Will the internet increase the sophistication of corporate imported technology? An empirical study based on PSM-DID method

YUE Yunsong1 LI Bing1 LI Rou1

(1.School of International Trade and Economics, Central University of Finance and Economics)

【Abstract】Based on the matching data of China Industrial Enterprise Database and China Customs Database from 2004 to 2009, this article conducts an empirical analysis of the impact of the Internet on the sophistication of enterprises’ imported technology by adopting Propensity Score Matching-Difference in Differences (PSM-DID) estimation method. The results show that the Internet has significantly improved the sophistication of Chinese enterprises’ imported technology overall, and this effect is most significant in the beginning stage of using the Internet by enterprises. Further heterogeneity test finds that the Internet has significantly improved the sophistication of small and medium-sized enterprises’ imported technology while it has no significant impact on large enterprises; it has significantly improved the sophistication of imported technology of the enterprises only in the highly and moderately open areas while it has no significant impact on enterprises in areas with low open degrees. This article enriches the study on the impact of Internet on trade, provides micro-level evidence for the promotional effect on the sophistication of the imported Internet technology, and provides positive revelation for the implementation of the “Internet plus trade” strategy.

【Keywords】 the Internet; enterprises; sophistication of imported technology;


【Funds】 Supported by Key Research Project of Humanities and Social Sciences of Ministry of Education (14JZD019) Beijing Social Science Fund Project (14JDJGB048). Thanks the anonymous reviewers for valuable comments and suggestions. Of course, the author takes sole responsibility for his views.

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    [1]. ① This method refers to the suggestion of Blundell and Costa Dias (2000), and the integration of the PSM-DID method in the matching is helpful to eliminate the impact of enterprises’ individual effects with no change along time on the estimation results and reduces the bias of non-parametric estimation. [^Back]

    [2]. ②This article attempts to use proximity matching, standard kernel matching, and radius matching. The final estimation results of the three matching methods are similar. Due to space constraints, we only report estimation results of the 1:5 proximity matching. Other estimation results can be obtained from authors if interested. [^Back]

    [3]. ③Due to limited space, no specific definition of matching variables is listed. If interested, readers can obtain them from the authors. [^Back]

    [4]. ④Due to limited space, this article did not give all matching test results. If interested, readers can obtain them from the authors. [^Back]

    [5]. ⑤The first year represents the establishing year, and the others in turn. [^Back]


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This Article


CN: 11-1692/F

Vol , No. 12, Pages 131-141

December 2016


Article Outline


  • Introduction
  • 1 Theory and mechanism analysis
  • 2 Empirical strategy, data description and index introduction
  • 3 Estimate results
  • 4 Conclusions
  • Footnote