TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration

Wei Wei, Wan-Li Zhang, Jun Wen and Jun-Sheng Wang

Economic Modelling, 2020, vol. 91, issue C, 534-549

Abstract: This article estimates agglomeration effects via calculating EG (Elilsion & Glaeser) and TFP growth (Total Factor Production) by considering the undesired output of the industrial enterprise database and the entropy weight method. Using panel data of 207 county-level cities in China and 28 two-digit manufacturing industries from 2003 to 2013 based on SIC codes, this paper analyzes the relationship between agglomeration and TFP growth through the smooth transition model under different regions and factor-intensity. The results are as follows. (1) A negative relationship appears in manufacturing productivity. The agglomeration effect changes to the crowded effect. Environmental pollution is also generated by transportation and inadequate pollution treatment technology. (2) The excessive agglomeration phenomenon of developed areas (eastern region) is less than the less developed areas (central and western regions). (3) Resource-intensity industries present two thresholds that indicate complex regional features. For various intensive industries in different regions, the relationship between GML and agglomeration is different. High agglomeration does not always promote TFP growth. (4) At different levels of urban industrial agglomeration, the influences of efficiency change and technical change on GML are different. Overall, moderate agglomeration in all regions helps promote economic development.

Keywords: Excessive agglomeration; Panel smooth transition model; Undesirable output; Factor-intensity; Tool variable method (search for similar items in EconPapers)
JEL-codes: O18 Q53 R11 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:91:y:2020:i:c:p:534-549

DOI: 10.1016/j.econmod.2019.12.022

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