Resource flow or yardstick competition: spatial dependence of educational expenditure among prefecture-level cities

Abstract

Primary and secondary education, provided by the local governments in China, plays an important role in attracting talented migrants. The race for talent and the education assessment from the top encourage local governments to compete with its neighboring localities in public education spending. Two theoretical frameworks can be applied to explain such strategic interactions among local governments—the resources-flow model and yardstick competition model. Using panel data of China’s prefecture-level cities from 2007 to 2016, this article conducts a spatial econometric analysis to test the two aforementioned models empirically. The estimation results show that aside from a significant positive spatial dependence of education expenditures among local government in the same province, it also occurs among prefecture-level cities in different provinces. Indeed, based on the data that demonstrated the comparison among cities in different provinces with similar economic distance is stronger than that with closer geographical distances.

Notes

1 The geocentric coordinates of prefecture-level cities are generated by the software Open GeoDa according to the administrative division map of China, and the statistical analysis software used was Matlab R2017b.

2 The direct and indirect effects of the variables estimated by the geographic distance matrix are in the appendix Table A1.

3 From the results of the Wald test and LR test, the model using can use the spatial lag model instead of the spatial Durbin model, but considering the per capita GDP, FDI and other indicators also produce space overflow, the spatial Durbin models are still used here. The spatial lag models, using fiscal revenue and population matrices, can draw the same conclusions and is more significant. The results are shown in Appendix B1, the direct and indirect effects of the variables estimated by the economic and social distance matrices are in the appendix Table B2.

Additional information

Notes on contributors

Chuanhao Tian

Chuanhao Tian ([email protected]) is a professor at the School of Public Affairs, Zhejiang University. He received his PhD in management at the School of Management, Zhejiang University. His current research examines spatial dependence of education expenditures among prefecture-level cities. He also is interested in rural land policies, land market and housing policy.

Yu Teng

Yu Teng ([email protected]) is a graduate student at the School of Public Affairs, Zhejiang University. Her current research examines spatial dependence of education expenditures among prefecture-level cities. She also is interested in public financial management and cadre incentives and urban development.

Hai (David) Guo

Hai (David) Guo ([email protected]) is an Associate professor at Department of Public Policy and Administration, Steven J. Green School of International and Public Affairs Florida International University. His research focuses on state and local public finance and budgeting.