration pattern for the total popula- tion. When we observed net migration of male population and of fe- male population separately, considering the age structure of these three SMSA's, there was a slight difference in the Saginaw SMSA. Net out-migration, which was feund among young adults in the Saginaw SMSA, was ascribed to the excess of net out-migration of male young adults over net in-migration of female young adults. On the other 29 hand, the Bay City and Muskegon-Muskegon Heights SMSA's continued to present the same pattern as to age-sex differentials.) They both ex- perienced net out-migration of young adults and old people of both sexes. Further examinations of net migration by age-sex composition are possible when we divide the population into more age categories than the four age groups examined so far. It is interesting to note that the Jackson SMSA, compared to all other SMSA's of Michigan, showed a unique migration pattern. In the Jackson SMSA male net in-migration greatly outnumbered female net in-migration in the age group between 25 and 34, while the situ- ation was reversed in other SMSA's. Moreover, for the male popula- tion, there was continuous net out-migration after the age of 35, although it is generally found that continuous outflow occurs after the age of 65. These findings might be explained by the fact that there is a large prison for males in the Jackson SMSA; most prisoners are young adults and they are discharged from prison when they become older adults. Also in the Detroit SMSA, the outflow started earlier, at around age 50 fbr both sexes. In the Grand Rapids SMSA the highest in-migration of male population occurs between the ages of 20 and 24 and the highest out- migration of female population takes place in the same age group. This was an unusual pattern. In all SMSA's high migration rates were fbund among young adults, particularly in the age group between 20 and 24, for both sexes. However, high migration rates occurred earlier fbr females 30 than males. In the Ann Arbor SMSA the highest migration rates took place in the age group between 20 and 24 for both sexes (191.6 for males and 178.3 fer females). Through the observation of net migration data during the period between 1950 and 1960, it was revealed that net migration for both sexes and for all age groups was feund in the Detroit, Flint, Grand Rapids, and Saginaw SMSA's. This was not observed in the decade data. In all these SMSA's, it was the young adult males that showed the highest net out-migration of all age groups. For female population of these SMSA's, the highest net out-migration was found both among the young adult and the older adult groups. During the decade, net out-migration of young people of both sexes took place only in the Ann Arbor and Lansing SMSA's; however, fer the period between 1955 and 1960, this net out-migration of young people of both sexes was observed in all SMSA's except-two; the Jackson and Kalamazoo SMSA's. It was to be expected that the SMSA's in which net out-migration of young people occurred would also experience net out-migration of the older adults of both sexes. This suggests that much of SMSA migration would be family-type migration. Moreover, unexpectedly, old females migrated into the Ann Arbor, Bay City, and Kalamazoo SMSA's, despite the net out-migration for both sexes during the decade in all SMSA's. 31 Net Migration by,A e- Sex- Color Compgaition: I 031960 Since the data of net migration for non-white population were not available for all SMSA's of Michigan, the analysis in this sec- tion is limited. The data were collected for the following seven SMSA's in which non-white p0pu1ation were more than 5,000 in 1950: Ann Arbor, Detroit, Flint, Grand Rapids, Jackson, Muskegon-Muskegon Heights, and Saginaw SMSA's. Since over 90% of the non-white popu- lation is black, the non-white population was considered here as being black. The most remarkable fact was that net in-migration was largely due to non-white net in-migration. Total net in-migration of white p0pu1ation was only 35,436, while that of non-white popula- tion was 111,643, over three times as large. In fact, 17% of the total non-white population in the seven SMSA's in 1960 consisted of net in-migration of non-white p0pu1ation, while net in-migration of. white p0pu1ation was only 0.8% of the total white population in the seven SMSA's in 1960. Here, it should be added that the great vol- ume of net in-migration of the non-whites fer all SMSA's was accounted fbr by the Detroit SMSA. It was also characteristic that although net migration of females exceeded that of males for both white and non-white popula- tions, the total difference in all seven SMSA's was small fbr the non-whites whereas it was as large as six times for the whites (See Appendix Tables 10 and II). 32 Another characteristic was that for both sexes of the whites, net out-migration took place among old people in all the SMSA's, but fer the non-whites net in-migration of old people was characteristic in most SMSA's. When we look at the net migration pattern of each SMSA, sev- eral new features may be observed. First, in spite of net out- migration of the whites of both sexes in the Muskegon-Muskegon Heights and Saginaw SMSA's, these.SMSA's showed net in-migration for the total p0pu1ation because of the excess of net in-migration of the non-whites. The Detroit SMSA also experienced net out-migration of white male population. This was mainly caused by a large net out-migration of old pe0ple. In the Ann Arbor and Jackson SMSA's, the same patterns were presented fer both white and non-white population. Net out-migration of young people, older adults, and old people was feund for both whites and non-whites and fer both sexes in the Ann Arbor SMSA. In the Jackson SMSA, net out-migration of male population was feund among older adults and old people, while out-migration of female population was found among old people, both white and non-white. Regarding net in-migration, the highest number was found among young adults fbr both sexes regardless of their color in all of the remaining SMSA's; except that in the Muskegon-Muskegon Heights and Saginaw SMSA's, this was true only fer the non-white population.' As we expected, the migration rates of non-white p0pu1ation were a great deal higher than those of the white population. Irre- spective of color, female migration rates were generally higher than 33 male migration rates, but among the younger adult age group in which the highest migration rates were feund, male migration rates were higher than female migration rates in allSMSA's except the Detroit and Grand Rapids SMSA's. The highest migration rates of non-white male population were located in the age group 25 to 29, while those of white male population were between 20 and 34. This was also often true fer females, although two exceptions were found for the non- white population in the Ann Arbor and Jackson SMSA's. The highest migration rates were found in the age group between 20 and 24 (See Appendix Tables 12 and 13). In-migration anggggtigégration by Agg: Appendix Table 14 shows that a great deal of both in-migration and out-migration was found among the young adults in all SMSA's. The high concentration was seen particularly in the 20's, although in-migration seemed to be more frequent during the late 20's and out- migration during the early 20's. In the Ann Arbor, Kalamazoo, and Lansing SMSA's; however, the situation was reversed, probably because of the effect of student enrollment. If we look at more specific age groups, we see that the mo- bility of children between 5 years old and 9 years old is not negli- gible: especially, in-migration of this age group in the Bay City, Flint, and Saginaw SMSA's, and out-migration of the same age group in the Flint, Kalamazoo, and Saginaw SMSA's were remarkable. 34 Appendix Table 14 shows also that, compared to in-migration, out-migration from the SMSA's was more likely to occur fbr those people whose age was 35 years old and over. This agrees with the preponderance of-out-migration observed for old pe0ple of 65 years old and over (See Figure 3). In-migration anggggtigggration by Sex: In order to make clear some differences between male migrants and female migrants in the SMSA's, the application of sex-ratio was used here. As shown in Appendix Table 15, in -migration to the SMSA's was found more frequent for females than males. On the other hand, out-migration from the SMSA's was fbund among male p0pu1ation. In the Jackson SMSA, male migrants were dominant in both in-migration and out-migration, while in the Kalamazoo SMSA, female migrants were- dominant in both in-migration and out-migration. It was found that every SMSA in which female in-migrants greatly outnumbered male in-migrants also showed an excess of female total over male total population; and, on the other hand, the SMSA's in which male in-migrants greatly outnumbered female in-migrants, had an excess of male total over female total p0pu1ation. The fermer case was seen in the Bay City, Grand Rapids, and Saginaw SMSA's. The latter case was found in the Ann Arbor and Jackson SMSA's. These findings suggest that either the sex composition of the p0pu1ation influences migration; that migration influences the 35 Figure 3. Percent distribution of in- and out-migrantn by age groups for Michigan SMSA's:1955-60 ( Muskegon- Muekegon Heighte SMSA in excluded ). In-nigrantc Saginaw Laneing Kalamazoo Jackson Grand Rapids Flint Detroit —--——.] ....- e - .or a- .w- Bay City Ann Arbor Catalina” 10 20 so 40 so 00 70 so 90100 wow "if’;jfii;...illiuliiiii . I I “ :I I I M :1 mm. " mm mm xx 3‘ IIIIIIIIIIIIIIIIIIIIIIHIIIIIIZ:::I Grand E“ “Elm H VIIIIIIIIIIIII T Rapids Jackson “1...... ,E——-—~BiIIIIIIIIIIIIIIIIIIIIIIIIIIIII i :I me... +:-——------ IIIIIIIIIIIIIIIIIIIIIIIIII "”1 Cw..-”- Saginaw EJIIIIIIII IIIIIIIIIIIIIIIIIIIIIIEW J LIIIIIIIIIIII I:::I _ 5—14 . 15—34 35— 64 36 sex composition; or, more likely, that something about an area has attracted one sex more strongly than the other, and continues to do so (Appendix Table 15). In-migrantion and Out-migration by Age-Sex 'Composition: 11955-19607 This section gives more explicit differences between male migrants and female migrants. It was found that males between 35 and 64 are out-migrants while females of that age are in-migrants. The total number of fe- male migrants 65 years old and over would be expected to be greater than male migrants since females greatly outnumber males at this age. However, in the Detroit and Flint SMSA's, aged male out-migrants ex- ceeded aged female out-migrants. It was interesting to note that in the Ann Arbor and Kala- mazoo SMSA's, the highest sex-ratios of in-migrants occurred among young people. Yet female out-migrants were predominant in the same age group. The Jackson SMSA was the only SMSA that showed a high sex-ratio fer both in-migrants and out-migrants in the younger adult age group. This SMSA, in fact, was also the only SMSA in which male population outnumbered female population in the age categories, except for old age groups. CHAPTER III THE RELATIONSHIP BETWEEN MIGRATION PATTERNS AND THE CHARACTERISTICS OF THE SMSA'S OF MICHIGAN In the previous chapter migration patterns in the SMSA's of Michigan were revealed through net migration and in- and out- migration by age, sex, and color. The aim of this chapter is to explicate the hypothesis that some social, economic, or combination of characteristics of the SMSA can explain the migration patterns fbund. It was observed that migration patterns of some SMSA's were quite different from the average, and that some were strikingly dif- ferent. Why did these differences occur? And why were some migra- tion patterns exhibited by groups of SMSA's? The pattern of differ- entials suggests a parallel pattern of characteristics: common mi- gration patterns reflect common attributes; unique patterns reflect unique attributes. The attributes I have attempted to correlate the migration patterns are, social, economic, and geographical ones. They are shown with demographic characteristics of each SMSA in Appendix Table 16. Based on the well-known relationship between migration and economic factors, a number of the characteristics chosen are economic. 37 38 Before we find relationship between the migration patterns and the characteristics of the SMSA's, we first group the SMSA's into the various common patterns and unique patterns as fellows: A.I Comnon migration patterns exhibited in theAnn Arbor, Kalamazoo, and Lansing SMSA's. a. The highest net in-migration rates-during the early twenties. Larger proportion of migrants than all other SMSA's. Net in-migration between 1955 and 1960. In-migration of ages in the early twenties and out-» migration of ages in the late twenties between 1955 and 1960. Net in-migration of the younger adult age group only, fbr both sexes (Ann Arbor and Lansing SMSA's). The highest sex-ratio of in-migrants among young adults and the lowest sex-ratio of out-migrants among the same age group (Ann Arbor and Kalamazoo SMSA's). B. Common migration patterns exhibited in the Bay City, Muskegon-Muskegon Heights and Saginaw SMSA's. a. b. Loss of young adult group. The highest net in-migration rates at the early thirties and the highest net out-migration at the early twenties. A small amount of net in-migration (Bay City and Muskegon-Muskegon Heights SMSA's). Net out-migration of total female po ulation (Bay City and Muskegon-Muskegon Heights SMSA'SI. A higher migration rate of male population than that of female population (Bay City and Muskegon-Muskegon Heights SMSA's). Net out-migration of young adults and of old people fer both sgxes(Bay City and Muskegon-Muskegon Heights SMSA's . 39 g. The highest number of net in-migration of the old adults fer the whites and of the young adults for the non- whites (Muskegon-Muskegon Heights and Saginaw SMSA's). h. Net in-migration for total population due to the great amount of net in-migration of non-whites-in spite of net out-migration of whites (Muskegon-Muskegon Heights and Saginaw SMSA's). i. Considerable in-migration of young people aged between 5 and 9 in the period, 1955 to 1960 (Bay City and Saginaw SMSA's). Common migration patterns exhibited in the Detroit, Flint, and Grand Rapids SMSA's. a. Net out-migration for total population during the period 1955-1960. b. Net out-migration of all four age groups during the period 1955-1960. c. Many more male than female out-migrants among old peo 1e during the period 1955-1960 (Detroit and Flint SMSA's . d. Higher migration rate of female population than of young adults)regardless of color (Detroit and Grand Rapids SMSA's . Unique migration patterns exhibited in individual SMSA's. a. The highest percent of migrants from different states mostly due to the non-whites (Flint SMSA). b. The largest number of net in-migrants of males aged 20 'to 24 and the largest number of net out-migrants of fe- males of the same age group (Grand Rapids SMSA). c. The excess of male net in-migration over female net in- migration (Jackson SMSA). d. A larger net in-migration of males than of females be- tween 25 years old and 34 years old (Jackson SMSA). e. Continuous net out-migration after the age of 35 fer males (Jackson SMSA). f. Predominance of males among both in- and out-migrants (Jackson SMSA). 40 9. Population increase due to the highest net in-migration rate (Kalamazoo SMSA). h. Net in-migration in all age groups between 1955 and 1960 (Kalamazoo SMSA). i. Predominance of female migrants for both in-migration and out-migration (Kalamazoo SMSA). j. Net out-migration for total male population (Lansing SMSA). Thus, one can identify nine SMSA's with common attributes. Although there is some overlap in this classification, I will show how the groupings are similar, and how certain conditions affect certain sub-classifications. Arranged more simply, common migration patterns are shown by: I) Ann Arbor SMSA, Kalamazoo SMSA, Lansing SMSA (special cases: Kalamazoo SMSA, Lansing SMSA) II) Bay City SMSA, Muskegon-Muskegon Heights SMSA, Saginaw SMSA III) Detroit SMSA, Flint SMSA, Grand Rapids SMSA (special cases: Flint SMSA, Grand Rapids SMSA) IV) Jackson SMSA, a case to itself Now, I intend to demonstrate the similarities within the groups and the differences between them concerning the characteris- tics of each SMSA. Group I consists of SMSA's in which a large university is a prominent-feature.. As expected, occupational attainment is very high. Median school years completed for persons 25 years old and over in all SMSA's is much higher than the arithmetic mean fer all SMSA's of Michigan (10.9). That is, median school years 41 completed (for persons 25 years old and over) in the Ann Arbor SMSA, in the Kalamazoo SMSA, and in the Lansing SMSA were 12.2, 11.7, and 12.0, respectively. Median school years completed were fbund to be near the mean in Group III and Group IV. The SMSA's which showed low median school years completed were Bay City (10.0), Muskegon-Muskegon Heights (10.4) and Saginaw (10.2). Thus, the SMSA's in Group II had particu- larly low educational attainment, lower than in any other group. Also the distribution of the percent of persons 25 years old and over who completed high school or more showed patterns similar to that of the median school years completed. The highest pr0portions were found in Group I and the lowest proportions were found in Group II. Propor- tions near the mean were found in the Groups III and IV. However, in regard to the percentage distribution of persons 25 years old and over who completed less than 5 years of school, expected patterns were found only in Group I. It seems that this measure varies more or less directly with the increase of the black population. How- ever, this is not the case in the Bay City SMSA in which a very high percentage of less educated persons are fbund in spite of the lowest percentage of black population. Group II was distinguished from the other groups, particu- larly in regard to income of families. At the same time this group of SMSA's showed the lowest educational attainment of all groups. Median income of the SMSA's in Group II were ranked as the lowest three ($6,041 in Bay City, $6,048 in Muskegon-Moskegon Heights and $5,983 in Saginaw). Moreover, these SMSA's were the only SMSA's in 42 which the percentages of families whose income was under $3,000 were higher than the percentages of families whose income was $10,000 and over. In Bay City, Flint, Muskegon-Muskegon Heights, and Saginaw SMSA's, the proportions of persons engaged in manufacturing were higher than those engaged in white collar occupations. With the ex- ception of the Flint SMSA, all SMSA's in Group II showed percentages in white collar occupations were less than those in manufacturing. In Group I, the Kalamazoo SMSA was less striking than the Ann Arbor and Lansing SMSA's, in the difference between employment in manufacturing and employment in white collar occupations. We find greater employment in white collar occupations in the Ann Arbor and Lansing SMSA's; in the Kalamazoo SMSA we find greater employment in manufacturing. The only major difference in the occupational distribution between the Kalamazoo SMSA and the Ann Arbor and Lansing SMSA's was that the percentage of female operatives and kindred workers in Kalamazoo was about twice as great as in the Ann Arbor and Lansing SMSA's (See Appendix Table 17). The distinctiveness of the Flint SMSA is clearly shown in Appendix Table 17: that is, the rates of employment as operatives and kindred workers fbr both sexes were very high. This was true also for non-white population.23 These facts might explain the unique migration pattern of the Flint SMSA which was described 23U.S., Bureau of the Census, Characteristics of the ngula- tion: 1960, vol. I, Part 24, Michigan,*Table 7B. 43 before; that is, the highest per cent of migrants from different states, mostly due to the non-whites. Another characteristic fbr which Michigan SMSA's exhibited differences was the number of establishments with 20 or more em-e ployees, for nondurable goods industries and for durable goods in- 24 Common patterns within the SMSA groups were not so dustries. strikingly exhibited as with the preceding characteristics. However, the most interesting applies to the Jackson and Kalamazoo SMSA's. Kalamazoo SMSA was the only SMSA in which the establishments of non- durable goods industries outnumbered those of durable goodsindus- tries; the latter accounted for more than 60% of all industries in all other SMSA's. In the Jackson SMSA, in contrast, the establish- ments of durable goods industries greatly outnumbered those of non- durable goods industries. That is, of all industries, about 81% was accounted fer by durable goods industries. While geographical features of the SMSA's might be expected to be associated with migration patterns, the results of our explora- tion were largely negative. As shown in Appendix Table 16, the geographic measures explored, i.e., distance between central cities, and size of central city do not yield clear-cut associations with particular migration patterns. 24Nondurable goods industries imply food and tobacco products; textile, apparel, and leather products; paper and printing; and chem- icals, petroleum, rubber and plastics products. Durable goods.indus- tries contain lumber, wood products and furniture; stone, clay and glass products; primary and intermediate metal products; electrical and nonelectrical machinery; transportation and ordinance (including missiles), and instruments and miscellaneous products. 44 However, two other geographical variables do require some comment: access to large bodies of water, and location within an industrial corridor. Access to large bodies of water tends to empha- size fishing and shipping occupations that traditionally correlate with poor education and low income. Michigan is nearly completely surrounded by the Great Lakes, so that contact with them must be considered an important fact. Of the ten SMSA's, half are adjacent or near to a lake : Bay City, Detroit, Muskegon-Muskegon Heights, Grand Rapids (a consequence of having absorbed Ottawa County in 1967) ).25 Thus, we see that all of and Saginaw (being adjacent to Bay City Group II are SMSA's adjacent to a Great Lake, and that Group III in- cludes two SMSA‘s that are adjacent. An industrial corridor is an area, demographically sharply differentiated from adjacent areas, formed by the gradual fusion of two or more industrialized locations through railroad or other avail- able transportation needed between those centers. Some area lying between two industrialized points can thus be expected, as time goes on, to change character from rural to industrial as the corridor takes shape. Such a change has taken place recently in Kalamazoo. It lies about half way between Detroit and Chicago, two notable 26 centers of industrial activity. The net in-migration rate is 25Grand Rapids SMSA is now considered to be located along the coast, since Ottawa County has been added in 1967. 26Harold C. Taylor, The Population of Kalamazoo County, Michi- an, Estimates as of July 1, 1956 and Forecasts to 1975 (KaTamazoo: eTW. E. UpjohnInstituteforCommunityResearch,1956), p. 20. 45 remarkably high, so that the effect of the formation of an industrial corridor is comparable to the effect of student enrollment. Apart from adjacency to lakes and recent formation of an industrial corri- dor, no important geographical factors were identified. Thus, com- mon or unique geographical features appear to be less significant than social and economic characteristics in relation to migration. CHAPTER IV SUMMARY AND CONCLUSIONS This chapter is devoted to a summary of an analysis of migra- tion to and from the SMSA's in the State of Michigan. We have shown that SMSA migration in Michigan is selective fbr age, sex, and color. Through the analysis of net migration (1950-1960 and 1955-1960) and in- and out-migration (1955-1960) for the ten SMSA's of Michigan, we can state the following in regard to selectivity by age, sex, and color: 1) Young adults in the age group between 15 and 34, partic- ularly between 20 and 34, were more migratory than any other age groups. 2) In-migration to the SMSA's took place especially among the young adults, while out-migration from the SMSA's occurred mostly among the old pe0ple aged 65 years old and over. 3) Females were slightly more migratory than males. 4) In-migration to the SMSA's was more frequent for females, while out-migration from the SMSA's was more frequent for males. 5) Out-migrants greatly outnumbered in-migrants among white old people, but in-migrants outnumbered out-migrangs among non-white old people. 6) The sex selectivity among the non-whites was less strik- ing than that among the whites. Such generalizations concerning differential migration by age, sex, and color, for the SMSA's of Michigan may not, of course, be applicable to other regions. However, the main purpose of this 46 47 thesis was not to make generalizations. Rather, it was to find migra- tion patterns which were shared (or unique) for the SMSA's of Michi- gan. In addition to general and shared patterns, we also found that some SMSA's had unique migration patterns. The second part of this study, then, was based on the follow- ing hypothesis: that SMSA's having similar social and economic char- acteristics will exhibit similar migration patterns; those having unique characteristics will exhibit unique migration patterns. Although the migration patterns investigated are limited to age, sex, and color, and although the communities selected here were the SMSA's of Michigan, some relationships between migration patterns and characteristics of the SMSA's emerged. From the results of migration differentials by age, sex, and color, the following fbur groups of SMSA's in Michigan were fbrmed: Group I) Ann Arbor SMSA, Kalamazoo SMSA, and Lansing SMSA Group II) Bay City SMSA, Muskegon-Muskegon Heights SMSA, and Saginaw SMSA Group III) Detroit SMSA, Flint SMSA, and Grand Rapids SMSA Group IV) Jackson SMSA This grouping was formed according to the pattern of similar- ities (or uniqueness) exhibited through the analysis of several dif- ferent sets of migration data. Thus, each group was similar, and each group had characteristics that contrasted with other groups. Perfect in group homogeneity was not found, of course, and certain differences may be found within a single group. 48 The aim of Chapter III was to find some characteristics with- in the SMSA's that were exhibited in common. The characteristics chosen represent selected social, economic, and locational factors relating to the SMSA's. They were: 1. Education of persons 25 years old and over. 2. The per cent distribution of employment in manufacturing and in white collar occupations. 3. The number of the establishments with 20 or more em- ployees of nondurable goods industries and durable goods industries. 4. Income of families. 5. Geographic features. The analysis of the characteristics showed that the influence of economic factors was particularly strong. The similarities and differences in economic factors predicted membership in the same or different group, as defined by migration pattern. Educational attain- ment too was closely related to the migration patterns formed. However, as compared to social and economic characteristics, the geographic factors did not seem to be significantly related to particular migration patterns. Had this study not been limited to the SMSA's in a single state, the influence of geographic factors might have been more significant. Migration patterns for communities, then, tend to be similar or different, depending upon the similarity or uniqueness of the characteristics of the communities. Therefore, we might say that if we find common migration patterns among some communities it is 49 not impossible to find some characteristics which would be common in those communities, and that if we find unique migration patterns in a community it is to be expected to find unique characteristic of the community. Moreover, if several migration differentials for two areas are known to be similar, other migration differentials will probably also be similar. However, the predictive power of the hy- pothesis would be strengthened, and the hypothesis further tested, by a wider study of migration patterns. In other words, the hypothe- sis stated may not be supported for migration in all places and at all times. LITERATURE CITED LITERATURE CITED Beegle. J. Allan and John F. Thaden. Population Chan es in Michi an, 1950-60. East Lansing: Michigan State University, I965. Bogue, Donald J. and Margaret J. Hagood. Differential Migration in the Corn and Cotton Belts. Subregional Migration in the United States, 1935-40, Vol. II, Scripps Foundation Studies in Population Distribution No. 6, 1953. Bogue, Donald J. "Techniques and Hypotheses for the Study of Differ- ential Migration,“ International Population Conference, Paper 114, 1961. Civic Affairs Research, Inc. Anatomy of a Community; Characteris- tics of the People of the MuskegonCounty Area. Muskegon, 1968. Clarke, John 1. Population Geography, London: Pergamon Press, 1965. Detroit City Plan Commission. The People of Detroit Master Plan Report. Detroit, 1946. Freedman, Ronald. Recent Migration to Chicago. Chicago: The Uni- versity Press, 1950. Genesee County Metropolitan Planning Commission. People: Today and Tomorrow: Genesee County, Michigan. Flint, T968. Goldberg, David, Allen Feldt, and William J. Smit. Estimates of Pop- ulation Change in Michigan, 1950-60. Ann Arbor: TheTunTVer- sity of Michigan, 1960. Goldstein, Sidney. Patterns of Mobility; 1910-50. Philadelphia: University a? PennsylvaniaPress, 1958. Hawley, Amos H. The P0pulation of Michi an 1840 to 1960: An Analy- sis of Grthh} Distribution and omposition. ’Ann Arbor: University of MiChigan Press, 1949. Hobbs, Albert H. Differentials in Internal Migration. Philadelphia: University of”PennsyTVania Press, T9421 50 51 Hodge, Leavy and Philip H. Hauser. The Challen e of America's Metro- politan Population 0utlook,_|966 to 1985 Neinork: Frederik A.iPraegeriInc., 1968. Jansen, Clifford J. Readings in the Sociology of Migration. New York: Pergamon Press,il970. Michigan Department of Public Health. Michigan Population Handbook 1965. Detroit, 1965. 'i Moore, Jane. Cityward Mi ration. Chicago: The University of Chicago Press, 19 8. Oyler, Merton D. Fertility_Rates and Migration of Kentucky Popula- tion 1920 to 1940, asiRelated’to Communicationgrlncome, and Education. Ph.D. thesis, University of Chicago, 1943. Ravenstein, Ernest G. "The Laws of Migration," Journal of the Royal Statistical Society, 48 (June, 1885), pp. 167-235. Sanford, Gilbert A. "Selective Migration in a Rural Alabama Commun- ity," American Journal of Sociology, 5 (October 1940), pp. 759-766. Schmitt, Robert C. The Future Population of Metropolitan Flint. Ann Arbor: Institute for HUman Adjustment, uniVersity of Michigan, 1947. Taeuber, Conrad and Irene B. Taeuber. The Changing Population of the United States. New York: J6hn Wiley 8 Sons,TInc., ‘ T958. Tayler, Harold C. The Population of Kalamazoo County, Michi an, Estimates as of July 1, 1956 and Forecasts to 1975. Kalama- zoo: 1The W. E. Upjohn Instituteiior CommunityiRESearch, 1956. Thompson, Warren 5. Migration within Ohio: 1935-40. Scripps Foun- dation Studies in P0pulation Distribution, Scripps Founda- tion for Research in P0pu1ation Problems, 1951. Thornthwaite, Warren C. Internal Migration in the United States. Philadelphia: University of Pennsylvania Press, 1934. U.S. Bureau of the Census. Count and Cit Data Book: 1967. U.S. Government Printing Office, Washington, 5.6., I967. . Po ulation Characteristics. Current P0pulation Reports, P-2 . ability of the PopuTation of the United States," 57 (April, 1955), 61 (October, 1955), 73 (March, 1957), 82 (July, 1958), 104 (September, 1960), 141 (September, 1965 , U.S. Government Printing Office, Washington, D.C. 52 U.S., Bureau of the Census. U.S. Census of Population: 1960. Characteristics of the Population: Michigan, Vol. I] Part 24, U.S. Government Priniihg Office, washington, D.C., 1963. . U.S. Census of Population: 1960. Migration between State Economic Areas. FinaT'Report PC (2)-2E} U.S. Government Printing Office, Washington, D.C., 1967. . U.S. Census of Population: 1960. Mobiligy for States and State EconomicTAreas. Final Réport PC I2)- U.Sl Govern- mentPrinting Office, Washington, D.C., 1963. . U.S. Census of P0pulation: 1960. State of Birth. Final Report PC (2)-2A. U.S. Government Printing Office,Washing- ton, D.C., 1963. U.S. Department of Agriculture. Net Migration of the Population, 1950-60rpy Age,_Sex, and color. Population-Migration Report, Vol. 1, Part 2. U.S. Government Printing Office, Washington, D.C., 1965. APPENDIX .omm_ "cowpepzqoa mo msmcwo .m.= ace “momp .N use; .H ._o> .pgonmz coppmgmwzlcowum_:qoa "mogaom mmo.~me mamm.mom.p pmo.mm¢._ mmm.¢mm.— .Nmm.omn.m o~m.~mr Pno.¢~ wm~.~mp Fmp.mm mephmmp 4 «mmupaupz .mcovuupan00 0:0 mo mupumwgmpuueeno .oma— "cowumpsqoa $0 mamcmo .m.: "mugzom 0L0 0.0 .0.00 0.00 .Amnmw 0.00 0.00 0.00 00, 3000000 . . . . 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