Abstract
Regulation of the banking and finance industry may lead to a more equal distribution of income if regulators pursue goals in the public interest. Alternatively, the economic theory of regulation predicts that regulatory and supervisory processes may be captured by the banking industry, leading to policies that promote the industry’s interests. The liberalization of the banking and finance sector since the 1980s has produced more intense banking supervision and prudential regulation. In this study we find that banking supervision regulation is associated with greater income inequality. These findings are consistent with the economic theory of regulation. We interpret these results as evidence that regulatory capture in the banking and finance industry can have pernicious effects on the distribution of income.
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Notes
Financial development refers to financial outcomes, such as more credit and greater access to financial products, associated with a functioning financial sector that provides financial and banking services. Financial liberalization refers to changes that reduce or reform those policies.
A few theoretical reasons support this conclusion, all of which stem from the fact that individuals with higher incomes might very well be more effective competitors in the market for regulation. First, higher-income individuals will, owing to their access to better educational opportunities, face lower information costs to understand the effects of various regulatory measures on their wealth. Second, owing to shared educational, social and cultural networks, interest groups consisting of richer individuals will confront lower costs of organizing to pursue their collective political goals. And, third, given their greater political connectedness, especially owing to greater access to the revolving door between regulatory agencies and various industries, such groups will incur lower transaction costs in negotiating with those in power. See Holcombe (2015) for an extension of public choice theory to the analysis of the effects of the regulatory market on the distribution of income.
Mishkin (2002) describes the passage of FDICIA in 1991, putting it in the context of political economy reasoning.
Borenstein and Bushnell (2015) describe the deregulation and the re-regulation of the electricity industry.
See Sect. 4 for a full description of the financial liberalization measures.
“[T]his is the only one [component] where a greater degree of government intervention is coded as a reform” (Abiad, et al. 2010).
Countries with a less clearly defined supervisory agency, including cases wherein the bank supervisor must obtain approval from multiple agencies, receive lower scores.
The SWIID estimates missing values through model-based multiple imputation (Solt 2009). The multiple imputation technique accounts for different degrees of confidence in inequality estimates by reporting 100 imputations for each country year of inequality. See Solt (2009) for a description of the standardization procedures. Empirical modeling with multiply imputed data involves estimating a model for each imputation and then averaging point estimates and standard errors for final interpretation.
Standard errors are clustered at the country level.
If data from the Abiad et al. index are missing for some of the five-year periods, the average is calculated using the available data.
The Gini coefficient series may be non-stationary which would also lead to spurious correlations. Christopoulos and McAdams (2017) test the stationarity of both the net and the gross Gini coefficient. In a set of unconditional panel unit root tests, they fail to reject the presence of a unit root at the 1% and the 5% level but reject the null at the 10% level. Once they account for structural breaks and covariates, they conclude that “there is very weak evidence in favor of the rejection of the null unit root hypothesis for the Gross inequality index while the evidence in favor of the stationary process is stronger for the Net inequality index.”
These results regarding stationarity are somewhat inconclusive. As such we re-estimate Eq. 1 in first differences to ensure the series is stationary, the results are described in footnote 16 in Sect. 5.2.
The market Gini coefficient rose by approximately nine points, whereas the net Gini coefficient increased by about six points.
We also conduct a robustness check estimated with fixed effects in which changes in the Gini coefficient are regressed on the lagged differences in banking supervision regulations and in financial liberalization. That check yields positive, but insignificant coefficient estimates for both variables. If estimated with random effects, banking supervision rules are positive and significant at the 10% level, whereas financial liberalization is statistically insignificant.
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Manish, G.P., O’Reilly, C. Banking regulation, regulatory capture and inequality. Public Choice 180, 145–164 (2019). https://doi.org/10.1007/s11127-018-0501-0
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DOI: https://doi.org/10.1007/s11127-018-0501-0