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Bank Regulation and Income Distribution Evidence from Branch Deregulation. Thorsten Beck, Ross Levine and Alexey Levkov. Finance and income inequality – cross-country. Motivation. Does banking sector development benefit the rich or the poor? Greenwood and Jovanovic (1993)

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bank regulation and income distribution evidence from branch deregulation

Bank Regulation and Income DistributionEvidence from Branch Deregulation

Thorsten Beck, Ross Levine and Alexey Levkov

motivation
Motivation
  • Does banking sector development benefit the rich or the poor?
    • Greenwood and Jovanovic (1993)
    • Galor and Zeira (1993), Galor and Moav (2004)
  • Do large banks help the rich and wealthy?
    • Extensive restrictions on banks in most of U.S. history
    • Debate on bank regulation often led in terms of income distribution
  • We use branching deregulation episode to assess impact of financial liberalization in income inequality
branching restrictions
Branching restrictions
  • Until mid-1970s most states restricted the ability of banks to freely branch within states and across states, reducing competition
    • Small banks with local monopolies (Flannery, 1984)
    • Created rents and lobby groups to defend them (White, 1982)
  • Technological progress undermined these restrictions (Kroszner and Strahan, 1999)
    • ATMs
    • Checkable money market mutual funds
    • Communication technology improvements

weakened geographic link between bank and client

branch deregulation
Branch deregulation
  • From mid-1970s until 1994 (Riegle-Neal Act), most states did away within intra- and inter-state branch restrictions
    • Growth accelerated (Jayaratne and Strahan, 1996)
    • Bank efficiency improved (Jayaratne and Strahan, 1998)
    • Rate of new incorporations increased (Black and Strahan, 2002)
    • Volatility decreased (Morgan, Rime and Strahan, 2004)
timing and effects
Timing and effects

National technological changes weakens local branch monopoly

State

Deregulation

Time

our paper
Our paper
  • Did branch deregulation result in an increase or decrease in income inequality as measured by Gini?
  • Cross-country evidence:
    • Beck, Demirguc-Kunt and Levine (2007): Financial development is associated with faster reductions in Gini
    • See also Clarke, Xu and Zhou (2007)
  • Debate on bank restrictions in general:
    • Political debate on bank regulation has been to a large extent about income distribution
    • Do we have to restrain banks from growing too big in order to protect the poor?
our econometric test
Our econometric test

Difference-in-difference estimation

Log(Gini)i,t = ai + bt + gDeregulationi,t + dXi,t + ei,t

  • X = State GSP, Govt. taxes/personal income, govt. expenditure/personal income, college graduates
  • Cluster on state-level
  • Drop observation in year of deregulation
  • Little concerns of endogeneity
  • Deregulation at different times allows to exploit state-time-panel
  • Single policy change - reduce identification and comparability problems often associated with cross-country
data income distribution
Data – income distribution
  • Current Population Survey (CPS)
  • Detailed information on different household income sources
  • Compute Gini across states for each year over 1977 to 2003
  • Compute for total household, total individual income, wage and salary income (male and female), proprietor income
data branch deregulation
Data – branch deregulation
  • Focus on intra-state branching deregulation
    • Allow bank holding companies to convert subsidiaries into branches; allow de-novo branching
  • Data on 48 states and DC
    • Drop Delaware and South Dakota (credit cards)
    • Most states deregulated during sample period
    • 15 states deregulated before 1977
    • Arkansas, Iowa and Minnesota were the last to deregulate
timing and effects12
Timing and effects

National technological changes weakens local branch monopoly

State

Deregulation

Time

branch deregulation and income distribution economic effect
Branch Deregulation and Income Distribution – Economic effect
  • Coefficient: 0.013
  • Within-state, within-time standard deviation of log of Gini 0.034
  • Branching deregulation explains 40% of variation of log Gini relative to state and year averages.
conclusions
Conclusions
  • Branching deregulation
    • Increased growth
    • Reduced income inequality

Pro-poor

  • Strongest effect among female wage and salary earners and proprietors
  • Effect of finance on income inequality seems to go both through labor market and access to credit