Exploring the heterogeneous impact of technological innovation on income inequality: Formulating the SDG policies for the BRICS-T economies

Abstract

The present research evaluates the effect of technological innovation distribution on the distribution of income using data from between 1992Q1 and 2019Q4 for the BRICS-T (Brazil, Russia, India, China, South Africa, and Turkey) nations. The BRICS-T nations present a good case for this research since this problem could be more widespread in developing countries with high prospects for economic growth. The quantile causality and quantile-on-quantile regression techniques have been used to evaluate this association. The research findings provide a range of outcomes from different countries, which can be grouped into three categories; (i) Technological innovation impacts income inequality positively. (ii) Technological innovation distribution impacts income inequality distribution negatively. (iii) The effects of technology innovation on income distribution are not evenly distributed. Significant policy ramifications are deduced that might inspire sustainable development plans in the BRICS-T nations. This research is one of the first studies to demonstrate a direct connection between income inequality and technological innovation across various quantiles within a country. The study also effectively shows how these techniques are utilized to deduce the policy ramifications of the Sustainable Development Goals (SDGs).

Keywords

Technological innovation income inequality BRICS-T nations quantile-on-quantile regression quantile causality

Get full access to this article

View all access options for this article.

References

Katz

Murphy

. Changes in relative wages, 1963–1987: supply and demand factors*. Q J Econ 1992; 107: 35–78.

Karni

Zilcha

. Technological progress and income inequality. Econom Theory 1995; 5: 277–294.

Rehme

. Education, economic growth and measured income inequality. Economica 2007; 74: 493–514.

Acemoglu

. Technical change, inequality, and the labor market. J Econ Lit 2002; 40: 7–72.

Adebayo

Bekun

Rjoub

, et al.

Another look at the nexus between economic growth trajectory and emission within the context of developing country: fresh insights from a nonparametric causality-in-quantiles test

Environ Develop Sustain 2022; 6(12): 182–200.

Sinha

Sengupta

Saha

. Technology policy and environmental quality at crossroads: designing SDG policies for select Asia pacific countries. Technol Forecast Soc Change 2020; 161: 120317.

Zhao

Sinha

Inuwa

, et al. Does structural transformation in economy impact inequality in renewable energy productivity? Implications for sustainable development. Renew Energy 2022; 189: 853–864.

Schumpeter

. The theory of economic development: An inquiry into profits, capital, credit, interest and the business cycle. Cambridge, MA: Harvard University Press, 1934.

Acheampong

. Economic growth, CO₂ emissions and energy consumption: what causes what and where? Energy Econom 2018; 74: 677–692.

10.

Josifidis

Supic

. Innovation and income inequality in the USA: ceremonial versus institutional changes. J Econom Issues 2020; 54: 486–494.

11.

Troster

. Testing for granger-causality in quantiles. Econom Rev 2018; 37: 850–866.

12.

Sim

Zhou

. Oil prices, US stock return, and the dependence between their quantiles. J Bank Financ 2015; 55: –8.

13.

Kirikkaleli

Adebayo

. Do renewable energy consumption and financial development matter for environmental sustainability? New global evidence. Sustain Develop 2021; 29: 583–594.

14.

Cetin

Demir

Saygin

. Financial development, technological innovation and income inequality: time series evidence from Turkey. Soc Indic Res 2021; 156: 47–69.

15.

Law

Naseem

NAM

Lau

, et al. Can innovation improve income inequality? Evidence from panel data. Econom Syst 2020; 44: 100815.

16.

Aghion

Akcigit

Bergeaud

, et al. Innovation and top income inequality. Rev Econ Stud 2019; 86: 1–45.

17.

Breau

Kogler

Bolton

. On the relationship between innovation and wage inequality: new evidence from Canadian cities. Econ Geogr 2014; 90: 351–373.

18.

Lin

. Green technology innovations, urban innovation environment and CO₂ emission reduction in China: fresh evidence from a partially linear functional-coefficient panel model. Technol Forecast Soc Change 2022; 176: 121434.

19.

Antonelli

Gehringer

. Technological change, rent and income inequalities: a Schumpeterian approach. Technol Forecast Soc Change 2017; 115: 85–98.

20.

Karagiannis

Raab

Palo

. Innovation and inequality in the EU: For better or for worse? https://doi.org/10.2760/365700 . 2018.

21.

Włodarczyk

. Innovations and income inequalities – a comparative study. J Int Studies 2017; 10: 166–178.

22.

Tchamyou

Erreygers

Cassimon

. Inequality, ICT and financial access in Africa. Technol Forecast Soc Change 2019; 139: 169–184.

23.

Solt

. The standardized world income inequality database*. Soc Sci Q 2016; 97: 1267–1281.

24.

Acheampong

Dzator

Shahbaz

. Empowering the powerless: does access to energy improve income inequality? Energy Econom 2021; 99: 105288.

25.

Acheampong

Shahbaz

Dzator

, et al. Effects of income inequality and governance on energy poverty alleviation: implications for sustainable development policy. Util Policy 2022; 78: 101403.

26.

Raza

Sharif

Wong

, et al. Tourism development and environmental degradation in the United States: evidence from wavelet-based analysis. Curr Issues Tourism 2017; 20: 1768–1790.

27.

Broock

Scheinkman

Dechert

, et al. A test for independence based on the correlation dimension. Econom Rev 1996; 15: 197–235.

28.

Granger

CWJ

. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 1969; 37: 424–438.

29.

Xiao

. Quantile cointegrating regression. J Econom 2009; 150: 248–260.

30.

Avink

Inuwa

Wang

, et al. Does structural transformation in economy impact inequality in renewable energy productivity? Implications for sustainable development. Renewable Energy 2022; 189: 853–864.