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) 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 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 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 Time State Deregulation National technological changes weakens local branch monopoly

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 Difference-in-difference estimation Log(Gini) i,t =  i +  t +  Deregulation i,t +  X i,t +  i,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 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 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

Branch Deregulation and Income Distribution – Statistical effect

Timing and effects Time State Deregulation National technological changes weakens local branch monopoly

Branch Deregulation and Income Distribution – Economic effect Coefficient: Within-state, within-time standard deviation of log of Gini0.034 Branching deregulation explains 40% of variation of log Gini relative to state and year averages.

Branch Deregulation and Income Distribution by Type of Income

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