Quantitative measurement of the effects of administrative division adjustments on regional development

doi:10.1007/s11442-021-1922-0

Abstract

Abstract:

Administrative divisions are the important foundation of national governance and social development, and the adjustment of administrative divisions is a critical way to promote regional coordinated development. Under the background of globalization and regionalization, timely adjustment of administrative divisions is a major step to reconstruct the regional development pattern. In the perspective of regional coordinated development, this paper constructs an Administrative Rank Potential Energy (ARPE) model to explore the mechanisms of administrative division adjustment (ADA) under coordinated regional development based on the theory of regional interaction, spatial field energy model and power exponential function. The results show that: (1) The development potential and influence of an administrative region are closely related to the administrative jurisdiction, administrative resources, and the potential of regional coordinated development. (2) The growth rate of ARPE in the study area from 2010 to 2015 was 20.7% compared to the period 2005 to 2010, and the potential for coordinated development increased to 3.05% from 0.21% before the “cancelling” the prefecture-level city of Chaohu. (3) The measurement results of the usefulness of ADA can not only distinguish the complex impacts brought about by social development, but also accord with real social and economic development conditions. The ARPE focuses on the both regional integrated development and individual development, thereby serving as a reference for explaining and evaluating adjustments to administrative divisions at the macro- and micro-scales.

Key words: administrative division adjustment, administrative rank potential energy, coordinated development, regional effects, Chaohu

WANG Kaiyong, FENG Rundong. Quantitative measurement of the effects of administrative division adjustments on regional development[J].Journal of Geographical Sciences, 2021, 31(12): 1775-1790.

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Target layer	Level-one indicator	Level-two indicator	Data treatment	Indicator type
Comprehensive strength of administrative region	Jurisdiction (horizontal management capacity)	Population	Permanent population density	Positive
		Economic strength	Per capita GDP	Positive
		Economic strength	^*Per capita fixed-asset investment ×[1-(GDP_i/GDP_N)]	Positive
		Land allocation capacity	Per capita urban construction land area ×[1-(GDP_i/GDP_N)]	Positive
	Administrative resources (vertical management authority)	Fiscal decentralization	Per capita fiscal revenue ×[1-(GDP_i/GDP_N)]	Positive
		Fiscal decentralization	Per capita fiscal expenditure×[1-(GDP_i/GDP_N)]	Positive
		Public management	Public management and social organization personnel×[1-(GDP_i/GDP_N)]	Positive
Coordinated development potential	Potential factor (regional integration capacity)	Market unity	^*Foreign direct investment ×[1-(GDP_i/GDP_N)]	Positive
		Market unity	Difference between average worker salary of a county and the median ×[1-(GDP_i/GDP_N)]	Negative
		Factor homogeneity	Fiscal revenue/GDP×[1-(GDP_i/GDP_N)]	Positive
		Factor homogeneity	Per capita disposable income ×[1-(GDP_i/GDP_N)]	Positive
		Development synergy	Industrial structure similarity coefficient calculated according to proportions of primary, secondary and tertiary industries	Negative
		Development synergy	GDP growth rate of each district	Positive
		Natural conditions	Slope calculated using digital elevation	Negative
		Natural conditions	Net primary productivity	Positive
Accessibility	Time cost	Cost distance	Shortest time cost distance	Negative

	Hefei				Wuhu				Chaohu		Hefei-Wuhu region
	Highest	Lowest	Average	Growth rate (%)	Highest	Lowest	Average	Growth rate (%)	Overall	Growth rate (%)	Average	Growth rate (%)
2005	1.23	0.02	4.73	-	0.86	0.01	2.74	-	1.17	-	8.64	-
2010	1.59	0.55	7.94	67.9	1.28	0.31	5.27	92.3	1.41	20.5	14.62	69.2
2015	4.3	0.76	14.14	78.1	3.28	0.55	12.55	138.1	0.76	-46.1	26.69	82.6