Long-term determinants of income inequality: evidence from panel data over 1870–2016

Hailemariam, Abebe; Sakutukwa, Tutsirai; Dzhumashev, Ratbek

doi:10.1007/s00181-020-01956-7

Cited by 23 publications

(20 citation statements)

References 47 publications

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“…The implication is that income inequality, energy intensity, population size, industrialization and urbanization in uence economic growth. Income inequality Granger causes economic growth with feedback effect, which corroborated with the nding of Hailemariam et al (2020). This implies that the status of income inequality dependents on the level of economic growth and the level of income inequality determines economic growth.…”

Section: Granger Causality Test Resultssupporting

confidence: 68%

Income inequality, economic growth and carbon dioxide emissions nexus: empirical evidence from Ethiopia

Hundie

2021

Environ Sci Pollut Res

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The relationship between income inequality, economic growth and CO 2 emissions is ambiguous both theoretically and empirically. Hence, this study examines the link between income inequality and CO 2 emissions in Ethiopia for time span covering 1979-2014 using ARDL bounds test and DOLS approach to cointegration. The Zivot-Andrews unit root test and Clemente-Montanes-Reyes unit root test reveal that some of the variables under consideration are stationary at level while others become stationary after rst differencing. Both ARDL and DOLS approaches con rm that there is a long-run relationship among the series during the study period. The long-run empirical results show that a 1% increase in economic growth accounts for a 1.05% increase in CO 2 emissions while a 1% increase in economic growth squared reduces CO2 emissions by 0.11%. The U-test result reveals that the relationship between CO 2 emissions and economic growth con rms existence of the Environmental Kuznets Curve hypothesis. The effect of income inequality on CO 2 is not robust to alternative estimation techniques; it is statistically insigni cant under the ARDL estimation, but DOLS estimates show that a 1% increase in income inequality increases CO 2 emissions by 0.21% in the long-run during the study period. In the long-run a 1% rise in urbanization, population size, energy intensity and industrialization each positively contribute to environmental degradation in Ethiopia by 0.38%, 0.22%, 0.07% and 0.11% respectively. Results from the Toda-Yamamoto Granger causality show a bidirectional causal relationship between CO 2 emissions and all other variables except economic growth. CO 2 emissions granger causes economic growth with no feedback effect. Results suggested important policy implications in the light of achieving its 2030 targets of lowcarbon economy for Ethiopia.

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Section: Granger Causality Test Resultssupporting

confidence: 68%

Income inequality, economic growth and carbon dioxide emissions nexus: empirical evidence from Ethiopia

Hundie

2021

Environ Sci Pollut Res

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“…e effect of financial inclusion on income inequality in the central region is not significant, which is consistent with the findings of Park and Mercado [14], who point out that it is questionable whether financial inclusion in developing Asian countries (especially China) has any inhibitory effect on income inequality. Furthermore, economic growth in the central region helps reduce income inequality, a finding which supports the main conclusions of Hailemariam et al [84], who examined the determinants of income inequality and argued that economic growth leads to a significant reduction in income inequality. Overall, the improvement of income inequality in the central region primarily depends on the path of economic growth, while financial inclusion mainly plays a role in poverty alleviation.…”

Section: That the Development Of Financial Inclusion Has Amplified In...supporting

confidence: 81%

“…In addition, we also consider that there are only 4 years of sample data after 2015, which will aggravate the sample loss in the case of subregional testing, and it seems inappropriate to use short panel data to establish the PVAR model. erefore, we borrowed the research ideas of Hailemariam et al [84] and continued to use nonparametric time-varying coefficient panel data models (NP-TVP) after the PVAR model to capture the time-varying effects of the main explanatory variables on RPOV. NP-TVP technology uses a pooled local linear dummy variable estimator (LLDVE), which has the advantage that it does not need to specify a certain function followed by the regime conversion in advance and allows data to directly reveal the nonlinear relationship between variables by using its own information.…”

Section: Econometric Modelmentioning

confidence: 99%

“…NP-TVP technology uses a pooled local linear dummy variable estimator (LLDVE), which has the advantage that it does not need to specify a certain function followed by the regime conversion in advance and allows data to directly reveal the nonlinear relationship between variables by using its own information. LLDVE was first proposed by Li et al [85] and has been applied by Hailemariam et al [84], Awaworyi Churchill et al [86], and Ren et al [87] in empirical studies. e form of the NP-TVP is as follows:…”

Section: Econometric Modelmentioning

confidence: 99%

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Dynamic Nonlinear Connectedness between the Financial Inclusion, Economic Growth, and China’s Poverty Alleviation: Evidence from a Panel VAR Analysis

et al. 2022

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Whether financial inclusion and economic growth can sustainably release poverty alleviation effects in long term has been the focus of academia and government sector. This article uses provincial panel data from 2004 to 2019 to examine the dynamic nonlinear connectedness between the financial inclusion, economic growth, income inequality, and poverty alleviation; the main objective is to reveal the direction and intensity of the long-term and short-term impact of each factor on poverty alleviation. By building a panel vector autoregression model (PVAR), the comparison analyses of national, eastern, central, and western sample groups verify the existence of dynamic nonlinear connectedness among the four variables. The study found that there is complex bidirectional causality between these variables, financial inclusion has the long-term impact on promoting poverty alleviation in China, the impact of economic growth is relatively weak, and income inequality has weakened the positive impact of financial inclusion on poverty alleviation. Through the analysis of impulse response function, variance decomposition, and time-varying nonparametric estimates in different economic regions, we find that the impact of financial inclusion on poverty alleviation presents a U-shaped characteristic, and the contribution of financial inclusion to poverty alleviation in western regions is significant, but poverty reduction in eastern and central region mainly depends on economic growth. For policymakers, financial inclusion can be an effective way to alleviate relative poverty, but the poverty governance should focus more on reducing income inequality in China.

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“…The difference in the policy impact on wage by various wage percentiles is small, and the negative effect disappears in the long term [38]. Hailemariam, Sakutukwa, and Dzhumashev (2020) found that income inequality responds negatively to positive innovation shocks among college graduates initially, but this effect becomes positive with some time lag for top-income inequality [39].…”

Section: Literature Reviewmentioning

confidence: 99%

Inequality in the Initial Wage of College Graduates at the College-Level Perspective

Yan-ming

Wang

2021

Sustainability

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College graduates, as a labor force with high human capital accumulation, have the problem of initial wage inequality, which is worth paying attention to. Based on the collated micro-survey data form “Employment and Entrepreneurship Development Report of Chinese College Graduates”, which contains 339 samples from vocational colleges, 453 from common colleges, and 360 from key colleges, this study empirically analyzed the inequality of college graduates’ initial wages at the college level. We found that the initial wage income level of college graduates is significantly influenced by the college level. The higher the level is, the higher the initial wage. The initial wage of graduates from key colleges is the highest, and the income inequality between them and vocational college graduates is the most significant. Moreover, there are structural differences in the wage premium effect of the college level on college graduates with a change in wage level. In addition, the study found that there is an obvious gender wage difference among college graduates, and political status, academic ranking, and student cadre experience as well as the nature of the workplace all contributed to the formation of wage premiums to a certain extent.

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Long-term determinants of income inequality: evidence from panel data over 1870–2016

Cited by 23 publications

References 47 publications

Income inequality, economic growth and carbon dioxide emissions nexus: empirical evidence from Ethiopia

Income inequality, economic growth and carbon dioxide emissions nexus: empirical evidence from Ethiopia

Dynamic Nonlinear Connectedness between the Financial Inclusion, Economic Growth, and China’s Poverty Alleviation: Evidence from a Panel VAR Analysis

Inequality in the Initial Wage of College Graduates at the College-Level Perspective

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