Does Distribution of Energy Innovation impacts Distribution of Income: A Quantile-based SDG Modeling Approach

Sinha, Avik and Sengupta, Tuhin and Kalugina, Olga and Awais Gulzar, Muhammad (2020): Does Distribution of Energy Innovation impacts Distribution of Income: A Quantile-based SDG Modeling Approach. Published in: Technological Forecasting and Social Change (22 July 2020)

Abstract

Despite the ongoing research on energy innovation and economic growth, little is known on how degree of energy innovation impacts income inequality within a nation. To address this research gap, we have developed a bivariate model to analyze how distribution of energy innovation affects the income distribution in a certain country. Using the Fisher Ideal Index, we have calculated energy efficiency as an indicator of energy innovation. Quantile-on-Quantile regression has been applied to capture the impact on energy innovation across different income quantiles in Next 11 countries. Results show that energy innovation can have different outcomes, across the member countries of N11 group, namely a) equitable and positive impact, (b) negative impact, and (c) inequitable impact in terms of distribution of income. We have inferred important policy implications, which might lead to sustainable development strategies in N11 countries. This study is one of the first to establish the direct link between energy innovation and income inequality across different quantiles within a nation. Further, we successfully demonstrate the application of advanced quantile methods in inferring Sustainable Development Goal (SDG) focused policy implications.

• Item Type: MPRA Paper
• Language: English
• Keywords: Energy Innovation; Energy Efficiency; Income Inequality; Sustainable Development Goals; Quantile-on-Quantile Regression
• Subjects: O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights; O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O30 - General

References

A. Drehobl, L. Ross, Lifting the high energy burden in America’s largest cities: How energy efficiency can improve low income and underserved communities, Transportation Research Board, National Academies of Science, Engineering, Medicine, 2016.

A. Lahiani, A. Sinha, M. Shahbaz, Renewable Energy Consumption, Income, CO₂ Emissions, and Oil Prices in G7 Countries: The Importance of Asymmetries, J. Energy Dev. 43(1/2) (2017) 157 191.

A. Sharif, O. Baris-Tuzemen, G. Uzuner, I. Ozturk, A. Sinha Revisiting the role of renewable and non-renewable energy consumption on Turkey’s ecological footprint: Evidence from Quantile ARDL approach, Sustain. Cities Soc., 57 (2020a), Article 102138.

A. Sharif, S. Mishra, A. Sinha, Z. Jiao, M. Shahbaz, S. Afshan, The renewable energy consumption-environmental degradation nexus in Top-10 polluted countries: Fresh insights from quantile-on-quantile regression approach, Renew. Energ. 150 (2020b) 670 690.

A. Sinha, M. Shahbaz, D. Balsalobre, Exploring the relationship between energy usage segregation and environmental degradation in N-11 countries, J. Clean. Prod. 168 (2017) 1217-1229.

A. Sinha, M. Gupta, M. Shahbaz, T. Sengupta, Impact of corruption in public sector on environmental quality: Implications for sustainability in BRICS and next 11 countries, J. Clean. Prod. 232 (2019) 1379 1393.

A. Sinha, T. Sengupta, R. Alvarado Interplay between technological innovation and environmental quality: formulating the SDG policies for next 11 economies. J. Clean. Prod., 242 (2020a), Article 118549.

A. Sinha, M.I. Shah, T. Sengupta, Z. Jiao, Analyzing technology-emissions association in Top-10 polluted MENA countries: How to ascertain sustainable development by quantile modeling approach. J. Environ. Manage., 267 (2020b), Article 110602.

C. Antonelli, A. Gehringer, Technological change, rent and income inequalities: A Schumpeterian approach, Technol. Forecast. Soc. Change 115 (2017) 85 98.

D. Hémous, M. Olsen, The rise of the machines: Automation, horizontal innovation and income inequality, Discussion Paper No. DP10244, Centre for Economic and Policy Research, 2014.

D. Le Blanc, Towards integration at last? The sustainable development goals as a network of targets, Sustain. Dev. 23(3) (2015) 176 187.

D.P. Claudia, S. Karagiannis, R. Raab, Innovation and inequality in the EU: for better or for worse?, Joint Research Centre, European Union, Luxembourg, 2018.

F. Kern, Using the multi-level perspective on socio-technical transitions to assess innovation policy, Technol. Forecast. Soc. Change 79(2) (2012) 298 310.

G. Cozzi, G. Impullitti, Government spending composition, technical change, and wage inequality, J. Eur. Econ. Assoc. 8(6) (2010) 1325 1358.

G.E. Metcalf, An empirical analysis of energy intensity and its determinants at the state level, Energ. J. 29(3) (2008) 1 26.

H. Mallick, H. Padhan, M.K. Mahalik, Does skewed pattern of income distribution matter for the environmental quality? Evidence from selected BRICS economies with an application of Quantile-on-Qauntile regression (QQR) approach, Energ. Policy 129 (2019) 120 131.

I. Fisher, The best form of index number, Q. Publ. Am. Stat. Assoc. 17(133) (1921) 533 551.

I. Kawachi, B.P. Kennedy, Income inequality and health: pathways and mechanisms, Health Serv. Res. 34(1 Pt 2) (1999) 215 227.

Information Technology & Innovation Foundation (ITIF), 2019. The Global Energy Innovation Index: National Contributions to the Global Clean Energy Innovation System. http://www2.itif.org/2019-global-energy-innovation-index.pdf.

International Energy Agency (IEA), 2019. Data and statistics. https://www.iea.org/data-and-statistics.

J. O’Neill, 2018. The “Next Eleven” and the World Economy. Project Syndicate. https://www.project-syndicate.org/commentary/n-11-global-economy-by-jim-o-neill-2018-04

J. Włodarczyk, Innovations and income inequalities–a comparative study, J. Int. Stud. 10(4) (2017) 166 178.

J.A. Schumpeter, The Theory of Economic Development. Harvard University Press, Cambridge, 1934.

J.H. Kim, A study on the effect of financial inclusion on the relationship between income inequality and economic growth, Emerg. Mark. Financ. Tr. 52(2) (2016) 498 512.

J.J. Rözer, B. Volker, Does income inequality have lasting effects on health and trust?, Soc. Sci. Med. 149 (2016) 37 45.

M. Shahbaz, M.A. Destek, I. Okumus, A. Sinha, An empirical note on comparison between resource abundance and resource dependence in resource abundant countries, Resour. Policy 60 (2019) 47 55.

M.A. Destek, A. Sinha Renewable, non-renewable energy consumption, economic growth, trade openness and ecological footprint: Evidence from organisation for economic Co-operation and development countries, J. Clean. Prod., 242 (2020), Article 118537.

M.A. Destek, M. Shahbaz, I. Okumus, S. Hammoudeh, A. Sinha, The relationship between economic growth and carbon emissions in G-7 countries: evidence from time-varying parameters with a long history, Environ. Sci. Pollut. R. (2020) 1 18.

M.R. Farzanegan, M.M. Habibpour, Resource rents distribution, income inequality and poverty in Iran, Energ. Econ. 66 (2017) 35 42.

M.W. Zafar, M. Shahbaz, A. Sinha, T. Sengupta, Q. Qin How renewable energy consumption contribute to environmental quality? The role of education in OECD countries, J. Clean. Prod., 268 (2020), Article 122149.

Mckinsey Quarterly, 2019. The decoupling of GDP and energy growth: A CEO guide. https://www.mckinsey.com/industries/electric-power-and-natural-gas/our-insights/the-decoupling-of-gdp-and-energy-growth-a-ceo-guide

N. Lee, Are innovative regions more unequal? Evidence from Europe, Environ. Plann. C. 29(1) (2011) 2 23.

N. Lee, A. Rodríguez-Pose, Innovation and spatial inequality in Europe and USA, J. Econ. Geogr. 13(1) (2013) 1 22.

N. Sim, H. Zhou, Oil prices, US stock return, and the dependence between their quantiles, J. Bank Financ. 55 (2015) 1 8.

N.C. Kakwani, Income inequality and poverty, World Bank, New York, 1980.

P. Aghion, U. Akcigit, A. Bergeaud, R. Blundell, D. Hémous, D., Innovation and top income inequality, Rev. Econ. Stud. 86(1) (2019) 1 45.

P.H. Leal, A.C. Marques Are de jure and de facto globalization undermining the environment? Evidence from high and low globalized EU countries, J. Environ. Manage. 250 (2019), Article 109460.

P.P. Walsh, E. Murphy, D. Horan The role of science, technology and innovation in the UN 2030 agenda, Technol. Forecast. Soc. Change, 154 (2020), Article 119957.

S. Breau, D.F. Kogler, K.C. Bolton, On the Relationship between Innovation and Wage Inequality: New Evidence from Canadian Cities, Econ. Geogr. 90(4) (2014) 351 373.

S. Yun, J. Lee, Advancing societal readiness toward renewable energy system adoption with a socio-technical perspective. Technol. Forecast. Soc. Change 95 (2015) 170 181.

S.I. Khattak, M. Ahmad, Z.U. Khan, A. Khan, Exploring the impact of innovation, renewable energy consumption, and income on CO2 emissions: new evidence from the BRICS economies, Environ. Sci. Pollut. R. 27 (2020) 13866 13881.

T. Kennedy, R. Smyth, A. Valadkhani, G. Chen, Does income inequality hinder economic growth? New evidence using Australian taxation statistics, Econ. Model. 65 (2017) 119 128.

United Nations Statistics Division (UNSD), 2019. UN data. http://data.un.org/.

V. Roy, S. Singh, Mapping the business focus in sustainable production and consumption literature: Review and research framework, J. Clean. Prod. 150 (2017) 224 236.

V. Roy, T., Schoenherr, P. Charan, The thematic landscape of literature in sustainable supply chain management (SSCM), Int. J. Oper. Prod. Man. 38(4) (2018) 1091 1124.

V.S. Tchamyou, G. Erreygers, D. Cassimon, Inequality, ICT and financial access in Africa, Technol. Forecast. Soc. Change 139 (2019) 169 184.

World Bank, 2019. World Development Indicators. http://data.worldbank.org/indicator.