Population urbanization, structural dividend and space-time effect: a perspective of labor market efficiency
(2.School of Economics, Southwest Minzu University)
【Abstract】From the perspectives of time and space, the paper investigates the growth effect and variation of population urbanization and industrial upgrading on labor market efficiency by using the data of China Labor-Force Dynamic Survey (CLDS) from 2012 to 2016. The results show that, urbanization has a lag effect on improving labor market efficiency, and the structural dividend effect is gradually highlighted and strengthened over time. Urbanization strengthens the productivity growth effect of industrial structure change, and forms a synergistic effect to promote labor market efficiency. Spatially, urbanization has a significant diffusion effect, which can improve labor market efficiency in adjacent regions. However, it will gradually form a spatial competition effect over time. As the simulation boundary expands, labor market efficiency has presented the nonlinear pattern as an inverted U, which breaks the strict hypothesis of distance attenuation. In addition, space-time effect of employment dividend shows that, although urbanization and industrial structure upgrading cannot produce significant long-term employment dividend in the region, they can bring continuous improvement of employment in adjacent regions through spatial spillover effect. In general, by actively weakening the spatial barriers between regions, avoiding the excessive economic aggregation, and expanding market boundary to promote market integration, China will expand structural dividends of urbanization and industrial structure upgrading, and finally improve the labor market efficiency.
【Keywords】 urbanization; structural dividend; spatial spillover effect; labor market efficiency;
(Translated by HAN Xueting)
. ① Although the micro data of China Labor-Force Dynamic Survey only cover 29 provincial regions, the interaction among markets in China should be considered when calculating the spatial term of urbanization. Therefore, 30 provincial regions other than Hong Kong, Macao, Taiwan and Tibet are taken as the research scope in the macro samples. [^Back]
. ① The centroid of any provincial region starts to search outwards from 0. When it is satisfied that each provincial region has at least one neighbor, and namely, the urbanization spatial term of each provincial region is not 0, it is the minimum distance (radius) range, which is 1265 km in this paper. [^Back]
1. Cai, F. Economic Research Journal (经济研究), (7) (2017).
2. Chen, D. Finance & Economics (财经科学), (11) (2017).
3. Gan, C. & Zheng, R. China Industrial Economics (中国工业经济), (2) (2009).
4. National Bureau of Statistics. China Statistical Yearbook (中国统计年鉴). Beijing: China Statistics Press, (2008).
5. Li, C. On Economic Problems (经济问题), (6) (2016).
6. Li, J. Population Research (人口研究), (1) (2015).
7. Li, X. & Chen, Y. Statistical Research (统计研究), (7) (2007).
8. Li, J. et al. Management World (管理世界), (7) (2010).
9. Liu, J. et al. Chinese Journal of Population Science (中国人口科学), (2) (2018).
10. Pan, W. Economic Research Journal (经济研究), (1) (2012).
11. Tang, D. & Sheng, W. Population Journal (人口学刊), (4) (2019).
12. Wang, P. & You, J. Economic Perspectives (经济学动态), (10) (2015).
13. Yang, R. & Li, N. Finance & Economics (财经科学), (6) (2016).
14. Zeng, Q. et al. Research on Economics and Management (经济与管理研究), (9) (2018).
15. Zeng, Z. & Zuo, J. Chinese Journal of Management Science (中国管理科学), (S3) (2013).
16. Zhang, L. China Population, Resources and Environment (中国人口·资源与环境), (9) (2012).
17. Zhou, H. Shanghai Journal of Economics (上海经济研究), (2) (2016).
18. Aldrighi, L., Colistete, R. P. (2013), Industrial Growth and Structural Change: Brazil in a Long-Run Perspective. Working Papers. Department of Economics 2013_10, University of São Paulo (FEA-USP).
19. Bertinelli, L., Black, D. (2004), Urbanization and Growth. Journal of Urban Economics. 56 (1): 80–96.
20. Bertinelli, L., Strobl, E. (2003), Urbanization, Urban Concentration and Economic Growth in Developing Countries. CREOIT Research Paper.
21. Baumol, W. J. (1967), Macroeconomics of Unbalanced Growth: The Anatomy of Urban Crisis. The American Economic Review. 57 (3): 415–426.
22. Bai, C., Ma, H., Pan, W. (2012), Spatial Spillover and Regional Economic Growth in China. China Economic Review. 23 (4): 982–990.
23. Cortuk, O., Singh, N. (2011), Structural Change and Growth in India. Economics Letters. 110 (3): 178–181.
24. Duranton, G., Puga, D. (2004), Micro-foundations of Urban Agglomeration Economics. In Henderson, J. V., Thisse, J. F. (eds.), Handbook of Regional and Urban Economics (Volume 4).
25. Fujita, M., Thisse, J. F. (2003), Does Geographical Agglomeration Foster Economic Growth? And Who Gains and Loses from It? The Japanese Economic Review. 54 (2): 121–145.
26. Glaeser, E. L., Resseger, M. G. (2010), The Complementarity Between Cities and Skills. Journal of Regional Science. 50 (1): 221–244.
27. Hartwig, J. (2011), Testing the Baumo-Nordhaus Model with EU KLEMS Data. The Review of Income and Wealth. 57 (3): 471–489.
28. Kangasharju, A., Pekkala, S. (2000), The Effect of Aggregate Fluctuations on Regional Economic Disparities in Finland. Conference Paper. 40th Congress of the European Regional Science Association: “European Monetary Union and Regional Policy.”
29. Krugman, P. (1991), Increasing Returns and Economic Geography. Journal of Political Economy. 99 (3): 483–499.
30. Le Sage, J., Pace, R. K. (2009), Introduction to Spatial Econometrics. CRC Press.
31. Mincer, J. A. (1974), Schooling, Experience, and Earnings. Columbia University Press.
32. Nordhaus, W. D. (2008), Baumol’s Diseases: A Macroeconomic Perspective. The B. E. Journal of Macro-economics. 8 (1): 1–39.
33. Peneder, M. (2003), Industrial Structure and Aggregate Growth. Structural Change and Economic Dynamics. 14 (4): 427–448.
34. Sancar, Cenap, Sancar, Canan (2017), The Econometrical Analysis of the Relationship Between Urbanization and Economic Growth (The Case of EU Countries and Turkey). International Journal of Economics and Administrative Studies. (19): 1–24.