Fiscal disparities among local governments in Zhejiang Province, China

ABSTRACT

Although nearly all local governments in China face serious fiscal challenges, fiscal pressures on some local governments are more severe than on others. Using data from 2011 through 2016, this paper measures the relative fiscal condition of local governments in a single Chinese province as a means of quantifying fiscal disparities within the province. We measure the fiscal gaps between local governments’ expenditure needs and revenue-raising capacity. Expenditure needs are estimated using a regression-based strategy to identify a set of characteristics of each local government that influence the costs of delivering local public services. We measure own-source revenue-raising capacity as a function of both local GDP and actual local government revenues. Although fiscal disparities remain, they are substantially reduced after the receipt of equalizing intergovernmental transfers. Because per capita transfers to rural local governments are much larger than transfers to large city governments, post-transfer fiscal health is actually weaker in the province’s larger cities than in smaller, more rural jurisdictions.

Acknowledgments

The authors would like to acknowledge financial support from the Fundamental Research Fund of the Capital University of Economics and Business. We also acknowledge support from the Peking University-Lincoln Institute Center on Urban Development and Land Policy and thank the Center director, Zhi Liu, for his advice and encouragement. We would also like to acknowledge the excellent suggestions from three referees and thank Roy Bahl and seminar participants at the Central University of Finance and Economics for helpful comments on an earlier version of this paper. Some of the work on this paper was completed while Andrew Reschovsky was a research fellow at the Lincoln Institute of Land Policy, Cambridge, Massachusetts.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. In China the term local government usually refers to all sub-central governments, including provincial governments. In this paper, however, we use the term local governments to refer to sub-provincial county or prefecture-level governments.

2. These data overstate China’s fiscal decentralization because the central government places limits on the spending autonomy of most sub-central governments. For recent efforts to measure spending autonomy, see Kantorowicz (2019).

3. This figure is based on spending through public finance budgets. In many provinces, the inclusions of spending through other budgets is likely to increase the share of spending being made by local (sub-provincial) governments.

4. For discussions of the definition and conceptual foundations of fiscal disparities, see Buchanan (1950), Ladd (2005), Bird and Tarasov (2004), and Dafflon and Vaillancourt (2020).

5. For a full description of the equalizing grant formula see Wang and Herd (2013) and Shen et al. (2012).

6. Inefficiencies may result from poor management decisions, inadequate training of public employees, or fraud and corruption.

7. R. W. Boadway and Flatters (1982) summarize the theoretical foundations for horizontal equalization, and the papers in R. Boadway and Shah (2007) discuss many of the conceptual and practical issues involved in the design of equalizing grants to subnational governments.

8. This fiscal system, known as Province-Managing-County (PMC), contrasts with the fiscal system that remains in place in some other provinces, where county governments are subordinate to larger prefecture-level governments, with the latter responsible for most fiscal and administrative decisions.

9. These 58 governments include all local governments in the province except for the prefecture-level city, Ningbo, four county-level municipalities in the Ningbo prefecture, and Shengsi, a small, remote island in Hangzhou Bay. The five municipalities in the Ningbo prefecture are not included in our analysis because they are governed directly by the central government. In 2016, 85% of the total population of Zhejiang resided in the local governments included in our study.

10. For a fuller discussion of the issues involved in measuring expenditure needs, see Ladd and Yinger (1989), Rye and Searle (1997), Chernick and Reschovsky (2007), and Kim and Lotz (2008).

11. For example, a local government with a larger share of school-age children will need to spend more (per capita) on public education and denser cities with taller buildings will need to spend more on fire protection.

12. In China, local government officials devote substantial resources (primarily from their Government Fund budget) to encourage economic development. Over time, these activities are likely to influence population flows (in-migration) and land-use patterns. However, in the short run, the factors that influence the costs of providing public services are likely to remain substantially unchanged.

13. It should be noted that as S_ij is almost certainly endogenous, equation 3(3) ${\mathrm{E}}_{\mathrm{i}\mathrm{j}}=\mathrm{h}\left({\mathrm{S}}_{\mathrm{i}\mathrm{j}},{\mathrm{P}}_{\mathrm{i}\mathrm{j}},{\mathrm{Z}}_{\mathrm{i}\mathrm{j}},{\epsilon }_{\mathrm{i}\mathrm{j}},{\mathrm{u}}_{\mathrm{i}\mathrm{j}}\right)$(3) needs to be estimated using simultaneous equation techniques.

14. Examples of studies of local government spending that involved the estimation of expenditure functions as a means of identifying cost factors include Bradbury et al. (1984), Ladd et al. (1991), Bandyopadhyay and Rao (2009), Bradbury and Zhao (2009), and B. Zhao (2018).

15. See Chernick (1998) for a detailed discussion of the RTS and other methods of calculating revenue-raising capacity, and Bahl (1972) for a discussion of the issues involved in implementing RTS in developing countries. The fiscal gap formula used by the Chinese central government to allocate general equalizing transfer payments to provincial governments is based in part on the standard revenue of each province. These standard revenues are calculated using the RTS methodology.

16. If a higher-level government wanted to encourage a higher (lower) level of local government tax effort, the standard rate could be set at a rate above (below) the average tax rate. In India, where local governments do a particularly poor job of collecting tax revenue, one study of the fiscal condition of local governments adjusted upward the average effective tax rates in order to reflect the under-collection of taxes (Bandyopadhyay & Rao, 2009).

17. In Zhejiang, local government officials lack discretion over revenue from user fees, as all local fees are set by the provincial government.

18. We initially attempted to include both year and local government fixed effects in our expenditure regression, but there was not enough temporal variation within local governments to allow us to statistically identify cost factors.

19. This calculation is based on Equation (5)(5) $\mathrm{E}{\mathrm{N}}_{\mathrm{i}\mathrm{j}}=\sum _j^{N}S{R}_{ij}\ast {\mathrm{S}}_{\mathrm{j}}{ }^{+}\ast \mathrm{C}{\mathrm{I}}_{ij}$(5) , where service responsibilities (SR) are identical for all local governments and where there is a single cost index reflecting the costs of total spending.

20. In 2016, the average per capita value of the three transfers program allocated to the 58 Zhejiang local governments was ¥343, ¥3,160, and ¥1,570, respectively.

21. For this exercise, fiscal gaps are calculated as expenditure needs minus the sum of own-source revenue-raising capacity and tax return transfers.

22. In 2016, the average equalizing grant to local governments in the smallest population quintile was ¥10,703, while the average grant to the largest quintile was only ¥1,840.

23. Approximately 60% of China’s population now live in urban areas. This percentage is forecast to rise to near 70% by 2030 (World Bank and the Development Research Center of the State Council of the PRC, 2014).

24. Our results show that in the absence of equalizing transfers, fiscal disparities among local governments in Zhejiang reflect differences in RRC and quite distinct differences in EN. The correlation between EN and own-source RRC is low (0.14) and not statistically different from zero.

25. The Gini coefficient of relative fiscal gaps calculated in the absence of equalizing grants equaled 0.276.

26. With the exception of the cities of Beijing, Shanghai, and Tianjin and the neighboring province of Jiangsu, per capita GDP is higher in Zhejiang than in all other provinces (China Statistical Yearbook, 2019, 2019b). With 68.9% of its population classified as urban in 2018, only three cities and two provinces are more urbanized than Zhejiang (China Statistical Yearbook, 2019, 2019a).

27. Zhao and Bradbury (2009), in a discussion of reforming equalization aid formulas, emphasize the political imperative of considering the current allocation of transfers in the design of new grant formulas.

Additional information

Funding

This work was supported by the Fundamental Research Fund, Capital University of Economics and Business, Beijing, China [QNTD202009]; Peking University-Lincoln Institute Center for Urban Development and Land Policy [F01-20201020-YY].

Notes on contributors

Yan Yan

Yan Yan is an Assistant Professor of Urban Economics and Public Finance at the Capital University of Economics and Business in Beijing, China. She is also a Research Associate at the Peking University-Lincoln Institute Center for Urban Development and Land Policy. Her research focuses on urban development, land policy, and local public finance. She earned a PhD in human geography from Peking University.

Andrew Reschovsky

Andrew Reschovsky is Professor Emeritus of Public Affairs and Applied Economics at the University of Wisconsin-Madison. He publishes widely on topics related to state and local government finance. He spent a year working at the Office of Tax Analysis in the U.S. Treasury, and has also served as an advisor to the Organization of Economic Co-operation and Development in Paris and the Financial and Fiscal Commission in South Africa. In 2011, he was awarded the Steven D. Gold award by the Association of Public Policy Analysis and Management in recognition of his contributions to state and local fiscal policy. He earned a PhD in economics from the University of Pennsylvania.