Does more finance mean more inequality in times of crisis?

Mathonnat, Clément; Williams, Bruce A.

doi:10.1016/j.ecosys.2020.100818

Cited by 3 publications

(2 citation statements)

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“…There is a vast KC literature that covers many different angles and methodological tools. The effect of the financial system on income inequality has been studied allowing for many control variables with differing results, mostly mixed on the impact of financial openness or financial development, see (Johansson and Wang (2014); Ni and Liu (2019); Hasan et al (2020); Mathonnat and Williams (2020); Brei et al (2023); Kebede et al (2023)).…”

Section: Literature Review Of the Kc And Institutional Quality Nexusmentioning

confidence: 99%

“…The resulting model uncertainty has been recognised in the literature and has been addressed in various degrees by using a BMA approach. The papers below attempt to tackle some of the above concerns, see Hortas-Rico and Rios (2019) Koske and Wanner (2013) Mathonnat and Williams (2020). However, all the above papers have not dealt with the issue of country heterogeneity and its possible effect on institutional quality variable selection as all countries are considered to belong to the same group irrespective of their different economic characteristics.…”

Section: Literature Review Of the Kc And Institutional Quality Nexusmentioning

confidence: 99%

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A Revisit to Political Institutions and Inequality

DENIZ,

Stengos

2023

Preprint

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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.

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