Does political decentralization affect income inequality? The role of governance quality

Tselios, Vassilis

doi:10.1080/00343404.2022.2101634

Cited by 10 publications

(1 citation statement)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, a positive impact of institutional development on inequality was found by Karakoc (2017). The work of Acemoglu and Robinson (2002) examined the political economy drivers of KC with a transmission mechanism from democratization to institutional changes, which encourages a more egalitarian income distribution, while a negative effect of political decentralization on inequality was discussed in (Tselios (2022)). Finally, the determinants of inequality from an institutional view point is given in Bahamonde and Trasberg (2021) Due to the wide range of dimensions and availability of a large number of different indicators describing different political institutions, there is a certain confusion in terms of which indicator to use and for what purpose.…”

Section: Literature Review Of the Kc And Institutional Quality Nexusmentioning

confidence: 99%

A Revisit to Political Institutions and Inequality

DENIZ,

Stengos

2023

Preprint

View full text Add to dashboard Cite

This study revisits the drivers of income inequality with political institutions at the core. We take a multidimensional institutional approach by defining political institutions in terms of governance, political freedom, political fragmentation and political scale. The main contributions of our study are (i) presenting the most extensive analysis up-to-date of the role of political institutions by decomposing it into distinct elements and (ii) considering the difficulty and the lack of consensus and clarity regarding the choice of instruments in the literature we define an alternative methodology to deal with the potential endogeneity of political institutions. We combine an analysis of club convergence, a clustering mechanism according to the long term income trajectories of the countries under investigation with Bayesian Model Averaging (BMA) within each cluster to determine the most important variables that affect inequality out of a large set of potentially important variables. Our results show that the effectiveness of political institutions differ among country groups and that there is no "one size fits all" policy prescription that links institutional quality and income inequality.

show abstract

Section: Literature Review Of the Kc And Institutional Quality Nexusmentioning

confidence: 99%

A Revisit to Political Institutions and Inequality

DENIZ,

Stengos

2023

Preprint

View full text Add to dashboard Cite

show abstract

Bridging energy transition and income inequality: The moderating effect of institutional transparency

Wang,

Yang,

2024

Sustainable Development

View full text Add to dashboard Cite

The emergence of the United Nations' Sustainable Development Goals has instigated a transformative phase in policy formulation, emphasizing the multifaceted approach required to attain these objectives. Central to this pursuit is the management of diverse goals and their intricate interactions. This paper rigorously examines the pivotal role of institutional transparency in the nexus between energy transition and income inequality across 127 countries from 2012 to 2020, within the framework of the Sustainable Development Goals. The estimated results from the non‐balanced panel threshold model suggest the existence of a threshold effect of institutional transparency in the impact of energy transition on income inequality. On the whole, the process of energy transition has had a detrimental effect on income inequality, with institutional transparency serving to moderate it. When institutional transparency falls within the first regime (lnCPI ≤3.3322), the second regime (3.3322 < lnCPI <4.3041), and the third regime (lnCPI >4.3041), a 1% increase in the proportion of renewable energy consumption results in average increases in disposable income inequality of 0.0165%, 0.0143%, and 0.0128%, respectively. This suggests that institutional transparency has a positive moderating effect on the detrimental impact of energy transition on disposable income inequality. However, this result does not hold true for market income inequality. Additionally, there is an “inverted U‐shaped” relationship between economic growth and income inequality, indicating the negative impact of energy transition on income inequality would be offset by its contribution to economic growth.

show abstract

Setting local economic growth targets: does it mitigate nationwide policy uncertainty?

Yang,

Ma,

Pan

2023

Regional Studies

View full text Add to dashboard Cite

The baseline results show that policy uncertainty and growth targets significantly affect company investments, as expected, and that the growth target mediates the relationship between policy uncertainty and investment. However, some omitted factors may influence our findings. Therefore, we conduct some robustness checks.Alternative EPU index. In our baseline regression, the uncertainty index is constructed by translating monthly data to quarterly and annual data. We directly convert monthly to annual metrics to check whether the method impacts our results. Specifically, each month is given a weight of 1/78, 2/78, ..., and 12/78, and the weighted average policy uncertainty index (EPUB) is calculated. Columns ( 1) and ( 2) of Table A1 report the estimated results using the alternative EPU index. The estimation in column (1) only controls for firm and year fixed effects, while column (2) adds firm-and city-level control variables. The two columns consistently show that the interaction term coefficient remains positive and statistically significant at the 1% level, thus suggesting that employing multiple ways to generate the yearly EPU index has a negligible effect on the main outcome.Furthermore, reconstruct China's EPU index using mainland Chinese newspapers. We also use their uncertainty indices to double-check the baseline results and employ the same method to convert the monthly to the yearly metric. EPUH1 is a step-by-step calculation, whereas EPUH2 is the weighted average of the monthly indices. The results in columns (3)-( 6) of Appendix Table A1 using the new metrics reveal that with or without control variable specifications, the estimated interaction term coefficient is positive and statistically significant at the 1% level. Moreover, in our preferred specification with control variables, the magnitude of the key coefficient is similar to that in the baseline results, suggesting that various methods for measuring policy uncertainty have a minimal impact on our major conclusions.Alternative measurements of the dependent variable. We employ total assets to normalise investment in our baseline model, which captures the effects on the relative level of investment. Here, we also examine the impact on the absolute level of investment, that is, the natural logarithm of the net value of fixed assets. Columns (1) and (2) of Table A2 report

show abstract

Does political decentralization affect income inequality? The role of governance quality

Cited by 10 publications

References 81 publications

A Revisit to Political Institutions and Inequality

A Revisit to Political Institutions and Inequality

Bridging energy transition and income inequality: The moderating effect of institutional transparency

Setting local economic growth targets: does it mitigate nationwide policy uncertainty?

Contact Info

Product

Resources

About