Journal
APPLIED ECONOMICS
Volume 50, Issue 25, Pages 2824-2843Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/00036846.2017.1409421
Keywords
DEA-Malmquist index; geographically weighted regression; regional development; spatial analysis; total factor productivity
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Total factor productivity (TFP) is a measure of long-term economic growth and a comprehensive industry-level productivity measure. There are large gaps in China's regional construction industry development due to unbalanced regional economy. Based on TFP measurement, this article puts forward a two-hierarchical analysis framework with coefficient of variation, Moran scatterplot and coefficient of convergence to analyse change trend of the construction industry TFP in three major regions in terms of spatial diversity, correlation and convergence. Then, the geographically weighted regression model is utilized to explore the influencing mechanism on the TFP. The results indicate the differences of the regional construction industry TFP are enlarging. There is obvious spatial correlation and heterogeneity in the regional TFP without a relatively stable space pattern. The TFP also exhibits convergence effects among three major regions. The construction industry productivity in all regions is significantly affected by economic environment, industrial organization structure and technological level. Industrial organization structure exerts the various influences on the productivity in different regions.
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