Effects of export and heterogeneity on wage gap in China: a theoretical extension and empirical analysis based on HIR model

MA Shuzhong1 WANG Xiaoxiao1

(1.Center for Research in Regional Economic Opening and Development, Zhejiang University 310027)

【Abstract】This study incorporates the heterogeneity of user cost of capital into the theoretical framework of HIR model to analyze the effects of export, heterogeneity of productivity, heterogeneity of screening labor and heterogeneity of user cost of capital on the wage gap in China. This study also empirically evaluates the effects by using China' s industrial firms' data from 1998 to 2007, and then simulates the extended model. The results show that heterogeneity has significant effects on a firm's wage, leading to the wage gap. After controlling heterogeneity of productivity, heterogeneity of screening labor and heterogeneity of user cost of capital, the study finds that the export wage premium of Chinese firms is about 2.8%, and the wage gap in export firms is smaller than that in non–export firms. Export wage premium is positively correlated to fixed export cost.

【Keywords】 wage gap; HIR model; export; heterogeneity;

【DOI】

【Funds】 Program for New Century Excellent Talents in University supported by Ministry of Education( NCET-12-0496);Humanities and Social Sciences Planning Fund of Ministry of Education (14YJA790038). the General Program of National Natural Science Foundation of China (71473217); Key Project of Philosophy and Social Sciences in Zhejiang Province (14JDQY01Z);

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    Footnote

    [1]. 1 User cost of capital is different from financing constraints: the user cost of capital is the total cost paid by an enterprise in gaining access to capital, including transaction cost and capital cost, while financing constraints are a kind of constrain faced by companies in financing. The two are not the same concept but are related, difference of financial constraints is the source of capital user cost heterogeneity. [^Back]

    [2]. 2 Restricted by length of the paper, the model calculation process is not given in detail, but can be available from the author on request. [^Back]

    [3]. 3 In taking logarithm, we used the following transformation: ln[1+Γ(γf-1)]=Γ*ln(γf),Γ=0/1. [^Back]

    [4]. 4 The data for stuff and workers in 1998 are missing, and replaced with the summary data for employees at the end of the year. [^Back]

    [5]. 5 The data for delivery value of export in 2004 are missing, but as in the sample, the export enterprises in both 2003 and 2005 accounted for 90% of total export enterprises in 2003 and 84% of those in 2005; it is then considered that the exporting status for the majority of enterprises did not change between 2003 and 2005, so the export status in 2003 is used to represent the export status in 2004. [^Back]

    [6]. 6 The corporate investment and intermediate inputs usage are correlated with the enterprise TFP, and thus may probably be used as instrumental variables. In our attempt, the summation of investment and intermediate inputs passed the instrumental variable test, and thus is a desirable instrumental variable. [^Back]

    [7]. 7 Due to limited space, the mathematical derivation of the simplified model is omitted here, but is available from the author on request. [^Back]

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This Article

ISSN:1002-4670

CN: 11-1692/F

Vol , No. 11, Pages 15-26

November 2015

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Article Outline

Abstract

  • Introduction
  • 1 Model extension
  • 2 Empirical test
  • 3 Simulation analysis
  • 4 Conclusion and policy implications
  • Footnote

    References