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Government institutions and the dynamics of urban growth in China
Author(s) -
RodríguezPose Andrés,
Zhang Min
Publication year - 2019
Publication title -
journal of regional science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.171
H-Index - 79
eISSN - 1467-9787
pISSN - 0022-4146
DOI - 10.1111/jors.12435
Subject(s) - dynamism , language change , china , government (linguistics) , economics , panel data , human capital , investment (military) , local government , development economics , foreign direct investment , capital (architecture) , politics , economic system , political capital , economic growth , political science , macroeconomics , geography , art , physics , literature , archaeology , public administration , quantum mechanics , econometrics , linguistics , philosophy , law
Economic growth in China in recent decades has largely rested on the dynamism of its cities. High economic growth has coincided with measures aimed at improving the efficiency of local governments and with a mounting political drive to curb corruption. Yet the connection between government institutions and urban growth in China remains poorly understood. This paper is the first to look into the link between government efficiency and corruption, on the one hand, and urban growth in China, on the other hand and to assess what is the role of institutions relative to more traditional factors for economic growth in Chinese cities. Using panel data for 283 cities over the period between 2003 and 2014, the results show that the urban growth in China is a consequence of a combination of favorable human capital, innovation, density, local conditions, foreign direct investment, and city‐level government institutions. Both government quality—especially for those cities with the best governments—and the fight against corruption at the city level have a direct effect on urban growth. Measures to tackle corruption at the provincial level matter in a more indirect way, by raising or lowering the returns of other growth‐inducing factors.