JACIII Vol.26 No.4 pp. 461-470
doi: 10.20965/jaciii.2022.p0461


China’s R&D Investment’s Impact on Environmental Pollution: An Integrated Approach Based on Panel Moderated Mediation and Regression Discontinuity

Aihua Lin*,† and Yukun Xu**

*College of Business, Minnan Normal University
36 Xianqian Street, Xiangcheng District, Zhangzhou City, Fujian Province 363000, China

**Research Center of Internet Finance and Blockchain, Fujian University of Technology
999 Dongsanhuan Road, Jin’an District, Fuzhou City, Fujian Province 350011, China

Corresponding author

January 14, 2021
March 1, 2022
July 20, 2022
R&D investment, panel moderated mediation analysis, regression discontinuity, IPAT model, STRIPAT model

How to reduce environmental pollution is fundamental for current civilization. Increasing in R&D investment may reduce the environmental pollution, yet whether and how R&D investment influence the environmental pollution needs further discussion and verification. Considering that the R&D investment can directly and also indirectly influence the environmental pollution by affecting the economic growth, and the fact that there is an obvious discontinuity for economic growth during the observed period, this paper firstly proposes an integrated approach based on panel moderated mediation analysis and regression discontinuity. It examines the R&D impact on environmental pollution on the basis of province-level data in China and uses the integrated approach to test its direct and indirect effect. Finally conclusion is made according to the findings.

Cite this article as:
A. Lin and Y. Xu, “China’s R&D Investment’s Impact on Environmental Pollution: An Integrated Approach Based on Panel Moderated Mediation and Regression Discontinuity,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.4, pp. 461-470, 2022.
Data files:
  1. [1] Y. Li, “Environmental innovation practices and performance: Moderating effect of resource commitment,” J. of Cleaner Production, Vol.66, pp. 450-458, 2014.
  2. [2] A. Lin, P.-P. Miglietta, and P. Toma, “Did carbon emission trading system reduce emissions in China? An integrated approach to support policy modeling and implementation,” Energy Systems, Vol.13, No.2, pp. 437-459, doi: 10.1007/s12667-021-00438-8, 2021.
  3. [3] S. Lorek and J.-H. Spangenberg, “Sustainable consumption within a sustainable economy - beyond green growth and green economies,” J. of Cleaner Production, Vol.63, pp. 33-44, 2014.
  4. [4] R.-B. Grover, “Green growth and role of nuclear power: A perspective from India,” Energy Strategy Reviews, Vol.1, Issue 4, pp. 255-260, 2013.
  5. [5] R. Padilla-Pérez and Y. Gaudin, “Science, technology and innovation policies in small and developing economies: The case of Central America,” Research Policy, Vol.43, Issue 4, pp. 749-759, 2014.
  6. [6] C.-N. MacCracken, J.-A. Edmonds, S.-H. Kim, and R.-D. Sands, “The Economics of the Kyoto Protocol,” The Energy J., Vol.20 (special issue), pp. 25-71, 1999.
  7. [7] W.-D. Nordhaus and J. Boyer, “Warming the world: Economic models of global warming,” The MIT Press, 2000.
  8. [8] D. Acemoglu, P. Aghion, L. Bursztyn et al., “The environment and directed technical change,” American Economic Review, Vol.102, No.1, pp. 131-166, 2012.
  9. [9] Z. Xu and J. Zhou, “An analysis on the public R&D and economic growth based on the cointegration,” Science Research Management, Vol.28, No.4, pp. 60-66, 2007.
  10. [10] F.-Y. Lu and D.-D. Jin, “An empirical analysis on the effect of R&D input to economic growth based on panel data,” China Industrial Economics, Issue 3, pp. 149-157, 2011.
  11. [11] J.-W. Kim, “The economic growth effect of R&D activity in Korea,” Korea and the World Economy, Vol.12, No.1, pp. 25-44, 2011.
  12. [12] A. Xiong, S. Xia, Z.-P. Ye, D. Cao, Y. Jing, and H. Li, “Can innovation really bring economic growth? The role of social filter in China,” Structural Change and Economic Dynamics, Vol.53, pp. 50-61, 2020.
  13. [13] T. Dietz and E.-A. Rosa, “Rethinking the environmental impacts of population, affluence and technology,” Human Ecology Review, Vol.1, No.2, pp. 277-300, 1994.
  14. [14] H. Bloch, S. Rafiq, and R. Salim, “Economic growth with coal, oil and renewable energy consumption in China: Prospects for fuel substitution,” Economic Modeling, Vol.44, pp. 104-115, 2015.
  15. [15] P. Wei, “Supply-side reform promote the growth of economy - An empirical research on 2004-2015 provincial panel data from China,” Inquiry Into Economic Issues, Vol.37, No.10, pp. 18-27, 2016 (in Chinese).
  16. [16] Y. Li, S. Gu, P. Gao et al., “Special articles for commemorating the 70th anniversary of the founding of new China,” Economic Research, Vol.54, Issue 10, pp. 4-23, 2019.
  17. [17] K.-J. Preacher, M.-J. Zyphur, and Z. Zhang, “A general multilevel SEM framework for assessing multilevel mediation,” Psychological Methods, Vol.15, No.3, pp. 209-233, 2010.
  18. [18] R. Mai, T. Niemand, and S. Kraus, “A tailored-fit model evaluation strategy for better decisions about structural equation models,” Technological Forecasting and Social Change, Vol.173, Article No.121142, doi: 10.1016/j.techfore.2021.121142, 2021.
  19. [19] R. Rabus, R. Nordhaus, W. Ludwig et al., “Complete Oxidation of Toluene Under Strictly Anoxic Conditions by a New Sulfate-Reducing Bacterium,” Applied and Environmental Microbiology, Vol.59, No.5, pp. 1444-1451, 1993.
  20. [20] R.-G. Newell, A.-B. Jaffe, and R.-N. Stavins, “The induced innovation hypothesis and energy-saving technological change,” The Quarterly J. of Economics, Vol.114, No.3, pp. 941-975, 1999.
  21. [21] A.-B. Jaffe, R.-G. Newell, and R.-N. Stavins, “Environmental policy and technological change,” Environmental and Resource Economics, Vol.22, Issue 1-2, pp. 41-70, 2002.
  22. [22] X. Shao, Y. Zhong, Y. Li, and M. Altuntaş, “Does environmental and renewable energy R&D help to achieve carbon neutrality target? A case of the US economy,” J. of Environmental Management, Vol.296, Article No.113229, doi: 10.1016/j.jenvman.2021.113229, 2021.
  23. [23] H.-W. Marsh, Z. Wen, and K.-T. Hau, “Structural equation models of latent interactions: Evaluation of alternative estimation strategies and indicator construction,” Psychological Methods, Vol.9, No.3, pp. 275-300, 2004.
  24. [24] P.-D. Mehta and M.-C. Neale, “People are variables too: Multilevel structural equations modeling,” Psychological Methods, Vol.10, No.3, pp. 259-284, 2005.
  25. [25] H.-W. Marsh, Z. Wen, K.-T. Hau, and B. Nagengast, “Structural equation models of latent interaction and quadratic effects,” G.-R. Hancock and R.-O. Mueller (Eds.), “Structural equation modeling: A second course,” pp. 267-308, Information Age Publishing, 2006.
  26. [26] K.-J. Preacher, D.-D. Rucker, and A.-F. Hayes, “Addressing moderated mediation hypotheses: Theory, methods, and prescriptions,” Multivariate Behavioral Research, Vol.42, Issue 1, pp. 185-227, 2007.
  27. [27] K.-J. Preacher, Z. Zhang, and M.-J. Zyphur, “Alternative methods for assessing mediation in multilevel data: The advantages of multilevel SEM,” Structural Equation Modeling: A Multidisciplinary J., Vol.18, No.2, pp. 161-182, 2011.
  28. [28] M.-S. Cole, F. Water, and H. Bruch, “Affective mechanisms linking dysfunctional behavior to performance in work teams: A moderated mediation study,” J. of Applied Psychology, Vol.93, No.5, pp. 945-958, 2008.
  29. [29] A.-U. Wiedemann, B. Schüz, F. Sniehotta, U. Scholz, and R. Schwarzer, “Disentangling the relation between intentions, planning, and behavior: A moderated mediation analysis,” Psychology and Health, Vol.24, Issue 1, pp. 67-79, 2009.
  30. [30] T. Andreeva and A. Kianto, “Knowledge processes, knowledge-intensity and innovation: A moderated mediation analysis,” J. of knowledge management, Vol.15, Issue 6, pp. 1016-1034, 2011.
  31. [31] T. Feng and D. Wang, “The influence of environmental management systems on financial performance: A moderated-mediation analysis,” J. of Business Ethics, Vol.135, No.2, pp. 265-278, 2016.
  32. [32] Y. Li, J. Dai, and L. Cui, “The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model,” Int. J. of Production Economics, Vol.229, Article No.107777, doi: 10.1016/j.ijpe.2020.107777, 2020.
  33. [33] J. Hahn, P. Todd, and W.-V.-D. Klaauw, “Identification and estimation of treatment effects with a regression-discontinuity design,” Econometrica, Vol.69, No.1, pp. 201-209, 2001.
  34. [34] D.-S. Lee, “Randomized Experiments From Non-Random Selection in U.S. House Elections,” J. of Econometrics, Vol.142, Issue 2, pp. 675-697, 2008.
  35. [35] P.-R. Ehrlich and J.-P. Holdren, “Impact of Population Growth,” Science, Vol.171, Issue 3977, pp. 1212-1217, 1971.
  36. [36] E. Asiedu and T. Stengos, “An empirical estimation of the underground economy in Ghana,” Economics Research Int., Vol.2014, Article No.891237, pp. 1-14, doi: 10.1155/2014/891237, 2014.
  37. [37] S. Kaghazian, I.-Z. Jojadeh, and Y. Naghdi, “Underground economy estimation in Iran by MIMIC method,” Economic Studies J., Issue 1, pp. 90-109, 2015.
  38. [38] J. Franić, “Undeclared economy in Croatia during the 2004-2017 period: Quarterly estimates using the MIMIC method,” Croatian Economic Survey, Vol.21, No.1, pp. 5-46, 2019.
  39. [39] M.-L. Anderson, “Subways, strikes, and slowdowns: The impacts of public transit on traffic congestion,” American Economic Review, Vol.104, No.9, pp. 2763-2796, 2014.
  40. [40] C. Hausman and D.-S. Rapson, “Regression discontinuity in time: Considerations for empirical applications,” Working Papers, 2017, [Accessed January 1, 2020].
  41. [41] S. Marsiglio, “On the relationship between population change and sustainable development,” Research in Economics, Vol.65, No.4, pp. 353-364, doi: 10.1016/j.rie.2011.01.007, 2011.
  42. [42] V.-M. Taghvaee, C. Mavuka, and J.-K. Shirazi, “Economic growth and energy consumption in Iran: An ARDL approach including renewable and non-renewable energies,” Environment, Development and Sustainability, Vol.19, Issue 6, pp. 2405-2420, 2017.
  43. [43] K. Li, L. Fang, and L. He, “How population and energy price affect China’s environmental pollution?,” Energy Policy, Vol.129, pp. 386-396, 2019.
  44. [44] C. Zhang and Y. Lin, “Panel estimation for urbanization, energy consumption and CO2 emissions: A regional analysis in China,” Energy Policy, Vol.49, pp. 488-498, 2012.
  45. [45] K. Ju, B. Su, D. Zhou, and J. Wu, “Does energy-price regulation benefit China’s economy and environment? Evidence from energy-price distortions,” Energy Policy, Vol.105, pp. 108-119, 2017.
  46. [46] E. Hille, “Pollution havens: International empirical evidence using a shadow price measure of climate policy stringency,” Empirical Economics, Vol.54, Issue 3, pp. 1137-1171, 2018.
  47. [47] J. Pang, H. Mu, and M. Zhang, “Interaction between shadow economy and pollution: Empirical analysis based on panel data of northeast China,” Environmental Science and Pollution Research, Vol.27, No.17, pp. 21353-21363, doi: 10.1007/s11356-020-08641-3, 2020.
  48. [48] X. Long, Y. Chen, J. Du, K. Oh, I. Han, and J. Yan, “The effect of environmental innovation behavior on economic and environmental performance of 182 Chinese firms,” J. of Cleaner Production, Vol.166, pp. 1274-1282, doi: 10.1016/j.jclepro.2017.08.070, 2017.
  49. [49] G. Gu and B. Xu, “Innovation Path of Manufacturing Enterprises and Strategies for Transformation and Upgrading in China,” J. Adv. Comput. Intell. Intell. Inform., Vol.21, No.6, pp. 1048-1055, 2017.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Aug. 05, 2022