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Erschienen in:

22.11.2023

Revisiting the effect of bank deregulation on income inequality

verfasst von: William B. Hankins, Anna-Leigh Stone, Gary Hoover

Erschienen in: Empirical Economics | Ausgabe 6/2024

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Abstract

We use recently developed difference-in-differences methodologies and a panel of US states over the period 1960–2015 to examine how bank branching deregulation impacted state-level income inequality. Existing research relying on traditional two-way fixed effects estimates and event studies provide mixed results. However, these results potentially suffer from biases due to treatment effect heterogeneity and the failure to account for multiple related treatments. Using bias-corrected difference-in-differences procedures and properly accounting for the timing of treatment, we find evidence that the combined effect of intrastate and interstate banking deregulation increased the income share of the top 10%, 5%, and 1% of income earners, respectively. Conversely, we find no evidence that intrastate branching deregulation in isolation impacted income inequality.

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Fußnoten
1
The event study design used in Freeman (2002) is of the type used in the corporate finance literature to evaluate the impact of some event on the value of a firm. This is different than another method, also called an event study, or dynamic treatment effect, design that is used to estimate the period-by-period impact of a policy change. The latter design is used in the current paper and has become a staple of the difference-in-differences approach.
 
2
Jayaratne and Strahan (1996) also include dummy variable for both types of deregulation, but do not study income inequality.
 
3
We thank an anonymous reviewer for suggesting the inclusion of government expenditures and the party of the governor as control variables.
 
4
In Appendix A, we address the identifying assumptions from De Chaisemartin and d’Haultfœuille (2023) and explain how our research design satisfies these assumptions. We thank an anonymous referee for this suggestion.
 
5
New Hampshire and Tennessee are also excluded since these states deregulated at both levels in the same year.
 
6
For example, while 28 states are used to estimate the initial effect of implementing interstate deregulation after intrastate deregulation, only 13 states can be used to estimate this effect four years after deregulation. Conversely, in the results that follow 15 states can be used to estimate the effect of intrastate deregulation ten years after adoption. The number of states available to estimate the effect of adopting interstate deregulation first is even smaller, with only 16 states available to estimate the instantaneous effect of adopting interstate deregulation and 2 states available to estimate the effect four years following adoption.
 
8
See Frank (2014) for a more thorough discussion of the creation of these data and the construction of the Gini coefficient and Theil index.
 
10
Given the small number of clusters in the sample using only states in which intrastate deregulation occurred before interstate deregulation, we also estimate p-values using the Wild bootstrap Stata procedure developed by Cameron et al. (2008). This procedure was implemented using the boottest command by Roodman et al. (2019). The p-values produced using this approach did not change our conclusions. These results are available upon request.
 
11
The calculation of treatment effect weights is done using the twowayfeweights Stata command.
 
12
This diagnostic statistic cannot be computed when two treatments are included. See https://​ideas.​repec.​org/​c/​boc/​bocode/​s458611.​html.
 
13
We also conduct this test using regressions without the control variables and reach the same conclusions. These results are available upon request.
 
14
This method can be implemented in Stata using the did_multiplegt command developed by De Chaisemartin, d’Haultfœuille, and Guyonvarch (2019).
 
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Metadaten
Titel
Revisiting the effect of bank deregulation on income inequality
verfasst von
William B. Hankins
Anna-Leigh Stone
Gary Hoover
Publikationsdatum
22.11.2023
Verlag
Springer Berlin Heidelberg
Erschienen in
Empirical Economics / Ausgabe 6/2024
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-023-02527-2

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