Why Has Regional Income Convergence in the U.S. Declined? Peter - PowerPoint PPT Presentation

Why Has Regional Income Convergence in the U.S. Declined? Peter Ganong (UChicago) and Daniel Shoag (Harvard) July 2016

Change in Log Income Per Capita 1940-1960, Coef: -.488 SE: .019 2 MS AL AR ND SD OK KY KS NC GA NM NE TN SC LA 1.5 TX CO UT MO IA ID MN WI VA AZ WV IN WY FL NH OR VT MT WA ME OH MI IL PA CA MD NV NJ NY MA CT RI DE 1 5 6 7 Log Income Per Capita, 1940

Change in Log Income Per Capita 1940-1960, Coef: -.488 SE: .019 1990-2010, Coef: -.198 SE: .057 1.4 2 MS AL AR ND SD OK KY KS NC GA NM NE ND TN SC LA WY 1.5 .9 TX SD LA CO MS UT MO IA MT ID MN WI AR VT VA AZ NM MA WV WV NE IN OK UT TX IA KS CO MN VA WA MD NH AL WY ME WI RI FL KY TN MO NJ PA CT NH OR ID AZ VT SC NY NC OR MT WA IL CA ME OH GA MI FL IL IN OH PA DE MI NV CA MD NV NJ NY MA CT RI DE .4 1 5 6 7 9.4 10.2 Log Income Per Capita, 1940 Log Income Per Capita, 1990

Timeseries of Coefficients - Convergence 0 -.2 -.4 -.6 1950 1980 2010 Coef: dInc = b*inc_t-20

Change in Log Population 1940-1960, Coef: .33 SE: .07 1 AZ FL NV CA NM MD DE .5 WA UT OR CO TX CT MI VA NJ OH LA IN WY ID NC IL GA SC WI NY NH MN TN KS MT MA RI AL ME MO PA IA NE VT KY SD 0 MS OK ND WV AR 5 6 7 Log Income, 1940

Change in Log Population 1940-1960, Coef: .33 SE: .07 1990-2010, Coef: -.09 SE: .12 1 1 AZ FL NV CA Change in Log Population, 1990-2010 NV NM MD DE AZ .5 WA UT OR .5 CO UT TX CT MI ID VA NJ CO GA OH TX LA IN FL NC WY WA ID NC IL NM GA SC WI OR DE NY SC NH MN TN KS MT TN VA MA RI CA AR MT WY AL ME MO PA MN MD OK AL NH KY IA SD IN MO NE WI VT MS NE KS KY SD NJ IL VT IA 0 MS OK MA CT ME ND LA NY PA ND OH MI WV RI WV AR 0 5 6 7 9.4 10.2 Log Income, 1940 Log Income, 1990

Timeseries of Coefficients - Convergence and Pop .4 .2 0 -.2 -.4 -.6 1950 1980 2010 Coef: dInc = b*inc_t-20 Coef: dPop = b*inc_t-20

Timeseries of Coefficients - Convergence and Pop .4 .2 0 -.2 -.4 -.6 1950 1980 2010 Coef: dInc = b*inc_t-20 Coef: dPop = b*inc_t-20

Timeseries of Coefficients - Convergence and Pop .4 .2 0 -.2 -.4 -.6 1950 1980 2010 Coef: dInc = b*inc_t-20 Coef: dPop = b*inc_t-20

Outline 1 Facts About Housing Prices 2 How Does Housing Supply Affect Convergence? New Measure of Supply Restrictions

Outline 1 Facts About Housing Prices ◮ Differences in Housing Prices Have Grown Relative to Differences in Incomes ◮ Housing Prices Have Lowered the Returns to Living in Productive Places For Unskilled Workers ◮ Migration Flows Respond to Skill-Specific Gains Net of Housing Prices 2 How Does Housing Supply Affect Convergence? New Measure of Supply Restrictions

Differences in Housing Prices 1960, Coef: .95 SE: .08 2010, Coef: 2.04 SE: .25 12 CA 13 CT NJ MA NJ NY CA NV MD Log Housing Value, 1960 IL Log Housing Value, 2010 MA NY CT OH 11.5 RI MN WA NV UT WI DE RI WY CO 12.5 MI MD FL WA NH VA OR AZ DE CO MT MO VA LA NM ID NH OR AZ IN PA FL IA UT MN ND VT VT IL GA NE KS KY SD ME TX AL ME TN ID NC WI WY MS OK MT 11 GA 12 WV SC PA NM MI NC AR OH MO SC TN LA IN NE TX KS IA SD KY AL ND OK 11.5 AR 10.5 MS WV 9.2 9.4 9.6 9.8 10 10.3 10.5 10.7 10.9 11.1 Log Income Per Cap, 1960 Log Income Per Cap, 2010

Changes in Returns to Migration Effect of $1 of Statewide Inc on Skill-Specific Inc Net of Housing 1.5 Unskilled HH Skilled HH 1 Coef .5 0 1940 1960 1970 1980 1990 2000 2010

Migration Flows – 2000 Low Skill Coef: -2.17 SE: 1.00 High Skill Coef: 4.07 SE: .69 8 8 Net Migration as % Pop Net Migration as % Pop 4 4 0 0 -4 -4 10.8 11 11.2 11.4 11.6 11.8 10.8 11 11.2 11.4 11.6 11.8 Log Nominal Income Log Nominal Income Low Skill Coef: 4.30 SE: 2.00 High Skill Coef: 4.71 SE: .89 8 8 Net Migration as % Pop Net Migration as % Pop 4 4 0 0 -4 -4 10.4 10.6 10.8 11 11.2 11 11.2 11.4 11.6 11.8 Log (Inc-Housing Cost) for Low Skill Log (Inc-Housing Cost) for High Skill

Outline 1 Facts About Housing Prices 2 How Does Housing Supply Affect Convergence? New Measure of Supply Restrictions

A New Regulation Measure Construction ◮ Number of hits per capita from state appeals courts for “land use” ◮ Omnibus measure. Captures many different anti-development tactics. Properties ◮ correlated with cross-sectional measures ⋆ American Institute of Planners, 1975 ⋆ Wharton Residential Land Use Regulatory Index, 2005 ◮ correlated with prices, conditional on state and year fixed effects Look at patterns separately for low elasticity and high elasticity states

Land Use Cases Per Million People 3 Cases Per Million People 2 1 0 1940 1950 1960 1970 1980 1990 2000 2010

How Regulations Affect Convergence The previous graphs split states at the median within each year. We can instead exploit the regulation measure to fix a cutoff level of regulation. Reg s , t = Percentile { LandUseCases st } Pop st Y s , t = α t + α t Reg s , t + β Inc s , t + β high reg Inc i , t − 1 × Reg s , t + ε s , t Dependent variables: log housing prices, population, human capital (growth accounting measure from a Mincerian regression), and income.

How Regulations Affect Convergence ln p house Dep Var d ln pop d ln HumanCapital d ln Inc Log Income 0.77*** (0.11) Log Income 0.83*** *Reg (0.26) N 384 Indicators for Year and Year*Reg in all specifications.

How Regulations Affect Convergence ln p house Dep Var d ln pop d ln HumanCapital d ln Inc Log Income 0.77*** 1.69** (0.11) (0.64) Log Income 0.83*** -1.88*** *Reg (0.26) (0.61) N 384 2,448 Indicators for Year and Year*Reg in all specifications.

How Regulations Affect Convergence ln p house Dep Var d ln pop d ln HumanCapital d ln Inc Log Income 0.77*** 1.69** -0.043*** (0.11) (0.64) (0.007) Log Income 0.83*** -1.88*** 0.040** *Reg (0.26) (0.61) (0.016) N 384 2,448 288 Indicators for Year and Year*Reg in all specifications.

How Regulations Affect Convergence ln p house Dep Var d ln pop d ln HumanCapital d ln Inc Log Income 0.77*** 1.69** -0.043*** -2.03*** (0.11) (0.64) (0.007) (0.10) Log Income 0.83*** -1.88*** 0.040** 1.30*** *Reg (0.26) (0.61) (0.016) (0.39) N 384 2,448 288 2,448 Indicators for Year and Year*Reg in all specifications.

Regime One ln p house Dep Var d ln pop d ln HumanCapital d ln Inc Log Income 0.77*** 1.69** -0.043*** -2.03*** (0.11) (0.64) (0.007) (0.10) Log Income 0.83*** -1.88*** 0.040** 1.30*** *Reg (0.26) (0.61) (0.016) (0.39) N 384 2,448 288 2,448 Indicators for Year and Year*Reg in all specifications.

Regime Two ln p house Dep Var d ln pop d ln HumanCapital d ln Inc Log Income 0.77*** 1.69** -0.043*** -2.03*** (0.11) (0.64) (0.007) (0.10) Log Income 0.83*** -1.88*** 0.040** 1.30*** *Reg (0.26) (0.61) (0.016) (0.39) N 384 2,448 288 2,448 Indicators for Year and Year*Reg in all specifications.

Omitted Variable Bias More generally, could there be a post-1980 shock that raised regulation levels and lowered convergence? Use pre-1980 measures of housing supply elasticity

Omitted Variable Bias Dep Var: Log Income Per Cap t - Log Income Per Cap t-20 Constraint: Regs in 2005 Regs in 1965 Buildable Land Pre Post Pre Post Pre Post Log Income -1.93*** -1.80*** -2.05*** -1.97*** -2.49*** -1.20*** (0.11) (0.33) (0.15) (0.47) (0.06) (0.08) Log Income 0.22 2.01*** 0.20 1.91*** -0.09 0.71*** *Constraint (0.27) (0.66) (0.27) (0.69) (0.10) (0.17) N 1,248 1,200 1,248 1,200 8,413 9,194 Geo State State State State County County Indicators for Year and Year*Constraint in all specifications.

Conclusion Weakening of directed migration and convergence in last 30 years Directed migration drove convergence: ◮ Regional labor markets clear through skill-sorting rather than net migration. Can be explained by supply shifts. ◮ Continued convergence in places with unconstrained supply State-level panel measure for housing regulations. ◮ We are happy to share this with other researchers.

Model Overview Model with multiple skill types, endogenous migration, and potentially restricted housing supply. Proposition 1: Directed migration drives convergence Proposition 2: Housing prices affect migration differently by skill level Substantive Expositional Y = AL 1 − α Regional labor demand is downward sloping U = c β ( h − H ) 1 − β Land is an Inferior Good within a City Migration is Costly

Simulation Reg ↑ Begins Reg ↑ Complete Mig Rate from South to North (Unanticipated) (Skilled & Unskilled) Rate of Convergence / Migration Mig Rate (Skilled) 0 Mig Rate (Unskilled) Income Convergence Rate t 0 t 1 t 2 Time