Socioeconomic Determinants of Fertility Behavior in Developing Nations Theory and Initial Results (1982) / Chapter Skim
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2.5 Illustration of Operationalization
2.5 Illustration of Operationalization
Pages 64-80
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From page 64... ...
The interaction terms in the LF structural equation require special treatment. There is no single effect of respondent's education (WED)
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From page 65... ...
(1978) Korea Peru Indicator 1960 1970 1960 1970 Percent adult literacy 71 88 61 72 Percent of 15-19 year-olds in primary or secondary 65 76 58 75 Life expectancy at birth 54 59 50 55 Infant mortality rate per 1,000 91 60 92 135 Percent of males 15-64 in nonagricultural occupat ions 31 45 37 41 GNP per capita (in 1974 U.S.$)
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From page 66... ...
The macro differences between Peru and Korea suggest that the effects of the socioeconomic determinants of LF should be smaller for Korea than for Peru, mainly because of family planning program strength. mere should not be major differences between the two countries in the socioeconomic determinants of age at first birth (~FB)
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From page 67... ...
The micro parameters for each country will vary for historical, cultural, geographic and other reasons having little or nothing to do with level of socioeconomic development or strength of family planning program effort. Some of these factors, such as breastfeeding, kinship, and cohabitation patterns, will directly influence fertility outcomes, and we plan to incorporate a number of these in future analyses.
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From page 68... ...
When the explanatory dimension is a set of categories, summary information for tests of significance pertains to the global test that all coefficients within a classification are simultaneously zero. Bracketed entries are the squared multiple partial correlations associated with the dummy variable classifications.
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From page 69... ...
For reasons noted at the end of the previous section, this apparent discrepancy will not be explored here. It does reaffirm, however, that there is no single all-purpose coding of education, just as there is no single all-purpose macro measure of culture, family planning program effort, or socioeconomic development.
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From page 70... ...
In terms of this second role, we hypothesize that increases in socioeconomic development should lead to increases in the intercept of the AFB equation. As long as both countries are placed in the high category of the social setting index, the essential equality of the AFB intercepts for Peru and Korea is compatible with this hypothesis.
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From page 71... ...
When the explanatory dimension is a set of categories, summary information for tests of significance pertains to the alohal tact chop al 1 I;; .,::_ _ classification are simultaneously zero. Bracketed entries are the squared multiple partial correlations associated with the dummy variable classifications.
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From page 72... ...
We use these derived coefficients in the macro regressions, together with their derived estimated variances. We may next consider how observed directions of relationships between the socioeconomic variables and LF correspond with what the theory hypothesizes for transitional settings, beginning with those effects not involved in the interactions.
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From page 73... ...
73 TABLE 2.8 Late Fertility (LF) Structural Equation, Currently Married Women Aged 40-44 in 1974, Peru and Korea World Fertility Surveys Dependent Variable is LF Explanatory Variables and Other Regression Information Peru Korea Childhood Residence (RESC)
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From page 74... ...
74 TABLE 2.8 (continued) Dependent Variable is LF Explanatory Variables and Other Regression Information Peru Korea Husband's Occupation (COCCI [d]
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From page 75... ...
However, instead of attempting to read off the patterns of effects directly from Table 2.8, we will use the device of standardizing conditional coefficients to remove insignificant interactions; this will yield reasonable approximations of the effects that would be obtained if the regressions were computed with the insignificant terms or classifications omitted.l3 To examine the EF effects on LF in Peru, we standardize over HOCC (using sample composition for this classification) to obtain EF effects conditional on WED -- the only significant interaction involving EF in the Peruvian data.
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From page 76... ...
For those with at least two boys, nonagricultural employers and self-employed workers outside of agriculture have lower LF than employees, but most importantly, lower LF than farmers. Even though the EF*
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From page 77... ...
Again, this is consistent with the expectations developed in Chapter 1. Considering next the interactive results for Korea, it is clear from Table 2.8 that the SCB variable does not interact significantly with WED or HOCC, using a global significance test.
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From page 78... ...
According to the result. of the global signif icance tests for the Korean data, EF interacts only with HOCC, and HOCC interacts only with EF; therefore, examination of the EF effects conditional on HOCC will tell the same story as examination of the HOCC effects conditional on EF.
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From page 79... ...
per capita and the relative size of the nonagricultural labor force over other macro indicators, this result is inconsistent with expectations. Given Korea's position relative to that of Peru on the social setting index, and given Korea's strong family planning program effort score compared to that of Peru, Korea should have the intercept with the larger absolute value, given that both are negative.
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From page 80... ...
2.6 MACRO ANALYSIS Our two fundamental hypotheses suggest a particular ordering of steps within the macro analysis. The first basic hypothesis is that the socioeconomic determinants of fertility affect the components of the reproductive process differently.
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