Summary:
Most economies that have undergone industrialization have found that the age structure of the population and the industrial structure have also changed. This change in age structure is known as the aging problem, and it is the demographic result of a lower fertility rate and longer life expectancy. The change in the industrial structure is known as “Kuznets facts,” a set of trends that includes a rising share of services, a falling share of agriculture, and an inverted-U shaped share of manufacturing. The development of China's economy during the reform era has exhibited these trends, but with some critical problems. First, China's population is rapidly aging, but China is still a middle-income country. Thus, the onset of the aging problem before China becomes a high-income country may hinder further development. Second, although the share of services has grown steadily in China, it is still relatively low, and its structure should be improved. In fact, the processes of population aging and structural change are not taking place independently. Based on cross-country data from recent decades, this paper finds that the relationship between population aging and the share of services depends on economic development. As per-capita income rises, the relationship changes from negative to positive. This paper incorporates the age structure into a two-sector model with an income effect and a price effect, and studies the effect of aging on the rise of services. In the model, people of different ages have various preferences for goods and services. In particular, elasticities of income for goods or services and the elasticity of substitution between them can change with age. The paper shows that aging can change the share of services through the mechanisms of the income effect and the price effect. For the income effect mechanism, the direction of the effect of aging depends on the survival level of consumption for goods, and the magnitude depends on per-capita consumption. For the price effect mechanism, the direction of the effect of aging depends on the magnitude of the effect of relative price on the consumption composition for people of different ages. When per-capita income is low, the income effect dominates, so the effect of aging on the share of services is negative. However, as per-capita income grows, the income effect diminishes, while the price effect becomes the dominant mechanism, causing the effect of aging on services to change from negative to positive. We calibrate the model with cross-country data from 1995-2010, and quantitatively evaluate the effect of aging on the share of services in different circumstances. We find that the effect of aging also depends on the degree of aging and the relative productivity between sectors. Moreover, when the elasticity of substitution between goods and services is low for young people and high for old people, or older people's survival level of consumption for goods is low, a rising degree of aging is likely to increase the share of services. The results are robust if we change the consumption rate of sectoral output or the labor mobility cost. We derive two policy implications from the findings. First, our findings are helpful for evaluating the effect of aging on the share of services in different countries. The results not only explain the stylized fact that the effect of aging on services changes from negative to positive along with development, but also highlight the factors that influence the effect of aging in different countries. In developing countries like China, per-capita consumption is low, so aging before becoming a high-income country could hinder the rise of services. In developed countries, the effect of aging may differ, depending on its degree. Thus, to evaluate the effect of aging on industrial structure in different countries, it is necessary to pay attention to factors like the differences in the preferences of people of different ages, the level of per-capita consumption, and the degree of aging. Second, we suggest that China's government should deal with the aging problem and develop services in the following ways. First, ensuring that per-capita income grows steadily and increasing the share of private consumption could diminish the negative effect of aging on services. Second, lowering the relative price of services by increasing the relative productivity of the service sector could also diminish the negative effect of aging on services. Third, decreasing the wage gap between sectors and removing institutional barriers in labor mobility could promote the development of services. Fourth, developing producer services to increase the value-added share of services in investment goods could attract more labor to produce investment goods in the service sector.
颜色, 郭凯明, 段雪琴. 老龄化、消费结构与服务业发展[J]. 金融研究, 2021, 488(2): 20-37.
YAN Se, GUO Kaiming, DUAN Xueqin. Aging, Consumption Composition and the Development of Services. Journal of Financial Research, 2021, 488(2): 20-37.
Acemoglu, Daron, and Veronica Guerrieri. 2008. “Capital Deepening and Non-balanced Economic Growth” Journal of Political Economy, 116: 467~498.
[9]
Cai, Wenbiao. 2015. “Structural Change Accounting with Labor Market Distortions” Journal of Economic Dynamic & Control, 57: 54~64.
[10]
Dekle, Robert, and Guillaume Vandenbroucke. 2012. “A Quantitative Analysis of China's Structural Transformation” Journal of Economic Dynamic & Control, 36: 119~135.
[11]
Duarte, Margarida, and Diego Restuccia. 2010. “The Role of the Structural Transformation in Aggregate Productivity” Quarterly Journal of Economics, 125: 129~173.
[12]
Guo, Kaiming, Jing Hang, and Se Yan. 2017. “Servicification of Investment and Structural Transformation: The Case of China” SSRN Working Paper, no. 3061631.
[13]
Herrendorf, Berthold, Richard Rogerson, and Akos Valentinyi. 2013. “Two Perspectives on Preferences and Structural Transformation” American Economic Review, 103: 2752~2789.
[14]
Kongsamut, Piyabha, Sergio Rebelo, and Danyang Xie. 2001. “Beyond Balanced Growth” Review of Economic Studies, 68: 869~882.
[15]
Leukhina, Oksana M., and Stephen J. Turnovsky. 2016. “Population Size Effects in the Structural Development of England” American Economic Journal: Macroeconomics, 8: 195~229.
[16]
Ngai, L. Rachel, and Christopher A. Pissarides. 2007. “Structural Change in a Multisector Model of Growth” American Economic Review, 97: 429~443.
[17]
Ungor, Murat. 2017. “Productivity growth and labor reallocation: Latin America versus East Asia” Review of Economic Dynamics, 24: 25~42.
[18]
Uy, Timothy, Kei-Mu Yi, and Jing Zhang. 2013. “Structural Change in an Open Economy” Journal of Monetary Economics, 60: 667~682.