生育政策、人口年龄结构优化与经济增长
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摘要
本文从生育率与预期寿命两个维度构建了世代交叠模型,探讨了人口年龄结构变动对经济增长的作用机制及其效应。理论模型发现,生育率与预期寿命对经济增长的影响有两种效应:一种是替代效应,另一种是收入效应。对于经济发展水平高的发达国家而言,生育率的下降和预期寿命的延长阻碍了经济增长,这正好与多数发展中国家的情形相反。这一理论发现在实证研究中得到了验证,生育率的正向收入效应与预期寿命的负向替代效应在发达国家中占据了主导力量,而生育率的负向替代效应与预期寿命的正向收入效应则在发展中国家起决定作用。过去40多年,中国生育率的下降和预期寿命的延长对经济增长的总贡献年均2.7241个百分点。但随着经济发展水平的提高,生育率下降与预期寿命延长的正边际效应正在消退,向负边际效应转变。鉴于此,本文认为当前是中国出台提高生育率政策和优化人口年龄结构的一个较佳时期,既能对当前经济增长产生较小冲击,又能提高潜在的经济增长,保持经济的可持续发展。
The increasingly unbalanced population structure is becoming a global issue, and its impact on economic growth has been a highly concerning issue around the world. In particular, some scholars in China have expressed concern that they are "not getting rich first". Studies have focused on either the overall demographic structure or one dimension of the demographic structure, with less research considering both fertility and life expectancy. This paper analyzes the transmission mechanism and effect of fertility and life expectancy on economic growth. To the best of our knowledge, the differences between this paper and previous studies are reflected in three main ways. First, this paper considers the impact of population structure on economic growth in terms of both fertility and life expectancy. Second, it develops a theoretical model to consider the problem of endogenous economic growth. Third, it incorporates the spatial effect of economic growth into its empirical research and considers the two-way causality of population structure and economic growth.To clarify the impact mechanism of population structure on economic growth, both fertility rate and life expectancy are simultaneously introduced into the overlapping generations model, which shows that fertility rate and life expectancy have two paths of action for economic growth. First, they change the ratio of education expenditure on income, which directly changes the level of education expenditure, creating a substitution effect on economic growth. Second, they influence income levels through the change in savings, creating an income effect on economic growth. Economies with higher levels of economic development tend to show that the income effect of fertility is greater than the substitution effect and that the substitution effect of life expectancy is greater than the income effect. The decline in fertility and the extension of life expectancy can slow down its economic growth, while the characteristics are just the opposite for those economies with lower economic development levels.This paper selects the balance panel data composed of 67 countries and regions from 1971 to 2015 and uses the spatial econometric model and the moment-to-moment method to measure and decompose the economic growth effect of population structure changes. The empirical results support the theoretical model, and the economic growth effects of population structure exhibit certain differences in different countries that can be roughly divided into three categories. The first category is represented by low-developing countries such as Burundi and Congo, where the substitution effect dominates both fertility and life expectancy. The decline in fertility and the extension of life expectancy have promoted and hampered their economic growth, respectively. However, the positive effect of the reduction in the number of births is greater than the negative effect of the extension of life expectancy, and thus demographic changes have driven the countries' economic growth. The second category is represented by high-developing countries such as China and Argentina, where the substitution and income effects dominate fertility rate and life expectancy, respectively. The decrease in the number of births and the extension of life expectancy have contributed to the economic growth of both countries. The third category is represented by developed countries such as the United States and Japan, where the income and substitution effects dominate both fertility and life expectancy. The decline in fertility and the extension of life expectancy have hampered these countries' economic growth.In the past 40 years, China's comprehensive decline in fertility and life expectancy has contributed nearly three percentage points to economic growth. However, as the economic level develops, the positive marginal effect of the decline in fertility rate and the extension of life expectancy is fading and shifting to a negative marginal effect. In view of this, this paper argues that it is a good time for China to introduce a policy to increase fertility and optimize the age structure of the population. This should not only have a minor impact on current economic growth but also increase the potential economic growth rate and maintain sustainable economic growth.
The increasingly unbalanced population structure is becoming a global issue, and its impact on economic growth has been a highly concerning issue around the world. In particular, some scholars in China have expressed concern that they are "not getting rich first". Studies have focused on either the overall demographic structure or one dimension of the demographic structure, with less research considering both fertility and life expectancy. This paper analyzes the transmission mechanism and effect of fertility and life expectancy on economic growth. To the best of our knowledge, the differences between this paper and previous studies are reflected in three main ways. First, this paper considers the impact of population structure on economic growth in terms of both fertility and life expectancy. Second, it develops a theoretical model to consider the problem of endogenous economic growth. Third, it incorporates the spatial effect of economic growth into its empirical research and considers the two-way causality of population structure and economic growth.To clarify the impact mechanism of population structure on economic growth, both fertility rate and life expectancy are simultaneously introduced into the overlapping generations model, which shows that fertility rate and life expectancy have two paths of action for economic growth. First, they change the ratio of education expenditure on income, which directly changes the level of education expenditure, creating a substitution effect on economic growth. Second, they influence income levels through the change in savings, creating an income effect on economic growth. Economies with higher levels of economic development tend to show that the income effect of fertility is greater than the substitution effect and that the substitution effect of life expectancy is greater than the income effect. The decline in fertility and the extension of life expectancy can slow down its economic growth, while the characteristics are just the opposite for those economies with lower economic development levels.This paper selects the balance panel data composed of 67 countries and regions from 1971 to 2015 and uses the spatial econometric model and the moment-to-moment method to measure and decompose the economic growth effect of population structure changes. The empirical results support the theoretical model, and the economic growth effects of population structure exhibit certain differences in different countries that can be roughly divided into three categories. The first category is represented by low-developing countries such as Burundi and Congo, where the substitution effect dominates both fertility and life expectancy. The decline in fertility and the extension of life expectancy have promoted and hampered their economic growth, respectively. However, the positive effect of the reduction in the number of births is greater than the negative effect of the extension of life expectancy, and thus demographic changes have driven the countries' economic growth. The second category is represented by high-developing countries such as China and Argentina, where the substitution and income effects dominate fertility rate and life expectancy, respectively. The decrease in the number of births and the extension of life expectancy have contributed to the economic growth of both countries. The third category is represented by developed countries such as the United States and Japan, where the income and substitution effects dominate both fertility and life expectancy. The decline in fertility and the extension of life expectancy have hampered these countries' economic growth.In the past 40 years, China's comprehensive decline in fertility and life expectancy has contributed nearly three percentage points to economic growth. However, as the economic level develops, the positive marginal effect of the decline in fertility rate and the extension of life expectancy is fading and shifting to a negative marginal effect. In view of this, this paper argues that it is a good time for China to introduce a policy to increase fertility and optimize the age structure of the population. This should not only have a minor impact on current economic growth but also increase the potential economic growth rate and maintain sustainable economic growth.
引文
蔡昉,2010:《人口转变、人口红利与刘易斯转折点》,《经济研究》第4期。
刘穷志、何奇,2012:《人口老龄化,经济增长与财政政策》,《经济学(季刊)》第10期。
刘生龙、胡鞍钢、郎晓娟,2012:《预期寿命与中国家庭储蓄》,《经济研究》第8期
潘文卿,2012:《中国的区域关联与经济增长的空间溢出效应》,《经济研究》第1期。
汪伟、艾春荣,2015:《人口老龄化与中国储蓄率的动态变化》,《管理世界》第6期。
王德文、蔡昉、张学辉,2004:《人口转变的储蓄效应和增长效应》,《人口研究》第5期。
Angrist, J. D., and W. N. Evans, 1998, “Children and Their Parents’ Labor Supply: Evidence from Exogenous Variation in Family Size”, American Economic Review, 88(3), 450—477.
Anselin, L., A.K. Bera, R. Florax, and M.J. Yoon, 1996, “Simple Diagnostic Tests for Spatial Dependence”, Regional Science and Urban Economics, 26(1), 77—104.
Baltagi, B.H., S.H. Song, B. Jung, and W. Koh, 2007, “Testing for Serial Correlation, Spatial Autocorrelation and Random Effects Using Panel Data”, Journal of Econometrics, 140(1), 5—51.
Becker, G.S, and R. J.Barro, 1988, “A Reformulation of the Economic Theory of Fertility”, Quarterly Journal of Economics, 103(1), 1—25.
Bloom, D. E., D. Canning, R. K. Mansfield, and M. Moore, 2007, “Demographic Change, Social Security Systems, and Savings”, Journal of Monetary Economics, 54(1), 92—114.
Cervellati, M., and U. Sunde, 2005, “Human Capital Formation, Life Expectancy, and the Process of Development”, American Economic Review, 95(5), 1653—1672.
Deardorff, A. V., 1976, “The Optimum Growth Rate for Population: Comment”, International Economic Review, 17(2), 510—514.
Elhorst, J.P., 2014, Spatial Econometrics: From Cross-Sectional Data to Spatial Panels, Springer, New York.
Fujita, M., P. Krugman, and A. J. Venables, 1999, The Spatial Economy, Cambridge, MA: The MIT Press.
Fujita, M., and J-F. Thisse, 2002, Economics of Agglomeration, Cambridge: Cambridge University Press.
Gradstein, M., and M. Kaganovich, 2004, “Aging Population and Education Finance”, Journal of Public Economics, 88(12), 2469—2485.
Hazan, M., and H. Zoabi, 2006, “Does Longevity Cause Growth? A Theoretical Critique”, Journal of Economic Growth, 11(4), 363—376.
Hoffman, M., 2011, “Does Higher Income Make You More Altruistic? Evidence from the Holocaust”, Review of Economics and Statistics, 93(3), 876—887.
Horioka, C. J., 2010, “Aging and Saving on Asia”, Pacific Economic Review, 15(1), 46—55.
Kalemli-Ozcan, S., 2002, “Does the Mortality Decline Promote Economic Growth?”, Journal of Economic Growth, 7(4), 411—439.
Kapoor, M., H. H. Kelejian, and I. R. Prucha, 2007, “Panel Data Model With Spatially Correlated Error Components”, Journal of Econometrics, 140(1), 97—130.
Kelejian, H. H., and I. R. Prucha, 1999, “A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model”, International Economic Review, 40(2), 509—533.
Kelley, A.C., and R. M. Schmidt, 1995, “Aggregate Population and Economic Growth Correlations: The Role of the Components of Demographic Change”, Demography, 32(4), 543—555.
Kimball, M. S., 1990, “Precautionary Saving in the Small and in the Large”, Econometrica, 58(1), 53—73.
Kunze, L., 2014, “Life Expectancy and Economic Growth”, Journal of Macroeconomics, 39(3), 54—65.
Lee, R.D., and A. Mason, 2010, “Fertility, Human Capital and Economic Growth over the Demographic Transition”, European Journal of Population, 26(2), 159—182.
Li, H. B., J. Zhang, and J. S. Zhang, 2007, “Effects of Longevity and Dependency Rates on Saving and Growth: Evidence from A Panel of Cross Countries”, Journal of Development Economics, 84(1), 138—154.
Lucas, R. E., 1988, “On the Mechanics of Economic Development”, Journal of Monetary Economics, 22(1), 3—42.
Mason, A., and R.Lee, 2006, “Reform and Support Systems for the Elderly in Developing Countries: Capturing the Second Demographic Dividend. GENUS, LXII(2), 11—35.
Millo, G., and G. Piras, 2012, “Splm: Spatial Panel Data Models in R”, Journal of Statistical Software, 47(1), 1—38.
Modigliani, F., and R.Brumberg, 1954, “Utility Analysis and the Consumption Function: An Interpretation of Cross-section Data,” In K. K. Kurihara (Ed.), Post-keynesian Economics. New Brunswick, N.J.: Rutgers University Press.
Romer, P. M., 1986, “Increasing Returns and Long-Run Growth”, Journal of Political Economy, 94(5), 1002—1037.
Tamara, F., 2010, “Child Mortality and Fertility: Public Vs Private Education”, Journal of Population Economics, 23(1), 73—97.
Weil, D. N., 2013, Economic Growth (Third Edition), Pearson Education, Inc.
Zhang, J., J. Zhang, and R. Lee, 2001, “Mortality Decline and Long-run Economic Growth”, Journal of Public Economics, 80(3), 485—507.
(1)特别地,当v=1时,代表性个体从全部子女处获得的总效用不受子女个数的影响;当v>1时,代表性个体从全部子女处获得的总效用与子女个数成反比;当v<1时,代表性个体从全部子女处获得的总效用与子女个数成正比。
(2)将小孩和老人的初始规模分别设定为生育数量n和存活概率与生育数量的比值π/n的原因是保持任意时期的人口年龄结构不变。任意时期小孩、成人和老人的人口占比分别为n2/(n2+n+π)、n/(n2+n+π)和π/(n2+n+π)。
(3)以各个国家之间平均距离的一半(4000公里)作为阈值。
(4)本文基于世界各地的经济组织或经济联盟构造经济权重矩阵——一个经济组织或经济联盟内部国家的经济关联非常紧密。文章选取的经济组织或联盟包括亚洲太平洋经济合作组织(OPEC)、欧洲联盟(EU)、经济合作与发展组织(OECD)、北美自由贸易区(NAFTA)、东盟与中日韩10+3合作、非洲联盟+中国、南美洲国家联盟。此外,本文还构造了一个特殊的0—1矩阵,将美中日等贸易大国设置为1,其他国家设置为0,该矩阵反映了贸易大国之间的相互作用关系。
(5)已有研究表明文化能够影响经济增长,那么具有共同语言的国家之间的经济活动可能更为紧密。本文中研究的67个国家主要涉及的共同语言包括:阿拉伯语、法语、西班牙语、斯瓦希里语、希腊语(土耳其语)、泰语、意大利语、英语(荷兰语)、汉语、日语、冰岛语、丹麦语、波斯语、德语、芬兰语、马来语、尼泊尔语以及葡萄牙语。
刘穷志、何奇,2012:《人口老龄化,经济增长与财政政策》,《经济学(季刊)》第10期。
刘生龙、胡鞍钢、郎晓娟,2012:《预期寿命与中国家庭储蓄》,《经济研究》第8期
潘文卿,2012:《中国的区域关联与经济增长的空间溢出效应》,《经济研究》第1期。
汪伟、艾春荣,2015:《人口老龄化与中国储蓄率的动态变化》,《管理世界》第6期。
王德文、蔡昉、张学辉,2004:《人口转变的储蓄效应和增长效应》,《人口研究》第5期。
Angrist, J. D., and W. N. Evans, 1998, “Children and Their Parents’ Labor Supply: Evidence from Exogenous Variation in Family Size”, American Economic Review, 88(3), 450—477.
Anselin, L., A.K. Bera, R. Florax, and M.J. Yoon, 1996, “Simple Diagnostic Tests for Spatial Dependence”, Regional Science and Urban Economics, 26(1), 77—104.
Baltagi, B.H., S.H. Song, B. Jung, and W. Koh, 2007, “Testing for Serial Correlation, Spatial Autocorrelation and Random Effects Using Panel Data”, Journal of Econometrics, 140(1), 5—51.
Becker, G.S, and R. J.Barro, 1988, “A Reformulation of the Economic Theory of Fertility”, Quarterly Journal of Economics, 103(1), 1—25.
Bloom, D. E., D. Canning, R. K. Mansfield, and M. Moore, 2007, “Demographic Change, Social Security Systems, and Savings”, Journal of Monetary Economics, 54(1), 92—114.
Cervellati, M., and U. Sunde, 2005, “Human Capital Formation, Life Expectancy, and the Process of Development”, American Economic Review, 95(5), 1653—1672.
Deardorff, A. V., 1976, “The Optimum Growth Rate for Population: Comment”, International Economic Review, 17(2), 510—514.
Elhorst, J.P., 2014, Spatial Econometrics: From Cross-Sectional Data to Spatial Panels, Springer, New York.
Fujita, M., P. Krugman, and A. J. Venables, 1999, The Spatial Economy, Cambridge, MA: The MIT Press.
Fujita, M., and J-F. Thisse, 2002, Economics of Agglomeration, Cambridge: Cambridge University Press.
Gradstein, M., and M. Kaganovich, 2004, “Aging Population and Education Finance”, Journal of Public Economics, 88(12), 2469—2485.
Hazan, M., and H. Zoabi, 2006, “Does Longevity Cause Growth? A Theoretical Critique”, Journal of Economic Growth, 11(4), 363—376.
Hoffman, M., 2011, “Does Higher Income Make You More Altruistic? Evidence from the Holocaust”, Review of Economics and Statistics, 93(3), 876—887.
Horioka, C. J., 2010, “Aging and Saving on Asia”, Pacific Economic Review, 15(1), 46—55.
Kalemli-Ozcan, S., 2002, “Does the Mortality Decline Promote Economic Growth?”, Journal of Economic Growth, 7(4), 411—439.
Kapoor, M., H. H. Kelejian, and I. R. Prucha, 2007, “Panel Data Model With Spatially Correlated Error Components”, Journal of Econometrics, 140(1), 97—130.
Kelejian, H. H., and I. R. Prucha, 1999, “A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model”, International Economic Review, 40(2), 509—533.
Kelley, A.C., and R. M. Schmidt, 1995, “Aggregate Population and Economic Growth Correlations: The Role of the Components of Demographic Change”, Demography, 32(4), 543—555.
Kimball, M. S., 1990, “Precautionary Saving in the Small and in the Large”, Econometrica, 58(1), 53—73.
Kunze, L., 2014, “Life Expectancy and Economic Growth”, Journal of Macroeconomics, 39(3), 54—65.
Lee, R.D., and A. Mason, 2010, “Fertility, Human Capital and Economic Growth over the Demographic Transition”, European Journal of Population, 26(2), 159—182.
Li, H. B., J. Zhang, and J. S. Zhang, 2007, “Effects of Longevity and Dependency Rates on Saving and Growth: Evidence from A Panel of Cross Countries”, Journal of Development Economics, 84(1), 138—154.
Lucas, R. E., 1988, “On the Mechanics of Economic Development”, Journal of Monetary Economics, 22(1), 3—42.
Mason, A., and R.Lee, 2006, “Reform and Support Systems for the Elderly in Developing Countries: Capturing the Second Demographic Dividend. GENUS, LXII(2), 11—35.
Millo, G., and G. Piras, 2012, “Splm: Spatial Panel Data Models in R”, Journal of Statistical Software, 47(1), 1—38.
Modigliani, F., and R.Brumberg, 1954, “Utility Analysis and the Consumption Function: An Interpretation of Cross-section Data,” In K. K. Kurihara (Ed.), Post-keynesian Economics. New Brunswick, N.J.: Rutgers University Press.
Romer, P. M., 1986, “Increasing Returns and Long-Run Growth”, Journal of Political Economy, 94(5), 1002—1037.
Tamara, F., 2010, “Child Mortality and Fertility: Public Vs Private Education”, Journal of Population Economics, 23(1), 73—97.
Weil, D. N., 2013, Economic Growth (Third Edition), Pearson Education, Inc.
Zhang, J., J. Zhang, and R. Lee, 2001, “Mortality Decline and Long-run Economic Growth”, Journal of Public Economics, 80(3), 485—507.
(1)特别地,当v=1时,代表性个体从全部子女处获得的总效用不受子女个数的影响;当v>1时,代表性个体从全部子女处获得的总效用与子女个数成反比;当v<1时,代表性个体从全部子女处获得的总效用与子女个数成正比。
(2)将小孩和老人的初始规模分别设定为生育数量n和存活概率与生育数量的比值π/n的原因是保持任意时期的人口年龄结构不变。任意时期小孩、成人和老人的人口占比分别为n2/(n2+n+π)、n/(n2+n+π)和π/(n2+n+π)。
(3)以各个国家之间平均距离的一半(4000公里)作为阈值。
(4)本文基于世界各地的经济组织或经济联盟构造经济权重矩阵——一个经济组织或经济联盟内部国家的经济关联非常紧密。文章选取的经济组织或联盟包括亚洲太平洋经济合作组织(OPEC)、欧洲联盟(EU)、经济合作与发展组织(OECD)、北美自由贸易区(NAFTA)、东盟与中日韩10+3合作、非洲联盟+中国、南美洲国家联盟。此外,本文还构造了一个特殊的0—1矩阵,将美中日等贸易大国设置为1,其他国家设置为0,该矩阵反映了贸易大国之间的相互作用关系。
(5)已有研究表明文化能够影响经济增长,那么具有共同语言的国家之间的经济活动可能更为紧密。本文中研究的67个国家主要涉及的共同语言包括:阿拉伯语、法语、西班牙语、斯瓦希里语、希腊语(土耳其语)、泰语、意大利语、英语(荷兰语)、汉语、日语、冰岛语、丹麦语、波斯语、德语、芬兰语、马来语、尼泊尔语以及葡萄牙语。