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Fiscal Decentralization and Fiscal Multiplier in China

  • Fei Guo ORCID logo EMAIL logo , Eric Evans Osei Opoku , Kate Hynes and Isabel Kit-Ming Yan
Published/Copyright: November 18, 2021

Abstract

A fundamental aspect of China’s transition to a market economy is the change in fiscal decentralization marked by the tax reform in 1993. This paper examines the effect of revenue and expenditure decentralization and their divergences on fiscal spending multipliers in China using nationally aggregate and provincial-level data from 1978 to 2017. Our investigations show that expenditure decentralization weakens the efficacy of spending policies, while revenue decentralization enhances the efficacy. Moreover, the divergence of revenue and expenditure decentralization has significantly decreased the provincial spending multiplier, while its effect on the aggregate spending multiplier is insignificant. The provincial results are robust to the inclusion of off-budgetary expenditure and revenue, using different estimates of multipliers and different measures of fiscal decentralization, considering from a long-run perspective, and addressing the endogeneity issue.

JEL Classification: E62; H5; H72; R5

Corresponding author: Fei Guo, School of Economics and Management, Ningxia University, No. 489, Helanshan West Road, Yinchuan, 750021, China, E-mail:

Award Identifier / Grant number: 7004995

Appendix
Table A1:

FD divergence in different provinces (before and after the fiscal reform).

Region FCS TSS
FD FD FD FD FD FD FD FD
divergence 1 divergence 2 divergence 3 divergence 4 divergence 1 divergence 2 divergence 3 divergence 4
Average Average Average Average Average Average Average Average
(1978–1993) (1987–1993) (1978–1993) (1987–1993) (1994–2017) (1994–2010) (1994–2017) (1994–2010)
Metropolitan cities 0.796 0.258 3.160 0.804 0.090 0.080 0.223 0.206
 Beijing 0.471 0.125 1.471 0.353 0.076 0.058 0.188 0.154
 Shanghai 1.331 0.465 6.461 1.670 0.060 0.057 0.186 0.186
 Tianjin 0.586 0.183 1.548 0.388 0.135 0.126 0.295 0.277
Coastal provinces 0.222 0.083 0.243 0.095 0.182 0.133 0.203 0.150
 Fujian 0.082 0.026 0.069 0.025 0.128 0.089 0.171 0.118
 Guangdong 0.086 0.024 0.098 0.036 0.075 0.057 0.117 0.091
 Hainan 0.441 0.267 0.279 0.250 0.480 0.350 0.386 0.279
 Hebei 0.071 0.020 0.062 0.017 0.247 0.180 0.225 0.170
 Jiangsu 0.295 0.104 0.359 0.132 0.069 0.052 0.109 0.081
 Liaoning 0.404 0.072 0.656 0.113 0.264 0.206 0.343 0.276
 Shandong 0.146 0.019 0.133 0.018 0.113 0.083 0.143 0.105
 Zhejiang 0.254 0.133 0.290 0.171 0.076 0.049 0.126 0.082
Inland provinces 0.112 0.061 0.099 0.050 0.395 0.303 0.313 0.233
 Anhui 0.094 0.061 0.059 0.037 0.372 0.281 0.245 0.175
 Chongqing 0.361 0.294 0.302 0.232
 Heilongjiang 0.176 0.074 0.233 0.081 0.482 0.347 0.442 0.340
 Henan 0.056 0.018 0.037 0.012 0.300 0.219 0.224 0.160
 Hubei 0.092 0.017 0.085 0.015 0.308 0.237 0.273 0.197
 Hunan 0.067 0.017 0.052 0.012 0.357 0.272 0.271 0.195
 Jiangxi 0.145 0.089 0.099 0.057 0.372 0.268 0.252 0.173
 Jilin 0.219 0.155 0.210 0.149 0.523 0.429 0.499 0.397
 Shaanxi 0.144 0.102 0.100 0.068 0.476 0.394 0.362 0.272
 Shanxi 0.068 0.022 0.061 0.018 0.371 0.269 0.286 0.213
 Sichuan 0.063 0.059 0.055 0.050 0.426 0.326 0.292 0.213
Minority provinces 0.530 0.272 0.432 0.210 0.850 0.652 0.585 0.429
 Gansu 0.235 0.154 0.165 0.094 0.934 0.697 0.483 0.356
 Guangxi 0.225 0.158 0.128 0.087 0.448 0.322 0.285 0.195
 Guizhou 0.321 0.123 0.154 0.057 0.831 0.657 0.355 0.244
 Inner Mongolia 0.678 0.328 0.543 0.258 0.549 0.467 0.596 0.461
 Ningxia 0.922 0.483 0.751 0.369 0.939 0.756 0.716 0.539
 Qinghai 0.904 0.485 0.896 0.419 1.543 1.135 1.142 0.793
 Xinjiang 0.722 0.339 0.679 0.338 0.769 0.558 0.658 0.491
 Yunnan 0.236 0.104 0.136 0.060 0.785 0.627 0.446 0.355
Total average 0.329 0.146 0.547 0.185 0.429 0.329 0.347 0.261
Average without 0.275 0.133 0.246 0.113 0.467 0.356 0.361 0.267
metropolitan cities
  1. The classification follows Zhang and Zou (1998). Significant values of the interested variable are highlighted in bold.

Table A2:

The effect of the FD divergence on fiscal spending multipliers (SVAR Estimates).

Dependent variable Spending multiplier using SVAR (a 2 = 0) Spending multiplier using SVAR (b 2 = 0)
(1) (2) (3) (4) (5) (6) (7) (8)
Measure of FD FD FD FD FD FD FD FD
FD divergence divergence 1 divergence 2 divergence 3 divergence 4 divergence 1 divergence 2 divergence 3 divergence 4
Panel A: OLS regressions
FD divergence −0.126** −0.147** −0.067*** −0.191*** −0.080*** −0.091*** −0.046*** −0.128***
[0.048] [0.066] [0.025] [0.064] [0.025] [0.030] [0.014] [0.047]
GDP per capita 0.007 0.008 0.023 0.018 −0.016 −0.015 −0.005 −0.009
[0.034] [0.035] [0.031] [0.032] [0.021] [0.021] [0.020] [0.020]
Exchange regime −0.041 −0.042 −0.023 −0.033 −0.021 −0.021 −0.009 −0.016
[0.031] [0.033] [0.028] [0.029] [0.015] [0.016] [0.014] [0.014]
Region 0.075 0.070 0.089 0.081 0.032 0.029 0.041 0.036
[0.098] [0.099] [0.097] [0.098] [0.077] [0.077] [0.077] [0.078]
Cons 0.816** 0.807** 0.595* 0.704** 0.573*** 0.564*** 0.434*** 0.507***
[0.354] [0.373] [0.301] [0.322] [0.161] [0.168] [0.136] [0.147]
Obs. 56 56 56 56 56 56 56 56
R-squared 0.204 0.194 0.195 0.196 0.069 0.053 0.064 0.063
Panel B: 2SLS regressions using initial FD divergences as instruments of FD divergences
FD divergence −0.151** −0.169** −0.068*** −0.215*** −0.071** −0.089*** −0.043*** −0.146***
[0.061] [0.077] [0.024] [0.060] [0.028] [0.031] [0.014] [0.038]
GDP per capita 0.003 0.006 0.023 0.017 −0.015 −0.014 −0.005 −0.010
[0.033] [0.034] [0.030] [0.031] [0.021] [0.021] [0.019] [0.019]
Exchange regime −0.045 −0.045 −0.023 −0.034 −0.020 −0.021 −0.010 −0.017
[0.031] [0.032] [0.027] [0.028] [0.015] [0.016] [0.013] [0.014]
Region 0.076 0.069 0.089 0.082 0.032 0.029 0.041 0.037
[0.094] [0.095] [0.093] [0.094] [0.073] [0.074] [0.074] [0.075]
Cons 0.865** 0.841** 0.595** 0.721** 0.555*** 0.561*** 0.433*** 0.519***
[0.350] [0.367] [0.287] [0.306] [0.161] [0.164] [0.130] [0.137]
Obs. 56 56 56 56 56 56 56 56
R-squared 0.203 0.193 0.195 0.196 0.068 0.053 0.064 0.062
  1. (i) Heteroscedasticity robust standard errors are in square brackets; *** p < 0.01, ** p < 0.05, * p < 0.1, (ii) Significant values of the interested variable are highlighted in bold.

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Received: 2020-12-18
Revised: 2021-10-17
Accepted: 2021-11-02
Published Online: 2021-11-18

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