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      China’s Low-Productivity Innovation Drive: Evidence From Patents

      1 , 2 , 2 , 3
      Comparative Political Studies
      SAGE Publications

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          Abstract

          Can China catch-up with the United States technologically by mobilizing its bureaucracy and assigning ambitious targets to local governments? We analyzed an original dataset of 4.6 million patents filed in China from 1990 through 2014 and paired this with a new, rigorous measure of patent novelty that approximates the quality of innovation. In 2006, China’s central government launched a national campaign to promote indigenous innovation and introduced bureaucratic targets for patents. Our analysis finds evidence that these targets, combined with political competition, pushed local governments to “game the numbers” by channeling relatively more effort toward boosting non-novel—possibly junk—patents over novel patents. Nationally, this is reflected in a surge of aggregate patents paired with a falling ratio of novel patents. China’s innovation drive is susceptible to manipulation and waste—it is enormous in scale but low in productivity.

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          Technical Change and the Aggregate Production Function

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            Political turnover and economic performance: the incentive role of personnel control in China

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              What Determines Productivity?

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                Author and article information

                Contributors
                Journal
                Comparative Political Studies
                Comparative Political Studies
                SAGE Publications
                0010-4140
                1552-3829
                November 03 2023
                Affiliations
                [1 ]Johns Hopkins University, Baltimore, MD, USA
                [2 ]University of Southern California, Los Angeles, CA, USA
                [3 ]National University of Singapore, Singapore
                Article
                10.1177/00104140231209960
                eb6a6d71-db61-445c-a1e9-5a042aefecaa
                © 2023

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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