人口
经济
激励
人口老龄化
抚养比率
人口增长
人口经济学
劳动经济学
生育率
人口学
市场经济
社会学
作者
David E. Bloom,David Canning,Günther Fink
出处
期刊:RePEc: Research Papers in Economics - RePEc
日期:2008-01-01
卷期号:: 1-48
被引量:37
摘要
Between 2000 and 2050, the share of the population aged 60 and over is projected to increase in every country in the world. Although labor force participation rates are projected to decline from 2000 to 2040 in most countries, due mainly to changes in their age distributions, labor force- to-population ratios will actually increase in most countries. This is because low fertility will cause lower youth dependency that is more than enough to offset the skewing of adults toward the older ages at which labor force participation is lower. The increase in labor-force-to-population ratios will be further magnified by increases in age-specific rates of female labor force participation associated with fertility declines. These factors suggest that economic growth will continue apace, notwithstanding the phenomenon of population aging. For the Organization for Economic Co-operation and Development (OECD) countries, the declines projected to occur in both labor force participation and labor-force-to-population ratios suggest modest declines in the pace of economic growth. But even these effects can be mitigated by behavioral responses to population aging-in the form of higher savings for retirement, greater labor force participation, and increased immigration from labor-surplus to labor-deficit countries. Countries that can facilitate such changes may be able to limit the adverse consequences of population aging. When seen through the lens of several mitigating considerations, there is reason to think that population aging in developed countries may have less effect than some have predicted. In addition, policy responses related to retirement incentives, pension funding methods, investments in health care of the elderly, and immigration can further ameliorate the effect of population aging on economic growth.
科研通智能强力驱动
Strongly Powered by AbleSci AI