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What makes environment-related technologies less effective? The role of uncertainty

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  • Pham, Hung Manh
  • Chu, Lan Khanh
  • Hoang, Dung Phuong

Abstract

This study examines the effect of environment-related technologies on environmental quality, conditional on the level of uncertainty. We apply two panel quantile regression approaches to panel data on the member countries of the Organization for Economic Cooperation and Development (OECD) over the period 1990–2015. The empirical results suggest that environment-related technologies and uncertainty both significantly help improve the environmental conditions, although the magnitude of these impacts vary across the level of environmental footprint. Notably, higher uncertainty could negate the beneficial effects of green patents on the environmental footprint, especially in a highly degraded environment. Several preliminary tests, such as cross-sectional dependence, stationarity, cointegration, and nonnormality, provide support for the adoption of panel quantile regression. The significant and heterogeneous relationships between the environmental footprint and its determining factors are also established. This research offers a scientific explanation for the ineffective adoption of environment-related technologies for improving environmental quality in many OECD countries for years and hence has valuable implications for policy makers about leveraging the beneficial impacts of environment-related technologies on the ecosystem.

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  • Pham, Hung Manh & Chu, Lan Khanh & Hoang, Dung Phuong, 2024. "What makes environment-related technologies less effective? The role of uncertainty," Economic Systems, Elsevier, vol. 48(4).
    • Handle: RePEc:eee:ecosys:v:48:y:2024:i:4:s093936252400044x
    DOI: 10.1016/j.ecosys.2024.101222
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    as
    1. Oskar Lecuyer & Philippe Quirion, 2019. "Interaction between CO2 emissions trading and renewable energy subsidies under uncertainty: feed-in tariffs as a safety net against over-allocation," Climate Policy, Taylor & Francis Journals, vol. 19(8), pages 1002-1018, September.
    2. Zhang, Yue-Jun & Peng, Hua-Rong & Liu, Zhao & Tan, Weiping, 2015. "Direct energy rebound effect for road passenger transport in China: A dynamic panel quantile regression approach," Energy Policy, Elsevier, vol. 87(C), pages 303-313.
    3. Brian Chi-ang Lin & Siqi Zheng & Nicolò Barbieri & Claudia Ghisetti & Marianna Gilli & Giovanni Marin & Francesco Nicolli, 2016. "A Survey Of The Literature On Environmental Innovation Based On Main Path Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 30(3), pages 596-623, July.
    4. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    5. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    6. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    7. Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2012. "Testing for Granger non-causality in heterogeneous panels," Economic Modelling, Elsevier, vol. 29(4), pages 1450-1460.
    8. Al-Thaqeb, Saud Asaad & Algharabali, Barrak Ghanim, 2019. "Economic policy uncertainty: A literature review," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    9. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.
    10. Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.
    11. Yu, Jian & Shi, Xunpeng & Guo, Dongmei & Yang, Longjian, 2021. "Economic policy uncertainty (EPU) and firm carbon emissions: Evidence using a China provincial EPU index," Energy Economics, Elsevier, vol. 94(C).
    12. Blum, Bianca & Hübner, Julian & Müller, Sarah & Neumärker, Karl Justus Bernhard, 2018. "Challenges for sustainable environmental policy: Influencing factors of the rebound effect in energy efficiency improvements," The Constitutional Economics Network Working Papers 02-2018, University of Freiburg, Department of Economic Policy and Constitutional Economic Theory.
    13. Levenko, Natalia, 2020. "Perceived uncertainty as a key driver of household saving," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 126-145.
    14. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    15. Aaberge, Rolf & Liu, Kai & Zhu, Yu, 2017. "Political uncertainty and household savings," Journal of Comparative Economics, Elsevier, vol. 45(1), pages 154-170.
    16. Antonio Musolesi & Massimiliano Mazzanti & Roberto Zoboli, 2010. "A panel data heterogeneous Bayesian estimation of environmental Kuznets curves for CO2 emissions," Applied Economics, Taylor & Francis Journals, vol. 42(18), pages 2275-2287.
    17. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, November.
    18. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    19. Huang, Zhehao & Liao, Gaoke & Li, Zhenghui, 2019. "Loaning scale and government subsidy for promoting green innovation," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 148-156.
    20. Anwar, Ahsan & Siddique, Muhammad & Eyup Dogan, & Sharif, Arshian, 2021. "The moderating role of renewable and non-renewable energy in environment-income nexus for ASEAN countries: Evidence from Method of Moments Quantile Regression," Renewable Energy, Elsevier, vol. 164(C), pages 956-967.
    21. Alam, Md. Mahmudul & Murad, Md. Wahid, 2020. "The impacts of economic growth, trade openness and technological progress on renewable energy use in organization for economic co-operation and development countries," Renewable Energy, Elsevier, vol. 145(C), pages 382-390.
    22. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    23. Chen, Wenhui & Lei, Yalin, 2018. "The impacts of renewable energy and technological innovation on environment-energy-growth nexus: New evidence from a panel quantile regression," Renewable Energy, Elsevier, vol. 123(C), pages 1-14.
    24. Sarkodie, Samuel Asumadu & Adom, Philip Kofi, 2018. "Determinants of energy consumption in Kenya: A NIPALS approach," Energy, Elsevier, vol. 159(C), pages 696-705.
    25. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(1), pages 85-106.
    26. Canh, Nguyen Phuc & Binh, Nguyen Thanh & Thanh, Su Dinh & Schinckus, Christophe, 2020. "Determinants of foreign direct investment inflows: The role of economic policy uncertainty," International Economics, Elsevier, vol. 161(C), pages 159-172.
    27. Mansor H. Ibrahim & Siong Hook Law, 2016. "Institutional Quality and CO 2 Emission–Trade Relations: Evidence from Sub-Saharan Africa," South African Journal of Economics, Economic Society of South Africa, vol. 84(2), pages 323-340, June.
    28. Seyed Komail Tayebi & Sanaz Younespour, 2012. "The Effect of Trade Openness on Environmental Quality: Evidence from Iran's Trade Relations with the Selected Countries of the Different Blocks," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 17(2), pages 19-40, spring.
    29. David Font Vivanco & René Kemp & Ester Voet & Reinout Heijungs, 2014. "Using LCA-based Decomposition Analysis to Study the Multidimensional Contribution of Technological Innovation to Environmental Pressures," Journal of Industrial Ecology, Yale University, vol. 18(3), pages 380-392, May.
    30. Khan, Zeeshan & Hussain, Muzzammil & Shahbaz, Muhammad & Yang, Siqun & Jiao, Zhilun, 2020. "Natural resource abundance, technological innovation, and human capital nexus with financial development: A case study of China," Resources Policy, Elsevier, vol. 65(C).
    31. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
    32. Pei-Fen Chen & Chien-Chiang Lee & Jhih-Hong Zeng, 2019. "Economic policy uncertainty and firm investment: evidence from the U.S. market," Applied Economics, Taylor & Francis Journals, vol. 51(31), pages 3423-3435, July.
    33. Grafton, R. Quentin & Kompas, Tom & Long, Ngo Van & To, Hang, 2014. "US biofuels subsidies and CO2 emissions: An empirical test for a weak and a strong green paradox," Energy Policy, Elsevier, vol. 68(C), pages 550-555.
    34. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    35. Shahbaz, Muhammad & Nasir, Muhammad Ali & Roubaud, David, 2018. "Environmental degradation in France: The effects of FDI, financial development, and energy innovations," Energy Economics, Elsevier, vol. 74(C), pages 843-857.
    36. Yang, Lu, 2019. "Connectedness of economic policy uncertainty and oil price shocks in a time domain perspective," Energy Economics, Elsevier, vol. 80(C), pages 219-233.
    37. Yue Pan & Qiuping Chen & Pengdong Zhang, 2020. "Does policy uncertainty affect corporate environmental information disclosure: evidence from China," Sustainability Accounting, Management and Policy Journal, Emerald Group Publishing Limited, vol. 11(5), pages 903-931, June.
    38. Garrone, Paola & Grilli, Luca, 2010. "Is there a relationship between public expenditures in energy R&D and carbon emissions per GDP? An empirical investigation," Energy Policy, Elsevier, vol. 38(10), pages 5600-5613, October.
    39. Adedoyin, Festus Fatai & Ozturk, Ilhan & Agboola, Mary Oluwatoyin & Agboola, Phillips O. & Bekun, Festus Victor, 2021. "The implications of renewable and non-renewable energy generating in Sub-Saharan Africa: The role of economic policy uncertainties," Energy Policy, Elsevier, vol. 150(C).
    40. Zhu Liu & Philippe Ciais & Zhu Deng & Steven J. Davis & Bo Zheng & Yilong Wang & Duo Cui & Biqing Zhu & Xinyu Dou & Piyu Ke & Taochun Sun & Rui Guo & Olivier Boucher & Francois-Marie Breon & Chenxi Lu, 2020. "Carbon Monitor: a near-real-time daily dataset of global CO2 emission from fossil fuel and cement production," Papers 2006.07690, arXiv.org.
    41. Ozcan, Burcu & Ozturk, Ilhan, 2019. "Renewable energy consumption-economic growth nexus in emerging countries: A bootstrap panel causality test," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 30-37.
    42. Davide Luzzini & Emma Brandon-Jones & Alistair Brandon-Jones & Gianluca Spina, 2015. "From sustainability commitment to performance: The role of intra-and inter-firm collaborative capabilities in the upstream supply chain," Post-Print hal-01289178, HAL.
    43. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    44. Bart Verspagen, 1997. "Measuring Intersectoral Technology Spillovers: Estimates from the European and US Patent Office Databases," Economic Systems Research, Taylor & Francis Journals, vol. 9(1), pages 47-65.
    45. Lan Khanh Chu, 2021. "Economic structure and environmental Kuznets curve hypothesis: new evidence from economic complexity," Applied Economics Letters, Taylor & Francis Journals, vol. 28(7), pages 612-616, April.
    46. Adams, Samuel & Adedoyin, Festus & Olaniran, Eniola & Bekun, Festus Victor, 2020. "Energy consumption, economic policy uncertainty and carbon emissions; causality evidence from resource rich economies," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 179-190.
    47. Ellabban, Omar & Abu-Rub, Haitham & Blaabjerg, Frede, 2014. "Renewable energy resources: Current status, future prospects and their enabling technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 748-764.
    48. Hauknes, Johan & Knell, Mark, 2009. "Embodied knowledge and sectoral linkages: An input-output approach to the interaction of high- and low-tech industries," Research Policy, Elsevier, vol. 38(3), pages 459-469, April.
    49. Bera, Anil K. & Jarque, Carlos M., 1981. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals : Monte Carlo Evidence," Economics Letters, Elsevier, vol. 7(4), pages 313-318.
    50. Fei Jia & Xiaoyong Huang & Xiangyun Xu & Haoyu Sun, 2020. "The Effects of Economic Policy Uncertainty on Export: A Gravity Model Approach," Prague Economic Papers, Prague University of Economics and Business, vol. 2020(5), pages 600-622.
    51. Chen, Wenying & Xu, Ruina, 2010. "Clean coal technology development in China," Energy Policy, Elsevier, vol. 38(5), pages 2123-2130, May.
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    More about this item

    Keywords

    environmental footprint; environment-related technologies; OECD countries; quantile regression; uncertainty;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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