Distribution dynamics, difference decomposition and convergence mechanism of producer services in Chinese urban agglomerations
【Abstract】Research objectives: This paper studied distribution dynamics, regional difference and convergence mechanism of the producer services development in eight Chinese urban agglomerations. Research methods: Based on the panel data of Chinese cities at the prefecture level and above from 2003 to 2015, this paper used kernel density estimation method to characterize the distribution dynamics, adopted Dagum Gini coefficient to decompose the regional difference, further used coefficient of variation to analyze their σ-convergence, and established spatial panel data model to test their β-convergence and club convergence. Research findings: Producer services development in each urban agglomeration has distinct gradient with bipolar or multipolar differentiation. The overall relative difference of the producer services development shows a slowly upward trend. The differences between urban agglomerations are the major source of overall difference, while the differences within urban agglomeration make minimal contribution. Producer services development shows typical σ-convergence in Beijing-Tianjin-Hebei and the Middle Reaches of the Yangtze River urban agglomerations, while none in other urban agglomerations. Except for the Pearl River Delta Urban Agglomeration, other seven urban agglomerations all have a significant absolute β-convergence. Eight urban agglomerations all have a significant conditional β-convergence. Moreover, three layers of urban agglomerations classified by function all have significant club convergence. However, spatial spillover partly contributes to β-convergence in only a few regions, and most regions have not yet shown significant spatial spillover. In addition, improving industrial development level, reducing transportation cost, strengthening knowledge spillover and optimizing institutional environment have different effects on the narrowing of regional difference within different urban agglomerations. Research innovations: This paper analyzed the distribution dynamics of the producer services development in eight Chinese urban agglomerations, explored the sources of regional difference, and revealed the effect of spatial spillovers in the convergence. Research value: This study provided evidences to evaluate the spatial structure and regional difference of producer services development in Chinese urban agglomerations. It has important policy implications for promoting the coordinated development of urban agglomerations.
【Keywords】 urban agglomerations; producer services; difference decomposition; convergence; spatial spillover;
. ① Chaohu City was cancelled in 2011. Sansha City was established in 2012. Danzhou City was established in 2015. Bijie City was established in 2011. Tongren City was established in 2011. Haidong City was established in 2013. Zhongwei City was approved to be established in April 2004. Longnan City was approved to be established in January 2004. The time when these cities were established or cancelled does not coincide with the research period in this paper, and there is serious missing of data of Lhasa City, so the research sample does not include these nine regions. [^Back]
. ② The specific results of the average development level of producer services in China’s eight urban agglomerations from 2003 to 2015 are available upon request. [^Back]
. ③ Due to space limitation, the calculation results of coefficient of variation are not reported here, which are available upon request. [^Back]
. ④ Due to space limitation, the calculation results of Moran’s I are not reported here, which are available upon request. [^Back]
. ⑤ Due to space limitation, the test results are not reported here and are available upon request. [^Back]
. ⑥ Due to space limitation, this paper only gives the estimates of convergence coefficient of the club convergence test and spatial coefficient. Results of the fixed effect test, Hausman test, (Robust) LM test, Wald and LR test and control variable estimation coefficients are available upon request. [^Back]
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