출산(出産)과 사회·경제적(社會·經濟的) 제변수(諸變數)와의 관계(關係)에 관한 연구(硏究) 개발도상국(開發途上國)과 선진국(先進國)의 비교(比較)를 중심(中心)으로 (1984)

In recent years, most of the less developed countries have population pressure. In this study, I intended to show the relationship between fertility and economic development which brings into the fertility decision, the taste changes in fertility control associated with development. Birth rate is high in the less developed countries, commonly more than twice as high as in the developed countries. Maybe, fertility is one of the single socio-economic variables distinguishing developed and less developed countries.
Kuznets says in his book that during the early stage of modern economic growth in Europe, birth rate rose initially as per capita income increased, but a secular downward trend in birth rates followed which dominated over the long run. Simon confirmed this argument by showing empirical evidence that the birth rate increases in early stages of development but decreases as income increases in less developed countries. That is，fertility is more sensitive to socio-economic variables in later stage of development.
Fertility responses to a given change in explanatory variable vary with the level of modernization. I hoped that empirical result shows the relationship between economic development and fertility at different stages of economic maturity, and relative importance of income and demographic variables in fertility decline.
My empirical data are a combined time-series cross-section of 25 Latin American and Asian countries (1950, 1960, and 1970) for less developed countries (LDC)，and cross-section of ten more developed countries (MDC) including Canada, U.S.A., and European countries. In addition to these data, multiperiod sample, from 1966 to 1982, for Korea is used for this study on the fertility-economic variable relationship.
Fertility is hypothesized to be a function of following.
CBR = F (PCG, IMR, FPR, IL, AG) where, CBR is Crude Birth Rate.
PCG is Per Capita GNP.
FPR is Female Labor Force Participation Rate.
IL is Illiteracy Rate.
AG is Agricultural Employment Rate.
Fertility is total number of births per woman in different age cohort. But since this measure is not available for many countries, I used crude birth rate to measure fertility.
I tested model by choosing linear and logarithmic form, and running by ordinary least square (OLS) method. The significance of each regression coefficient in the fertility equation is tested by t-statistic. T-statistic shows that in 1970 for the MDC, female participation rate and illiteracy rate are significant at 0.1 level, using a two-tailed test, while per capita GNP, infant mortality rate, agricultural employment are not significant. But, for LDC, 1950, 1960 and 1970 have the same significance test result: both agricultural employment and female participation rate are significantly different from zero. For Korea, during 1966 1982, all the variables except female participation rate are significant. With some exceptions, most of the signs of the coefficients are the same as I expected. Economic causes do not adequately explain the high level of fertility for LDC, during early stage of economic development. R-squares are 0.3569 in 1950 and 0.5012 in 1960, whereas in 1970, the R-square improves to .6349. In linear model, “Chow Test” indicates that, in the year of 1970, the effects of variables on fertility are almost the same for two different groups of countries.
Table 2 (Elasticity Multipliers) shows that crude birth rate can be reduced in MDC by encouraging greater female participation in the labor forces (where a one percent increase in the female participation rate reduces the birth rate by .28 percent.) Also for MDC a one percent increase in the agricultural employment results in .28 percent reduction in the birth rate.