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APEC Study Series Economic Factors Affecting Birth Rates in APEC Economies APEC, 경제성장

저자 Junsok Yang 발간번호 24-03 자료언어 English 발간일 2024.12.13

원문보기(다운로드:590) 저자별 보고서 주제별 보고서

본고는 경제변수가 출산율에 어떻게 영향을 주는 지를 패널데이터 회귀분석을 통하여 살펴본다. 데이터는 세계은행 공개데이터베이스에서 발췌하였으며, 180여 개의 국가들을 포함한 전 세계 데이터세트와 APEC 회원국에만 한정된 데이터세트를 사용하였다. 본고에서 검토한 경제변수들은 1인당 GDP 수준 및 성장률, 남녀 노동시장 참여율, 산업별 남녀 노동시장 참여율이며, 부록에서 추가로 남녀의 교육차이 및 가사 참여도의 영향도 검토해 보았다. 단, 부록에 포함된 분석은 통계 불확실성으로 인해 신뢰성이 약하지만, 관심받을 만한 결과를 포함하고 있다. 먼저 전 세계 1991년부터 2022년간의 데이터를 사용하여 1인당 GDP의 수준 및 현재와 과거의 1인당 GDP 성장률이 출산율에 미친 영향을 살펴보았다. 전 세계 데이터를 사용할 때 1인당 GDP 수준이 높으면 출산율이 낮아지고, 1인당 GDP의 성장률(당해, 1년 전, 또는 지난 5년간 평균)이 높아지면 출산율이 낮아진다는 타 연구와 유사한 결과가 나타났다. 그러나 APEC 회원국은 세계 추세 이상으로 성장률이 추가적으로 낮아진다는 결과가 나타났다. APEC 회원국만 포함된 데이터를 사용할 때도 대체로 유사한 결과가 나타났다.

1인당 GDP의 수준 및 성장률을 통제변수로 사용하고 남녀 노동시장 참여율을 추가한 결과로 전 세계 데이터를 사용한 경우, 남자와 여자 모두 노동시장 참여율이 높을수록 출산율은 높아지는 것을 확인했다. 그러나 남자 참여율의 영향이 여자 참여율의 영향보다 높았다. 데이터를 APEC 경제들만 제한하고 회귀분석을 진행하였더니 남자의 참여율은 출산율에 영향을 주었지만, 여자의 참여율은 별다른 영향을 주지 않은 것으로 나타났다.

1인당 GDP의 수준 및 성장률을 통제변수로 사용하고 남자와 여자의 산업별(농업, 공업, 서비스업) 노동시장 참여 비율을 독립변수로 사용한 결과, 전 세계 데이터를 사용한 경우, 남녀를 불구하고 공업 참여비중이 높아질수록 출산율에 부정적인 영향을 미친 반면, 서비스와 농업 참여비중이 높아질수록 출산율에 긍정적인 영향을 미쳤으며, 남녀 모두 서비스보다는 농업 참여비중이 출산율에 미치는 영향이 높았다. 반면 APEC 경제만 분석한 경우, 여성은 농업보다는 서비스 참여비중이 출산율에 더 큰 긍정적 효과를 가지고 왔다.

부록에서는 남녀 교육의 차이와 남녀 가사 참여 시간 비중을 독립변수로 출산율에 주는 영향을 분석하고자 시도해 보았으나, 이 데이터가 없는 국가들이 많았고, 데이터를 수집하는 국가에 있어서도 이들이 데이터를 매년 수집하지 않아 패널데이터가 상당히 불균형적이었다. 그럼에도 불구하고 데이터가 있는 국가들에 대해 회귀분석을 시도해 보았는데, 남녀 교육차이가 심할수록 출산율에 부정적인 영향을 주는 것으로 나타났다. 반면 남녀 가사시간 차이는 출산율에 별다른 영향을 주지 않는 것으로 나타났다.

결론적으로 경제가 성장하면서 출산율이 감소된다는 점이 확인되었으므로 경제정책, 특히 복지후생정책 및 연금정책과 같은 노후정책을 고려할 때 연령구조적 변화를 고려해야 하며, 출산율을 높이기 위해서는 여성의 서비스 산업 진출을 장려해야 할 것이다. 또한 전 세계 차원에서는 여성들의 취업이나 소득뿐만이 아니라 남성들의 취업과 소득도 출산율에 중요한 역할을 하기에 출생률을 높이기 위해서는 가족 차원에서의 소득과 취업을 고려해야 할 것이다. 특히 APEC 회원국 데이터를 사용할 때는 여성 취업률보다 남성 취업률이 출산율에 더 영향을 미쳤다.
In the last ten years, fertility rates for advanced and developing economies have been falling faster than expected. Korea has been leading the decline, but almost all advanced and developing economies have experienced accelerated decline in birth rates. Some researchers now expect the world to start experiencing falling global population as quickly as in 2030s.

Even more surprising is that fertility rates for APEC economies have been falling even faster. APEC economies with the highest fertility rates are only slightly above the replacement rate of 2.1; with most economies, even developing members, in the 1% range. This paper is intended to be an exploratory dip into looking at correlations between birth rates and various economic data. We try to examine some of the popular reasons behind the falling birth rates, to see whether they have validity based on data, and see whether APEC economies are special in the sense that the birth rates are falling faster for APEC economies. The paper looks at economic data using panel data regressions to see why birth rates are falling overall, and why they are falling faster for APEC economies. We will concentrate more on trying to find correlations between variables in the data than coming up with theoretical reasons, which will require a much richer data set.

In Section II, the paper lists some of the popular reasons often cited for declining birth rates; Section III is a short general discussion on the data used. Sections IV and V examines whether the data backs some of these popular reasons for the decline. Section IV looks at the relationship between some basic economic growth variables and fertility rates, and serves as a base for further analysis. Section V looks at the relationship between employment data and fertility rates, Given the faster fertility decline for APEC economies, Section VI looks at whether the formation of APEC had a role in the faster decline of fertility rates. Appendix A looks at the relationship between gender education disparities and fertility rates, and Appendix B is a short exploration on whether there is a case to be made that gender disparities in housework is a factor in lower fertility rates.

In this paper, we used panel data of more than 180 economies to examine some factors affecting fertility rates. The factors examined included economic growth factors such as per capita GDP and GDP growth rates; gender based labor and employment factors such as male and female labor participation rate, and the ratio of male and female workers working in various industries. We also considered how some gender based disparities in education, and time spent doing housework for men and women affected fertility rates, though the results are less definite for these cases due to irregular nature of data available. We ran regressions on the global data set, and then for some regressions, only on data for APEC member economies.

Where we used global panel data, we re-confirmed some results that researchers had found before – namely, the higher the per-capita GDP, the lower the fertility rate; the higher the growth rate, the lower the fertility rate. So more income is not always the answer for fostering fertility rates. However, we did find that current growth variables predicted fertility rates better than past growth rate variables, showing perhaps that the trend of falling fertility rates is a more powerful force than a good economic environment fostering more births. These regressions also showed that APEC economies are qualitatively similar to the global group, but with a faster decline. Given similar situations, APEC economies experience a lower fertility rate than global group as a whole.

Using the economic growth variables as controls, we added labor market data to the regressions, and we found that, for the global group, increases in male and female labor participation increased fertility rates. However, perhaps somewhat against expectations, the effect of male labor participation rate had greater effect than female labor participation. Again, given similar situations APEC economies had lower fertility rates. When we used only APEC economy data, female labor force participation had no significant effect on fertility rates. Only the male labor force participation mattered, and higher the male participation rate, higher the fertility rate.

Then we used the shares of male and female labor force on agriculture, industry (manufacturing) and service industries. For the global data set regressions, as expected, a rise of the share working in agriculture would raise the fertility rate, and a rise of the share working in industry would lower fertility rate, as expected. Service industry participation came in between – the effect on fertility rate higher than industry and likely a positive effect, but lower than the effect from agricultural industry participation. The results were same for males and females.

However, when we used only APEC economy data, the qualitative results were significantly different. Male labor force industry share behaved the same as the global group, but for females, share of workers in services had a higher positive effect on fertility rate than agriculture. Industry, as expected had the lowest and negative effect. The effect of female workers participation in different industries on fertility rates seems to be significantly different for APEC economies compared to global group as a whole. Which may be the reason why APEC economy fertility rates fell faster than the global group, but it may also imply that if APEC economies give more flexibility to female workers in service industries, fertility rates may pick up. Further and deeper studies should be taken to see whether the pattern of female employment in APEC economies differ significantly compared to other economies, especially the possible differences between developing APEC economies and other developing economies.

Analysis looking at gender disparities in education for primary and secondary education showed that it is the disparities in secondary education which may be the key to differences in fertility rates, but the results should be taken carefully, since the data for gender disparity in education was available irregularly, so an unbalanced panel data was used, and gender disparities for primary and secondary education seems to be highly correlated. Also, the time disparity between men and women doing housework was also examined, but there were no results that led us to believe that the disparity in doing housework affected fertility rates, contrary to many popular media reports in Korea and elsewhere. But again, data was only available irregularly, so an unbalanced panel data was used, so results may not be as credible as regressions using labor force variables. For these regressions, a separate APEC economy regressions were not attempted due to paucity of data.

These regression results show that declining fertility rate is a strong trend based on rising wealth and growth rates; but the trend may be partially reversed if appropriate labor market adjustments can occur. For APEC economies, encouraging women to go into the services sector which perhaps offer an urban living coupled with flexible labor time schedule may partially offset the declining fertility rates.

Drawing some policy implications from the analyses, while Korea and other APEC economies may be able to keep fertility rates from falling “too low,” it will not be able to raise the rates to the replacement rate of 2.1. Thus, when designing welfare policies, the policymakers must keep the declining population and demographic implications in mind. Over-promising benefits for post-retirement public pension will become a critical problem, and governments should encourage private measures to the public to get them ready for post-retirement.

Second, for would-be mothers, encouraging employment in the service sector may alleviate some of the rapid decline in the fertility rates. Encouraging employment in the services sector, making services job for women available in small and large cities may do better in raising fertility for APEC economies. Women who work for the public sector tend to have more children, in part due to more flexible schedules and consideration for pregnant mothers.

Also, for fertility rates, male employment seems to be as important or perhaps more important than female employment. So, while more flexible time scheduling may be warranted for the would-be mother, any income implications should be approached from the point of view of the entire household.

While the Korean media often cites complaints that men do not do enough housework, as a contributor to low fertility, using global data, this study did not find any particular evidence for that explanation. While the complaint may be valid for Korea, there seems to be little reason to believe that it is a major reason globally, but because of data deficiency, the results may not be clear cut.

Of course, more research is needed. During the modernization and development process, the economic position of husband and wife in the family seems to change from being complementary to more of substitutes – where in the olden days, women specialized in housework aspect of the household and men specialized in wage earning or outside work, now men and women have similar work characteristics, and the global group regressions in this study did not consider such changes in characteristics about husband and wives; but the results that we have derived may be showing the effects of such changes.
Executive Summary

I. Introduction: Motivation

II. Possible Reasons for Falling Birth Rates

III. Data and Methodology

IV. Per Capita GDP and Fertility

V. Labor Market Considerations

VI. Did APEC Contribute to Falling Fertility?

VII. Policy Implications and Conclusion

References

Appendix

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