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Corruption And Innovation: Linear And Nonlinear Investigations Of Oecd Countries

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  • JUN WEN

    (School of Economics and Finance, Xi’an Jiaotong University, Shaanxi, P. R. China)

  • MINGBO ZHENG

    (#x2020;Shih Chien University, Kaohsiung, Taiwan)

  • GEN-FU FENG

    (School of Economics and Finance, Xi’an Jiaotong University, Shaanxi, P. R. China)

  • SUNWU WINFRED CHEN

    (#x2020;Shih Chien University, Kaohsiung, Taiwan)

  • CHUN-PING CHANG

    (#x2020;Shih Chien University, Kaohsiung, Taiwan)

Abstract

Employing annual data over the period 1996–2013 for 29 OECD countries, this paper explores the impact of corruption on domestic innovative activity, measured by the number of patent and trademark applications, via a linear panel fixed effect model and a nonlinear panel smooth transition regression with all lagged explanatory variables as instrumental variables and under the consideration of potential endogeneity biases. The results indicate several important findings. First, there exists a strong threshold effect between the control of corruption and levels of innovative activity across nations. Second, we note that corruption only has a substantial positive impact on innovation when it is over the threshold level, but not when a country has a seriously corrupt government with low bureaucratic quality, no matter for patent or trademark applications. Hence, heterogeneous beliefs about low transition speed show that OECD countries may not take actions instantly and identically to pursue better bureaucratic quality. Finally, we discover that an improvement over corruption presents greater impacts on patent applications than on trademark applications. Taken together, we confirm that corruption plays a fundamental role in determining innovation activities in OECD countries, offering meaningful policy implications for those policymakers and industries in accordance with our findings.

Suggested Citation

  • Jun Wen & Mingbo Zheng & Gen-Fu Feng & Sunwu Winfred Chen & Chun-Ping Chang, 2020. "Corruption And Innovation: Linear And Nonlinear Investigations Of Oecd Countries," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 65(01), pages 103-129, March.
  • Handle: RePEc:wsi:serxxx:v:65:y:2020:i:01:n:s0217590818500273
    DOI: 10.1142/S0217590818500273
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    Citations

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    Cited by:

    1. Shuangyan Li & Anum Shahzadi & Mingbo Zheng & Chun-Ping Chang, 2022. "The impacts of executives’ political connections on interactions between firm’s mergers, acquisitions, and performance," Economic Change and Restructuring, Springer, vol. 55(2), pages 653-679, May.
    2. Iorio, Roberto & Segnana, Maria Luigia, 2023. "Exploring the link between corruption and innovation: the moderating role of institutional context and competitive pressure," CELPE Discussion Papers 165, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    3. Wen, Jun & Zhang, Sen & Chang, Chun-Ping, 2022. "Legal origins and innovation: Global evidence," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    4. Wen, Jun & Yin, Hua-Tang & Jang, Chyi-Lu & Uchida, Hideaki & Chang, Chun-Ping, 2023. "Does corruption hurt green innovation? Yes – Global evidence from cross-validation," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    5. Yunpeng Wang & Chun-Ping Chang, 2023. "The effect of policy stability on clean energy investment," Economic Change and Restructuring, Springer, vol. 56(1), pages 327-344, February.
    6. Mariia Blikhar & Mariana Golynska & Bogdana Shandra & Oksana Matviienko & Viktoriia Svyshcho, 2021. "Rule of Low as Factor of Investments in Ukraine," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 199-210.
    7. Wu, Jiamei & Chen, Zhibin & Guo, Chong, 2022. "How does anti-corruption affect green innovation? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 405-424.
    8. Chen, Xia & Fu, Qiang & Chang, Chun-Ping, 2021. "What are the shocks of climate change on clean energy investment: A diversified exploration," Energy Economics, Elsevier, vol. 95(C).
    9. Yang, Qi-Cheng & Zheng, Mingbo & Chang, Chun-Ping, 2022. "Energy policy and green innovation: A quantile investigation into renewable energy," Renewable Energy, Elsevier, vol. 189(C), pages 1166-1175.
    10. Malik, Ashish & Froese, Fabian Jintae, 2022. "Corruption as a perverse Innovation: The dark side of digitalization and corruption in international business," Journal of Business Research, Elsevier, vol. 145(C), pages 682-693.
    11. Wen, Jun & Deng, Peidong & Fu, Qiang & Chang, Chun-Ping, 2022. "Does health innovation relieve disease burden? The comprehensive evidence," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    12. Hung Quang Doan & Nam Hoang Vu & Binh Tran-Nam & Ngoc-Anh Nguyen, 2022. "Effects of tax administration corruption on innovation inputs and outputs: evidence from small and medium sized enterprises in Vietnam," Empirical Economics, Springer, vol. 62(4), pages 1773-1800, April.
    13. Chen, Yin-E & Li, Chunyan & Chang, Chun-Ping & Zheng, Mingbo, 2021. "Identifying the influence of natural disasters on technological innovation," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 22-36.
    14. Yemin Ding & Lee Chin & Fangyan Li & Peidong Deng, 2022. "How Does Government Efficiency Affect Health Outcomes? The Empirical Evidence from 156 Countries," IJERPH, MDPI, vol. 19(15), pages 1-18, August.
    15. Jun Wen & Waheed Ali & Jamal Hussain & Nadeem Akhtar Khan & Hadi Hussain & Najabat Ali & Rizwan Akhtar, 2022. "Dynamics between green innovation and environmental quality: new insights into South Asian economies," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 39(2), pages 543-565, July.
    16. Dokas, Ioannis & Panagiotidis, Minas & Papadamou, Stephanos & Spyromitros, Eleftherios, 2023. "Does innovation affect the impact of corruption on economic growth? International evidence," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 1030-1054.
    17. Wen, Jun & Wang, Siqin & Yang, Xiuyun & Zhou, Xiaozhou, 2023. "Impacts of epidemics on innovation: An empirical analysis," Technovation, Elsevier, vol. 119(C).

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