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The effect of public subsidies on corporate R&D investment: An application of the generalized propensity score

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  • Dai, Xiaoyong
  • Cheng, Liwei

Abstract

This paper aims to investigate how the effect of public subsidies on corporate R&D investment varies with different levels of public subsidies. Based on the generalized propensity score methodology, we estimate a dose–response function, using a large sample of Chinese manufacturing firms. Our results suggest public subsidies follow an S-shaped relationship and inverted-U correlation with the firm's total R&D and private R&D investment, respectively. There is a saturation point beyond which a further increase in public subsidies does not yield an increase of firm's total R&D investment. A minimum threshold value of public subsidies is required to induce the firm's private R&D spending. There are also critical values beyond which a further increase in public subsidies would partially or completely crowd out a firm's private R&D investment. Our conclusion implies the existence of an optimal interval of subsidy, and thus could help to improve the efficiency of public subsidies.

Suggested Citation

  • Dai, Xiaoyong & Cheng, Liwei, 2015. "The effect of public subsidies on corporate R&D investment: An application of the generalized propensity score," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 410-419.
    • Handle: RePEc:eee:tefoso:v:90:y:2015:i:pb:p:410-419
    DOI: 10.1016/j.techfore.2014.04.014
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    More about this item

    Keywords

    Public subsidies; R&D investment; Generalized propensity score;
    All these keywords.

    JEL classification:

    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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