›› 2016 ›› Issue (04): 24-35.

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Research on agglomeration of producer services Threshold and manufacturing upgrading - based on triple effect of the cluster

LU Fei, LIU Ming-hui   

  1. Economics College of Xinjiang University of Finance and Economics, Urumqi, Xinjiang 830012, China
  • Received:2016-03-31 Online:2016-07-15 Published:2016-07-21

Abstract: Based on the literature review and theoretical deduction. First, the article puts forward triple effects of producer services agglomeration on the upgrade of manufacturing industry, the analysis states that the effect producer services agglomeration have made on the upgrade of manufacturing industry showed inverted U-vurve and there is a threshold characteristics exists in the effects each variable selected worked on manufacturing industry upgrade with the help of producer service industry agglomeration. The part of the empirical test. Based on China's 31 provincial-level panel data during 2002 to 2013 and set panel data model, and set the agglomeration of producer service industry as the threshold variable then set the threshold panel model.Two models comprehensive confirmed the three hypotheses and distinguish the critical point of elements working on manufacturing upgrading with the help of producer service industry agglomeration. Results of the article further indicate that gathered elastic effects of producer industry has gradually present decreasing trend in the rank of Central Region, Eastern Region and western region.Considering space into the context,the effect of different elements wok on manufacturing industry to upgrade by aggregate producer sevice industry shows out different linear or nonlinear characteristic. Thereby make the empirical analysis combining with China's 2013 data,which recognize that different regions has different driving factors, then propose to upgrade manufacturing industry under the guidance of the regional producer services agglomeration.

Key words: productive service industry agglomeration, manufacturing industry upgrading, fixed effect panel model, random effect panel model, threshold panel model

CLC Number: