New perspective on improving OFDI’s reverse innovation spillover effect: empirical test based on environmental regulation

HAN Xianfeng1 HUI Ning1 SONG Wenfei2

(1.School of Economics & Management, Northwest University)
(2.Northwest Institute of Historical Environment and Socio-Economic Development, Shaanxi Normal University)
【Knowledge Link】asymptotic distribution

【Abstract】From the perspective of environmental regulation, this paper studies OFDI’s reverse innovation overflow effect using the provincial panel data from 2004 to 2015 and the technique of threshold regression. What the study shows are as follows. (1) OFDI significantly promotes the domestic innovative efficiency, while there exists an obvious triple–threshold effect as far as the environmental regulation is concerned. (2) When the environmental regulation with a lower intensity positively impacts the OFDI’s reverse innovative spillover, it is relatively limited. Only when the environmental regulation intensity exceeds a certain threshold level, can the effect be maximized. However, the environmental regulation with a higher intensity does not always ensure positive impact. A harsher environmental regulation may weaken the OFDI’s reverse innovative spillover. (3) Although the current intensity of environmental regulation fails to drive the OFDI’s reverse innovation spillover in the most effective way, it is not far away from the optimal intensity range of environmental regulation. It is practicable to further release OFDI’s reverse innovation spillover through increasing the environmental regulation intensity in the short term, but in the long term, we still cannot ignore the “intensity” constraint of environmental regulation. (4) Under the constraint of environmental regulation, OFDI’s reverse innovation spillover effect shows a significant spatial heterogeneity. Positively inverted U–shaped, U–shaped and inverted U–shaped curves with nonlinear features have been observed in the eastern, central and western regions respectively. In the regions along the Belt and Road, it is featured by nonlinear positively inverted U–shaped, and nonlinear U–shaped curve exists outside the regions along the Belt and Road. All these findings provide a strong basis for implementing diverse and dynamic environmental regulation policies in different regions and thus promoting OFDI reverse innovation overflow more effectively.

【Keywords】 outward foreign direct investment (OFDI); environmental regulation; regional innovation efficiency; threshold effect;


【Funds】 Western Project of National Social Science Fund of China (17XJL004) Youth Project of National Natural Science Foundation of China (71703121) Basic Scientific Research Fund for the Central Universities of Shaanxi Normal University (16SZYB38)

Download this article

(Translated by Wei Yang)


    [1]. ① As to the AR(1) model for panel data,denotes the vector of the exogenous variable in the model, which includes the time trends and fixed effects of each cross section. Parameter ρi denotes the autoregressive coefficient. The random error term uit satisfies the independent and identically distributed assumption. If |ρi|<1, it corresponds to the yi stationary series. According to different restrictions of the parameter ρi in the model, the unit root test methods of the panel data can be divided into two categories of the panel unit root test in the same situation and in different situations. [^Back]

    [2]. ② Panel cointegration test results are not reported here due to space limitations. [^Back]

    [3]. ① Regional grouping based on the Belt and Road aims to further reveal the heterogeneity and dynamic law of OFDI’s reverse innovation spillovers, so as to provide references for China to better implement the Belt and Road initiative and formulate corresponding regional innovation plans. [^Back]

    [4]. ① This paper believes that OFDI has a self-selection effect, which will be more significant under the constraints of environmental regulation. Since OFDI’s reverse spillovers in the eastern region has higher requirement for environmental regulation, it prefers to study and absorb green and clean technologies in developed countries, and to better adapt to the severe environmental regulations in the region by green-seeking reverse spillovers of OFDI, thereby enhancing regional innovation capability. [^Back]


    [1] Li, B., Han, X. & Song, W. Forum on Science and Technology in China (中国科技论坛), 2013 (5): 68–76.

    [2] Li, M. & Liu, S. Management World (管理世界), 2012 (1): 21–32.

    [3] Li, S. & Yu, J. Journal of International Trade (国际贸易问题), 2016 (12): 28–38.

    [4] Liu, H. & Yan, T. Science Research Management (科研管理), 2015, 36 (1): 1–7.

    [5] Mao, Q. & Xu, J. The Journal of World Economy (世界经济), 2014 (8): 98–125.

    [6] Qi, C., Huang, X. & Fan, Y. Journal of International Trade (国际贸易问题), 2013 (4): 115–122.

    [7] Qiu, Z. Shanghai Journal of Economics (上海经济研究), 2015 (9): 24–30.

    [8] Shan, H. The Journal of Quantitative & Technical Economics (数量经济与技术经济研究), 2008 (10): 17–31.

    [9] Xie, W, Zhou, K. & Wei, X. Economic Survey (经济经纬), 2014 (3): 42–47.

    [10]Wang, X. & Yao, H. World Economy Studies (世界经济研究), 2016 (11):86–100.

    [11]Yin, D. & Zhang, J. Journal of International Trade (国际贸易问题), 2016 (1):109–120.

    [12]ATHREYE S., KAPUR S. Introduction: The Internationalization of Chinese and Indian Firms: Trends, Motivation and Strategy. Industrial and Corporate Change, 2009, 13 (2): 209–221.

    [13]BITZER J., KEREKES M. Does Foreign Direct Investment Transfer Technology across Borders? New Evidence. Economics Letters, 2008, 100 (3): 355–358.

    [14]BORENSZTEIN E, GREGORIO J, J W LEE. How Does Direct Investment Affect Economic Growth? Journal of International Economics, 1998, 45 (1): 115–135.

    [15]CHANG C., CHEN S., MC ALEER M. Globalization and Knowledge Spillover: International Direct Investment, Exports and Patents. KIER Working paper, 721, 2012.

    [16]CHEN V Z, LI J, SHAPIRO D M. International Reverse Spillover Effects on Parent Firms: Evidences from Emerging–market MNES in Developed Markets. European Management Journa1, 2012 (3): 204–218.

    [17]HANSEN. Threshold Effect in Non–dynamic Panels: Estimation, Testing, and Inference. Journal of Econometrics, 1999, 93 (2): 345–368.

    [18]HUANG S. Capital Outflow and R&D Investment in the Parent Firm. Research Policy, 2013, 42 (1): 245–260.

    [19]KOGUT B., CHANG S. Technological Capabilities and Japanese Foreign Direct Investment in the United States. The Review of Economics and Statistics, 1991 (73): 401–413.

    [20]LEE G.The Effectiveness of International Knowledge Spillover Channels. European Economic Review, 2006, 50 (8): 2075–2088.

    [21]SEYOUM M, WU R, YANG L. Technology Spillovers from Chinese Outward Direct Investment: The Case of Ethiopia. China Economic Review, 2015 (33): 35–49.

This Article


CN: 11-1692/F

Vol , No. 04, Pages 103-116

April 2018


Article Outline



  • Introduction
  • 1 Literature review
  • 2 Research design
  • 3 Empirical results and analysis
  • 4 Conclusions and policy recommendations
  • Footnote