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Transcript of Centre for Economic Performance Lionel Robbins Memorial Lectures … · 2017-07-11 · Centre for...
Centre for Economic Performance Lionel Robbins Memorial
Lectures
Policies to Improve Upward Mobility
Professor Raj Chetty
Professor of Economics, Stanford University
Hashtag for Twitter users: #LSERobbins
Professor Robin Burgess
Chair, LSE
Raj Chetty
Stanford University
Improving Equality of Opportunity New Lessons from Big Data
Lecture 2: Policies to Improve Upward Mobility
Photo Credit: Florida Atlantic University
Note: Lighter Color = More Upward Mobility
Download Statistics for Your Area at www.equality-of-opportunity.org
The Geography of Upward Mobility in the United States
Probability of Reaching the Top Fifth Starting from the Bottom Fifth
How can we improve social mobility in areas with low rates of mobility?
Focus on two of the correlations identified in the last lecture
1. Segregation
2. School Quality
3. Income Inequality
4. Family Structure
5. Social Capital
Improving Social Mobility: Two Policy Questions
How can we improve social mobility in areas with low rates of mobility?
Focus on two of the correlations identified in the last lecture
1. Segregation
2. School Quality
3. Income Inequality
4. Family Structure
5. Social Capital
Improving Social Mobility: Two Policy Questions
Lecture 2 Outline
1. Segregation and Housing Policy
2. Education Policy
Lecture 2 is based primarily on two sets of papers:
1. Chetty, Hendren, Katz. “The Long-Term Effects of Exposure to Better
Neighborhoods: New Evidence from the Moving to Opportunity Experiment”
AER 2016.
2. Chetty, Friedman, Rockoff. “Measuring the Impacts of Teachers I and II”
AER 2014a,b
Many potential policies to try to promote integration:
– Subsidized housing vouchers to rent better apartments
– Mixed-income affordable housing developments
– Changes in zoning regulations and building restictions
Are such housing policies effective in increasing social mobility?
Standard economic theory actually predicts that cash grants of an
equivalent dollar amount are better
Segregation and Affordable Housing Policies
Understanding effects of housing policies on mobility is of particular
interest given the amount governments spend on such policies
U.S. spends $45 billion per year on housing vouchers, tax credits for
developers, and public housing
Are these policies effective, and how can they be better designed if
one wishes to improve social mobility?
Segregation and Affordable Housing Policies
Begin with an empirical analysis of the effectiveness of housing
voucher subsidies
Moving to Opportunity Experiment implemented from 1994-1998
4,600 families at 5 sites: Baltimore, Boston, Chicago, LA, New York
Families randomly assigned to one of three groups:
1. Experimental: housing vouchers restricted to low-poverty (<10%)
Census tracts
2. Section 8: conventional housing vouchers, no restrictions
3. Control: public housing in high-poverty (50% at baseline) areas
Moving to Opportunity Experiment
Control
ML King
Towers
Harlem
Experimental
Wakefield
Bronx
Common MTO Residential Locations in New York
Section 8
Soundview
Bronx
MTO Experiment: Exposure Effects?
Prior research on MTO has found little impact of moving to a better
area on economic outcomes such as earnings
– But has focused on adults and older youth at point of move [e.g., Kling, Liebman, and Katz 2007]
We test for exposure effects among children
– Does MTO improve outcomes for children who moved when
young?
– Link MTO to tax data to study children’s outcomes in mid 20’s
(a) Earnings (b) College Attendance
Impacts of MTO on Children Below Age 13 at Random Assignment
50
00
7
00
0
90
00
11
00
0
13
00
0
15
00
0
17
00
0
0
5
10
1
5
20
2
5
$11,270 $12,994 $14,747 16.5% 18.0% 21.7%
p = 0.014 p = 0.101 p = 0.435 p = 0.028
Control Section 8
Control Section 8
Experimental
Voucher
Experimental
Voucher
Indiv
idual E
arn
ings a
t A
ge ≥
24 (
$)
Colle
ge A
tten
dance, A
ges 1
8-2
0 (
%)
(c) Neighborhood Quality (d) Fraction Single Mothers
Impacts of MTO on Children Below Age 13 at Random Assignment
15
1
7
19
2
1
23
2
5
0
12
.5
25
3
7.5
23.8% 21.7% 20.4% 33.0% 31.0% 23.0%
p = 0.007 p = 0.046 p = 0.610 p = 0.042
Control Section 8
Control Section 8
Experimental
Voucher
Experimental
Voucher
Zip
Povert
y S
hare
(%
)
Bir
th w
ith n
o F
ath
er
Pre
sent
(%)
Impacts of MTO on Children Age 13-18 at Random Assignment
(a) Earnings
50
00
7
00
0
90
00
11
00
0
13
00
0
15
00
0
17
00
0
$15,882 $13,830 $13,455
p = 0.259 p = 0.219
Control Section 8
Experimental
Voucher
Indiv
idual E
arn
ings a
t A
ge ≥
24 (
$)
(b) Fraction Single Mothers
0
12
.5
25
3
7.5
5
0
62
.5
41.4% 40.2% 51.8%
p = 0.857 p = 0.238
Control Section 8
Experimental
Voucher B
irth
with n
o F
ath
er
Pre
sent
(%
)
Impacts of Experimental Voucher by Age of Random Assignment
Household Income, Age ≥ 24 ($)
-60
00
-4
00
0
-20
00
0
2
00
0
40
00
Exp
erim
en
tal V
s.
Co
ntr
ol IT
T o
n I
nco
me
($
)
10 12 14 16 Age at Random Assignment
Impacts of Moving to Opportunity on Adults’ Earnings
50
00
7
00
0
90
00
11
00
0
13
00
0
15
00
0
17
00
0
Indiv
idual E
arn
ings a
t A
ge ≥
24 (
$)
Control Section 8 Experimental
Voucher
$14,381 $14,778 $13,647
p = 0.569 p = 0.711
Housing vouchers can be very effective but must be targeted carefully
1. Vouchers should be targeted at families with young children
– Current U.S. policy of putting families on waitlists is especially
inefficient
Implications for Housing Voucher Policy
Housing vouchers can be very effective but must be targeted carefully
1. Vouchers should be targeted at families with young children
2. Vouchers should explicitly encourage families to move to affordable,
high-opportunity areas (opportunity bargains)
– In MTO experiment, unrestricted “Section 8” vouchers produced
smaller gains even though families could have made same moves
– Low-income families rarely use cash transfers to move to better
neighborhoods [Jacob et al. QJE 2015]
– These results suggest that behavioral biases may be important in
understanding housing choices [Chetty AER 2015]
Implications for Housing Voucher Policy
1. Costs: areas that offer better opportunity tend to be more expensive
• There are many opportunity bargains: areas with relatively low
rents that offer good opportunities for kids
Integration through Housing Vouchers: Potential Concerns
Soundview
Wakefield
Park Slope
East Midwood
Rockaway Park
MLK Towers
(Harlem)
-30
-2
0
-10
0
1
0
20
Oppo
rtu
nity I
nde
x:
Effect o
n C
hild
’s E
arn
ing
s (
%)
500 1,000 1,500 2,000
Average Monthly Rent in ZIP Code ($)
Opportunity Bargains at the ZIP Code Level in the New York Area
1. Costs: areas that offer better opportunity tend to be more expensive
• There are many opportunity bargains: areas with relatively low
rents that offer good opportunities for kids
• Vouchers can save taxpayers money relative to public housing
projects in long run
Integration through Housing Vouchers: Potential Concerns
Impacts of MTO on Annual Income Tax Revenue in Adulthood
for Children Below Age 13 at Random Assignment
0
20
0
40
0
60
0
80
0
10
00
1
20
0
Annu
al In
com
e T
ax R
evenue, A
ge ≥
24 (
$)
$447.5 $616.6 $841.1
p = 0.061 p = 0.004
Control Section 8 Experimental
Voucher
1. Costs: areas that offer better opportunity tend to be more expensive
2. Negative spillovers: does integration hurt the rich?
• Empirically, more integrated neighborhoods do not have worse
outcomes for the rich
Integration through Housing Vouchers: Potential Concerns
Salt Lake City Charlotte
20
3
0
40
5
0
60
7
0
0 20 40 60 80 100
Parent Percentile in National Income Distribution
Ch
ild P
erc
entile
in N
ation
al In
com
e D
istr
ibu
tion
Intergenerational Mobility in Salt Lake City vs. Charlotte
1. Costs: areas that offer better opportunity tend to be more expensive
2. Negative spillovers: does integration hurt the rich?
3. Limits to scalability: general equilibrium effects
• Moving everyone in Harlem to Bronx is unlikely to have significant
effects
• Ultimately need to turn to policies that increase integration in other
ways rather than moving low-income families
Integration through Housing Vouchers: Potential Concerns
A variety of other policies could potentially increase residential housing
integration
– Providing tax credits to encourage building affordable properties in
higher-income neighborhoods
– Retaining housing options for low and middle income families as
city centers gentrify
– Improved urban planning, e.g. changes in zoning regulations and
transportation
– Investing in local public infrastructure, such as schools
Place-Based Approaches to Integration
Improving school quality is one widely discussed approach to
improving children’s outcomes
But simply spending more on schools may not be enough
[Hanushek 2001]
– U.S. spends more than most other developed countries on
education, yet has significantly worse outcomes
Need to understand which educational inputs matter most for
children’s long-term success: class size, teachers, resources?
– Each of these has been studied in detail in recent work; focus
here on teachers as an example
Education Policy
Tax records
Earnings, College Attendance, Teen Birth
Using Big Data to Study Teachers’ Impacts
School district records
2.5 million children
18 million test scores
One prominent measure of teacher quality: teacher value-added
Measuring Teacher Quality: Test-Score Based Metrics
How much does a teacher raise her/his students’ test scores on average?
50
52
54
56
‘93 ‘94 ‘95 ‘96 ‘97 ‘98
Scores in 4th Grade Scores in 3rd Grade
School Year
Avera
ge T
est S
core
Entry of Teacher
with VA in top 5%
A Quasi-Experiment: Entry of High Value-Added Teacher
51
52
53
54
55
‘93 ‘94 ‘95 ‘96 ‘97 ‘98
Scores in 4th Grade Scores in 3rd Grade
School Year
Avera
ge T
est S
core
Entry of Teacher
with VA in bottom 5%
A Quasi-Experiment: Entry of Low Value-Added Teacher
50
36.0%
36.5%
37.0%
37.5%
38.0%
38.5%
5th Median 95th
Attendin
g C
olle
ge a
t A
ge 2
0
Effect of Teacher Quality on College Attendance Rates
Teacher Quality (Value-Added) Percentile
Teacher Quality (Value-Added) Percentile
Earn
ing
s a
t A
ge 2
8
Effect of Teacher Quality on Earnings
$20.5K
$21.0K
$21.5K
$22.0K
5th Median 95th
12.5%
13.0%
13.5%
14.0%
14.5%
5th Median 95th
Wom
en
with T
ee
na
ge
Birth
s
Effect on Teacher Quality on Teenage Birth Rates
Teacher Quality (Value-Added) Percentile
+$50,000 lifetime earnings per child = $1.4 million per classroom of 28
students
= $250,000 in present value at 5% int.
rate
Teacher Quality (Value-Added) Percentile
5th 95th Media
n
The Value of Improving Teacher Quality
Improving quality of elementary education can be a key
policy tool to increase upward mobility
– Teacher quality appears to be particularly important,
perhaps more so than reductions in class size
– Better teachers have roughly the same effect on long-
term outcomes from grades K-8
Education: Policy Lessons
Critical to attract and retain top talent in teaching in
primary school
– Superstar model: reward and retain talented teachers
– Higher salaries can help but ultimately may require
efforts to change professional status (e.g., Finland)
– Programs such as Teach First have been successful but
would be more effective if teachers stay
Education: Policy Lessons
“We know a good teacher can increase
the lifetime income of a classroom by
over $250,000.... Every person in this
chamber can point to a teacher who
changed the trajectory of their lives”
- Barack Obama, State of the Union,
2012
“A recent study by Harvard and Columbia
economists found that students with
effective teachers are less likely to
become pregnant, more likely to go to
college and more likely to get higher-
paying jobs....Ineffective teachers are
hurting our students’ futures – we can’t
allow that.”
- Michael Bloomberg, State of the City,
2012
Policy Impacts
Is Increasing Social Mobility Desirable?
Thus far we have assumed that our objective should be
to increase social mobility
But policies that increase mobility may not be desirable
from an efficiency perspective
– Random allocation of college seats maximizes social mobility
– But violates principles of meritocracy and would likely reduce
total economic output and growth
Tomorrow’s lecture: assess tradeoff between mobility
and growth, focusing on innovation as a driver of growth