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University Microfiims
A Xerox Education Company RICO-VELASCO, Jesus Antonio, 1941- MODERNIZATION AND FERTILITY IN PUERTO RICO: AN ECOLOGICAL ANALYSIS. The Ohio State IMiversity, Ph.D., 1972 Sociology, demography
University Microfilms, A XEROX Company, Ann Arbor, Michigan
THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED MODERNIZATION AMD FERTILITY IN PUERTO RICO: AN ECOLOGICAL ANALYSIS
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate School of The Ohio State University
By
Jesus Antonio Rico Velasco, B.A., M. S.
The Ohio State University
1972
Approved by
Adviser Department of Sociology PLEASE NOTE:
Some pages may have
indistinct print.
Filmed as received.
University Microfilms, A Xerox Education Company ACKNOWLEDGMENTS
Grateful acknowledgment is made to Dr. Kent P. Schwirian whose advise, support and stimulation were crucial in supplementing ray intellectual curiosity in the fields of methodology, especially multivariate analysis, and population and human ecology.
ii April 10, 1 9 4 1...... B o m - Cali, Colombia,
1963***t*»*>,,*«o,•**••>•«*••£•••• B,A,, Univsrsidad National de Colombia.
1 9 6 6 ...... Viviendista. CINVA Bogota, Colombia,
1 9 6 9...... M.So, The Ohio State University, Columbus, Ohio,
1 9 6 9-I9 7 1...... Research Assistant, Mershon Center, The Ohio State University, Columbus, Ohio
1 9 7I-I9 7 2 Research Associate, Department of Rural Sociology, The Ohio State University.
PUBLICATIONS
Kent P. Schwirian and Jesus Rico-Velascc, "The Residential
Distribution of Status Groups in Puerto Rico's Metropoli
tan Areas," Demography. 8 (1971), PP. 81-90,
ill FIELDS OF STUDY
Major Field; Sociology Studies in Human Ecology. Professor Kent P. Schwirian Studies in Methodology. Professor Kent P. Schwirian
Studies in Population. Professors Kent P. Schv/irian, Alvan Zarate, and Yuan Tien
iv TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS...... 11 VITA ...... Ill LIST OF TABLES...... vll LIST OF FIGURES...... Ix
Chapter I. INTRODUCTION...... 1
The Problem...... 1 Contributions and Justification of the Study...... 3 The Scope of the Study...... 5 The Social Setting....,...... 6 II. MODERNIZATION AND FERTILITY: A THEORETICAL FRAMEWORK...... 19 Urbanization, Industrialization and Fertility...... 20 Socioeconomic Status and Fertility 28 Women in the Labor Force and Fertility...... 49
III. METHODOLOGICAL CONSIDERATIONS...... 6 ?
Data and Variables...... 6 ? Techniques of Analysis...... 7 I Estimation of the Empirical Correlation Matrix...... 78 Testing the Correlation Matrices...... 85 Models and Hypotheses ...... 91
IV. THE FINDINGS...... IO3
General Structural Path Models...... 105 Model I: 1 9 5 0...... 105 Chapter Page Model II: I960...... 115 Specific Structural Path Models...... 129 Model III: 1 9 5 0-1 9 6 0 . Urbanization- Industrialization and Fertility 130 Model IV; 1950-1960. Socioeconomic Status and Fertility,...,...... 135 Model V: 1 9 5 0-I9 6 O. Participation of Women in the Labor Force and Fertility...... l40 V. SUMMARY AND CONCLUSIONS...... l48
APPENDIX...... 159 BIBLIOGRAPHY...... 16 0
Vi LIST OF TABLES
Table Page
1, Deaths and Crude Death Rates, Puerto Rico, 194-0-1967...... 10 2* Total and Age Specific Death Rates for Puerto Rico, 194-0, 1950, and i9 6 0 ...... 11 3. Life Expectation at Birth, Puerto Rico, 1 9 1 0 -1 9 6 5...... 12 4-. Age Specific Birth Rates and Total Fertility Rates For Puerto Rican Women, 194-0, 1950 and i9 6 0 ...... 14-
5 . National Accounts and Related Economics, Puerto Rico at a Glance, 1955-196?.... 16
6 . Comparison of Relevant Publication Concerning Urbanization, Industrialization and Fertility... 29 7. Comparison of Relevant Publication Concerning Socioeconomic Status and Fertility...... 50
8 . Comparison of Relevant Publications Concerning The Participation of Women in the Labor Force and Fertility...... 62 9. Zero-order Correlation for the Six Variables. Puerto Rico, 1950...... 10? 10, Estimated Correlation Matrix from Path Coefficients and Differences Between Original and Estimated Correlations, Model I: 1950...... 112 Zero-order Correlation Matrix for the Six Variables, Puerto Rico, i9 6 0 ..... II6 Table Page
12. Estimated Correlation Matrix from Path Coefficients, and Differences Between Original and Estimated Correlations, Model Ii; I960...... 126
1 3 . Estimated Correlation Matrix from Path Coefficients, and observed Correlation Matrix. Model III: 1950-1960. Urbanization, Industrialization and Fertility...... 1 34 14. Differences Between the Observed Correlation Matrix And The Estimated Correlation Matrix, Model III: 1 9 5 0-1 9 6 0 . Urbanization, Industrialization and Fertility...... 136
1 5 . Estimated Correlation Matrix from Path Coefficients, and Observed Correlation Matrix. Model IV: 1950-1960. Socioeconomic Status and Fertility iff-i
1 6 . Estimated Correlation Matrix from Path Coefficients and Observed Correlation Matrix. Model IV: 1950-1960. Participation of Women in the Labor Force and Fertility...... 1/15
1 7 . Differences Between the Observed Correlation Matrix and the Estimated Correlation Matrix. Model V: 1950-1960. Participation of Women in the Labor Force and Fertility...... if^y
18. Comparison of Direct Path Coefficients To Fertility Ratios, 1950-1960, Puerto R ico...... 155
viii LIST OP FIGURES
Figure Page
1. Model I: 1 9 5 0. General Structural Path Diagram for Puerto Rican Fertility...... 93
2. Model II: i9 6 0 . General Structural Path Diagram for Puerto Rican Fertility...... 97 3. Model III: 1950-1960. Urbanization, Industrialization and Fertility. ^ . 99 4. Model IV: 1950-1960. Socioeconomic Status and Fertility...... 101 5. Model V: 1950-1960. Participation of Women in the Labor Force and Fertility...... 102
6 . Revised Structural Path Diagram. Model I: 1 9 5 0. Puerto Rico...... 109 7. Revised Structural Path Diagram. Model II: I960. Puerto Rico...... 117
8 . Revised Structural Path Diagram. Model III: 1 9 5 0-1 9 6 0 . Urbanization, Industrialization and Fertility. Puerto Rico...... 131 9. Fully Recursive Causal Model with all Paths Drawn. Model IV: 1950-1960. Socioeconomic Status and Fertility. Puerto Rico...... 137 10, Revised Structural Path Diagram. Model V: 1 9 5O-I9 6 O, Participation of Women in the Labor Force and Fertility, Puerto Rico...... 144 INTRODUCTION The Problem
This study attempts to examine the ecological correlates of community fertility levels of Puerto Rico, a society in the midst of economic development. Past studies have shown the importance of three dimensions in explaining differential community fertility levels. These three dimensions are the level of urbanization and in dustrialization of the society, the community's socio economic status, and the non-familiai activity of the population. One of the most important indicators of urbanization is urban concentration. Family planning takes place in the cities first and later diffuses to the rural areas. This pattern of lowered urban fertility has been persistent and ubiquitous in the more economically advanced nations as well as in newly developing societies. The employment of the population in manufacturing in dustries is associated with the concentration of people in urban areas, Thus it would be expected lower birth rates in those populations where there is a large scale urbanization-industrialization process, In this study, education and income have been selected to indicate the community's socioeconomic level. The SES of the population has generally had an impact upon birthrates. With increasing education, rational decision making is extended to size of family. Social mobility, achievement motivation, and opportunities for attainment are raised so that the people are more aware of and knowledgeable about the future consequences of present social actions, increasing income usually means that population members may divert childbearing and child- rearing costs to the satisfaction of other social needs. Thus one would expect lower birth rates in those com munities where social and economic well-being is higher. The non-familiai activity dimension refers to the participation of women in the labor force. The differential commitment to non-familial roles has a direct effect upon actual and expected family size. Work or other form of activities are incompatible with the mother role. Thus
it would be expected that higher participation of women in the labor force impinges upon fertility. Demographers have often treated urbanization and industrialization, socioeconomic status, and the partici pation of women in the labor force as virtually autonomous and independent sociological dimensions to explain fertility at either individual or community levels, instead of viewing these three components as significantly inter related phenomena. This study aims to assess the network of the relationships among these dimensions and the Puerto Eican fertility ratios. That is, it attempts to analyze the impact of urbanization-industrialisâtion, SES, and the participation of women in the labor force upon fertility in a developing society. Furthermore, a causal ordering of the three dimensions is postulated, and a negative relation ship with fertility is predicted on the basis of findings reported by previous studies. A causal model in the path analysis form is utilized to assess the relationships among the independent variables as well as their association with fertility levels.
Contributions and Justification of the Study Any scientific enterprise has its underlying contributions. Two major ones can be inferred from the findings of this investigation. First, some theoretical and methodological implications are advanced. Theo retically, the whole network of the relationship between indicators of modernity and fertility is analyzed. This study gives support to the proposition that community fertility rates are to some extent a function of both the general level and timing of societal development. In methodology the study shows that structural path models are useful for testing hypotheses and theory construction. Second, the study may have implications for family planning or population control in developing countries. An uncontrolled economic development can have dreadful con sequences for family planning. The present study implies that changes in the social structure are the sine qua non conditions for birth control. These changes are ubiquitous in the process of modernization. Increases in the concen tration of people in urban areas and employment in manu facturing industries, increases in the SES of population members, and the nonfalial activities of women would have a direct negative effect on fertility performance. The present study differs from other studies on Puerto Rican birth rates in that it focuses on an attempt to specify the network of the relationships that make up the multivariate socioeconomic components of community fertility levels. It recognizes that community fertility is a very complex phenomenon, and supports the fact that an adequate understanding of the changes in birth rates requires the analysis of its constituent parts. In effect, this study goes beyond the traditional correlation and regression analysis and tests different causal models by path analysis. No magic is claimed for the technique used in the interpretation of this complex phenomenon. However, some techniques are better than others. The use of path analysis forces the researcher to be precise in the theo retical formulations of his problem and statement of hypotheses. The achievement of this stage is the first step in hypotheses testing and theory construction. The set of recursive equations and the structural path diagram are formulated in such a way as to represent the relation ships assumed to operate among the variables in the real world. Theory and empirical references are the two major guidelines in the construction of a good structural model. General fertility studies, previous research on the Puerto Rican birth rates, and the wealth of valid aggregate com munity data have made possible in this work the development of several causal models that are tested in a cross- sectional and longitudinal approach.
The Scope of the Study This study is limited to an ecological analysis of the community fertility levels in a developing society. The central argument is that to a certain extent the fertility of the Puerto Rican populations is a function of the timing and general level of societal development. To support this argument, the author has analyzed the three interdependent sociological dimensions — urbaniza tion- industrialization, SES, and the participation of women in the labor force — in several structural causal models in the path analysis form. These are explained as causes of the Puerto Rican community fertility levels. The study of the relationship between moderniza tion and fertility requires the presentation of an adequate theoretical framework, the definition and specification of
variables, and the use of techniques included in this analysis. The former requirement is given in Chapter II, which presents a general review of the literature on fertility, relevant to this study, and the theoretical grounds on which the path models are built. The latter requirement is discussed in Chapter III, which specifies the kind of data used in the analysis, the variables, hypotheses, and methodological principles followed in the construction, and the test of the structural path models suggested. Chapter IV is a presentation of the findings. First, the general structural model for each census period is explained, and the changes that have occurred through time in the network of the relationship among the variables are specified. Second, the specific longitudinal models are discussed and analyzed. The final chapter in cludes some general methodological and theoretical impli cations on studies related to fertility, and the findings encountered and conclusions reached in the study.
The Social Setting
Puerto Rico was chosen for detailed analysis, first, because of its transcendental importance for under standing the demographic changes that are taking place or will occur in current Latin American populations and. seeorid, because it is an example of a society that has experienced major and rapid social, economic and demo graphic changes in this century that are hardly paralleled by other developing societies with similar characteristics. Finally, the wealth of valid aggregate community data makes possible the analysis and explanation of the network of relationships among fertility levels and several indi cators of modernization. Data from the 1950 and I960 censuses^ are used to demonstrate the prevalent inverse relationship between modernization and fertility. A brief look at some of the major changes that have taken place in the Puerto Rican society seems necessary. The Island of Puerto Rico was ceded to the United
States in October, I8 9 8, as a result of the Spanish-American War and according to the Treaty of Paris. The island was recognized as a territory and possession of the American government until 1 9 5 2, when a self-governing commonwealth was established, a status similar to the remaining states of the Union with difference that the Commonwealth of Puerto Rico has neither voting representation in Congress nor federal taxation. When the first census of Puerto Rico was taken by the Spanish government in 1765, the island had # , 88]
^U.S. Department of Commerce, Census of Population: 1 9 5 0 (Washington D.C.: Government Printing Office, 1953). And, Census of Population: I960 (Washington D.C.: Government Printing Office, 1 9 6 3 ). inhabitants. Immediately after the Spanish War ended, the War Department of the United States took a population census, and the island had 953,2^3. The rate of natural increase was so high that the population almost doubled
every 25 years. Between 1899 and I960 the rate of growth slowed down; however, the population more than doubled. The census of 1950 showed an 18,3 percent increase in population over the 19^0 census. In the last census, I960,
the island had a population of 2 ,3^9 ,5 ^f5 , that is, a 6 .2
percent increase over the 1950 population of 2,210,705.^
Changes in the population trends that have ac companied the economic development can be considered unprecedented. Puerto Rican mortality levels compare very favorably to those more developed societies. Indeed, this society has benefited from the time dif ferentials in the development process. Death control techniques, especially the use of m o d e m medicine and environmental sanitation, have diffused from those nations, principally the the United States, much further along in the process of modernization.^ The amazing decline in
2 lbid. '^Kent P. Schwiran and Jesus Rico-Velasco, "Eco logical Aspects of Mortality in a Developing Country: The Case of Puerto Rico," (unpublished paper presented at the Annual Meetings of the Ohio Valley Sociological Society, Cleveland, Ohio 1971). mortality rates between 1940 and 1 9 6 ? is summarized in Table 1. The downward mortality trend has not been evenly distributed across the age composition of the population. Age specific death rates show that most of the gains have occurred in infant and child mortality. The average infant death rate for 1940 was 137*1 infant deaths per thousand population. For 1950 this rate was drastically reduced to 81,7, and in I9 6 0 , an average of 43,5 was reported. Table 2 summarizes the total age specific death rates for Puerto Rico in the last three intercensal periods. More impressive have been the gains in life expectation at birth in Puerto Rico since 1910, Table 3 presents the life expectation and the percent increase over previous periods. There has been an increase of 77 percent in life expectancy since 1920. The life at birth has increased over one year per annum since 1940, This is at least twice and often three times higher than the maximum national rates ever recorded among populations of the West.
Although fertility is responding to modernization, Puerto Rican fertility is high by any measure. The child- woman ratio (children under 5 years old per 1 ,0 0 0 women
15 to 49 years old) was 725 in 1950. In I960 it dropped to 664 children per 1,000 women 15 to 49 years old. This measure does not directly refer to any actual number of TABLE 1
DEATHS AND CRUDE DEATH RATES, PUERTO RICO, 1940-1967
Year Number of Deaths Rate Per 1,000 Population
1967 16,780 6.2 I960 15,841 6.7
195 5 16,221 7.2
1 95 0 21,895 ,9.7
1 945 28,857 1 3 .7
194 0 34,468 18.4
Sources: Puerto Rico Department of Health, Annual Vital Statistics Report (San Juan: Division of Demographic Registry and Vital Statistics, 1968). U.S. Department of Health, Education and Welfare, Vital Statistics of the United States (Washington D.C.: Government Printing Office, 1 9 4 0-1 9 6 0 ). TABLE 2. TOTAL AIID AGE SPECIFIC D a RATES FOR PUERTO RICO, 1940, 1950 AND 1960.
Ages Eeath Rates* Death Rates* Census Deaths Death Rates* Population (1,000 pop) Population (1,000 pop) Population (1,000 pop) (1) (2) (3) (3) / (2) (5) (6) (6) / (5) (8) (9) (9) / (8) (4) (7) (10)
Total 1,868,308 34,463 18.4 2,210,703 21,895 9.9 2,349,545 15,791 8,221 71,041 5 iso? 75,881 3,307 1-4 6,759 295,236 2,911 278,522 1,444 672
246,860
148,008 1,551
526
1,146 1,206 1,132 1,134 1,227 21,236 80+ 2,140 120.8 21,363 3,116 145.8
î calculated by the author. 12
TABLE 3
LIFE EXPECTATION AT BIBTH, PUERTO RICO, I9IO.I9 6 3 .
Life Expectancy Percent Increase Over (males and females) Previous Periods
1910 38.4 --I- —
1920 38.5 0.0
1930 41.4 7.8
1940 46.0 11.1
1950 60.5 33.7 i9 60 69.7 1 3 .2
1963 69.2 0.0
1965 7 0 . 4 1.7
Sources: Information for 1 9 1 0 to 1950 is taken from Reuben Hill, et. al., op. cit. Data for I960 to 1 9 6 5 from Natham Keyfitz and Wilhelm Flieger, World Population: An Analysis of Vital Data (Chicago: The University of Chicago tress). •13
but rather to the population of children under five years who are survivors of previous births during the five years preceding the census ; however, it is a useful indirect evidence of fertility performance. According to Hill, Styeos and Back the child-woman ratio, in 1950, was 1? percent higher than the average for reporting Latin American countries, and 35 percent higher than the average
Caribbean Island.^ In the last intercensal period, this measure shows a perceptible decline from 725 to 664 children per 1 ,0 0 0 women 15 to 49 years old, a 10 per cent decline in ten years. Two more refined measures of fertility are provided in Table 4. As seen in this table the most fertile age period in 1940 was for women between 2 5 -2 9; in 1 95 0 and I9 6 0 the most fertile group of women was between20-24. The first group is an indication of postponement of marriage probably due to the reper cussions of the world's depression of the 1930's. The last two groups are indicators of a lowering of age at marriage, probably as a result of the economic development in the island. The other condensed measure is the total
Reuben Hill, J. Mayone Stycos and Kurt W, Back, The Family and Population Control. A Puerto Rican Experiment in Social Change (Chapel Hill; The University of North Carolina Press, 1959), PP. 11-13. '.CABLE 4. AGE SPECIFIC BIRTH E ) total PERTILIK rates for PUERTO RICAN WOMEN, 1940, 1950, AND I960.*
Reported Birth Rates* Reported Birth Rates* Reported Birth Rates* Population (2)/(3)xl,000 Population (5>/(6)xl,000 Population (8)/(9)xl,000
(2) (3) (4) (5) (6) (7) (8) (9) Under 15 7,813 106,689 73.2 10,172 111,316 91.3 11,574 124,258 26,097 101,847 19,475 81,651 11,937 65,154 10,152 8,648 65,754 7,152 2,116 43,485 2,626 10.6 unknwjn 8,173 2,793
39.317
37,937
Fertility 4.69 4.49
^Calculated by the Author.
Sources: Population Data, U.S. Department of Commerce, Census of Population. 1940. 1950. 1960. (Washington, D.C.; Government Printing Office, 1943, 1953, 1963). 15 fertility rate which shows an increase in fertility per- forcanoe between 19^0-1950, and a slightly-falling fertility apreciable in the last period. All these changes in population trends have ac companied the process of economic development. An ex panding economy in the last two decades has touched upon all aspects of the Puerto Bican society. The foundations for this progress was laid during the post-war period by such programs as Operation Bootstrap, In the 1950's and
1960's the major national accounts and related economics present rapid structural changes. The gross national product went up 15A points percent per year on the average. The per capita income rose from #44? in 1955 to
$1,047 in 1 9 6 7 . The average family income shows a similar increase. International trade, employment rates, and other sectors of the economy have risen and are expected to further expand and consolidate in the near future. A summary picture of selected sectors of this booming economy is given in table 5, Of greater importance than the economic boom per se are the changes in the social structure of the society. Institutional changes have destroyed the personalized and authoritarian relationships of the older hacienda system and the isolation and self-sufficiency of the small farmer or minifundio, A cash-minded economy and improvements in .16
:;:;o’-îC3 . puhstc 7.IC0 .,r oiv.xa.i, 1555-1967.
1955" i960 1967 1955" 967"
l i
Average Family
III. Trade 687.0 Importe
785.0 11:: 545.0 6%:: 81.0
127,950.0 179,657.0 202,803.0 4.87
1 ,135.0 2 ,021.9 15.62
387.0 587.0 1,372.0 25.51
: .-snd Social Planning, Statistical
I available for enplny-.-'nt. 17 communication and transportation have been introduced.5 Puerto Bico has moved from an agrarian society to one in which industry plays an increasingly important role in the economy. The standard of living of the population has moved from among the lowest in the world to well among the highest, 6 Bourne and Bourne? observed that these changes took place in the urban areas with enormous housing developments, super-highways, supermarkets, shopping centers, and general commercial activities. They also pointed out that these changes have diffused from cities to rural communities through population movement and increased communication.
This social setting provides an excellent oppor tunity to study the ecological correlates of community fertility, Puerto Rico is a society in the midst of its economic development process in which the singular rela tionship between modernization and community birth rates
5julian H. Steward, et. all.. The People of Puerto Rico (Chicago; University of Illinois Press, 1 9 5 6 ), p. 486-4'8). ^Melvin M. Tumin, Social Class and Social Change in Puerto Rico (Princeton: University Press, 1961), p. ^57. 7Dorothy D. Bourne and James R. Bourne, Thirty Years of Change in Puerto Rico: A Case Study of Ten Selected Rural Areas (New York: Pracer Publications, 1966), 18 can be assessed. Several causal models are postulated to test this relationship, assuming that the socioeconomic status of the Puerto Rican municlplos and the partici pation of females in the labor force are intervening variables between the levels of urbanization, industriali zation and fertility ratios as recorded in the censuses of
1 9 5 0 and i9 6 0 . The theoretical and methodological grounds on which these models are built are presented in the next two chapters. CHAPTER II
MODERNIZATION AND FERTILITY: A THEORETICAL FRAMEWORK
The decline in fertility levels in modem developed countries is the outcome of changes in socio-structural processes and individual decision making. The understanding of these two factors, societal influence and individual decision, is the major focus of attention on fertility research. This study addresses itself to the influence that some macro-social structures have exercised upon community fertility levels. Indicators of three major factors were selected for detailed analysis: (1 ) urbaniza tion and industrialization; (2) socioeconomic status (SES); and (3) women's participation in the labor force. The first assumption is that modern urban-industrial life produces socio-cultural changes that constrain fertility performance. In this process of urbanization and industrialization specific values, attitudes, and abilities are developed which allow individuals to adequately function in an urban society. The second assumption is that in the process of modernization the community's socioeconomic status mediates the influence on fertility rates. Increasing SES usually means that the educational level of the population is raised so that there is greater probabilities of people planning
19 20 their lives according to future goals. Increasing income and occupational status usually means changes in the attitudes of individuals with the emergence of new social aspirations so that people's emotional values shift to more rational decisions in relation to fertility per formance, The final assumption is that increasing labor- force opportunities and changes in the women's roles in an urban-industrial society influence women to prefer a smaller family size, therefore lowering community fertility levels.
Urbanization. Industrialization and Fertility
Malthus was one of the first writers to ascertain the existence of the relationship between population trends and consumption patterns in economic theory. He advanced the following two well established generalizations in the social sciences: (1 ) that human beings usually tend to demand more goods than they actually need to maintain their level of subsistence; and (2 ) that through the process of free universal education the population of the lower classes increase their aspirations, taking the upper classes as their reference groups. This desire for goods and higher educational attainment will make the individuals regular consumers. Consumption and education will help the economy to grow and keep the society in balance as a result of the internalization of the norm of small family size that was 21 prevalent among the members of the upper classes. Thus according to Malthus^ economic as well as social conditions, manifested in terms of per capita income and standard of living, will affect the growth and size of populations.^
More recently, during the first decades of the present century, Thompson^ envisioned the close relation ship between modernization and population trends. His findings have led to the definitions of what is known as the Theory of the Demographic Transition, As originally formulated this theory was conceived of as eracompassing three types of countries at different stages in their process of modernization. One group was formed by those countries where both birth and death rates are subject to little voluntary control, and where the positive checks determine the size and growth of population. These countries are identified as "preindustrial societies," with high mortality and high fertility and low natural popula tion increase. The second group was composed of those countries where birth rates are coming under control, but
^Thomas R. Malthus, An Essay on the Principle of Population (London: Reeves and Tuner, 7th ed., lo72). For a similar treatment of Malthus' theory, see for e.ample, William Pettersen, "The Malthus-Goodwin Debate, Then and Now," Demography, 8 (1971), pp. 13-25, ^Warren S. Thompson, "Population," American Journal of Sociology, 34 (1929), PP. 959-975» rather slowly* The death rates are declining more rapidly
than the birth rates, so that there is an increase in natural growth or at least it is not declining. These countries are identified as "societies in transition," The last group was constituted by countries with very rapidly declining birth rates, but low death rates, approaching a stationary or decreasing population. These countries are identified as "modem societies," Generally speaking this theory of the demographic transition as been supported by empirical evidence from many different societies. However, the validity of some of its theoretical components has been questioned by many social scientists. For example, Van Nort and Karon3 criticized the theory for its false prognosis concerning Western population trends. Deducting from the theory, Thompson^ saw the population of western societies as "stationary", and Notestein^ as an "incipient decline,"
Both interpretations were completely undercut by the rise
3Leighton Van Nort and Bertram P, Karon, "Dem ographic Transition Re-Examined," American Sociological Review. 20 (I960), pp, 387-395. ^Warren S. Thompson, Plenty of People (New York: Ronald, Revised edition, 1948H 3prank W, Noteste in, "Population - The Long View," in Theodore W. Schultz, ed,, Food For the World (Chicago: university of Chicago Press, 194-5), PP. 35-37. 23
in western fertility commonly known as the post-war "baby boom."^ Among those demographers whose explanations are given in terms of the Theory of the Demographic Transition, two theoretical streams have developed: (1 ) one group has presented empirical evidence to support the proposition concerning the inverse relationship between modernization and fertility; (2 ) the second group has presented contra dictory evidence. Some of their views are summarized below. For example, in 1929, Whelpton? analyzed the process of industrialization in the United States since 1800, and its effects on natural increase. He concluded that industrialization has cut down the rate of natural increase of population. Jaffe^ studied urban-rural dif ferential fertility in a number of non-European countries as of the present time and in a number of European nations and in the United States during the early nineteenth century. He showed that with only one exception the rural fertility rate was observed to be substantially higher
decent reformulation of the theory takes different criticism into account. See, for example, Donald 0. Cowgiil, "Transition Theory as General Population Theory," Social Forces. 4l (1963), pp. 270-2?^. Kingsley Davis, Population Index. 29 (1963), pp. 3^5-366. 7p. K. Whelpton, "Industrial Development and Popula tion Growth," Social Forces. 6 (1928), pp, 4-^8-467; 629-639. ®A. J. Jaffe, "Urbanization and Fertility," American Journal of Sociology. 48 (1942), pp. 48-59. 24 than the urban rate. What factors account for this urban- rural differential fertility? He found that, The answer which the majority of population students believe to be the most plausible lies in the field of standards of living. Although the various theories advanced have all differed somewhat from one another, they may be sum marized as follows. Let us consider the ‘■plane of living” of a population group as the sum total of all goods and services available to that particular group; let us consider the "standard of living" as that plane of living which the group desires for itself and believes it is in a position to attain. We then find that fertility decreases as the ratio of the standard of living to the plane of living increases. In other words, when people want "luxuries" or are "ambitious" or are seeking "social advancement," they find it necessary to limit the number of their children.9
Kirk’s^O findings support the generalization of the inverse relationship between industrialization and fertility. He contends that the rational control of human fertility for declining birth rates is associated with increasing modern ization. Furthermore, he found that large families are an economic handicap and produce social inconveniences in con temporary urban society. Blacker^^ in a broad view of the world’s death and birth rates concluded that high fertility
9lbid., p. 59 l^Dudley Kirk, Europe’s Population in the Interwar Years (Paris: UNESCO, 1946).
P. Blacker, "Stages in Population Growth," The Eugenics Review. 39 (194?), pp. 88-101. 25
are reduced probably as a quasi-automatic by-product of
industrial development, Irene Taeuber,^^ in her study of the Population of Japan, analyzed the interrelations
between industrialization, urbanization and fertility. She noted that,
The rapidity of the decline in fertility was related to the extent of the economic and cultural changes that influenced individuals and families. Industrial employment and urban residence that left cultural milieu and values untouched had little influence on fertility. As industrialization and urbanization developed, increasing proportions of the population were influenced directly or indirectly by them. Economic inadequacy, cultural stability, intellectural quiescence, and high fertility became an associated complex of life and values among even more limited groups. The economic and cultural changes were not con fined to geographic area, occupation, or social structure. It is this sense that the experience of Japan suggests that declining fertility is a necessary correlate of industrialization and urbanization.13 Recently, Davis1^ added further support to the proposition of the inverse relationship between moderniza tion and fertility. He observed that Taiwan has been used by other demographers as an example of failing birth rates as a favorable response to a well organized program to make contraceptive devices available. According to Davis
12Irene Taeuber, The Population of Japan (Princeton: Princeton University Press, 1958).
13lbid., p. 257. 1^Kingsley Davis, “Population Policy: Will Current Programs Succeed?" Science. 158 (196?), pp. 730-739. 26
this is a misinterpretation of social reality. The fer tility decline in Taiwan, he said, is a response to modern ization similar to that made by all countries that have be come industrialized. These observations can be extended to the analysis of birth rates in Korea and similar developing nations. Contrasting research presents empirical evidence questioning or rejecting the viewpoint that modernization affects fertility performance. For example, Cowgill^^ questioned the existence of the inverse relationship in transitional societies, and he suggests that the fertility of some underdeveloped areas is in fact increasing. Robinson^^ gives evidence at variance with the widely ac cepted generalization that rural fertility is higher than urban fertility. Heer and T u r n e r ^ 7 in their study on
Latin American Fertility came to the following conclusion: In summary, we feel that the results we have
^•^D.O. Cowgiil, "The Theory of Population Growth Cycles," American Journal of Sociology. 55 (19^!'9), pp. 163-lWI ^^Warren C. Robinson, "Urban-Rural Differences in Indian Fertility," Population Studies. In- (1961), pp. 218-23^. See, also, his article, "Urbanization and Fertility: The Non-Western Experience," Kilbank Memorial Fund Quarterly. ^1 (1963), PP. 291-308, ^^David N. Heer and Elsa S. Turner, "Areal Differences in Latin American Fertility." Population Studies. 18 (1965) PP. 279-292. 27
obtained are such that serious consideration must be given to the hypothesis that a rapid increase in the level of economic development tends, ceteris paribus. to lead to higher fertility. Of course the other factors are never equal. What appears to happen can be stated as follows. An increase in the level of economic development leads to an increase in fertility as married couples become more optimistic concerning their future economic status. On the other hand, the increase in the level of economic development then sets in motion other forces, such as increased knowledge and use of birth control and increase in net economic cost of children, which tend to reduce fertility. In the long run, the forces depressing fertility tend to be stronger than the forces increasing fertility unless the increase income per head continues at a high rate. Thus many, if not most, nations exhibit the classic pattern of fertility decline with advancing industrialization,
In a more recent article, Heer^9 questioned the influence of economic development on fertility. His results imply that economic development, if it is to be effective in reducing fertility, must be accompanied by certain changes in social structures. More recently, Zarate^® has demonstrated that the over-all fertility in
iSlbid., p, 290,
I9David M, Heer, "Economic Development and Fertility," Demography. 3 (1966), pp. 423-444, 20Alvan 0, Zarate, "Fertility in Urban Areas of Mexico: Implications for the Theory of the Demographic Transition," Demography, 4 (1967), PP. 363-373. "Differential Fertility in Monterrey, Mexico, Prelude to Transition?" Milbank Memorial Fund (Quarterly. 45 (1967), pp, 93-108. "Some Factors Associated with Urban-Rural Fertility Differentials in Mexico," Population Studies. 21 (1967), pp. 283-293. 28
Mexico has risen since 1940, and that this rise is more pronounced in large urban areas. It is suggested that among certain segments of Mexican society, the- response
to economic development has been an increase rather than a reduction in fertility, A summary picture of the discussion around the interrelations between industrialization, urbanization and fertility is presented in Table 6 , The authors have been purposely selected so that they are not a random sample from the pool of demographers. Their views, for classificatory purpose, are taken as they are expressed in the specific titles. As may be seen in this Table 6 , there appears to be a theoretical swing along the time dimension. The earlier publications tend to give more general support to the in verse relationship between modernization and fertility than the more recent ones. This variation may be due to the fact of the emphasis placed on comparative studies and new approaches in the field of population studies.
Socioeconomic Status and Fertility As a consequence of the process of modernization, people become more mobile., their achievement motivation is enhanced, and the opportunities for attainment increase.
These aspects are stressed by Dumontin his classical
2iArsene Dumont, Depopulation et Civilisation: Etude Démographique (Paris: Lecrosnier et Babe, 1890), TABLE 6. COMPARISON OP RELEVANT PUBLICATIONS CONCERNING URBANIZATION, INDUSTRIALIZATION AND FERTILITY.*
Generalization: There is an inverse relationship "between urbanization, industrialization and fertility.
Supporting Findings Questioning or Rejecting Findings
Author(s) and Title Date Author(s) and Title Date (Year) (Year)
Thomas R„ Malthus, An 1872 1. Frank W. Notestein, 19^5 on the Principle of Population, "Population the Long View."
2. P. K. Whelpton, "Industi'ial 1928 2. D. 0. Cowgiil, "The Theory 1949 Development and Population of Population Growth Cycles." growth."
3. Warren S, Thompson, 1929 3. Leighton Van North, 1956 "Population." "Biology, Rationality, and Fertility: A Footnote to Transition Theory." 4, A. J. Jaffe, "Urbanization 1942 4. Norman Ryder, "The 1957 and Fertility." Conceptualization of the Transition in Fertility."
5. Dudley Kirk, Europe » s 1946 5. Richard L. Meier. 1958 Population in the Interwar "Concerning Equilibrium in Years. Human Populations," TABLE 6 — Continued,
6 . C, P. Blacker, "Stapes in 19^7 6 . Warren C. Robinson, 1963 Population Growth." "Urbanization and Fertility: The Non-Westem Experience,"
7. Irene Taeuber, The 1958 7. David K. Heer and Elsa 196 5 Population of Japan. Turner, "Aereal Differences in Latin American Fertility."
8 . Kingsley Davis, 1967 8 . David M. Heer, "Economic 1966 "Population Policy: Will Current Development and Fertility." Programs Succeed?"
9. Bernard C. Rosen and Alan B. 1971 9. Alvan 0. Zarate, 196 7 Simmons, "Industrialization, "Fertility in Urban Areas Family and Fertility." of Mexico; Implications for the Theory of Demographic Transition."
■^''■Complete exhalt at ions are given in the Bibliography. 31 study of the fertility decline in Prance, and by Banks^^ in his study of family planning among the Victorian middle classes. These two authors gave support to the social mobility/fertility hypothesis as a corollary of the general process of modernization in a society. The general propositions advanced by these two authors are known as the Dumont-Banks' model, which can be summarized as follows:
(1 ) human reproduction must be perceived not in a natural, but in a rational perspective, (2 ) the social structure must be open with real opportunities and channels of social mobility for those who fulfill their family responsi bilities, (3 ) as a by-product of modernization, there is a rise in expectations and social class aspirations; aiicl (4) some kind of knowledge and birth control devices should be available for those who desire to control their fer tility, and as a consequence move up in social prestige. The Dumont-Banks’ model has been very useful in explaining the past demographic history of countries. For example Glass^^ gives evidence contending that the dif ferences between social classes in the United States were
A. Banks, Prosperity and Parenthood: A Study of Family Planning; Among the Victorian Middle Classes (London: Rootledge and Kegen Paul, 195^).
23d . V. Glass, Population Policies and Movements in Europe (London: Oxford University Press, 1940). 32 very similar to those in England and Wales, France, Belgium, and the Scandinavian countries. In all these countries fertility has fallen very markedly from about the third quarter of the 19th century. The pattern suggests that the decline in fertility was the result of social and economic changes that introduce the norm of small family size principally among the members of the middle classes. As the small-family norm spread down the social structure, there was a reduction of classes differences in family size. With the decline of differentials by social class, other factors such as religion and ethnicity became more important to explain fertility differentials. However, more recent tests of the Dumont-Banks' model in the Itaited States and one in Australia suggest that there is no relation between mobility and fertility. For example, R. Freedman found that, The American findings may indicate what happens in a society when mobility becomes so predictable and routine as to minimize its social and monetary costs and when the goal of mobility is a life style which includes a moderate number of children .... In a society with high mobility even the nonmobile may limit family size to maintain their place in the social order. They must run in order to stand still.24-
^^onald Freedman, "The Sociology of Human Fertility: A Trend Report and Bibliography," Current Sociology. 10-11 (1961-1962), p. 60. 33
Tien25 examined in some detail the relationship between mobility and family size and the timing of first birth within marriage among 126 university teachers in Australia. The results imply that family size per se is not related to social mobility. However, the timing of first birth within marriage is consistent with the hypothesis. In summary, this standard generalization of the inverse relationship between social mobility and fertility
is based on the assumption that fertility control is started by the upper and middle classes, and later in the process the small family size norm is adopted by the working classes. After the process has been completed a reverse pattern may be expected in which the upper classes will have more children than lower classes because they can afford them. However, a convergence toward small family size has been observed in modern developed countries where the relationship between social class and fertility may eventually disappear. Several other attempts^é have been made to present empirical evidence to
25Yuan H, Tien, "The Social Mobility/Fertility Hypothesis Reconsidered: An Empirical Study," American Sociological Review. 26 (1961), pp, 247-257.
26see, for example, Jerry Berent, "Fertility and Social Mobility," Population Studies. 5 (1952), pp 24-5-260; E. Digby Baltzell, ‘'Social Mobility and Fertility within an Elite Group," Milbank Memorial Fund Quarterly. 21 (1953), pp. 411-420; Charles P. Westoff, “The Changing Focus of Differential Fertility Research; The Social Mobility 34
support or reject the social mobility hypothesis. The findings of these investigations are often conflicting: some.report findings that support the inverse relation ship; some others indicate diminishing magnitudes on the relationship.
Very often, social mobility is operationalized or determined by variations in socioeconomic status measured in terms of occupation, education, and income. Scientists interested in population studies have been unable to use the more refined indices of social class developed in the social sciences, probably because of the difficulty of collecting this type of information but, above all, because the availability of official information on income, occupation, and education, for populations has resulted in more practical, inexpensive, fruitful research efforts. These three categories have
been used in different ways: (1 ) researchers have com bined them to form an index of SES; (2) most contemporary
Hypothesis," Milbank Memorial Fund Quarterly. 31 (1953), pp, 24-38; John F. Kantner and Clyde V, Kiser, "The Interrelation of Fertility, Fertility Planning and Inter- generational Social Mobility, " Milbank Fund Quarterly, 32 (1954), pp. 69-103; Ruth Hiemer and Clyde V, Kiser, "Economic Tension and Social Mobility in Relation to Fertility Planning and Size of Planned Family," Milbank Memorial Fund Q.uarterly. 32 (1954), pp. 294-311; and Wolf Scott, ‘Fertility and Social Mobility Among Teachers," Population Studies. 11 (1958), pp, 251-261, 35
social scientist have used occupation as probably the
best single index of social class; and (3 ) some authors have utilized education and income as indicators of SES
differentials. In this study these first two variables have been selected to indicate the community' socioeconomic level. A vast amount of demographic studies have dealt with the relationship between these indicators of socio
economic status and fertility. In modem Western societies the typical pattern has been that the higher the family's socioeconomic status, the fewer children it has. This generalization is more tenable when societal comparisons
are made. It has been shown that modern Western societies, in general, tend to have lower fertility rates than those
of underdeveloped or developing societies. It has also been found that within the same society, regional dif ferences in fertility levels are associated with the socioeconomic development of communities. Jaffe,^7
for instance, in his study of fertility differentials among the white population of Early America divided the inhabitants of New York, Boston, and Providence by the
taxes they paid; the rural population of the New York
27a , j . Jaffe, "Differential Fertility in the White Population in Early America," Journal of Heredity. 31 (19^0), pp. #7-411. 36
state by the property they had, and the population of the
Southern states by the number of slaves they owned. He found, in all the cases studied, an inverse relationship between socioeconomic status and family size. The most important American studies of family planning and fertility can be classified in two types:
(1 ) those studies based on large-scale field surveys such as the Indianapolis Study, the Growth of American Families Study (GAP) and the Princeton studies, and (2) those studies based on official government data (Current Population Survey and Vital Registration Statistics) such as the series of studies of Cohort fertility by P. K. Whelpton and his collègues^® and the study on the fertility of American Women.In the Indianapolis Study, the first hypothesis listed was: "The higher the socio-economic status, the higher the proportion of couples practicing contraception effectively and the smaller the planned families." The first part of the hypothesis was definitely borne out; increases in socioeconomic status means increase
28see, for example, P. K. Whelpton, Cohort Fertility: Native white Women in the United States (Princeton: Princeton University Press, 195^). 29wilson Grabill, Clyde V, Kiser and P. K. Whelpton, The Fertility of American Women (New York: John Wiley and Sons, 1950)." 37
in the proportion of couples practicing contraception. The second part of the hypothesis was not supported. The findings in relation to this hypothesis are summarized as follows: As expected, the familiar inverse relation of fertility to socio-economic status is rather sharply manifested for the total sample of "relatively fecund" couples. It is also found to some extent within the "number planned" group considered separately. Within the "number and spacing planned" group, however, the opposite type of relation is found. The fertility rates for this group______are relatively low, but they tend to be directly instead of inversely related to socio-economic status. This direct relation is most sharply manifested when husband's income is used as the measure of socio economic status, but it is also found rather consistently in classifications by rental value of the home, net worth, occupation, education, and score on Chapin's Social Status Scale, 30
In the Princeton and GAP studies, unlike the
Indianapolis Study, the association between socioeconomic status and fertility is non-existent or very modest. In these studies, socio-economic status was divided for analytical convenience as well as conceptual refinement into three components: (1) education, (2) social status
as reflected in occupational prestige and other indices; and (3) economic status, indexed by income and related
30ciyde V, Kiser and P. K. Whelpton, "Resume of the Indianapolis Study of Social and Psychological Factors Affecting Fertility," Population Studies. 7 (1953), p. 97. 38 measures. In general, researchers found that a direct relationship between higher socio-economic status and desire for larger families and successful contraceptive record was partly borne out. Education appears to be more important than income, occupation, and rural back ground. For Protestants and Jews the relationship between education and success in family planning was positive in direction; for Catholics, a negative relationship emerged. With the second component of SES, the social dimension, a positive association with famil.y-size preferences and successful fertility planning was found among the Jewish group. For Catholics, only slight positive relationship appeared, and for Protestants little association or no relation was observed. With the third component of SES, the economic, hardly any relationship was present for the total sample. 31
Studies based on official data have shown that for the prewar period there is considerable evidence of the negative association between fertility and SES as measured
31nharles F. Westoff, et. al., Family Growth in Metropolitan America (Princeton: Princeton University Press, 1961), pp. 212-236. For a summary of findings of GAF and Princeton Studies see, for instance, Ronald Freedman, "American Studies of Family Planning and Fertility: A Review of Major Trends and Issues," in Clyde V. Kiser, Research in Family Planning (Princeton: Princeton University Press, 195^), pp. 212-22?. 39 by occupation, education or income. But during the post war period, Grabill, Kiser and Whelpton32 noted that there is no doubt of an existing contraction in fertility dif ferentials by occupation of the husband and education of the women. More recent studies have demonstrated that the pattern of actual and completed fertility still reflects the negative association between SES and fertility, Kiser, Grabill and Campbell33 in their analysis of trends and variations in fertility in the United States found that; (l)Because 1940-50 increases in fertility of white ever-married women 20-39 tended to be directly associated with educational attainment, the tra ditional inverse relation of fertility to educational attainment narrowed considerably. The maintenance, or even enlargement, since 1950 of the educational differentials in fertility among white ever-married women unver 25 years of age and among nonwhite women under 30 suggest that the phenomenon of educational differentials in fertility is not one that soon will disappear altogether. Among women under 25 years old, the fertility of the nonwhite surpassed that of the white women at all educational levels. Among women 25 years of age and over and of college attainment, the fertility of nonwhite wives fell below that of white wives. At lower educational levels the nonwhite women tended to exceed the white women with respect to family size and the percentage of this excess tended to increase with lowering of educational attainment,
32wilson Grabill, et, al., op. cit., pp. 113-261; 380-419. 33ciyde V. Kiser, Wilson H. Grabill and Arthur A. Campbell, Trends and Variations in Fertility in the United States (Cambridge: Harvard University Press, 1968). 40
(2 )Among both white and nonwhite women, married and husband present, the average number of children ever b o m tended to be inversely related to occupational status of the husband, (3)The relation of income of the husband during 195 9 to number of children ever b o m to white women, married and husband present, differed sharply by age of woman. The relation was direct at ages 2 5 -2 9, and in verse at ages 30 and over. A plausible interpretation of this is that young people of high income are more likely than people of low income to concentrate their child bearing into a relatively short period after marriage. Being more adept at family planning, they are in position to do this,34
Ecological studies on fertility differentials among areas within the same society or between different countries have contributed to the literature on the relationship between SES and fertility. For example,
Wrong35 in his study of fertility differentials in Western nations, noted that from the beginning of the decline in the birth rate to 1910, there appeared to be an Inverse relationship between socioeconomic status and fertility. In the second period, from 1910 to 1940, a contraction of the relative differences in fertility among socioeconomic groups occurred. Clearly the degree to which birth rates were inversely associated with social class diminished
% b i d , p, 178; 207 and 235.
35Dennis H, Wrong, "Trends in Class Fertility in Western Nations," Canadian Journal of Economics and Political Science. 24 (1958). on, 216-229:.... 41 between 1900 and 1940* After 1940, the Baby Boom occurred, "Increases in proportions of marriages, a decline in the average age at marriage, a reduction in the numbers of women remaining childless, and a slight increase in the average size of completed families appear to have been the major demographic trends underlying the general rise in indices of current fertility.In summary, several studies have shown that the traditional inverse relation ship between SES and fertility observed in the United States for many years has diminished and tends to disappear in the population at large. For example, Mayer^*^ has attributed this factor to the general narrowing in class differences as a result of the general adoption of the middle class norm of the small family size spread out in the total population of the country, with the exception of some minority groups where "high" fertility is still prevalent. The argument and debate over the relationship between indicators of SES and fertility are still present, For instance, in a more recent analysis of United States
36ibid. p, 226,
3?Kurt Mayer, "Diminishing Class Differentials in the United States," Kyklos. 12 (1959), pp. 605-628. 42 fertility trends and differences, Westoff and Westoff38 based on the 196 5 National Fertility Study, found that the higher the education, the lower the fertility, with a gradual adoption of lower fertility by those in the less educated groups. There still remains a stronger negative association between education of the wife and fertility. Women with fewer years of school completed tend to have a higher number of children; however, over time this generali zation is changing as more women attend college and fewer people with only elementary education fade into the past. They also found that a similar inverse association exists between family income and the fertility of married women.
Kupinsky39 using data from the 1/1,000 sample from the I960
United States Census of Population and the I960 growth of American Families Study, found that the negative relation ship between socio-economic status and fertility among married women is still prevalent but may reflect different patterns of child-spacing rather than completed fertility. The discussion becomes more complicated when
30Leslie A, Westoff and Charles F. Westoff, From Now to Zero. Fertility. Contraception and Abortio: in America (Boston: Little, Brown and Company, 1 9 7I),
39stanley Kupinsky, "Non-Familial Activity and Socio-Economic Differentials in Fertility," Demography 8 (1971), PP. 353-367. 43 cross-cultural or comparative studies on fertility in underdeveloped or developing societies are brought into the picture. For example, Heer^O noted that various factors which usually accompany the process of economic development, such as education, serve to reduce fertility.
If his hypothesis is correct, relatively large govern mental expenditures on health and education will enhance the reduction in fertility. These increases in education and health will be obtainable from an increase in national economic level alone. Stycos,^^ on the other hand, in his analysis of human fertility in Latin America concluded that education possesses little of the magic character often attributed to it with respect to fertility. “The fact that Latin American nations with the highest degree of education tend to have the lowest birth rates we found largely explicable in terms of their greater urbanization. Within countries, the clearest ecological relation between educa tion and fertility occurs for the more developed nations, or for the more urbanized areas within nations.
^Opavid M, Hear, op. cit.
4lj, Mayone Stycos, Human Fertility in Latin America (Ithaca, N.Y.: Cornell University Press, 1968),
42 Ibid, p, 268. 44
Like the situation with occupation and education, the negative relationship between income (per capita income, family or individual income) and fertility has been questioned, rejected or redifined = The most prominent has been the so-called "income determination* hypothesis formulated by Becker,^3 in a paper on the economic analysis of fertility he sustains that an increase in income would increase both the quality and quantity of children. Several studies^ present empirical evidence to support Becker's formulation. For example, D, Freed- man^5 using a national sample of women in child-bearing years (18-39) in the United States found that fertility is positively related to relative income. She notes that. There is evidence that husband's income does make a difference over the longer childbearing period if it is considered in relation to the average income for the husband's occupational
^3Gary S. Becker, "An Economic Analysis of Fertility," in National Bureau of Economic Research (Princeton: University Press, I960), pp. 209-231,
^^Among these studies given empirical evidence to support the income hypothesis are W. Stys, "The Influence of Economic Conditions on the Fertility of Peasant Women," Population Studies. 11 (195?), PP. 136= 148. Gordon P, DeJong, "Religious Fundamentalism, Socio- Economic Status, and Fertility Attitudes in the Southern Appalachians," Demography. 2 (1965), PP. 540-548,
^5d . Freedman, "The Relation of Economic Status to Fertility," American Economic Review. 53 (1963), pp. 414-426. 45
status and age. An income which is associated with more children but being in a higher absolute income class means fewer children if the higher income is only what is usual for the husband's age and occupational status.46
Kunz,47 using I960 census data for the United States, showed evidence at variance with the traditional inverse relationship of income and fertility. He found support to the hypothesis that couples with more "relative income," when compared with other couples with the same socio economic status and age, would be able to afford the same style of life and would have additional money to support more children.
In a different analysis, but related to this topic, Easterlin,48 utilizing the Kuznets-cyeles conception of time-series changes, notes that a relationship between the labor market experience (the primary source of income) and the level of population growth may be found. Based on data for the Ihiited States he advanced the following proposition: Assuming continuation into the longer-term future of a reasonably high level employment economy, one
46ibid. p. 422. 47phiiiip R, Kunz, "The Relation of Income and Fertility," Journal of Marriage and the Family 27 (1965), pp. 5 0 9-5 1 3 .
48Richard A. Easterlin, "The American Baby Boom in Historical Perspective," The American Economic Review. 51 (1961), pp. 867-911. 46
might imagine a more or less seIf-generating mechanism, by which in one period a decline in the rate of labor market entry causes a concurrent rise in the rate of change of fertility, and this in turn leads, with a lag of around two decades, to a rise in the rate of labor market entry and a consequent, decline in the rate of change of fertility.^"
Contradictory findings are repeated in different macro- sociological studies that have included income as in dependent variable entering in the explanation of com munity fertility levels. For instance, Adelman^^ in a study covering a wide range of 3 7 countries, suggests that there is a systematic dependence of community fer tility upon some of the important socioeconomic variables.
She speculates that this relationship can be utilized to estimate the potential demographic- changes which may be induced by programs of economic development .51 on the
^9%bid. p. 9 0 0.
50Irma Adelman, "An Econoraitric Analysis of Population Growth," American Economic Review. 53 (1963), PP. 314-339. 51por a recent critical review of Adelman's paper and other authors who have used regression equa tions to predict the impact of socio-economic develop ment on fertility variations, see Barbara S. Janovitz, "An Empirical Study of the Effects of Socioeconomic Development on Fertility Rates," Demography. 8 (1971), pp. 319-330. 47 other hand, Weintraub,^^ in a sample of 3 0 nations including both developed and developing societies, found that popula tion and economic growth are interdependent to a point in which excessive population growth would cancel economic growth. With three independent variables; (l) mean per capita income, (2 ) mean infant mortality rate, and (3 ) proportion of population living in farms; he discovered that fertility was positive rather than negative when associated with per capita income.
A new approach has gained considerable empirical validation to explain the past and current SES fertility differentials. This approach is called the "rural-farm background hypothesis,” which spells out the conditions under which the current negative relationship between SES and fertility exists. The evidence supports the proposition that the inverse relationship between SES and fertility found in urban areas is due to the presence of high fertility people with a rural background who now comprise a large segment of the lower classes in the urban populations. Furthermore, the approach suggests that the negative relationship between SES and fertility does not exist in the indigenous urban population. In
52Eobert Weintraub, "The Birth Rate and Economic Development; An Empirical Study." Econometrica. 30 (1 9 6 2 ), pp. 8 1 2 -8 1 7 . 48 this respect, Goldberg states,
Any study of urban fertility differentials is complicated by the presence of rural elements in the population. With the massive flow of population from rural to urban places, a cross section of an urban population at any point in time will be made up largely of people who themselves have migrated from rural areas, or who are children of migrants who have had some farm experience. About one-third of all adults living in non-farm places in the United States are first generation farm migrants. Formation of values about the role of women, homemaking, and specially size of family are not made independently of this experience. We may expect some carry over of rural values or behavior no matter how dysfunctional they may be in the urban setting,53 Before turning to the relationship between the participation of women in the labor force and fertility, some final comments on the use of different indicators of SES are presented. As pointed out by Wrong (supra p,^1) most contemporary sociologists agree that, if defined with sufficient specificity, occupation is probably the best single index of SES for large-scale statistical
53pavid Goldberg, "The Fertility of Two-genera tion Urbanites," Population Studies. 12 (1959), P. 215. Similar findings supporting the rural-farm background hypothesis are presented by Ronald Freedman, "American Studies of Family Planning and Fertility: A Review of Major Trends and Issues," op. cit. Otis D, Duncan, "Farm Background and Differential Fertility," Demography. 2 (1965), pp. 240-249, and, Neal Ritchey and Shannon Stokes, "Residence Background, Socioeconomic Status, and Fertility," Demography. 8 (1971), PP. 369-377. 49
inquires. However, for P e t e r s e n , 54 education has several advantages over occupation as an index of -SES. Under all circumstances, college graduates and students can be ranked above high school, but the same can not be done when people are classified according to their occupation, for example, the ranking of same professional occupations on the same level with managerial positions. There is also the fact that young men usually start at low-level occupation and move up during their lifetime. Education, on the other hand, when completed becomes a fixed attribute for the rest of their lives. Other authors will argue that income is a more realistic indicator of SES, or that a combination of all is needed. Table 7 presents a comparison of the most relevant published views on the relationship between socioeconomic status and fertility, as discussed in this section.
Women in the Labor Force and Fertility The final aspect to be discussed here is related to the family function or role structure approach from which the "non-familial activity" hypothesis has been derived. This hypothesis states that there is a negative relationship between women participation in the labor
MacMillan Company, 1969), p. 499. TABLE 7. COMPARISON OP RELEVANT- PUBLICATIONS CONCERNING SOCIOECONOMIC STATUS AND FERTILITY.*
Generalization: There is an inverse relationship between socioeconomic status and fertility.
Supporting Findings Questioning or Rejecting Findings
Ai:thor(s) and Date Author(s) and Title Date (Year)
1. Arsene Dumont, Depopulation 1890 1. David Goldberg, "The 1959 et Civilisation: Etude » Fertility of Two Generations Demo,graphique. Urbanites." 2. A. J. Jaffe, "Differential 1940 2. Kurt Mayer, "Diminishing 1959 Fertility in the White Class Differentials in the Population in Early America." United States." 3. D. V. Glass, Population 3. Gary S. Becker, "An I960 Policies and Movements in Economic Analysis of Europe. Fertility." C. V. Kiser and P. K. Whelpton, 1953 4. C. F. Westoff, Family 1961 "Resume of the Indianapolis Study Growth in Metropolitan of Social and Psychological Factors America. Affecting Fertility." TABLE 7 — . Continued
5. J. A. Banks, Prosperity and 195^ 5. R, Freedman, "The Sociology 1 9 6 I Parenthood. of Human Fertility,"
6. Dennis Wrong, "Trends in 1958 6. Yuan H. Tien, "The Social 1 9 6 I Class Fertility in Western Mobility/Fertility Hypothesis Nations." Reconsidered."
7. I, Adelman, "An Econometric 1963 7. H. Weintraub, "The Birth 1962 Analysis of Population Growth." Rate and Economic Development,"
8. C. V. Kiser, W. H. Grabill 1968 8. D. Freedman, "The Relation I963 and A. Campbell, Trends and of Economic Status to Fertility," Variations in Fertility in the United States.
9. L. A. Westoff and C. F, 1971 9. P. R. Kunz, "The Relation 1965 Westoff, From Now to Zero. of Income and Fertility," Fertility. Contraception"and Abortion In America.
10. S. Kupinsky, "Non-Familial 1971 10, J, M, Stycos, Human 1968 Activity and Socio-Economic Fertility in Latin America. Differentials in Fertility."
* Complete, exhaltations are given in the Bibliography. 52 force and fertility levels. In short, when women work in an industrial, urban society, they tend to have fewer children. In fact, in Western countries, female labor force participation has been one of the most impressive indepen dent variables used to explain fertility performance, parallelling the effects of religious affiliation. The inverse relationship between the labor=force participation of married women and their family size has been very well documented in census data for Western Europe and the United States.In the Indianapolis Study, women participation in the labor force was correlated with both fertility- planning status and size of the planned family. Pratt and Whelpton^^ indicated that an inverse relationship between "fecund" women working and family size was observed in the Indianapolis Study. Furthermore, they found that not only women participation in the labor force was inversely related to fertility, but women participation in formal organizations, as an indicator of nonfamiliai activity, was also, negatively related to actual and desired family
^^United Nations, The Determinants and Consequences of Population Trends (New York: Population Studies, United Nations Publications, No. 1?, ST/SOA/Ser. Al?, 1953), PP. 88-89. ^^Lois Pratt and P. K. Whelpton, "Social and Psychological Factors Affecting Fertility." Milbank Memorial Fund Quarterly. 30 (1956), p. 1245-1È80. 53
size. Utilizing data from the "Growth of American
Families" Study (GAP), Ridley37 found that the longer the
work experience of married women, the smaller the size of family these women are likely to expect. In effect, her data showed that wives who have worked five or more years since marriage expect on the average approximately
one child less than married women who have never worked. However, this study could not show whether this inverse relationship was due to the fact that, "Wives want small
families in order to be able to work, or they want and expect small families for other reasons which nevertheless
free them for w o r k , "58 Furthermore, Namboodiri,59 using
data from the GAP study (1955) and confining his analysis to non-farm women who were married only once and who had at least one live birth, demonstrated that the duration
of the wife's employment is significantly related to the spacing of children as well as their number. He also showed that the relationship persists in a significant
57jeanne C. Ridley, "Number of Children Expected in Relation to Non-Pamilial Activities of the Wife," Milbank Memorial Fund Quarterly. 37 (1959), pp. 277-296,
58ibid,, p. 293 59n. Krishnan Namboodiri, "The Wife's Work Experience and Child Spacing," Milbank Memorial Fund Quarterly. 42 (1964), pp. 65-75. 5^ part of the population of the United States even when controlling for religious affiliation. In fact, he found that non-Catholic women who work longer have fewer children, and the few they have are b o m at longer intervals apart.
For Catholics the inverse relationship between working and
fertility is quite strong; however, when they control far spacing of children, the relationship is relatively weak. In general the findings reported in the Indianapolis Study and the Growth of American Family Study are supported by
the Princeton Study.
Grabill, Kiser and Whelpton^^ using census data
(1 9 5 0) for the United States calculated age specific rates of children ever born for ever-married white women, by residence and labor force status. They found that within each type of residence (urban, rural nonfarm, and rural farm) the fertility rates were considerably lower for women in the labor force than for those not in the labor force. Further analysis revealed that these findings
apply to nonwhite women as well. Recently, K u p i n s k y 62
^^See, for example, Ronald Freedman, "American Studies of Family Planning and Fertility: A Review of Major Trends and Issues," op. cit., p. 223.
^^Wilson H. Grabill, et. al., pp. 262-272. 62stanley Kupinsky, op. cit. 55 using data from the I960 census of the United States and the I960 GAP Study supported the hypotheses that labor force participation of the wife is highly negatively correlated with fertility. Participation in the labor force produces longer reduction in the fertility of upper status women than for those of lower status. However, he notes that this relationship holds there only for women with rural backgrounds, and it does not hold for those from large urban areas. Freedman,^3et. al., using 1962 Current Population Survey Data in the United States, showed that there is a clear inverse relationship between years worked and fertility. They encountered that the relationship holds whether fertility is measured as actual number of live births or expected births.
Among several metropolitan areas in eight countries, Collver^^ found a negative correlation between women in the labor force and fertility ratio. In an earlier study of 20 countries of varying degrees of modernization, Collver and
^3Ronald Freedman, et. al., "Current Fertility of Married Couples in the United States," Population Index, 29 (1963), pp. 366^391. ^^Andrew Collver, "Women's Work Participation and Fertility in Metropolitan Areas," Demography. 5 (1958), pp. 55-60. 56
Langloiss^^ found a significant high negative correlation (r= -.60) between fertility and women working. According to the regression analysis, the number of children per 1,000 women would decline by 7 for each 1 per cent increase in participation of women in the labor force rate. In their classical study on birth rates and cottage industries, Jaffe and Azumi^^ reported that fertility is highest
among married women who are agricultural workers, and significantly lower among women who are not working. "Among women who are non-wage earners in non-agriculture,
the average number of children born per woman (or per mother) is only slightly less than for women who are not
in the labor force. Among women who leave their homes for work, however, the average number of children b o m is significantly lower than among women who are engaged in cottage industries."6? in summary, they concluded that;
...it seems clear that employment in a non- agricultural industry carried on, at, or very near the residence of the woman, and under con ditions in which she can combine home and work
^^Andrew Collver, and E. Langloiss, "The Female Labor Force in Metropolitan Areas: An International Comparison," Economic Development and Cultural Change. 10 (1962), pp. 3 6 1 -3 9 2.
^^A. J, Jaffe and K. Azumi, "The Birth Rate and Cottage Industries in Underdeveloped Countries," Economic Development and Cultural Change: 9 (I960), pp.'52-63.
^7lbid.. p. 59. 57
duties, is conducive to significantly higher fertility, i.e., higher than her fertility would be if she worked away from home. In both areas the fertility of women who re mained outside the labor force was about the same as (or very slightly higher than) that of women engaged in cottage industries. Women who left their homes for work, however, averaged about one-half child fewer than did women in either of the two preceding groups.
However, not all the studies on fertility and women's participation in the labor force support the existence of the inverse relationship. For example, Stycos,^9 using birth registration data for the city of Lima, Peru, found that the mean birth order for housewives is virtually identical to that of service workers, the latter consti tuting two-thirds of the female labor force. According to these findings, he suggests that in Lima, there is not a clear-cut relation between fertility and employment status. Based on survey data gathered in Turkey in 1963, Stycos and Weller,70 controlling for urban-rural residence, education and exposure to conception within marriage, found no relationship between women's participation in the labor force and fertility. Using special tabulation
^°Ibid.. p. 62. ^9j. Major Stycos, Human Fertility in Latin America, op. cit. pp. 236-259’!!
70j. Mayone Stycos and R. H. Weller, “Female Working Roles and Fertility,' Demography. 4 (196?), pp. 210-217. 58 from the Puerto Rican census of I960, Carleton?^ reported that college women now have more children than do high school graduates when educational differentials are standarized by economic activity, that is to say, assuming 26.9 per cent of the women in each educational group are economically active.
Several reasons have been advanced to explain the inverse relationship between woman participation in the labor force and their fertility performance, (l) B l a k e contends that employment introduces awareness into women’s lives of the opportunity costs involved in childbearing; it exposes them to all kinds of educational influences, in cluding those that will help them to reduce fertility; and it gives them legitimate alternative satisfactions and activities such as recreation, stimulation, creative activity, and financial remuneration. (2) C o l l v e r ? ^ suggest that the participation of women in the labor force has inhibiting effects on fertility, especially
?lRobert 0, Carleton, "Labor Force Participation: A Stimulus to Fertility in Puerto Rico?" Demography. 2 (1965), pp. 233-239. 72Judith Blake, "Demographic Science and the Redirection of Population Policy," in Kenneth C. Kemmeyer, Population Studies; Selected Essays and Research (Chicago: iBand McNally and Co., 1969), PP. 378-400. "
73Andrew Collver, op, cit. 59 in urban areas, because there is an increase in the proportion of women that remain single and because it provides alternatives to child rearing to married women, (3) Weller?^ advanced the hypothesis that participation in the labor increased influence by the wife in family decision-making, particularly with respect to having additional children; this increased influence in decision making is associated with lower fertility among working women; and, above all, the negative relationship between women working and fertility is stronger among wife- dominant and egalitarian families than among husband- dominant couples. Similar contentions are formulated by
R i d l e y , 75 who suggests that the participation of women in the labor force leads to equaliterian relationships between husbands and wives, therefore lowering their number of children, (4) And according to T i e n , 76 dif ferential commitment to the non-familial role has an
7^Robert H, Weller, "The Employment of Wives, Dominence, and Fertility," Journal of Marriage and the Family. 30 (1968), pp, 437-9491 75Jeanne Ridley, "Demographic Change and the Roles and Status of Women," The Annals of the American Academy of Political and Social Science, 375 (1968) pp, 1 5 -2 5 .
7 6 Yuan H. Tien, Social Mobility and Controlled Fertility (Wew Haven: College and University Press, 1965), For a summary presentation of this approach see his article, "Mobility, Non-Pamilial Activity, and Fertility," Demography. 4 (1967), pp. 218-22?, 6o
effect upon actual and expected family size; work or other forms of activities, such as participation in formal organizations outside the home, are incompatible with the
mother role. The result is a role conflict that may produce a reduction in family size* Tien went further to specify the conditions under which the inverse relationship
between women working and fertility holds. Confronting
the question of whether a) wives do not work because they have too many children or because they prefer large
families to employment, b) some wives work because they have few children or they have less children because they want to work or have worked, Tien inferred that, . , . married women with small families are more likely to be career-oriented than those with large families. Not unlike their working husbands, such married women too may seek a place for themselves in the occupational world. They are the working wives who take time off from actual or potential employment to have children.77 On the other hand, there are many married women with large families who also work. Probably they do work in order to
supplement the family income. In this case these wives should not be considered in the same group with the working wives. Tien suggests, Rather, they should be distinguished as the working mothers who, in contrast to the
7?Yuan H. Tien, "Mobility, Non-familial Activity, and Fertility," op. cit. p. 226. 61
working wives, take time off from childbearing and childrearing to work. They work to supplement family income rather than to gain a place of their,own on a par with that of their husbands.7b
To conclude this discussion on the relation between women working and fertility, one additional observation may be advanced. So far, in most of the relevant literature on the non-familial activity-fertility hypothesis, the in verse relationship has been established between women participation in the labor force and their fertility performance. To the author's knowledge, the participation of men in familial activities and its influence in re ducing fertility has not been explored. With the emergence of egalitarian types of families and the increased partici pation of men in household activities, and the observable changes in the traditional male roles in m o d e m societies, the inverse fertility pattern could be explored in terms of males' roles vis-avis females' roles. A summary picture on the relationship between the participation of women in the labor force and fertility is presented in Table 8. Most of the studies concerned with this relationship have found evidence to support the generalization that an inverse association of the non- familial activity of women and their fertility performance
78ibid.. p. 227. TABLE 8. COMPARISON OP RELEVANT PUBLICATIONS CONCERNING THE PARTICIPATION OP WOMEN IN THE LABOR.FORCE AND PERTILITY,*
Generalization: There is an inverse relationship between the participation of women in the labor force and fertility.
Supporting Findings Questioning or Rejecting Findings
Author(s) and Title Date Author(s) and Title Date (Year) (Year)
1. United Nations, The 1953 1. R. 0. Carleton, "Labor 1965 Determinants and Consequences Force Participation: A of Population Trends. Stimulus to Fertility in Puerto Rico?" 2. L, Prat and P. K. Whelpton 1956 2. J. M, Stycos and R, H, 196? "Social and Psychological Factors Weller "Female Working Roles Affecting Fertility," and Fertility,"
3. A. Collver, "Women's Work 1958 3. J. M, Stycos, The Human 1968 Participation and Fertility Fertility in Latin America, in Metropolitan Areas,"
4. J. C. Ridley, "Number of 1959 Children Expected in Relation to Nonfamilial Activities of the Wife." Continued
5. N. K. Namboodiri, "The 196^ Wife's Work Experience and Child Spacing."
6. Y. H. Tien, Social Mobility ,1965 and Controlled Fertility.
7. A. J. Jaffe and K. Azumi, I960 "The Birth Rate and Cottage Industries in Underdeveloped Countries,"
Complete exhalt at ions are given in the Bibliography, 64
exists. Only a few investigations have found evidence at variance with the general trend. In summary, this chapter presented and documented several hypotheses concerning the past and present theory and research on fertility levels in a society in the midst of economic transition. It discussed three basio approaches: (1) The relationship between urbanization, industrialization and fertility; (2) the relationship between SES and fertility, and different hypotheses with independent components such as the social mobility fer tility hypothesis and the income determination hypothesis; and (3) the relationship between women in the labor force and fertility, or in general, the non-familial fertility hypothesis. As it may be noticed, these three dimensions, urbanizations and industrialization, SES, and women in the labor force, have been considered as independent explana tions of couples’ fertility or community fertility levels.
Instead, they should be lumped together in a more meaning ful theoretical and methodological model. These three dimensions are not independent of each other. Increases in urbanization and industrialization in society probably will eventually increase the socioeconomic status of its constituent members, and as a consequences of it, increase the participation of women in the labor force. Furthermore
it is already established that urbanization and industriali zation have a direct effect on fertility, and also they 65 exercise an indirect effect on the birth rates through other sociological dimensions such as SES or women in the labor force. The same proposition can be argued for SES which has a direct effect on fertility, and an indirect effect through other components such as participation of women in the labor force. In short, the data suggests that a more meaningful theoretical explanation and methodological approach is needed. The heuristic value of the approach used here is demonstrated by data from the Puerto Rican census of 1950 and I960. Furthermore, variations present in the network of the relationships among the different components or indicators of the three dimensions can be assessed through time. The present study is not a mere repetition of what had been done in the past. Instead, it is an attempt to incorporate related and specific hypotheses (i.e., urbanization, industrialization and fertility; SES and fertility; and the non-familial fertility hypothesis) into a more com prehensive theoretically meaningful analysis. It is expected for future research that several social and psychological factors that affect the fertility of couples can be brought together in a more coherent theory and methodological analysis. In other words, the schema presented in this study can be utilized to link macro- sociological dimensions (urbanization, industrialization. 66
or modernization in general), individual variables (inter
course, conception, gestation and parturition?^)^ and socio-
psychological variables (attitudes, values and beliefs).
79Kingsley Davis and Judith Blake, "Social Structure and Fertility: An Analytical Framework." Economic Development and Cultural Change, k (1956). pp. 211-235. CHAPTER III
METHODOLOGICAL CONSIDERATIONS
This study tends to provide a test to a general hypothetical construct on the effect of modernization on Puerto Rican fertility as reported in the 1950 and I960 censuses. The analysis is performed at two levels. First, the three dimensions discussed in the preceding chapter are put together in two structural path diagrams postulated for the last two censuses. Second, the individual hy potheses are tested with a longitudinal approach suggested by Blalock,^ but slightly modified to fit the path analysis form, in which in a temporal sequence the values of a variable X at time 2, are a function of the scores the same variable X had at time 1.
Data and Variables Data on six socio-demographic variables were taken from the 1950 and I960 censuses^ for 75 Puerto Rican
1Hubert M . Blalock, Jr., Causal Inferences in Nonexpertmental Research (Chapel Hill: The University of North Carolina Press, 1964). ^U. S. Department of Commerce, Census of Popula tion: 1950 (Washington, D.C.: United States Government Printing Office, 1953)* And, U. S. Department of Commerce, Census of Population: I960 (Washington D.C.: United States Government Printing Office, I9 6 3 ).
67 68 munlclplos (areal units roughly equivalent to counties in the United States), The dependent variable is the fertility ratio give by; Fertility ratios = children under 5 years of age x 1,000. women 14-4^ ye^rs old Five standarized indicators of modernization have been selected that represent the urbanization and industriali zation dimension, the socioeconomic status of the com munity, and the participation of women in the labor force. These independent variables are: 1, percent population urban (living in places of 2 ,5 0 0 and over)
2. percent employed persons in manufacturing 3o median income in dollars 4, median school years completed by adults population 5. percent females 14 years of age and older in the labor force. The fertility ratio was determined as the dependent variable because it is provided similarly in the 1 95 0 and I960 censuses. There are several circumstances that might affect this statistical measurement, for example: (1) high infant and childhood mortality; (2) underenumeration of children under age 5; (3) migration of women; and (4) enumeration of migrant mothers in urban areas that left their children behind to be counted in rural areas. In spite of these shortcomings of the measure selected, this 69 writer feels, however, that the fertility ratio is appro priate for the purposes of this study because: (1) it is
indeed a relative measure of the fertility levels of various aereal segments of the same population; (2) the infant and childhood mortality were already down between 1950 and I960; (3) there are not reasons to believe of an over or underenumeration of children under 5 years ; and (4) it has been shown that the migratory process of Puerto Ricans to the mainland is a family event rather than an
individual occurrence.3 Under the assumption that statisti
cal bias operates in this fertility measure in Puerto Rico,
the perverse effects operate on the numerator as well as in the denominator probably balancing out any substantial distortion on the community fertility levels. The independent variables are taken as they appear in the census books. The Puerto Rican data, as a part of the United States census system, is considered as fairly accurate and trustworthy. The urban population of Puerto Rican municipios comprises all persons living in places of 2,500 inhabitants or more. The percent employed persons
3This fact can be inferred from different publica tions. See for example, A. J. Jaffe, People. Jobs and Economic Development (Glencoe: Free Press, 1959). J. Mayone Stycos, Human Fertility in Latin America, op. cit. And, G. C. Myers and E. W. Morris, "Migration and Fertility in Puerto Rico," Population Studies. 20 (1966), pp. 20-34. 70 in manufacturing includes all civilians 14 years old and over who were working in industries such as lumber and wood products, metal industries, machinery, tobacco manufactures, textile products, apparel, etc. The median income is the datum that divides the population distribu tion into two equal groups, one having incomes above the median and the other with incomes below the median point.
In this case, the median is based on the distribution of persons 14 years old and over with income. The median family income would have been preferred; however, it is not given in the 1950 census. The median number of school years completed is that value which divides the distribution into two groups, the group above having com pleted more schooling and the group below having completed less schooling. This median of school years completed included all persons 25 years old and over. The percent of women in the labor force includes all females 14 years old and over working at the moment of the census. The utility of this variable for demographic research is increased in the Puerto Rican census because this category of women in the labor force does not include persons doing only incidental unpaid family work. Thus, students, housewives, retired workers, seasonal workers, and in mates of institutions are not included in the percentage 71
distribution of this variable
Techniques of Analysis
Since it seems that the nature of the relationship
between fertility and the three selected dimensions, urbanization and industrialization, the community's socio economic status, and participation of women in the labor force is to some extent a function of the general process
of modernization or social development, it is suggested that the dimensions are not independent of each other;
on the contrary they are interdependent so that the net work of the relationship among fertility and the different
indicators should be assesed in a total and comprehensive structural model. The analysis proceeds as follows: (1) Two variables (percent urban and percent in manufacture) are selected as indicators of urbanization and industriali
zation, respectively. Representing the community's SES, the median income and the median of schooling completed were selected. Finally, the percent of females working represents the participation of women in the labor force;
(2) Several multiple correlation and regression problems were solved from which the collective impact of the modernization components upon fertility and the general
^Por a more detailed definition of the variables included see, U. S . Department of Commerce, o^. cit. 72
contribution of each variable to fertility's explanation were assertained; (3) A causal ordering of the three
dimensions was hypothesized for 1 95 0 and I960, and for specific tests of the relationship between each individual dimension and community fertility levels. These causal
models are based on the known Puerto Rican societal development experience and on basic demographic theory spelled out in the preceding chapter; (4) The path co efficients or standarized regression coefficients called for in the models were calculated; (5) The models were modified according to the calculated path coefficients eliminating low path values and then solving for the new
path coefficients called for in the revised models; and (6) The correlation matrices were predicted on the basis of the encountered path coefficients and compared to the original correlations assessing the validity of the models presented. The idea of path analysis was originally developed in biology and by Wright-5 and Li,^ and later developed and
5s, Wright, "The Method of Path Coefficients," Annals of Mathematical Statistics. 5 (1938), pp. 161-215. See, also, "The Interpretation of Multivariate Systems" in 0. Kempt home, et. al. (Eds.), Statistics and Mathe matics in Biology (Ames: Iowa State College Press, 1954), PP. 11-33. ^G. C. Li, Population Genetics (Chicago: Univer sity of Chicago PresF] 1955). See also, "The Concept of Path Coefficient and Its Impact on Population Genetics," Biometrics. 12 (1956), pp. 190-210. 73 introduced in the social sciences primarily by Duncan.7 According to Heise® there are two types of models in path analysis: estimation models and structural models. The estimation models are used for descriptive and measurement purposes, and they are based on a pragmatic attitude of the researcher to specify the network of the relationship among the variables under consideration. The structural models are used for testing hypotheses and theory con struction. In these models a set of recursive equations and the path diagrams are formulated in such a way as to represent the relationships assumed to operate among the variables in the real world. The use of structural models forces the researcher to give a reasonable theoretical explanation for the timing of the variables and a state ment of the hypotheses included in the analysis.
The central idea to path analysis is to isolate from the original zero-order correlation between two variables the direct and indirect effects. The direct effect of a variable on another is called the path co efficient or standarized regression coefficient. The
7o. D. Duncan, "Path Analysis: Sociological Examples," American Journal of Sociology. 72 (1 9 6 6 ), PP. 1-16.
®David R. Keise, "Problems in Path Analysis and Causal Inference," in Edgar Borgata (ed.), Sociological Methodology, 1 9 6 9 (San Francisco: Jessey-Bass, 19o9), PP. 38-73. 74 standarization procedure makes the values of the path coefficients always range from plus and minus unity.
Thus, the zero-order correlation ^xy (standarized from
+1 to -1) is the sum of the direct and indirect effects. This correlation value in terms of regression coefficient (hyx) is given by: (1) ^xy = byx [i] where r is the correlation between the variable X and the variable Y; b is the slope of the regression line con necting X and Y; and S is the standard divitions,
A similar expression can be written for partial correlation coefficients. For example:
(2) ^xy,z = byx.z f 1-^xz Sx (_ 1-ryz Sÿ
The value ^xy.z is nondirectional and only indicates the relationship between two variables controlling for a third. In path analysis the researcher is interested in direc tionality of the direct effects. The path coefficients or Beta weights or standarized regression coefficients indicating the direct effect of a variable on the other is given by:
(3) Bxy = byx F L syj where Bxy is the standarized regression coefficient; byx is the regression coefficient; and S the standard deviation 75
When the values of X and Y are given in standard scores
(Z scores) then equation (3) is equal to (1). Otherwise, the path coefficients can be calculated from equation (4) as follows: (4.) pxy = byx.az [»] where pxy is the path coefficient between X and Y or the direct effect; byx.az is the value of the partial regression coefficient or slope; Sx is the standard deviation of the independent variable; and Sy is the standard deviation of the dependent variable.
However, knowing only the zero-order correlations among the variables, one can compute the path coeffi cients employing the "basic path theorem" which is written as follows:
(5) 'ij = Z Piq rqj where r is the zero-order correlation; p is the path coefficient; i is the number of the dependent variable; j is the number of the independent variable, and the index q runs over all variables from which there are direct paths leading to X^. A simple procedure to calculate the path coeffi cients from the empirical correlations in matrix operations has been advanced by N y g r e e n . 9 poj, example, in a recursive
°G. T. Nygreen, "Interactive Path Analysis," The American Sociologists. 6 (1971), pp. 37-^3. 76 causal model with five variables and with all paths drawn, if the researcher wants to calculate the path leading from
1 to 5; from 2 to 5; 3 to 5; and 4 to 5, in matrix form the procedure is:
I'll 1*12 1*13 1^141*14" ^51 ■-51 1*21 1*22 1*23 1*24 ^52 1*52
1*31 1*32 1*33 1*34 ^53 -53
_i*4l % rzj.3 ^44r i ^ / 5 4 -54 A X b
This leads to a series of simultaneous equations of the form: (6) A X = b where A is the matrix of known correlation coefficients;
X is a vector of particular path coefficients as designated in the "path theorem" ; and b is another vector of known correlation coefficients. If A is a nonsingular matrix, that is, if the matrix A has an inverse such as that the determinant A of the matrix A is not equal to zero, then the solution to equation (6) is: (7) X = A“^ b where the vector X is equal to the vector b premultiply by the inverse of the matrix A. 10
l^This procedure is very useful when a correlation and regression computer program is not available. Other wise, the procedure has only a heuristic value. 77
Before turning to one of the most crucial aspects in path analysis, that of predicting the original correla tion. matrix from the known path coefficients, we should mention briefly the basic assumptions that are involved in the formulation of a path analysis: (1) The assumption of interval scale measurements on all variables is no longer required since Boyledemonstrated the use of path analysis using ordinal data, and Boudoi^^ developed the dependency analysis using nominal data through the cal culation of Coleman'8^3 measures of effects. (2) Homo- cedasticity, that is, the standard deviations (or vari ances) of the variables should tend to be equal in rela tion to the regression line. (3) Low multicollinearity is assumed, however, when there is high multicollinearity there are procedures such as the oblique principal com ponent analysis to create new dimensions with low multi- cellenerity and then enter the dimensions in path analysis form. (4) The effects between variables are linear and
p . Boyle, "Path Analysis and Ordinal Data," American Journal of Sociology. 75 (1970), pp. ^61-480.
Boudon, "A New Look at Correlation Analysis," in H. M. Blalock and A. B, Blalock (Eds.), Methodology in Social Research (New York: McGraw Hill, 1968), pp. 199-235,
-3James S. Coleman, Introduction to Mathematical Sociology (Glencoe: The Free Press, 196ÏÏ'), chapters ^ and 6. 78
additive as indicated by the "path theorem". (5) There is a one-way causation. That is, the path coefficients are unidirectional in a causal model. And (6) the re
siduals are uncorrelated with any endogenous independent variables.14
Estimation of the Empirical Correlation Matrix In sociology, the growing application of causal
models and structural systems have a direct bearing on evaluation, reformulation and construction of sociological theory. The use of path analysis forces the social scientist to be precise in the theoretical formulation
of his problem and statement of hypotheses. The achieve ment of this conceptual clarity is the first step in hypotheses testing and theory construction. The rela tionships described in the hypotheses are then formulated in a set of recursive equations and in a structural path
diagram. While many researchers solve for the path co efficients called for in the path diagram, they frequently neglect to evaluate the overall adequacy of the model.
Thus, the readers are frequently left with the question as to how good a fit the model is to social reality.
^^For a more comprehensive treatment of the assumption basic to formulations of causal model in path analysis form, see D. R. Heise, op. cit. See also G. T. Nygreen, op. cit. 79
Testing the mathematical adequacy of a structural path diagram is the most important aspect of path analysis. However, it is the most neglected step by users of this statistical technique. There are two mathematical pro cedures to estimate the original correlation matrix;
(l) using the path theorem to get the basic parameters for estimation; (2 ) using a paradigm via matrix operation. Path Theorem. For multivariate analysis, the path theorem is stated above in equation (5). In this instance, the zero-order correlation between two variables in a recursive system can be expressed as the sum of the direct and indirect effects of the independent variables (j) and the dependent variables (i) which are transmitted via other independent variables (q ) included in the system. ^-5 In a fully recursive causal model with all possible paths drawn the value of the estimated correlations r^j are identical to the origiiual zero-order correlations. How ever, when a path is deleted between any j and any i variables, its direct effect is zero. If the predicted correlation approaches the original correlation, then the model can be considered mathematically correct. When the predicted correlation deviates considerably from the
C. Land, "Principles of Path Analysis," in Edgar Borgatta (Ed.), Sociological Methodology 1969 (San Francisco: Jessey-Bass, 1969), pp. 3-37. 80
original correlation, the model is subject to serious question. This approach is based on an exhaustive list of all possible direct and indirect effects traced back from i to j through q«The principle of recalculating the original correlation matrix through the path theorem is very simple for application in a multivariate system of no more than three or four variables. When more vari ables are introduced into the system, the process of estimating the correlations r^j becomes overwhelming. Since most sociological research necessitates the inclusion of large numbers of variables, the recalculation of the original correlation matrix through the path theorem therefore is unmanagable.
Matrix Operation. The second procedure using matrix operations is recommended for those interested in multivariate analysis consisting of more than four vari ables. The paradigm is reduced to a series of equations involving vector-matrix multiplication.^7 Follow this
^^Sorae numerical examples can be found in William G, Spady and Donna Greenwood, "Instant Path Analysis: An Elementary Cookbook," AERA Division Generator. 1 (1970), pp. 3-8. ^"^The Algebraic notation follows Paul Horst, Matrix Algebra for Social Scientists (New York: Holt, R inehart m d W ins ton, 1963). This part is based on the paradigm advanced by David E, Heise, o£. cit.. pp. 70-71. 81 procedure: (1 ) Construct an m x m matrix with all the path coefficients which appear in the final transformed model, and identify the rows of this matrix P as vectors Vj^. For example, in a five-variate case the P matrix will be:
Yo = 1 0 0 0 0
Vl = ?21 1 0 0 0 V2 = P3I P32 1 0 0
V3 = P4 l P42 P43 1 0
V4 = P51 ^52 ^53 P5^ 1
(2) Create an Indentity matrix I, of the same order That is :
0 0 0 0
1 0
0 1
0 0
(3) To estimate the first r^j, that is ri2 » multiply the identity matrix I by the transposed row vector In
18.'The row vector Vq does not have any value in the calculations and is presented for clarity in the discussion 82 matrix form this operation is written as follows:
P21 ^12 1 1
0 = 0 0 0 0 0
Vl
(4) To estimate the empirical correlations r^^, V2j, enter the vector a in the matrix I as the row vector (k + 1), and also enter its transpose as the column vector (k + 1). The resulting new matrix is now identi fied as the matrix D. In matrix form this step is written as follows:
a* =
1 ri2 0 0 0 ?31 ri3
a = ri2 1 0 0 0 ^32 1*23 0 0 1 0 0 1 = 1
0 0 0 1 0 0 0
0 0 0 0 1 0 0
D V2 b
er vector b as a vector (k + 2 ) in the matrix D, and the transpose of the vector b as the column vector 83
(k +2). The resulting matrix is D^. To estimate the empirical correlations r2li., simply multiply Dj by V^, That is in matrix form:
- a' = b ‘ =
1 ri2 ^13 0 0 P41 ri4 a = ri2 1 ^^23 0 0 ^42 ^24 b = ri3 T23 1 0 0 = 1*34 0 0 0 1 0 1 1
0 0 0 0 1 0 0
Dl V3 (6) Finally, enter vector c in the matrix as the row vector (k +3), and its transpose as the column vector
(k + 3). The resulting matrix is D2 . To calculate the empirical correlations rj5 , r2 5 , 1*3 3 , and rj^,^, multiply matrix D2 by the vector Vzp. In matrix form this operation is indicated as follows : 1r a' = b' = c« =
1 0 ri2 ^1 3 ^14 ^51 ^15 1 0 ^12 r23 ^24 ^52 ^25 b = 1 0 ^13 ^23 ^ 3 4 î^53 = ^35 c = 1 0 ^'14 ^24 ^3 4 ^45 0 0 0 0 1 1 1
D2 V4 84
Replace this final vector d in the matrix D2 , as the row vector (k + 4 ) and the transpose as the column vector (k + 4) in the resulting matrix D^; the top or bottom triangular matrix is the estimated correlation matrix. The final matrix is:
a' = b« = c' = d' = 1 ri2 ^1 3 ^*14 ^ 1 5
a = ^12 1 r23 **24 ^2 5 b = 1 ^1 3 ^2 3 ^3 4 ^35 c = ri4 ^24 ^ 3 4 1 ^4 5 d = 1 ^ 1 5 ^ 2 5 ^35 ^43
D3
The procedure suggested here consists of solving for a series of equations that imply the use of vector- matrix multiplication techniques. The derived equations in matrix form are:
I V l = a
D ?2 = b DiV^ = c
DpVit - d
% = Z Where I, D, Di» .Djj are matrices of the order m x m; Vjj, ar e ve ct or s fr om t he ma tr i x P of t heVl, Vg. Vjj, are vectors from the matrix P of theVl, path coefficients; and a, b, c, d . . . . Z are the 85
resulting vectors that enter as row and column vectors in the matrices I, B, I>i , . . , D^. The procedure is very tedious when performed by hand computations. However, it is well suited for use of digital computers, A simple program of vector-matrix multiplication is provided in the appendix for inspection. The program given assumes that the subroutine "vecmat" is available in the time-sharing public computer library. If it is not available, the subroutine can be introduced into the program from any computer subroutine manual.
Testing the Correlation Matrices The final stage of path analysis to be discussed
is concerned with tests for the significance of the dif ferences between the estimated and actual correlation matrices. The first technique described have been pro posed in the mathematical literature for testing correla tion matrices. The second techniques offered are the result of practical experience using simple tests that have shown effective utility,
1, Several procedures with illustrative numerical examples have been presented in the statistical literature to test a null hypothesis specifying a population correla tion matrix (P) and its homogeneity or independence with
samples correlation matrices (R^, R2 » . Kullback, for example, has reviewed the asymptotic behavior of certain 86 tests on correlation matrices and has presented some interesting numerical examples. He has proposed a sta tistic assumed to have "(1) an asymptotic distribution under the null hypothesis, and a non-central under the alternative hypothesis, with appropriate degrees of freedom and non-centrality parameters; (2) has additive properties; and (3) has a convexity property. "^9 Aitkin, Nelson and
Beinfurt^® proposed a number of exact and approximate likelihood ratio tests for correlation matrices. Recently, building upon Kullback*s work, Jennrich^^ has derived an asymptotic X^ test for the equality of two correlation matrices, which has significant promise for use as a test for the significance of differences between the two correlation matrices in path analysis. For this reason the derivation of the test is presented in its complete form.^^
Kullback, "On Testing Correlation Matrices," Applied Statistics. 16 (1967), PP. 80-85.
20d . a , Aitkin, W. E. Nelson, and Karen H, Reinfurt, "Tests for Correlation Matrices." Biometrika. 55 (1968). PP. 3 2 7-3 3 4 .
2^R. I. Jennrich, "Asymptotic X^ Test for the Equality of Two Correlation Matrices," Journal of the American Statistical Association. 6 5 '(1 9 7 0), pp. 904-912, 22lbid.. p. 90S. 87
Let Ri and Rg be sample correlation matrices based on independent samples of sizes ni and Y12 from two p-variate normal populations with correlation matrices Pi and ?2 o If Pi and P2 have a common non-singular value P, then as ni * 00 and n2 >co,
7 ^ 1 (1 - P) Y and - P)- (1) where Y is a symmetric zero diagonal random matrix whose super-diagonal components have a multivariate normal distribution with mean zero and nonsingular covariance matrix r . It follows from the inde pendence of the samples that
niU2 (Hi - R2)- (2) ni + n2
as ni, no »o q . Moreover,
L R = (niRi + n2R2) / (ni + n2 ) yP (3) and
(X, R) -i, (Y, P). (4)
Since x2(Xj_ R) is a continuous function of (X, R), at least for R non-singular,
X2 = x2 (X, R ) ------> X2 (Y, P). (5)
Then it follows that v2 has an asymptotic x^-distri- bution with p(p - l) / 2 degrees of freedom whenever Pi = P2 = P. If Pi = P2 then X, and hence x2, approach infinity as ni, n2 »oo Thus a test 88
based on is sensitive, asymptotically at least, to all departures from the null hypothesis Pj = P2 . Summarizing the computation of x2, let R = (rij),
S = ( 6 ij + rijr ^), c = nin2 /(ni + n 2 ) and
Z = ci-R-^(Ri - R2 ). Then
X2 = I tr (Z2)_dg« (Z) s'^dg(Z). (6 )
Even though this technique was derived to test the equality between two sample correlation matrices draxm from the same population, the statistics can be generalized to test the independence of any two correlation matrices from the same population, from different populations, or sample correlation matrices.
2, To alleviate the statistical and mathematical manipulation involved in Jennrich's test, several simple and practical tests will be offered. Test 1: A basic rule to be applied for testing the adequacy of a path model is to analyze the discrepancies between the original correlations and the estimated correla tions. If the differences do not go above ,0 5 , or the number of such discrepancies is kept small, the model is said to be mathematically sound. Test 2: If the estimated correlation matrix (Re) is from the same population as the original correlation 89 matrix (R), which is the case in path analysis, then Rg is a linear function of R. Thus, if Rg is identical to R, the relationship between the two will be r = 1.0. Since one of the major purposes of path analysis is to eliminate negligible and insignificant paths, the correlation between the expected and actual matrices for a well constructed model should be greater than .90. It should be noticed that no accepted criteria for determining insignificance of path coefficients has been established. Some authors have used the standard error to eliminate paths, as suggested by D u n c a n . ^3 However, when sample size is fairly large, almost any value of a path coefficient will be significant at the .01 or .05. One way to evaluate the importance of a path coefficient in a model is to apply one of the suggested tests in which the path coefficients are not considered independently, but rather are combined with other paths to evaluate the effectiveness of the total model.
Test 3: A procedure that has shown satisfactory results in the practice is presented below. Let R^j^ be the matrix of the differences between R (the original correlation matrix) and R@ (the estimated correlation matrix), such as: R& = R = Re
23o. D. Duncan, op. oit.. p. 7. 90
After Rh has been calculated, compute the mean correlation difference considering the elements r^j of the matrix R^. This mean is simply;
. xa = E I'l L ...... ^ N where is the raeam correlation difference; £ | r^jis the sum of the absolute values of the zero-order correlation differences between the elements of the original and estimated matrices; and N is the total number of zero- order correlation differences. If the two matrices (R and Eg) differ considerably in terms of the mean correlation coefficient (%) and the significance test (using a t or Z test) indicates that the discovered value Xg^ is significant at a specified level ( . 0 1 or
.0 5 ), the formulated path model cannot be accepted as mathematically sound. Test k: An analysis of variance between the two matrices may be applied. In this specific case, with one observation per cell there is no within error term. If the variation between the two matrices is significant
(at the ,0 1 or ,0 5 ), the model being tested should be rejected. To conclude this section, a word of caution: All of the above mentioned tests should be considered as “gross" measures for testing correlation matrices. They 91
are hueristic devices that will help to establish criteria for testing the validity of the path models.
Models and Hypotheses Five models with their corresponding set of
recursive equations and specific hypotheses are tested in this study. They are (1) a general structural path diagram postulated for the fertility ratios of the 75
Puerto Rican munieipios as reported in the 1950 census, identified as Model I; 1950; (2) a general structural path diagram postulated for the fertility ratios of the
75 municipios as reported in the I9 6 0 census, identified
as Model II: 1 9 6 O; (3) a specific structural path diagram formulated to test the particular relationship between urbanization, industrialization and fertility, assuming that the urbanization, industrialization and fertility
levels in I960 are a function of their values in 1 9 5 0, identified as Model III: Urbanization, Industrialization and Fertility; (4) a specific structural path diagram
advanced to test the relationship between the community's
SES and fertility levels, assuming that SES and community
fertility in I9 6 0 are a function of the income, education and fertility levels in 1950, identified as Model IV; SES and Fertility; and (5) a specific structural path
diagram to test the relationship between women's participa tion in the labor force when accompanied by urbanization. 92 and the fertility levels, assuming that the values of these variables in I9 6 0 are a function of the values these variables had in 1950, identified as Model V: Participa tion of women in the labor force and fertility. Model I; 1950: This model and its corresponding set of recursive equations are presented in figure 1, In this model it is hypothesized that the urbanization- industrialization dimension has a direct negative effect on the Puerto Rican fertility. It is expected that the community SES is a function of the level of urbanization and industrialization of the society. It is also expected that the participation of women in the labor force is a function of the levels of urbanization, industrialization, and the SES of the community. It is hypothesized that the community's SES and the participation of women in the labor force have a direct negative effect upon fertility.
Urbanization (Xj) and industrialization (X2 ) are declared exogenous variables in the system. These exogenous variables give formal completness to the path diagram. The other variables, education (X3 ), income (XJ4,), women working (X5 ) and fertility (X^) are endogeous; that is, they are determined or in fluenced by at least one presiding variable included in the model. The curved arrow linking Xi and X2 means that there is not any assumption of causal priority 93
FIGURE 1
MODEL I: 1 9 5 0. GENERAL STRUCTURAL PATH DIAGRAM FOR PUERTO RIGAN FERTILITY.
X6
Where : Xi Urban) = ei
%2 Manufacturing) = ©2
X3 (Education) = P31 + P32 %2 + e3
Xi,, (Income) = P4l X j + Pi|,2 X2 + Pi,.]X3 + e/,,
X3 (Women Labor Force) = P51 Xi + P32 %2 + P53 X3
+ P]i^ Xi,, + 63
X5 (Fertility Ratio) = P6l Xi + P62 %2 + P63 X^ + P5i,, X,^
+ P 6 5 + eg 94 between urbanization and industrialization. However, the Puerto Rican experience supports the idea that earliest in time has been urbanization. The principal preconditions for urbanization that took place in the today developed nations in the Western World (revolution in agriculture, technology, commerce, transportation, and the demographic revolution) do not seem to operate cross-culturally. In the less developed nations, it seems that industrializa tion did not precede urbanization. Even though this is happening, the demographic experience of developed as well as underdeveloped countries permit some empirical bases to postulate the impact of urbanization on fertility trends. As Hauser and Schnore point out:
With the emergence of urbanism as a way of life, rational decision-making was extended to size of family, and fertility was deliberately controlled by urban populations. Within urban areas family planning originated among the elite, better- educated, and higher-income groups and then diffused to the remainder of the population. This process is by no means yet completed. The poor and uneducated even in urban areas are not yet controlling their fertility. Although it is true that birth rates have gone up in urban even more than in rural areas with fluctuations in fertility, the general pattern of lower urban than rural fertility is ubiquitous and persistent. It is also clear in the more economically ad vanced nations that family planning has spread from urban to rural areas and that rural fertility is now also experiencing a great d e c l i n e . 24
^^Philip M. Hauser and Lee F. Schnore, The Study of Urbanization (New York: John Wiley and Sons, Inc., 1965), p. 33. 95
The implications of industrialization on the demographic history of most countries are very similar to those of urbanization. In many ways industrialization is asso ciated with urbanization. However, these two process can vary independently of each other, urbanization can take place without industrialization, and some manufac turing development is possible without large-scale urban ization. In the process of modernization, however, the relationship between urbanization and industrialization is expected to increase. Indeed, in the process of societal development, the cities are the centers of social change. It is in the urban areas that industrialization takes place first and then later may diffuse to the rural sections of the society; thus it is common in a developing society for urban and rural differences to come accentuated in the midst of its economic development process.^5 in fact, ur banization and industrialization are strongly related with aspiration for mobility, achievement motivation and general indexes of socioeconomic status. Through these processes urbanization-industrialization, SES, and women participation
25see, for example. Kent P. Schwirian and Jesus Rico-Velasco, "The Residential Distribution of Status Groups in Puerto Rico's Metropolitan Areas," Demography. 8 (1 9 7 1), pp. 81-90, Kent P. Schwirian and Ruth K. Smith, "Primacy, Modernization and Urban Structure: The Ecology of Puerto Rican Cities," Paper presented at the 1 971 Annual Meetings of the American Sociological Association. 96
in the labor force, eventually fertility will decline. In
general, as Moore has pointed out. As the practice of limiting the size of one's ■family becomes somewhat more widespread, the historical fertility differentials in the west will probably be more or less repeated in the developing areas. That is, urban, professional, business, and managerial groups will probably lead in fertility reduction. Consequently, there will be an inverse relation between fertility and indexes of socioeconomic status. This expectation obtains whether one follows some variant of the mobility hypothesis as the attitudinal factor in family limitation, or simply considers the greater exposure of elite groups to Western ideas and p r a c t i c e s , 26
Thus, urbanization (X^) and industrialization (X2 ) are
viewed as having a positive impact upon education (X3 ), income (Xzj,) and women working (X^), and a negative effect upon fertility. Education and income are viewed as having a direct effect on women working, and negative on fertility. Finally, having women in the labor force is viewed as causing a negative effect on fertility.
Model II; I960. This model is graphically depicted and accompanied by its set of recursive equations in figure 2. In this model, it is expected the exogenous indicators
of the urbanization-industrialization dimension operate directly on fertility and indirectly to SES and women in the labor force. The hypothesis is that the community's
26wilbert E. Moore, The Impact of Industry (Engle wood: Prentice-Hall, Inc., 1965), p. ?4. 97
FIGURE 2
MODEL II: I960. GENERAL STRUCTURAL PATH DIAGRAM FOR PUERTO RICAN FERTILITY.
X6
Where :
{% Urban) = ei
%2 {% Manufacturing) : eg
(Education) = P31 Xi + P32 Xg + 03
X|^ (Income) = Pi+1 Xi + P 42 X g + PZ1.3 X 3 4-
X^ (Women Labor Force) : P51 Xj + P32 X2 + P53 X3
P32*. Xif + 63
X5 (Fertility Ratio) = P6 l Xi + p52 X2 + P63 X3
+ P64- Xj^ + P65 X^ + eg 98
SES in i9 60 is a function of the levels of urbanization and industrialization of the society at that particular
moment. This writer also theorizes that the participation of women in the labor force is a function of both the urbanization-industrialization and SES of the society.
These last two dimensions are expected to exercise a direct negative effect on the community's fertility schedules
in Puerto Rico. More specifically, it is hypothesized that the direct effect of per cent urban, per cent manufacturing, income, education, and women in the labor force to be negative. The direct effect of income and education on women in the labor force is expected to be positive. The urban concentration variable and the per cent of people employed in manufacturing industries are hypothesized to have a positive direct effect on the socioeconomic status dimension. Model III; 1950-1960 Urbanization. Industrializa tion and Fertility. This model and its recursive equations are graphically presented in figure 3. In general, urbani zation (/o urban), and industrialization in manufactur ing) are hypothesized to have a direct negative effect on community fertility levels in Puerto Rico. Furthermore, it is assumed and expected that the values of the variables in i960 are a function of their values in 1930. 99
FIGURE 3
MODEL III: 1950-1960. URBANIZATION, INDUSTRIALIZATION AND FERTILITY.
Where: Xj Urban 1950) : ei
%2 Manufacturing 1950) : 62
X3 (Fertility Ratio 1950) = P3 I Xj + P3 2 X2 + 63
X4 i% Urban i9 6 0 ) = P/fl Xi + P4 3 X3 +
X^ Manufacturing 1 9 6 O) = P52 %2 + P53 X3
P5 4 XJI4. + 63
X5 (Fertility Ratio i9 6 0 ) = P63 X3 + P64 Xzj.
P65 ^5 + ®6 100
Model IV: 1950-1960 Socioeconomic Status and Fertility. This model and its set of recursive equations
are presented in figure 4. Here, it is expected that the
socioeconomic status in a society, measured in terms of education and income, has a negative effect on fertility
levels. Furthermore, it is anticipated that the socio economic status and community fertility in i9 60 are a function of the income, education and fertility levels in
1 9 5 0. Model V; 1950-1960. Participation of Women in the Labor Force and Fertility. This model and its recursive equations are given in figure 5. The partici pation of women in the labor force has inhibiting effects on fertility schedules. The effects of this variable upon fertility is accompanied in this model by the expected negative effects of concentration of people in urban areas upon fertility. It is expected that the values of these variables in I960 are a function of the scores these variables had in 1 9 5 0. 101
FIGURE 4
MODEL IV: 1 9 5 0-1 9 6 0 . SOCIOECONOMIC STATUS AND FERTILITY.
Where :
(Income 1950) : ei
%2 (Education 1950) 62
X3 (Fertility Ratio 1950) ■ P31 Xj + P32 %2 + 63
(Education I960) ^ P42 %2 + P43 X3 + ei|.
X3 (Income I960) ^ P51 + p^3 X 3
P54 X4 + 65
Xg (Fertility Ratio 1 9 6 O) : P63 X 3 4- P64 X4.
P65 ^5 + 66 102
FIGURE 5
MODEL V: 1 9 5O-I9 6 O. PARTICIPATION OF WOMEN IN THE LABOR FORCE AND FERTILITY.
:^6
Where :
Xj Urban 1950) = ei
%2 (Women Labor Force 1950) = ©2
X3 (Fertility Ratio 1950) = P3 I X^ + P32 X2 + 03
Xij, {% Urban I960) “ P4l %i + P4 3 X3 + e/j.
X^ (Women in Labor Force I960) = P52 %2 + P53 X3
P54 + 65
X5 (Fertility Ratio I960) = P63 X3 + P64 X 4
P65 ^5 **■ ©6 CHAPTER IV
THE FINDINGS
The main functions of this chapter are (1) to analyze all the possible combined effects that urbani- zation-industrialization, SES, and woman participation in the labor force may have on the Puerto Rican fertility ratios as reported in the census of 1950 and I960 and to test the general structural path diagrams postulated for their two censuses; (2) to point out all the possible changes of the direct effects of the selected dimensions that may have occurred during these two census period; and (3) to analyze the specific relationships of each of the dimensions with fertility ratios postulated in a time- function approach. All these hypothesized relationships are interpreted by means of path analysis, A great deal of flexibility in some of the assumptions governing the use of this statistical technique is expected. For example, the assumption of causality is not demostrable in most sociological research. Experimentation demands the obser vation and measurement of the time ordering and covariation of two variables eliminating possible intervening sources in the process. Absolute control over the variables is required to warrant the causal link between the vari ables. With human beings this kind of experimentation
103 104 is almost totally condoned. However, the social scientists can, indeed, observe time-order and covariation between selected variables, construct their causal models and infer "mathematical causality" or contiguous relation ships. Blalock discusses this problem in the following words : The problem of causality is part of the much larger question of the nature of the scientific method and, in particular, the problem of the relationship between theory and research. There appears to be an inherent gap between the languages of theory and research which can never be bridged in a completely satisfactory way. One thinks in terms of a theoretical language that contains notions such as causes, forces, systems, and properties. But one's tests are made in terms of covariations, operations, and pointer readings.
One admits that causal thinking belongs com pletely on the theoretical level and that causal laws can never be demonstrated empirically. But this does not mean that causal laws can never be demonstrated em pirically, But this does not mean that it is not helpful to think causality and to develop causal models that have implications that are indirectly testable. In working with these models it will be necessary to make use of a whole series of untestable simplifying assump tions, so that even when a given model yields correct empirical predictions this does not mean that its correctness can be demonstrated.
Causal laws, then are assumed by the scientist. When they appear to be violated, he reformulates them so as to account for existing facts. For example, in noting that two bars move together in an apparently inexplicable way, one may postulate the existence of some previously un suspected property (e.g., magnetism). In such a manner he may discover new variables and formulate revised causal laws that predict to 105
a wider range of empirical phenomena. But he cannot directly assess the validity of the causal principle itself. It becomes merely a highly useful theoretical tool.^ In all of the general structural path models in this research, a time-order and covariation are assumed among the variables considering SES and the participation of women in the labor force as intervening variables between the urbanization-industrialization of the society and its fertility levels. In the specific structural path models each of the three dimensions, urbanization- industrialization, SES and proportion of women in the labor force are considered as preceding in time the fertility schedules recorded in the censuses. In these specific models the time-order is evident; however, the covariation is more difficult to analyze since it is assumed that the variables selected in i960 are a time- function of the values these variables had in 1950. The results and findings of the study are presented in the following section.
General Structural Path Models
Model I; 1950. It was initially hypothesized that urbanization-industrialization, SES and the propor tion of women in the labor force have a direct negative
^Hubert M. Blalock, op. cit.. p. 5 et passim. 106
influence on family size. Thus the greater the concen tration of population in urban areas and employment in manufacturing enterprises, the lower the community fer
tility levels. The higher the education level of the community and its income in dollars, the lower the birth rates. And the larger the participation of women in the labor force, the lower the fertility. It is anticipated that these three dimensions are functional, interdepen dent social phenomena. Furthermore, the socioeconomic status of the community and the participation of women
in the labor force act as intervening variables between urbanization-industrialization and the community fertility
levels. To assess the mathematical structure of the problem under investigation the zero-order correlation
matrix for the variables as of 1950 was calculated. The results are presented in Table 9. All of the variables
included are negatively related to fertility. The tra
ditional inverse relationship between urban (r^^ = -.5 2 0 ^),
employment in manufacturing (r26 = -.35^7), education
(r^6 = -.4602), income (riu^ = -.4604). women in the labor force (r^g = -.4541) and fertility is maintained as
moderate to high significant relationships are shovrn. At this point some indications of the hypothesized inverse TABLE 9. ZERO..ORDER CORRELATION MATRIX FOR THE SIX VARIABLES. PUERTO RICO, 1 9 5 0,
Xi X2 ^3 X4 X6
Urban Xl 1.0
Manufacturing X2 .2124 1.0 Education .5438 .0742 1,0 Income .6314 .0332 .6706 1.0
Women Working ^5 .1783 .8390 .1672 .0449 1.0 Fertility Ratios X6 -.5204 -.3547 -.4602 -.4604 - . 4 5 4 1 1 .0 108 relationship between the selected sociological dimensions appears to hold on an areal bases for Puerto Rico in 195Q* Obviously, knowledge of these individual correla tions add little to the theoretical understanding of fertility performance. Thus, path analysis is used to assess the network of the hypothesized relationships and to isolate the direct influence of the variables upon the municipios' fertility ratios. The path coefficients and the recursive equations for the hypothesized relationships in 1950 appear in Figure 6, after negligible and insignificant paths were deleted in the original model. According to this revised structural model, ^5 percent of the variance in community fertility is a function of urban concentration, education, income, and the proportion of women working. Of the four variables, the strongest effect is that of women in the labor force (p^^ = -.3779). Thus, the greater the partici pation of women in the labor force, the lower the level of community fertility. Next in importance is the urban variable (p^^ = -.2630). Thus with education, income, and women working controlled, the greater the concentra tion of the population in cities, the lower the birth rates. Income (p^Z; = -.1946) and education (p^^ = -.1236), with urban and working women controlled, have a direct negative influence on fertility. Thus, considering 109 FIGURE 6
REVISED STRUCTURAL PATH DIAGRAM. MODEL I: 1950. PUERTO RICO.
\|TT2957
-.2630
2124
urban) =1.0 (g j )
%2 manufacturing) =1.0 (eg)
Xj (education) = .$ 4 3 8 (Xj) + 0 .0 (Xg) + .8 3 9 2 (e^)
% (income) =,378? (Xj) + 0 .0 (Xg) + ,4 6 4 7 (Xj) + .6703 (e^)
X5 ()g women working) = .0 (X^) + .8 1 9 5 (Xg)+ .1 7 7 0 (X^) + (-.1 0) (X,^) + .6296 (e^)
Xg (Fertility Ratios)=-, 2630 (X^) + 0 .0 (Xg) + (-. 1236 ) (Xg) + (-.1946 ) (.^) +
(-.3 7 7 9) (X5) + .7383 (eg) 1 10 education and income as the surrogate measures of community SES, it can be concluded that the higher the SES of the of the population members in the Puerto Rican municipios. the lower their fertility. The path diagram presented in Figure 6 also shows the urban variable as a determinant of the SES in 1950.
The paths between urban and education (p^i = .5^38) and between urban and income (p/^i = .378?) indicate that the higher the concentration of people in cities, the higher their education and income. The path between education and income (p^^ = .464?) confirms the traditional co variation of these two variables. Approximately 30 percent of the variation in education is explained by urban concentration alone. For income, 55 percent of its variation is explained by urban and education acting together. The employment of persons in manufacturing industries in 1950 made no significant contribution to the explanation of the SES of the community. The pre dicted direct influence of the employment in manufactur
ing enterprises on SES does not hold. This is probably explained by the low relationship between urban concen tration and the proportion of people employed in manu facturing industries in 1950 (r^g = .2124). In fact, it seems that urbanization preceded industrialization in Puerto Rico. This will explain why the effect of employment in manufacturing industries in 1950 upon the SES of the municipios was not perceptible. However, manufacturing industries were the major sources of wo men's work. The path coefficient between manufacturing and working women (p^2 = .8195) is an indication of the strong relationship between the two. At this point it should be noted that the path coefficient between income and women working (p^i^. = -.10), with education and manu facturing controlled, indicates a negative influence between the two variables. Thus it seems that while manufacturing industries were the major sources of em ployment for women, their income was relatively low. On the other hand, a relatively higher level of educa tion was required as manifested by the positive link between the two variables (p^^ = .1770). Finally, 70 percent of the variation in the proportion of women working in the Puerto Rican municipios in 1950 is ex plained by the mutual association of the proportion of people employed in manufacturing industries, of education and of income level.
The revised structural path diagram depicted in Figure 6 seems to provide the best fit to the data. Evidently, the path coefficients calculated for this model faithfully reproduce the actual correlations among the variables. Table 10 shows the estimated correlation matrix from the path coefficients (above the diagonal) TABLE 10. ESTIMATED CORRELATION MATRIX FROM PATH COEFFICIENTS (above diagonal), AND DIFFERENCES BETWEEN ORIGINAL AND ESTIMATED CORRELATIONS (below the diagonal).
MODEL I: 1950
Xi X2 X3 X4 ^5 ^6
Urban Xl 1.0 .2124 .5438 .6314 .2071 -.5313 Manufacturing X2 .0000 1.0 .1155 .1341 .8265 -.4085 Education ^3 .0000 -.0413 1.0 .6706 .2045 -.4743 Income ,0000 .1009 .0000 1.0 .1285 -.4921
Women Working X5 -.0288 .0025 ,0373 -.0836 1.0 -.4826 Fertility Ratios X6 -.0109 -.0538 -.0141 -.0317 -.0285 1.0 113 and the values of the differences between the actual and estimated correlations (below the diagonal). The predictability and internal mathematical validity of the model seems to be quite good. Only two of the pre dicted r*s deviate from the 36 original correlations by more than ,05 in magnitude. The mean correlation difference (X^cL = .12) is insignificant at the ,01 level, which indicates also that the model fits the Puerto Rican data for 1950 quite well. In summary, it can be concluded that for 1950 the Puerto Rican fertility ratios of the municipal areas were a function of the urban concentration, education, income and the participation of women in the labor force. The proportion employed in manufacturing in dustries, however, did not have any direct influence on fertility, and its impact was indirectly through the proportion of women working. This may be explained by the small number of manufacturing enterprises in the Puerto Rican municipios in 1950. These findings give support to several specific studies of Puerto Rican fertility which have shovrn the influence of modernization variables on the birth rates. These other studies were conducted during the 1950's. 114
For example. Combs and Davis^ in their study on the differential fertility in Puerto Rico in 1950 indicated that in spite of the high fertility at all ages, the rate of reproduction in the population tended to decline.
They predicted a future trend of lowered fertility as a result of the differentials observed between white and nonwhite fertility. White natality was sufficiently below that of non-whites, which would lead to a plausible long-run family limitation in a large segment of the population. Also, differentials in education, rural- urban background, and commercial and industrial progress were producing a secular movement toward a decline in community fertility rates. Similar findings were reported by Hatt^ about the same time. He suggested that there was a perceptible falling fertility in this developing society, and that the new generations of Puerto Ricans had taken on low fertility values which in the long run would change the birth level. He also, being strongly impressed by the economic development on the island.
1Jerry W. Combs and Kingsley Davis. "Differential Fertility in Puerto Rico," Population Studies. 5 (1951), pp. 104-116. See also "The Pattern of Puerto Rican Fertility," Population Studies. 4 (1 9 5 1), pp. 364-379.
2paul Hatt, Backgrounds of Human Fertility in Puerto Rico: A Sociological Survey (Princeton: University Press, 1952). 115
indicated that modernization should accelerate fertility decline. Model II; I960. Table 11 presents the zero- order correlation matrix for the variables as of I9 6 0 . In this census year, fertility ratios were correlated at -.3 3 ^ 8 with urban concentration, at -.3840 with employment in manufacturing industries, at -.4659 with education, at -.5213 with income, and at -.5348 with the non-familial activity of women. These are signifi cant moderate to high correlations which indicate that the pattern of an inverse relationship between indicators of urbanization-industrialization, SES, and women in the labor force and fertility levels is maintained and have been pervasive in the Puerto Bican society through time. On the basis of these correlations and findings reported in past studies, a causal ordering of the variables was advanced and graphically depicted in Figure 7. In this general structural path diagram for i9 6 0 (Figure 7), it is expected that the SES of the community and the participation of women in the labor force are intervening variables between the level of urbanization-industrialization and the fertility schedules. The path coefficients for the hypothesized relationships and the recursive equations appear in Figure 7, after TABLE 11. ZERO-ORDER CORRELATIONS MATRIX FOR THE SIX VARIABLES. PUERTO RICO, I960.
Xl X2 ^3 X4 :(5 :(6
Urban 1.0
Manufacturing X2 .4060 1.0 .1 0 9 2 1.0 Education ^3 .^^67 Income Xl^ .5504 .4010 .7240 1.0 Women Working ^5 .5525 .6548 .4891 .6844 1.0 Fertility Ratios X6 -.3348 -.3840 -.4659 -.5213 -.5348 1.0 117 FIGURE 7
REVISED STRUCTURAL PATH DIAGRAM. MODELE II! I9 6 O. PUERTO RICO.
,6l3t
.17; .Wo 3622
\ji-. 6538
urban) = 1.0 (e^)
Xg(^ manufacturing) =1.0 (Cg)
Xj(educatlon) =.6 1 3 5 (X^) +(-.1399) (Xg) + .8 2 0 2 (e^)
Xi^(ir.coms) = .0 (X^) -i- .3 2 5 8 (Xg) + .68% (Xj) + .6090 (e^î
Xç(^ women working) = . 0 (X^) + .4^06 (Xg) + .17 55 (X3) + .5 6 2 2 (î^) + .5883 (e^)
Xg(Fertility Ratios)= .0 (Xj) + (-.1620) (Xg) + (-.2506) (X3) + (-.1230) (X^) +
(-.2219) (X5) + .7188 (eg) 118
insignificant paths were deleted from the original pos tulated model. According to this revised structural
model, 36 percent on the variations of fertility ratios
in i960 are explained by the proportion employed in
manufacturing industries, education and income, and the participation of women in the labor force. Comparing
this result obtained for I960 with that for 1950, a reduction in the ability to predict the variations in community fertility levels should be noted. This find ing may indicate what happens in a society when com munities' differentials in urbanization-industrializa
tion, SES, and the proportion of women working are reduced in the process of modernization or societal development, so that other factors such as religion,
etnicity, or psycological aspects become more important in explaining the fertility of populations. Of the four variables explaining fertility in
i9 6 0 , the strongest effect is that of education (P53 =
-.2 5 0 6 ). Thus the greater the education level in a
population, the lower its fertility. Comparing the
direct effect of education on fertility in i9 60 with the direct influence the same variable had on fertility in
1 9 5 0, it should be noted that its direct impact upon birth rates had Increased and almost doubled in a decade. Thus from this evidence it follows that the education 119
level in the Puerto Rican municipios is increasing its importance in the explanation of communities* fertility- different ials . Next in importance is the effect of the partici
pation of women in the labor force on fertility (p^^ =
-.2 2 1 9). Thus the inverse association between the non- familial activity among women and their community fertility has persisted in the Puerto Rican society. However, the influence of this variable on fertility, when employment in manufacture, education and income are controlled, had decreased by i9 6 0 . There are dif ferent explanation for this: (l) in general, there had been a reduction in the proportion of women (14 years old and over) in the labor force between 1950 and I960; and (2) the effect of manufacturing enterprises on women working had also decreased (P52 = .8195 in 1 9 5 0, to p^2 = .4 9 0 6 in i9 6 0 ), which indicates that manufactur ing industries were no longer the main sources of employ ment for women in Puerto Rico, At this point it should be pointed out that even though the number of women working had diminished its direct effect on fertility as shown in the analysis of causal paths, the strong negative relationship between the two variables persists as manifested by a high significant correlation of
^56 = -.5 3 ^8 . On the other hand, the proportion employed 1 20 in manufacturing industries that had an indirect influence on fertility through women working in 1 9 5 0 had decreased its impact on the proportion of women in the labor force
(P52 = .8 1 9 5 in 1 9 5 0, to P52 = .4-906 in I960). Thus it seems that occupations other than manufacturing had be come more important sources of work for women in Puerto Rico. This is expected and congruent in a societal development process. The weakest effect among the four variables directly influencing fertility is that of income (p^^ =
-.1 2 3 0 ). However, the negative effect of income level on fertility was still manifested in I9 6 0 . Looking at the two revised structural models,
1950 and i9 6 0 , one can note the following general changes:
(1) The explanation of variance on fertility, using indicators of urbanization-Industrialization, SES and women working as predicting variables, had decreased between 1950 and I960. This finding is expected in the process of societal development. When the three dimen sions become ubiquitous in a society, other variables should enter into the explanation of fertility differen tials. (2) Urban concentration that in 1 9 5 0 was directly exercising a negative influence on fertility was no longer operating in the same fashion in i960. Its direct effect had been reduced to zero, and its influence was 121 indirectly distributed through other variables such as education, income and the participation of women in the labor force. The population of Puerto Rico is increas ingly concentrated in cities, so that the increases in urbanization at the community level became so small that the changes observed on this variable did not have any effect on the fertility level, (3) On the other hand, employment in manufacturing industries that did not have any direct effect on fertility in 1950 had begun by I960 to exercise a direct negative influence on the birth rates. (4) Education was becoming more important as an explanatory variable of fertility while income was diminishing its direct negative effect. These structural changes that took place in the Puerto Rican society between 1950 and I960 seem to confirm the general proposi tion that community fertility is a function of the timing and level of societal development.
Other indications of this postulated increase in societal development can be inferred from the 1950 and i960 models. The relationship between urban concentration and the proportion of the population employed in manu facturing industries had increased from Vi2 - .2124 in
1 950 to ri2 = .4 0 6 0 in I960. Thus urbanization and
industrialization are associated social phenomena in this developing society. While community fertility levels 122 should respond inversely to the emergence of moderniza tion, the direct influences of some of its components such as urbanization and industrialization may change through time. In the process of modernization, as in the case of Puerto Rico, the urban concentration is expected to lose its direct negative effect on the birth rates and to distribute its influence indirectly through other social and economic variables. Industrialization, on the contrary, opening up new job opportunities and activities for women, is expected to increase its direct negative effect on the urban birth rates.
While urbanization has had a positive impact upon the educational level (p^^ = .5/4-38 in 1 9 5 0; p^^ =
.6 1 3 5 in I960), the employment in manufacturing industries has not made any direct impact on education in 1 9 5 0, and was showing a negative influence on education in I960
(P32 = -.1 3 9 5). This negative influence may be explained by a higher concentration of individuals with low educa tional attainment in manufacturing enterprises in I960. This is also expected in the process of modernization.
The higher the level of industrialization in a society, the higher the demand for and placement of better quali fied personnel, leaving the bulk of jobs for individuals with low educational status. Together the urban concen tration and the proportion employed in manufacturing 123 industries in i9 6 0 explain 32 percent of the variation in educational level. Even though employment in manufacturing industries had a negative influence in education, it had a positive direct effect on income. This is clearly indicated in the i9 6 0 model. It seems that the influence of employ ment in manufacture on income level in 1 95 0 was very low and insignificant. The causal path between these two variables was zero. The mutual variations of education and employment in manufacture in I960 had an overall positive impact upon the income level of the community.
The causal path between education and income had signi ficantly increased between the two intercensal periods
(Pii3 = .46^7 in 1950; pi^3 = ,6884 in I960). The causal path between employment in manufacture and income was directly and significantly positive (p^_2 = .3 2 5 8 ), These findings are in accordance with what is expected in the process of modernization or socioeconomic development. The mutual association between urbanization-industriali- zation and SES had increased, giving as a result an improvement in the standard of living of the Puerto Rican population. In 1950 the income level was a function only of urban concentration and education; in I960 the com munity's income level was a function of urbanization, industrialization, and education. Together these three 124
variables explain 62 percent on the community's income variation. The participation of women in the labor force in the Puerto Hican municipios is to a considerable extent
a function of the SES of the population and the indus
trialization level in the society. Together, education, income, and the proportion employed in manufacturing
industries explain 65 percent of the variance in the proportion of women working. Of the three variables, manufacturing (p^2 = ,4906) was the most important vari able, and the next in importance was income (p^ij, = .3622). Comparing these findings in I960 to those in 1950, one
sees a clear indication of the increasing status of women
in the society. A smaller proportion of women older than l4 were in the Puerto Rican labor force by I960. However, the women that were working got higher salaries, as in dicated by the changes in the causal links between the
two variables in 1950 and I960 (p^Z|. = -.10 in 1 9 5 0; p^j[^ =
.3 6 2 2 in i9 6 0 ). Also, a smaller proportion of women were working in manufacturing industries in I960, which indi cates that females are probably employed in different occupations other than manufacture. This is clearly indicated by the changes in the causal paths between these two variables in the two census (P52 = .8195 in
195O; P52 = .4806 in I960). Education has maintained its 125 direct positive effect of the proportion of women working during the analyzed intercensal period. At this point the question needs to be raised as to what extent this model for I960 faithfully reproduces the actual correlations among the variables. In Table 12 the r values are predicted from the revised model's path coefficients (above the diagonal) and the differences encountered between the original correlation matrix (see Table 11) and the estimated correlations (below the diagonal). The predictability and mathematical validity of this model is excellent. Only one of the predicted r's deviate from the 36 observed r's by more than .0 5 in magnitude. This discrepancy is on the prediction of the correlation between urban concentration and the partici pation of women in the labor force. The deviation is so low (.0 7 0 1 ) that when combined with the other differences in the model it loses its importance. The mean correla tion difference = .0^0 is nonsignificant beyond the .001 level.
In summary, one can conclude that for I960 the Puerto Rican fertility ratios at the community level are a function of the education and income level, the propor tion of women in the labor force, and the overall increase in the proportion of people employed in manufacturing industries. The urban concentration variable has been TABLE 12, ESTIMATED CORRELATION MATRIX FROM PATH COEFFICIENTS (above the diagonal),
AND DIFFERENCES BETWEEN ORIGINAL AND ESTIMATED CORRELATIONS (below the diagonal).
MODEL II: i960
Xl X2 X3 X4 ^5 Xe
Urban Xl 1.0 ,4060 .5567 .5 1 5 5 .4824 -.3757
Manufacturing X2 .0000 1.0 .1 0 9 2 .4009 .6 5 4 7 -.3839 Education ^3 .0000 .0000 1.0 .7 2 3 9 .4890 -.4658 Income .0 3 4 9 .0001 .0001 1.0 .6843 - . 5 2 1 2
Women Working .0 7 0 1 .0001 .0001 .0000 1.0 -.5346
Fertility Ratios -.0409 — 0 0001 -.0001 -.0001 -.0001 1.0 127 losing its direct negative effect on fertility, and its influence is now distributed indirectly through the SES of the community and the proportion of women working. Findings that support this conclusion have been reported by Macisco^ in his ecological study on the association of some socioeconomic and demographic vari ables with the cumulative fertility ratios for the 75 municipios. He found that the fertility of Puerto Rican women was associated with measures of income, education, labor force status, population, and journey to work. His findings indicated that an inverse relationship of fer tility with SES holds on an areal basis in Puerto Rico.
A more recent study by Taeuber^ discussed the effects of modernization upon the community's SES and its fertility levels. She found that fertility was negatively related to such indexes of modernization as higher education, income, and white collar occupations. She concluded that urbanization and industrialization are the signal indica tors of the demographic transition in Puerto Rico.
->Jhon J. Macisco, Jr.. "Fertility in Puerto Rico: An iicological Study," Sociological Analysis. 26 (1965), pp. 1^7-164.
^Irene B, Taeuber, "Demographic Modernization: Continuities and Transitions," Demography. 3 (1 9 6 6 ), pp. 90-108. 128
At this point a general conclusion may be inferred from the two models. The inverse relationship between urbanization-industrialization, SES, and the participa tion of women in the labor force with community fertility levels seems to hold on an areal basis for Puerto Rico. As indicated, in the process of modernization some of its empirical indicators may change their influences on the society's birth rates. For example, the urban concentra tion variable has lost its direct influence on the birth rates, and is distributing its effects indirectly through other variables such as the SES of the community and the proportion of women in the labor force. The employment in manufacturing variable is losing its indirect in fluence on the birth rates through the proportion of women working, and it is directly affecting the fertility rates. In general, the direct negative effect of some of the macro-social structures on the fertility of popula tion members is expected to decrease in the process of modernization. Some other indicators such as religion, etnicity, and other social and psycological variables will be more important in the future explanations of fertility rates.
The expectation that the SES of the community and the participation of women in the labor force are inter vening variables between the urbanization-industrialization 129
and community fertility levels is definitely borne out.
The author feels that one reason there is so much dis crepancy on findings related to the association between
SES and fertility is because the SES indicators have been treated by themselves without any relation to the social structure of the society. The SES of a population is the result of the overall process of modernization. The higher the modernization level in a society, for example
manifested in term of urbanization and industrialization, the higher the SES of the population, and therefore, the
lower its fertility level. Thus it would be expected that SES, and hence the participation of women in the labor force, operate as intervening variables between urbanization-industrialization and the birth rates.
Specific Structural Path Models While the revised structural path diagrams depicted
in figures 6 and 7 fit Puerto Rico for 1950 and I960, there is another objective in this research; that is to examine the influences of each separate dimension on the Puerto Rican birth rates, assuming that the values
obtained by the empirical indicators in I960 are a func tion of the scores they had in 1950. Hence to analyze these relationships, some causal models in the path analysis form were formulated in the preceding chapter. 130 and their discussion and mathematical tests are presented in the following section.
Model III: 1950-1960, Urbanization-Industrializa tion and Fertility. It was initially hypothesized that urbanization-industrialization has a direct negative effect on fertility, and that its influences in I960 were to some extent a function of the magnitude of its impact on fertility in 1950. The path coefficients and the set of recursive equations appear in figure 8 after insignificant paths were deleted from the original model (Figure 8). According to this revised structural model,
2 9 percent of the variance in fertility levels in 1950 was explained by urban concentration and employment in manufacturing alone. In I960, approximately 58 percent of the variations on the fertility ratios of the Puerto Rican municipios were explained by the level of the direct influence of urban concentration and manufacturing in
I960 and the fertility rates in 1950; and by the indirect influence of the urban and manufacturing values in the municipios in the past. That is to say that fertility levels in I960 were a function of the urbanization and industrialization of the communities at that particular time, plus the effects of the levels of urbanization, industrialization and fertility in 1950. Evidently, the fertility rates in 1 9 5 0 were reduced because of urban FIGURE 8 ^31
REVISED STRUCTURAL PATH DIAGRAM. MODEL III: 1950-1960. URBANIZATION-
INDUSTRIALIZATION AND FERTILITY. PUERTO RICO
\E%. 7207
1950
3331
,4261
\lï^.5777
(urban 1950) = 1 . 0 (e^)
Xg (manufacturing 1950) = 1.0 (@g)
X^ (fertility ratios I950) = -.3858 (X^) + (-.2929) (Xg) + .8 42 1 (63)
Xj^ (urban i960) = .7691 (X^) + 0 .0 (Xg) + (-.1509) (X3 ) + .$ 2 8 4 (eif)
Xg (manufacturing i960) = 0.0 (X3.) + .4261 (Xg) + 0.0 (X3 ) + .3331 (X^) + .8117 (e^)
Xg (fertility ratios I96O) = 0.0 (X%) +0.0 (Xg) + .7408 (X3 ) + .10 (Xi^) + (O.I5I9)
(X5 ) + .6498 (eg) 132 concentration (p^i = -.3 8 5 8) and the proportion of the population employed in manufacturing industries {P32 =
-,2 9 2 9). Thus, the greater the urban concentration and employment in manufacturing industries the municipios had in 1 9 5 0, the lower their fertility. The picture in I960 was a little different. The effect of urban concentration when fertility 1950 and manufacturing 1960 are controlled, is positive but rela tively low (p^Zj. = .100). In the general model (Figure 7) the influence of urban concentration upon fertility was found to be zero when SES, women working, and manufactur ing was controlled. This indicates that when more vari ables are considered in the analysis, the effect of urban concentration on fertility is indirectly distributed through them. This rather low positive influence of urban concentration on the birth rates may be the result of the concentration of rural migrants in the Puerto Rican cities that occurred between 1950 aud I960. It is expected, however, on the evidence found in the general models that the influence of urbanization will altogether disappear in the process of modernization and some other variables will enter in the explanation of community fertility levels.
The urban variable in i9 60 is a function of the mutual association of fertility and urban concentration in 1 9 5 0. While urban concentration in 1950 had a positive 133 effect upon urbanization in I960 = .7691), the influence of fertility 1 95 0 had a negative impact (P43 =
-.1 5 0 9). Thus, the greater the concentration of popula tion in urban areas at a specific point in time, con trolling for fertility rates, the higher the urbanization at a later time. The negative effect of fertility in 1950 I upon urban concentration in I960 indicates that the urban areas have maintained a lower fertility than the rural areas in the Puerto Rican society. Together, fertility in 1950 and urban concentration in 1950 explain 72 per cent of the variance of urban concentration in i9 6 0 .
The relationship between urbanization and indus- trilization in 1950 (ri2 = P12 = .24.89) has increased and is manifested by a direct influence of the urban variable on the industrialization indicator (P3 /4, =.3 3 3 1 ).
The level of industrialization in Puerto Rico in I960 was to a certain extent a function of the level of urban ization in i9 60 and the influences received from the employment in manufacturing enterprises in 1950. Together these two variables explain 34 percent of the variance on the indicator of industrialisation in I960. The revised structural path diagram depicted in figure 8 is a relatively good fit to the data. Table 13 gives both the originally observed correlations among the variables (below the diagonal) and the r values TABLE 13, ESTIMATED CORRELATION MATRIX FROM PATH COEFFICIENTS (above the diagonal), AND OBSERVED CORRELATION MATRIX (below the diagonal). MODEL III: 1950-1960 URBANIZATION-INDUSTRIALIZATION AND FERTILITY.
Xl X2 ^3 X4 ^5 X6
Urban 1950 Xl 1.0 .2489 -.4587 .8383 .3853 - . 3 1 4 5 Manufacturing 1950 X2 .2489 1.0 -.3889 .2 5 0 1 .5 0 9 4 -.3404 Fertility Ratios 1950 X3 -.4587 -.3889 1 .0 -.5036 -.3334 .7410 Urban I960 Xi^ .8383 .1 7 1 0 -.5037 1.0 .4 3 9 6 -.3398 Manufacturing I960 X5 .4155 .4831 -.3681 .4060 1.0 - . 3 5 4 9 Fertility Ratios I960 X6 -.3262 -.4412 .7464 -.3348 -.3840 1.0 135 predicted from the revised model's path coefficientes (above the diagonal). The validity and mathematical predictability of the model seems quite good. Table 14 shows the differences between the originally calculated correlations and the estimated correlations from the path coeff icientes. Only two of the predicted r's deviate from the 36 observed r's by more than .0 5 in magnitude, and considering the two only one by more than .10. This singular relatively large deviation is between fertility i960 and the employment in manufacturing industries in
1 9 5 0. The original correlation was r26 = .4412, and the estimated values was T26 = -.3404. It was found that even though these two variables are negatively related, the influence of the industrial indicator in 1 9 5 0 upon the fertility levels in 1 9 6 O is indirectly through the birth rates recorded in 1950. Thus the observed path coefficient between these two variables is then p^2 = 0.0. This is the reason why this coefficient is not a good predictor of the original correlation.
Model IV; 1950-1960. Socioeconomic Status and Fertility. Figure 9 describes a fully recursive causal model with all possible paths drawn depicting the net work of the relationships between SES and fertility in
1950 and i9 6 0 . Together, income and education in 1950 explain approximately 19 percent of the variations on TABLE 14. DIFFERENCES BETWEEN THE OBSERVED CORRELATION MATRIX AND THE ESTIMATED CORRELATION MATRIX. MODEL III: 1950-1960 URBANIZATION-INDUSTRIALIZATION AND FERTILITY.
Xl X2 X3 X4 ^5 ^6
Urban 1950 Xl 1.0 Manufacturing 1950 X2 .0000 1.0 Fertility Ratios 1950 .0000 .0000 1.0 Urban i960 X4 .0000 .0791 .0001 1.0 Manufacturing I960 ^5 .0302 -.0263 .0347 .0336 1,0 Fertility Ratios I960 X6 -.0117 -.1008 .0054 .0050 .0291 1.0 137 FIGURE 9
FULLY RECURSIVE CUASAL MODEL WITH ALL PATHS DRAWN. MODEL IV: 1950-1960.
SOCIO-ECONOMIC STATUS AND FERTILITY. PUERTO RICO.
'Jl-. 6 1 i960 1950
.1632
,6912
-.360 2239
vIT-. 1861
(income 1950) "1.0 (e^)
%2 (education i960) « 1,0 (62)
X3 (fertility ratios 1950) = -.239^ (X^) + (-.2405) (Xg) + .'9 0 2 1 (e^)
X^ (education i960) « .3 2 5 8 (X^) + .326 ? (Xg) + (-.3602 ) (X3) + .15862 (e^)
Xc (income i960) = .5 4 0 1 (Xi> + (-.0 7 9 4 (X2) + (-.1613 ) (X3) + .3 1 7 8 (Xi^) + 5 • 5587 (eg) Xg (fertility ratios i960) = .1 6 3 2 (X^) (-.2004) (X2) + .6912 (Xg) + .2 2 3 9 (%) +
(-.3328) (Xg) + . 6 2 4 8 (eg) 138 birth rates in 1950. These two variables present a negative direct influence on fertility as shown by the path coefficientes p^^ = -.2394 and p^g " -.2405 respec tively. In I960, together the SES of the municipios and their fertility levels in 1 9 5 0, plus their mutual association with the SES of the municipios in i9 6 0 ex plain 61 percent of the variance in the community fer tility levels recorded in 1 9 6 O. Income level in 1950 has a positive direct effect on fertility in I960 (p^i =
.1 6 3 2 ), but education in 1950 has a negative direct influence on fertility in i960 (PAo = -.2004). It is possible that these opposite effects have counteracted each other in the process of the Puerto Rican moderniza tion. On the other hand, education level in I960 has a positive influence on fertility (p^4 = .2 2 3 9), and income has a direct negative effect on fertility (p5^ = -.3328).
Thus, it seems that that the influences of the indicators of SES for 1 9 5 0 and i960 are not very consistent with the formulated theoretical expectations. Income and education in 1950 had a positive direct impact on the community levels of education in i9 6 0 (pi4.i = .3 2 5 8 and P42 = .326? respectively). Thus, when fertility rates are controlled, the higher the SES at an earlier time, the higher the level of education at a later period. Income in i960 was a function of the 139
SES in 195 0 and the education level in i960 , when fer tility rates are controlled. Together these three vari- able.s explain 68 percent of the income level variations. At this point it should be noted that a fully recursive causal model with all possible paths drawn becomes trivial and theoretically uninteresting. This was the only model that faithfully reproduced the original correlations observed among the variables. Other models tested did not even approach a good fit to the data. When any path coefficient was deleted from the fully recursive model, even if it was very small in magnitude, an increase in the deviations from the original correla tions was found. This failure to reproduce the original correlations when some paths were deleted on the fully drawn model may be due to (1) the high multicollinearity between income and education as measures of SES; (2) the intervening character of SES between modernization and fertility; or (3) the relationship between education and income may be mediated by several variables when a time dimension is introduced in the causal model, making false the assumption that the income and education level in i960 is a complete function of the income and education level in I960. For these reasons any of the tested models with path deleted did not reproduce the original correlations, thus making their validity and mathematical 140 predictability very questionable. Obviously the presented model in figure 9 will faithfully reproduce the original correlation when they are predicted from the model's path coefficients. As expected in path analysis, the predicted and observed correlations of a fully drawn model are identical. Table
15 gives both the originally observed correlations (be low the diagonal) and the r values predicted from the path coefficients. There is not, of course, any devia tions between the two matrices. Model V; 1950-1960. Participation of Women in the Labor Force and Fertility. The participation of women in the labor force in 1 9 5 0, with urban con centration controlled, had a negative influence on fer tility ;p32 = -.3 8^0 ). Urban concentration was selected to accompany the women working variable because in newly developed societies today, the participation of women in the labor force takes place in the cities. As a consequence of the concentration of job opportunities in cities, where relatively all industrialization, commerce, and communication are centered, women necessarily have to find jobs in the urban areas. In Puerto Rico in
1 95 0 there was a relatively low correlation between women working and urban concentration (ri2 = .1474); however, with the process of modernization and general TABLE 1 5 . ESTIMATED CORRELATION MATRIX FROM PATH COEFFICIENTS (above the diagonal), AND OBSERVED CORRELATION MATRIX (below the diagonal).
MODEL IV: 1 9 5 0-1 9 6 0 .
SOCIOECONOMIC STATUS AND FERTILITY.
Xl X2 X3 X4 ^5 X6
Income 1950 Xl 1.0 .6167. . -.3877 .5536 .8428 - . 2 2 3 9
Education 1950 X2 .6167 1.0 -.3881 .3162 .7679 - . 3 0 1 3
Fertility Ratios 1950 X3 -.3877 -.3881 1 .0 -.3398 - . 7 2 1 2 .6573 Education i960 Xif, .5536 .3162 -.3398 1.0 .7 2 3 8 -.3786
Income I960 ^5 .8428 .7679 - . 7 2 1 2 .7 2 3 8 1.0 - . 5 3 1 8 Fertility Ratios I960 X6 -.2239 -.3013 .6573 -.3786 -.5318 1.0 142 economic development that took place especially in the urban areas, urban concentration exercised an increased direct effect on the proportion of women working =
.3 1 8 6 ). Together, urban concentration and the propor tion of women working explain 35 percent on fertility variations in 1 9 5 0. It should be noted that the direct influence of the women working variable on fertility rates had di minished between 1950 to I960 from P32 = -.3840 to pg^ =
-,1 5 2 7 , Proportionately, Puerto Rico may be one of the few societies where in the process of societal develop ment there has been a reduction in the proportion of women 14 years old and over in the labor force. In fact,
in 1 95 0 the proportion of women working in the island was 2 1 .3 . Ten years later, in I960 there was a decline by 1 .3 percent points, that is to 20.0 percent of women 14 years old and over working. However, an increase has been recorded in those mimicipios where urbanization and industrialization is strongly concentrated, espe cially in the Puerto Rican metropolitan areas. This is probably an indication of female migration to those municinios where more opportunities may be found, or of the migration of females to the continental United States, especially to New York City, where a heavy number of Puerto Rican migrants is located. The path coefficients 143 and the set of recursive equations that supports these observations are presented in the causal model depicted in Figure 10,
As a consequence of the percent decline in the participation of women vf or king between 1950 and I960, the proportion of women in the labor force in i960 is not a function of the values of this variable in 1 9 5 0, Evidently the path coefficiente between the two is zero. In those municipios where fertility was low in 1950 and where the majority of the population were living in urban areas, there was a higher participation of women in the labor force. Together, urban concentra tion in I960 and fertility in 1950» explain 46 percent of the variations on the proportion of females working.
At this point the question as to what extent this model is a good predictor of the actual correla tions among the variables should be raised. Table 16 shows both the originally observed relationships among the variables (below the diagonal) and the r values predicted from the revised model's path coefficients (above the diagonal). The overall predictability and validity of the model seems to be quite good. Only two of the predicted r's deviate from the 36 observed r's by more than ,0 5 in magnitude. There is not, in deed, any large deviation between the two matrices. 1 # FIGURE 10
REVISED STRUCTURAL PATH DIAGRAM, MODEL V: 1950-1960. PARTICIPATION OF
WOMEN IN THE LABOR FORCE AND FERTILITY. PUERTO RICO.
N5T.7207 I I 1^60
1037 -.1509 ,3186
(urban 19 5 0) = 1 .0 (e^)
%2 (women working 19 30) = 1 ,0 (eg)
X3 (fertility ratios 1950) = -.4021 (X^) + (-.3840) (X2 ) + .8033 (ej)
(urban i96 0 ) = .7691 (X^) +0.0 (Xg) + (-.1509) (X3 ) + .5284 (e^^)
X5 (women working I96O) = 0.0 (X^) + 0.0 (X2 ! + (-.4644) (X3 ) + .3186 (Xu) + .7306 (e^)
Xg (fertility ratios i9 6 0 ) = 0.0 (Xi) +0.0 (Xg) + .7032 {X3 ) + .1037 (X^) + (-.1527)
(X5 ) + .6 5 4 4 (eg) TABLE 16. ESTIMATED CORRELATION MATRIX FROM PATH COEFFICIENTS (above the diagonal),
AIÎD OBSERVED CORRELATION MATRIX (below the diagonal). MODEL V; 1950-1960. PARTICIPATION OF WOMEN IN THE LABOR FORCE AND FERTILITY.
Xl X2 ^3 X4 ^5 X6
Urban 1950 Xl 1,0 .1 4 7 4 -.4583 .8383 .4801 -.3089
Women Working 1950 X2 .1474 1.0 - . 4 4 3 2 .1802 .2632 - .3 3 3 1
Fertilitjr Ratios 1950 -.4587 - . 4 4 3 3 1.0 - . 5 0 3 6 -.6248 .7463
Urban I960 .8383 .0827 - . 5 0 3 7 1.0 .5 5 2 4 - . 3 3 4 7 .2582 Women Working I960 ^5 .5 1 3 7 -.6249 .5 5 2 5 1.0 - . 5 3 4 7 Fertility Ratios I960 X6 -.3263 -.3863 .7464 -.3348 -.5348 1 .0 146
The raaginitudes of the departures between the two matrices are presented in Table 17. The structural causal models presented here reflect necessarily the theoretical views of the author. The nature of the relationships between the fertility rates and the selected sociocstructural dimensions — urbanization-industrialization, SES, and the proportion of women working — are to some extent a function of the general level and timing of societal development. Furthermore, the socioeconomic status of the communities measured in terms of income and education levels, and the participation of females in the labor force, seem to be intervening variables between the general level of modernization (operationalized in terms of urban concen tration and the proportion of people employed in manu facturing industries) and community fertility levels.
However, at any point in these models presented, addi tional intervening indicators could be added such as social and psycologicctl variables, until some theoretical closure may be found when several antecedent phenomena explain almost all of the variation in the fertility rates. TABLE 1 7 , DIFFERENCES BETWEEN THE OBSERVED CORRELATION MATRIX AND THE ESTIMATED CORRELATION MATRIX.
MODEL V: 1 9 5 0-1 9 6 0 .
PARTICIPATION OF WOMEN IN THE LABOR FORCE AND FERTILITY.
Xl X2 X3 X4 X5 X6
Urban 1950 Xl 1.0 Women Working 1950 X2 .0000 1.0
Fertility Ratios 1950 X3 .0000 .0001 1.0
Urban 1 9 6 O X4 .0000 -.0975 .0001 1.0
-.0050 .0001 .0001 Women Working I960 X5 .0336 1 .0
Fertility Ratios 1 9 6 O X6 - . 0 1 7 3 .0 5 3 2 -.0001 .0001 .0001 1.0 SUMMARY AND CONCLUSIONS
This study has examined the ecological correlates of community fertility levels of a society in the midst of economic development. Specifically, it has been the purpose of this research to explore the effects of ur banization- industrialization, community socioeconomic status, and the participation of women in the labor force upon fertility ratios in a developing society. As an indicator of urbanization, urban concentration was selected. The proportion of people employed in manufacturing industries was utilized as a surrogate indicator of industrialization. Education and income were used as measures of the community's socioeconomic level. And the non-f ami liai activity dimension was operationalized by the proportion of women in the labor force. As a measure of the fertility in the community, the fertility ratios for each mimicipio were used and analyzed as the major dependent variable in the study.
Demographers have often treated urbanization, industrialization, socioeconomic status, and the partici pation of women in the labor force as virtually autonomous
124-8 149 and independent sociological dimensions to explain fer tility performance at either the individual or societal level, instead of viewing these three components as
significantly interrelated phenomena. This study was aimed at assessing the network of the relationships among the selected de mens ions and the Puerto Rican fer tility ratios. It was an attempt to bring together different strands of demographic research into a more comprehensive and meaningful theoretical and methodological framework,
A causal ordering of the three dimensions was postulated, and an inverse relationship with fertility
levels was advanced on the basis of previous findings
of past studies. Five structural path diagrams were presented showing the network of the relationships among the selected indicators. Two causal models were identi fied as the general structural path models. One of them analyzed the network of the relationships for the data as reported in the 1950 Puerto Rican census. The other one depicted the relationships among the variables as recorded in the census of I960. The other three
models were identified as specific structural path models with the intention of examining the influence of each separate dimension on the birth rates assuming that the values obtained by the indicators in I960 were a time- 150 function of the scores they showed in 1 9 5 0. Some past and present theoretical presentations and research findings on the general relationship between modernization and fertility were documented. The first assumption springing up from the reivew of the literature was that modern urban-industrial life produces socio cultural changes that constrain fertility performance. In the process of urbanization and industrialization, specific values, attitudes and abilities are developed which allow individuals to adequately function in an urban society. The second assumption was that in the process of modernization the community's socioeconomic status mediates or is an intervening variable between the level of modernization and fertility. Increasing
SES usually means that the educational level of the population is raised so that there are greater oppor tunities for people planning their lives according to future goals. Increasing income usually results in changes in the attitudes of individuals so that achieve ment of social aspirations are rationally planned; this rationality usually is extended to family size. The final assumption was that labor force participation and changes in the women's roles in a developing society influence females to prefer smaller family size, therefore lowering the general community fertility levels. These 151 assumptions taken from the literature on fertility are, in this study, put together in structural causal models to explain the birth rates of the different areal units of the Puerto Rican population. Data for testing the hypothesized relationships postulated in the causal models, assumed to operate in this developing society, were obtained from the 1 9 5 0 and i96 0 Puerto Rican censuses. The six sociodemographic variables included in the analysis were standarized to percentages for each of the 75 municipios. The meth odological approach proceeded as follows: (l) several multiple correlation and regression problems were solved, from which the collective impact of the modernization components upon fertility, and the general contribution of eauh indicator to fertility's explanation were asser- tained; (2) a causal ordering of the three dimensions was hypothesized for 195 0 and I960, and for particular tests of the relationship between each individual dimension and fertility using a tims-function approach; (3) the path coefficients called for in the models were calculated; (4) the models were modified according to the calculated path coefficients, with those negligible and insignificant paths from the original models being deleted, and then solving for the new causal links called for in the new path diagrams ; and (5) the original correlation matrices 152
were predicted on the basis of the revised models' path coefficients, and the differences between the estimated and origial matrices were assessed to evaluate.the validity
and mathemital soundness of the models. This study gives support to the proposition
that community fertility rates are to some extent a
function of both the general level and timing of societal development. In Model I: 1950, ?t was found that ^5 percent of the variance in community fertility ratios was a function of urban concentration, education, in come, and the participation of women in the labor force.
Of the four variables the strongest effect was that of women in the labor force (p^^ = -.3779); next in impor tance was the influence of urban concentration (p^j =
-.2630), followed by income (p^/,. = -.1946) and by educa tion (p£,^ = -.1236). Thus, in general, the inverse relationship between some indicators of urbanization,
SES and the participation of women in the labor force was definitely b o m born out from the Puerto Rican data in
1 9 5 0. The indicator of industrialization, that is, the proportion employed in manufacturing industries, did not show any direct influence on fertility, and its impact was indirectly distributed through the proportion of women working.
In Model II: i9 6 0 , about 36 per cent on the 153
variations of fertility ratios was explained by the manufacturing variable, income and education, and women working. The reduction in the percent variance explained between 1950 and I960 was approached in terras of societal development process. When the community's differentials in urbanization-industrialisât ion, SES, and proportion of women working are reduced in the process of moderni
zation, some other important factors such as religion, ethnicity or psychological variables may enter as con tributing more to the explanation of variations in the birth rates. Of the four variables explaining fertility
in i9 6 0 , the strongest effect was that of education
(P63 = -.2 5 0 6 ), next in importance was the influence of the participation of women in the labor force (p^^ =
-,2 2 1 9), and the lowest effects were those of manufactur
ing (p52 = -.1 6 2 0 ), and income = -.1 2 3 0 ). A definite
pattern emerged at this point from the findings: the general hypothesized inverse relationship between urban ization- industrialization, SES, women working, and fertil
ity levels was pervasive and consistent through time in the Puerto Rican society.
While community fertility levels should respond inversely to the emergence of modernization, the direct influences of some of its components such as urbanization
and industrialization are expected to vary through time. 15^
In the process of societal development, as is the case in
Puerto Rico, the urban concentration variable is expected to lose its direct negative effect on the birth rates, and to distribute its influence indirectly through other social and economic parameters. On the other hand, in dustrialization is expected to raise its negative direct effect on birth rates in developing societies. Increase In the non-familial activity of women is incompatible with the mothers' roles. Increasing opportunities for women to work outside the home will have a direct nega tive effect on the actual and expected number of children.
However, some of the indicators of industrialization such as the employment in manufacturing industries, are expected in the long run also to lose their negative effect on fer tility, and probably distribute their influence through other socioeconomic variables. (See Table 18.) In Model III: 1950-1960, using a time-function approach, approximately 58 percent of the variations on the fertility ratios were explained by the level of
urbanization-industrialization of the municipios in 1 9 6 O plus the influence of their past fertility in 1950. The surprising finding in this model was the positive effect
of urban concentration upon fertility rates in i9 60 (pSip = .10), when the effects of fertility rates in
1950 and the influence of the manufacturing variable 155
TABLE 18 ’COMPARISON OP DIRECT PATH COEFFICIENTS TO FERTILITY RATIOS, 1950-1960. PUERTO RICO
Variable Direct Path Coefficients To Fertility (X^)
1950 I960
Urban -.2630 •
Manufacturing X2 -.1620
Education X^ - . 1 2 3 6 - . 2 5 0 6
Income X^^ -.1946 - . 1 2 3 0
Women Working X5 -.3777 - . 2 2 1 9
Coefficient of
Determination R^ .4 5 4 9 .3618 156 in i9 60 were controlled. This rather low positive in fluence of urban concentration on birth rates was ex plained as a result of the concentration of rural migrants, with unusually high fertility, in the urban areas of
Puerto Rico between 1950 and 1 9 6 O, Model IV: 1950-1960 was a fully recursive causal model with all possible paths drawn depicting the network of the relationships between SES and fertility. Several models were tested deleting negligible paths, but they failed to reproduce the original correlations. This problem was explained in terms of (1) the high multi collinearity observed between income and education as measures of SES; (2) the intervening character of SES between modernization in general and fertility levels; and (3) the existence of intervening variables between income and education when a time dimension was introduced into the causal model. In Model V: 1950-1960, the network of the rela tionship between the participation of women in the labor force when accompanied by urban concentration was analyzed. It was found that as a consequence of the percent of decline in the proportion of women working between 1950 and i96 0 in Puerto Rico, the proportion of women working in i960 was not a time-function of the proportion in
1 9 5 0. However, the general inverse relationship between 157 the participation of women in the labor force and fertility was maintained (P32 = -.3840 in 1950; and p^^ = -.1527 in I960). This study represents only a small step in the " development of a comprehensive theoretical and meth odological model of human fertility. It was an attempt to establish the importance of three social interdependent phenomena in fertility studies both from a theoretical and methodological perspective, with causal models in the path analysis form being used for testing hypothesis and theory construction. More empirical studies are needed both at the individual and societal level in other social settings and probably with more precise measures of fertility performance. The variables selected as indicators of the three deminsions are considered as reliable for further research; however, they can be redefined and improved. Furthermore, some other variables could be added at any point in the models presented. Also, different levels of analysis can bo used in causal models linking macro-sociological dimensions (urbaniza- tion-industrialization) with individual variables (inter course, conception, gestation and parturition), and socio-psychological variables (attitudes, values, beliefs, paremtal communication, family structure, roles and authority). 158
While the revised models fit Puerto Rico for
1950 and i9 6 0 , they must be considered as a step toward a better understanding of community fertility levels. Further development and testing of similar and new models is needed. The author has already planned to test a similar causal model for the 1970 Puerto Rican census, and to compare the results with the findings presented in this investigation. It is the author's theoretical preconception that through the development and testing of causal models of the form elaborated here, a more comprehensive theory of fertility at either individual or societal levels may result. Finally, the comparison of several models at different points in time from the same social setting or from different societies will provide a tremendous opportunity for increasing the knowledge about the network of the relationships between population trends and mod/^mization. APPENDIX
A maximum of ten-variate analysis can be per formed with this program. The r and k parameters determine the order of the matrix to be multiplied by the vector Z.
The subroutine "vecmat" is assumed available in the public library.
10, DECLARE a(10,10), z(10), x(lO); 15. DECLARE vecmat ENTRY XT KEY (libr) LIB (PUBLIC); 20, GET LIST (r, k); 30, DO i = 1 TO r; 40, DO j = 1 TO k; 50, GET LIST (a(i, j)); 60 END; 70, END; 80, DO i = 1 TO r; 90, GET LIST (z(i)); 100, END; 110, CALL vecmat (z, a, x, r, k); 120, DO i = 1 TO r; 130, PUT LIST (x(i)); 140, END; 150, END; xeq k Bibliography
Adelman, Irma, “An Econometric Analysis of Population Growth," American Economic Review. 53 (1 9 6 3 ). Aitkin, D. A., W. E. Nelson and Karen H, Reinfurt. "Tests for Correlation Matrices," Biometrika. 55 (1968), Baltzell, Digby E, "Social Mobility and Fertility Within an Elite Group," Milbank Memorial Fund Q.uarterly, 21 (1953). Banks, J. A, Prosperity and Parenthood: A Study of Family Planning Among The Victorian Middle Classes, Tbondon: Rootledge and Kegen Paul, 1954),
Becker, Gasry S. "An Economic Analysis of Fertility," in National Bureau of Economic Research (Princeton: University Press, I9 6 O),
Berent, Jerry, "Fertility and Social Mobility," Popula tion Studies. 5 (1 9 5 2), Blacker, G, P. "Stages in Population Growth," The Eugenics Review. 39 (194?). Blake, Judith, "Demographic Science and the Redirection of Population Policy," in Kenneth C= Kemraeryer, Population Studies: Selected Essays and Research TChicago: Rand McNally and Co., (1 9 6 9).
Blalock, Hubert M, Jr. Causal Inferences in Non- experimental Research (Chapel Kill: The University of liorth Carolina Press, 1964).
Boudon, R, "A New Look at Correlation Analysis," in H, M, Blalock and A, B, Blalock (Eds,)» Methodology in Social Research (New York: McC-raw Hill, 1 9 6 8 ), Bourne, Dorothy D, and James R, Bourne, Thirty Years of Change in Puerto Rico: A Case Study of Ten Selected Rural Areas (New York: Pracer Publication, 1966),
Boyle, H, P, "Path Analysis and Ordinal Data," American Journal of Sociology. 75 (1970),
160 l 6 l
Carleton, Robert 0. "Labor Force Participation: A Stimulus to Fertility in Puerto Rico?" Demography . 2 (1965). Coleman, James S. Introduction to Mathematical Sociology (Glencoe: The Free Press, 1964).
Collver, Andrew. "Women's Work Participation and Fer tility in Metropolitan Areas," Demography. 5 (1958). and E. Langloiss. "The Female Labor Force in Metropolitan Areas: An International Comparison," Economic Development and Cultural Change. 10 (1962).
Combs, Jerry W. and Kingsley Davis. "Differential Fertility in Puerto Rico." Population Studies. 5 (1951).------:------"The Pattern of Puerto Rican Fertility," Population Studies. 4 (1951). Cowgill, D. 0. "The Theory of Population Growth Cycles," American Journal of Sociology. 55 {19^91. "Transition Theory as General Population Theory," Social Forces. 4l (1963).
Davis, Kingsley and Judith Blake, "Social Structure and Fertility: An Analytical Framework," Economic Development and Cultural Change. 4 (1956).
"The Theory of Change and Response in Modem Demographic History," Population Index, 29 (1 9 6 3 ). "population Policy: Will Current Programs Succeed?" Science. 158 (1 9 6 7 ).
DeJong, Gordon F. "Religious Fundamentalism, Socio economic Status, and Fertility Attitudes in the Southern Appalachians," Demography. 2 (1 9 6 5 ).
Duncan. Otis D. "Farm Background and Differential Fertility," Demography. 2 (1 9 6 5 ).
"Path Analysis: Sociological Examples," American Journal of Sociology. ?2 (1 9 6 6 ).
Dumont, Arsene. Depopulation et Civilisation: Etude Démographique (Paris: Lecrosnier et Babe, 1890). 162
Easterlin, Richard A, "The American Baby Boom in Historical Perspective," American Economic Review. 51 (1961). Freedman, Deborath, "The Relation of Economic Status to Fertility," American Economic Review. 53 (1963).
Freedman, Ronald. "American Studies of Family Planning and Fertility: A Review of Major Trends and Issues," in Clyde V. Kiser, Research in Family Planning (Princeton: University Press, 1952). ______. "The Sociology of Human Fertility: A Trend Report and Bibliography." Current Sociology. 10-11 (1961- 1962).
______. "Current Fertility of Married Couples in the United States," Population Index. 29 (1963). Glass, D. V. Population Policies and Movements in Europe (London: Oxford University Press, 1940).
Grabill, Willson, Clyde V. Kiser and P. K. Whelpton. The Fertility of American Women (New York: John Wiley and Sons, 1958). Goldberg, David. "The Fertility of Two-generation Urbanites," Population Studies. 12 (1959). Hauser, Philip M, and Lee F. Schnore. The Study of Urbanization (New York: John Wiley and Sons, Inc. 1965). Hatt, Paul, Backgrounds of Human Fertility in Puerto Rico: A Sociological Survey (Princeton: University tress, 1952). Heer, David M. "Economic Development and Fertility," Demography . 13 (1966)..
and Elsa S. Turner. "Aereal Differences in Latin American Fertility." Population Studies. (1965). Heise, David R. "Problems in Path Analysis and Causal Inference," in Edgar Borgotta (ed.). Sociological Methodology. 1969 (San Francisco: Jessey-Bass, 1969). 163
Hill, Reuben, J. Mayone Stycos and Kurt W. Back, The Family and Population Control, a Puerto Rican Experiment in Social Change (Chapel Hill; University of North Carolina Press, 1959).
Horst, Paul. Matrix Algebra for Social Scientists (N ew York: Halt, Rinehart and Winston, 1963). Jaffe, A. J. "Differential Fertility in the White Population in Early America," Journal of Heredity. 31 (1940). Urbanization and Fertility," American Journal of Sociology. 48 (1942).
People. Jobs and Economic Development '(Glencoe: Free Press, 1959). and K. Azumi. "The Birth Rate and Cottage Industries in Underdeveloped Countries," Economic Development and Cultural Change. 9 (I960).
Janovitz, Barbara S. "An Empirical Study of the Effects of Socioeconomic Development on Fertility Rates," Demography. 8 (1971).
Jennrich, R. I. "Asymptotic Test for the Equality of Two Correlation Matrices," Journal of the American Statistical Association. 65 (1970).
Kantner, John F. and Clyde V. Kiser. "The Interrelation of Fertility, Fertility Planning and Intergenerational Social Mobility." Milbank Memorial Fund Quarterly 32 (1954). Keyfitz, Natham and Wilhelm Flieger. World Population: An Analysis of Vital Data (Chicago: The University of Chicago Press, 1968).
Kirk, Dudley. Europe's Population in the Interwar Years (Paris: UNESCO, 1946).
Kiser, Clyde V. and P. K. whelpton. "Resume of the Indianapolis Study of Social and Psychological Factors Affecting Fertility." Population Studies. 7 (1953). Wilson H. Grabill and Arthur A, Campbell. Trends and Variations in Fertility in the United States (Cambridge: Harvard University Press, 1968). 16^
Kuliback, S. “On Testing Correlation Matrices," Applied. Statistics. 16 (1967). Kunz, Phillip R. "The Relation of Income and Fertility," Journal of Marriage and the Family. 2? (1965).
Kupinsky, Stanley. "Non-Familial Activity and Socio economic Differentials in Fertility," Demography. 8 (1971). Land, K. C. "Principles of Path Analysis," in Edgar /Borgafta (ed.). Sociological Methodology 1969 (San Francisco: Jessey-Bass, 1 9 6 9). Li, C. C. Population Genetics (Chicago: University of Chicago Press, 1955). "The Concept of Path Coefficient and its Impact on Population Genetics" Biometrics. 12 (1956). Macisco, John Jr. "Fertility in Puerto Rico: An Eco logical Study," Sociological Analysis. 26 (I9 6 5 ).
Malthus, Thomas R. An Essay on the Principle of Popula tion (London: Reeves and Tuner, 7th ed. IÔ7 2 ).
Manheim, Uried. Puerto Rico Builds (San Juan: Housing Investment Corporation, 1968). Mayer, Kurt. "Diminishing Class Differentials in the United States." Kykla.g.. 12 (1959). Meier, Richard L. "Concerning Equilibrium in Human Populations," Social Problems. 6 (1958). Moore, Wilbert E. The Impact of Industry (Englewood; Prentice-Hall, Inc. 1965).
Myers, G. C. and E. W. Morris. "Migration and Fertility in Puerto Rico," Population Studies. 20 (1966). Namboodiri. Krishnan N. "The Wife's Work Experience and Child Spacing," Milbank Memorial Fund Gluarterly. 42 (1964).
Notestein, Frank W. "Population - The Long View," in Theordore W. Schultz (Ed.). Food For the World (Chicago: University of Chicago Press, 1945). 165
Nygreen, G. T. "Interactive Path Analysis," The American Sociologists. 6 (1971). Petersen, William. Population (New York: The MacMillan •Company, 1969). "The Malthus-Gcdwin Debate, Then and Now," Demography. 8 {1971). Pratt, Lois and P. K. Whelpton. "Social and Psychological Factors Affecting Fertility." Milbapk Memorial Fund Quarterly. 3 0 (1956). Puerto Rico. Statistical Yearbook (San Juan: Bureau of Economics and Social Planning, 1955-1960). Puerto Rico Department of Health. Annual Vital Statistics Report (San Juan: Division of Demographic Registry and Vital Statistics, 1968). Ridley, Jeanne C. "Number of Children Expected in Relation to Non-Familial Activities of the Wife," Milbank Memorial Fund Quarterly. 37 (1959). "Demographic Change and the Roles and Status of Women," Annals of the American Academy of Political and Social Science, 375 (1 9 6 8 ).
Riemer, Ruth and Clyde V. Kiser. "Economic Tension and Social Mobility in Relation to Fertility Planning and size of Planned Family," Milbank Memorial Fund Quarterly. 32 (1954). Ritchey, Neal and Shannon Stokes, "Residence Background, Socioeconomic Status, and Fertility." Demography. 8 (1 9 7 1). Robinson, Warren C. "Urban-Rural Differences in Indian Fertility," Population Studies. 14 (1 9ÔI).
"Urbanization and Fertility; The NonWestem Experience." Milbank Memorial Fund Quarterly. 4l (1963). Rosen, Bernard C. and Alan B. Simmons, "Industrialization, Family and Fertility," Demography. 9 (1 9 7 1).
Ryder, Norman. "The Conceptualization of the Transition in Fertility," Cold Spring Harbor Symposium on Quantitative Biology, 22 (1957). 166
Schwirian, Kent P,. and Jesus Eico-Velasco, The Resi dential Distribution of Status Groups in Puerto Rico's Metropolitan Areas," Demop:raohy. 8 (1 9 7 1). "Ecological Aspects of Mortality in a Developing Country: The Case of Puerto Rico," paper presented at the Annual Meetings of the Ohio Valley Sociological Society, Akron, Ohio, 1971. and Ruth K, Smith, "Primacy, Modernization and Urban Structure: The Ecology of Puerto Rico Cities," Paper presented at the 1971 Annual Meetings of the American Sociological Association. Scott, Wolf, "Fertility and Social Mobility Among Teachers," Population Studies. 11 (1958), Spady, William G, and Donna Greenwodd, "Instant Path Analysis: An Elementary Cookbook," AERA Division Generator, 1 (1970). Steward, Julian et. all. The People of Puerto Rico (Chicago: University of Illinois Press, 1956), Stycos, M. J. Human Fertility in Latin America (Ithaca, N. Y.: Cornell University Press, 1968),
and R, H, Weller. "Female Working Roles and Fertility," Demography, 4 (1967)
Stys, W, "The Influence of Economic Conditions on the Fertility of Peasant Women." Population Studies. 11 (1957). ------Taeuber, Irene, The Population of Japan (Princeton: University Press, 1958).
"Demographic Modernization: Continuities and Transitions," Demography. 3 (1966).
Tien, Yuan H. "The Social Mobility/Fertility Hypothesis Reconsidered: an Empirical Study," American Sociological Review. 26 (1961).
Social Mobility and Controlled Fertility (New Haven: College University Press, 1 9 6 5 ),
Mobility, Non-Familial Activity, and Fertility," Demography. 4 (1967), 167
Thompson, Warren S, "Population," American Journal of Sociology. 3 4 (1 9 2 9). ______. Plenty of People (New York: Ronald, 1948), Tumin, Melvin R. Social Class and Social Change in Puerto Rico (Princeton: University Press, 1961), United Nations. The Determinants and Consequences of Populations TFends (New York: Population Studies, United Nations Publications, No, 17. 1953). U. S. Department of Commerce, Census of Population: 1950 (Washington, D.C,: Government Printing Office, 1953). Census of Population: I960 (Washington, D.C.: Government Printing Office 1 9 6 3 ), Census of Population: 1940 (Washington, D.C . G o v e r n m e n t Printing Office 1943) U. S. Department of Health, Education and Welfare. Vital Statistics of the United States: 1940 (Washington, D.C.: Government Printing Office 1941),
Vital Statistics of The United States: 1950 (Washington, D.C.: Government Printing Office, 1951) Vital Statistics of The United States: I960 (Washington, D.C.1 Government Printing Office, 1961),
Van North, Leighton and Bart ram P. Karon... "Demographic Transition Re-Examined," American Sociological Review. 20 (i960). Weintraub, Robert. "The Birth Rate and Economic Development: An Empirical Study." Econometrica. 30 (1962), ------Weller, Robert H, "The Employment of Wives, Dominence, and Fertility." Journal of Marriaere and the Family' 30 (1 9 6 8 ),------
Whelpton, P. K. "Industrial Development and Population Growth," Social Forces. 6 (1928).
______. Cohort Fertility: Native Women in the United States (Princeton; University Press, 1954). 168
Westoff, Charles P. "The Charging Focus of Differential Fertility Research: The Social Mobility Hypothesis," Milbank Memorial Fund Quarterly. 31 (1953).
et. all. Family Growth in Metropolitan America (Princeton: University Press, 1961) Westoff, Leslie A, and Charles F. Wes toff. From Now to Zero. Fertility. Contraception and Abortion in America (Boston: Little. Brown and Co.. 1971). Wright, S. "The Method of Path Coefficients," Annals of Mathematical Statistics. 5 (1938).
"The Interpretation of Multivariate Systems." in 0. Kempthorne, et. al. (Eds.). Statistics and Mathematics in Biology (Ames: Iowa State College rress, lv5^;. Wrong, Dennis H. "Trends in Class Fertility in Western Nations," Canadian Journal of Economics and Political Science, 24- (1958) .
Zarate, Alvan 0 . "Fertility in Urban Areas of Mexico: Implications for the Theory of the Demographic Transition," Demography. 4 (196?).
. "Differentials Fertility in Monterrey, Nexico, Prelude to Transition?" Milbank Memorial Fund Quarterly. 45 (1967).
______. "Some Factors Associated with Urban-Rural Fertility Differentials in Mexico." Population Studies. 21 (1967).