Which financial inclusion indicators and dimensions matter for income inequality? A Bayesian model averaging approach

Rogelio Mercado and Victor Pontines

Empirical Economics, 2024, vol. 67, issue 2, No 8, 609-654

Abstract: Abstract This paper employs Bayesian model averaging (BMA) and uses posterior inclusion probability (PIP) values to evaluate which financial inclusion indicators, dimensions, and other determinants of income inequality should be considered in an empirical specification assessing the relationship between financial inclusion and income inequality, given model uncertainty. The results show that for the lower income country group, financial access and usage indicators are the most relevant financial inclusion indicators. For financial inclusion dimension, we find evidence on the importance of financial access. However, the results for upper income country group are different, suggesting the need to differentiate between the two groups in assessing the importance of financial inclusion on income inequality. These results suggest that theoretical models linking financial inclusion and income inequality could well focus on the role of financial access by providing theoretical foundations on the mechanics as to how this dimension of financial inclusion impact income inequality particularly for lower income countries.

Keywords: Bayesian model averaging; Financial inclusion; Income inequality; Bayesian inference (search for similar items in EconPapers)
JEL-codes: C11 C52 O15 O16 (search for similar items in EconPapers)
Date: 2024
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Working Paper: Which Financial Inclusion Indicators and Dimensions Matter for Income Inequality? A Bayesian Model Averaging Approach (2022)
Working Paper: Which Financial Inclusion Indicators and Dimensions Matter for Income Inequality? A Bayesian Model Averaging Approach (2022)
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DOI: 10.1007/s00181-024-02559-2

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