arin dube presentation on minimum wage policies in the us
TRANSCRIPT
Arindrajit Dube
Department of Economics
University of Massachusetts Amherst,
and IZA
Resolution Foundation, UK
March 4, 2015
Minimum Wage Policies in the US: Past Lessons and Future Directions
2Arindrajit Dube Department of Economics (UMass Amherst) IZA
Why study the U.S. minimum wages?
U.S. minimum wage setting is a total mess
• Oh, but what a great mess it is!
We have tons of different minimum wages
• “Quasi experimental variation”
• BUT … they’re not random
• Have to devise clever ways of deciphering causal effects –it’s fun being a labor economist in U.S.!
Enacting city-wide minimum wages in metro areas
• New feature in developed countries
• Substantially higher levels of minimum wage (50-60% median FT wage)
3Arindrajit Dube Department of Economics (UMass Amherst) IZA
Ratio of US federal minimum to median wage of FT workers: 1960- 2012
4Arindrajit Dube Department of Economics (UMass Amherst) IZA
States and cities step in with federal inaction
Number of states withminimum wages higher
than the federal level
Number of cities with minimum wage laws
0
5
10
15
20
25
30
35
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
29
14
5Arindrajit Dube Department of Economics (UMass Amherst) IZA
Min. wages in 2015, and ratio to median FT wage
0%
10%
20%
30%
40%
50%
$0
$2
$4
$6
$8
$10
South
Dakota
Verm
ont
Nevada
Califo
rnia
Okla
hom
a
Arizona
Ohio
Rhode I
sla
nd
Kentu
cky
Louis
iana
New
York
Mis
souri
Illinois
New
Mexic
o
Ala
ska
Ala
bam
a
Kansas
Georg
ia
Colo
rado
Uta
h
New
Jers
ey
Wis
consin
Min
nesota
Massachusett
s
Mary
land
Virgin
ia
Minimum wage Ratio of minimum to median wageSources: American Community Survey Data; state/fed MW from NCSL
6Arindrajit Dube Department of Economics (UMass Amherst) IZA
Challenges in identifying causal effects
Starting in early 1990s, use of variation across states
Pioneered by Neumark and Wascher (1992)
Problem: states raising minimum wages
systematically different
Assumption of “parallel trends” across not tenable
Minimum wage “effects” often occur prior to policy
implementation
7Arindrajit Dube Department of Economics (UMass Amherst) IZA
Generalizing the case study approach
Card and Krueger (1994, 2000) case study of NJ/PA
– leveraging proximity
Dube Lester and Reich (2010, Review of Economics
and Statistics) All pairs of contiguous counties straddling state borders
(“border discontinuity”)
UI-based payroll data on restaurant employment from
1990-2006
Dube Lester and Reich (2014, Journal of Labor
Economics, forthcoming) Additionally study young workers
Additionally look at hires and separations (turnover)
8Arindrajit Dube Department of Economics (UMass Amherst) IZA
Research design: comparing contiguous border counties
! 60!
Figure A1 Map of Contiguous Border Pairs
County pair centroids no more than 75 miles apartMinimum wage differenceNo difference County pair centroids more than 75 miles apartMinimum wage differenceNo difference Not in either sample
Source: Dube, Lester Reich (2014)
9Arindrajit Dube Department of Economics (UMass Amherst) IZA
Impact of a 10% increase in the minimum wage:
Restaurant Sector
Average earnings 2.0%*
Prices 0.7%*
Employment 0.1%
Turnover rate 2.1%*
Teens
Average earnings 2.2%*
Employment 0.6%
Turnover rate 2.0%*
Sources: Aaronson (2001); Dube, Lester Reich (2010, 2014)
10Arindrajit Dube Department of Economics (UMass Amherst) IZA
Ongoing controversy?
Not much disagreement that employment effect in the restaurant sector is small
• Neumark, Salas and Wascher (2014) “matching estimator”
• Totty (2014)
• Addison, Blackburn and Cotti (20
• Dube, Lester and Reich (2010, 2014)
Bigger disagreement – teens (e.g., Neumark, Salas and Wascher 2014)
• Shrinking share of minimum wage workers
• Weight of studies that account for non-random selection find small effects
11Arindrajit Dube Department of Economics (UMass Amherst) IZA
Absorbing a wage increase
Price increases are important channel of absorption
Turnover reduction is sizable
• Workers tend to stay in jobs longer
• Indicative of “search frictions” mattering
• Lower cost of replacement
• Higher incentive for training
Early evidence on reallocation across firms (from low to high productivity)
12Arindrajit Dube Department of Economics (UMass Amherst) IZA
Impact of a 10% increase in the minimum wage:
Family Income (all non-elderly)
10th pctile income 3.2%*
Poverty rate 2.4%*
SNAP enrollment 2.4%*
Poverty rate net of tax credits
and transfers:
2.0%*
Sources: Dube (2014); Reich and West (2014).
Statistical significance at 5% level indicated by *
13Arindrajit Dube Department of Economics (UMass Amherst) IZA
But…how high? Organizing for city-wide standards
14Arindrajit Dube Department of Economics (UMass Amherst) IZA
City-wide policies – nature of urbanization
Increasingly urban
Cities are increasingly more unequal
• Between each other
• Within themselves – especially high wage cities
• Increased job polarization - professional and service workers
High wage cities are also high cost-of-living cities
• Especially for those at the bottom
15Arindrajit Dube Department of Economics (UMass Amherst) IZA
0%
10%
20%
30%
40%
50%
60%
$0
$2
$4
$6
$8
$10
$12
$14
$16
Min
imu
m t
o M
ed
ian
Wag
e R
ati
o
Min
imu
m W
ag
e (
20
15
$)
City Minimum wage State Minimum wage
Min-to-Median Ratio
Biggest metro areas: Minimum Wages
Sources: American Community Survey Data; state/fed MW from NCSL; city MW from UC Berkeley CLRE. Assumes a
2.5% inflation rate for converting future wages to 2015$
16Arindrajit Dube Department of Economics (UMass Amherst) IZA
Characteristics of three city minimum wages
Sources:
San Francisco - Reich, Jacobs, Bernhardt and Perry (2014)
San Diego - Reich, Jacobs, Bernhardt and Perry (2014)
Seattle - Klawitter, Long, Plotnick (2014)
17Arindrajit Dube Department of Economics (UMass Amherst) IZA
Raising city minimums up to 60% of median FT wage
Potentials for larger job losses
Somewhat outside of our knowledge base
• Our cross border evidence from 35-55 percent of median
• Limited understanding of heterogeneity and nonlinearity of effects (best evidence: Zipperer 2014)
Movement across city borders
• To date, very limited evidence of such movement
Coordination across cities within metro area
• Jurisdictional coordination in San Fran. and Wash. DC areas.
Automation – robots!
• iPad use in McDonald’s
18Arindrajit Dube Department of Economics (UMass Amherst) IZA
Raising city minimums up to 60% of median FT wage
Potentials for offsets
Mitigate wage polarization in cities
Price adjustment – likely easier in highly polarized cities
Allow more low-wage workers to live within city
• Increase demand for services from wage hikes
• Neighborhood effects
Move towards high-training/low-turnover model
• Evidence suggesting movement from low to high productivity firms (Aaronson et al. 2014)
• Limitation: turnover reductions will diminish at higher minimum wage levels