Competitive Effects of Means-Tested School Vouchers

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Competitive Effects of Means-Tested School Vouchers David Figlio, Northwestern and NBER Cassandra Hart, Northwestern December 2009

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Competitive Effects of Means-Tested School Vouchers. David Figlio , Northwestern and NBER Cassandra Hart, Northwestern December 2009. Introduction. School choice options have become increasingly prevalent in recent years - PowerPoint PPT Presentation

Transcript of Competitive Effects of Means-Tested School Vouchers

Page 1: Competitive Effects of  Means-Tested School Vouchers

Competitive Effects of Means-Tested School Vouchers

David Figlio, Northwestern and NBERCassandra Hart, Northwestern

December 2009

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Introduction• School choice options have become increasingly

prevalent in recent years• Considerable attention paid to potential competitive

effects of choice, both positive (efficiency) and negative (cream-skimming)

• Challenging to gauge competitive effects because of interrelationship between private school supply and public school performance

• Prior literature: cross-sectional studies of private school penetration in US and international; Milwaukee vouchers; Florida school grades; Sweden voucher program introduction; Chile voucher cross-section

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This paper

• Study introduction of large new school voucher program; use introduction of this program as source of plausibly exogenous variation that increased demand for private school options after 2001

• Look at quantity and variety of nearby private school options in year prior to program announcement, which could generate variation in access to the program

• Florida is large and varied in its pre-program private school supply

• Identifying off of a policy change; use student data from 99-00 through 06-07

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How vouchers might affect public schools

• Competition effect• Composition effect• Resource effect

• First year of program was before any students left the public schools – but were applying

• Work in progress: still trying to tease out three effects in the “mobility” years of the program

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Florida’s Corporate Tax Credit Scholarship Program

• Funded by fully tax creditable corporate contributions to one of three Scholarship Funding Organizations, each with geographic range; total contributions capped by Legislature

• Began with 20,000+ students, now at 27,000+ students• Students below 185% of poverty line and attending

public school in prior year (or entering grades K/1) eligible; renewal requires income below 200% of poverty line

• Initial voucher was $3,500; now, it’s $3,950-$4,100 (around 90% of average “rack rate” religious school tuition/fees in Florida)

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Private school landscape in Florida

• 2000 Census 5% microdata sample: 11.4% of Florida students 6-17 attended private schools; 5.4% of income-eligible students attended private schools

• Large regional variation in private school penetration at MSA level

• Considerable within-MSA variation as well (wait a few slides)

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Regional variation in private school penetration in 2000 Census

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Data

• (Standardized) student test scores, basic demographics from 1999-2000 through 2006-07 from Florida Education Data Warehouse– Developmental scale scores employed, grades 3-10– Exclude students with disabilities (eligible for other

voucher program, McKay Scholarships)

• 9.8M student-year observations; 2.8M students• Private school universe from Florida Dept of Education– Public and private addresses geocoded using ARCGis– Private competitors measured by grade span served

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Empirical approach

• School and time fixed effect models (clustered SE)• Dependent variable: standardized student DSS test

scores, controlling for prior-year test scores when available

• Controls for student characteristics and grade• Policy variable: private school competition (measured

in 2000) x post-policy• “Post-policy” occurs once program is announced• Other models look year-by-year after policy is

announced

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Competition measures

• Physical distance in miles to nearest private school competitor (measured negative)

• Number of private competitors within 5 miles• Number of types of private competitors within 5 miles

– Types (self-identified by schools): non-religious; non-denominational; Catholic; Protestant; Evangelical; Baptist; Islamic; Jewish; “Christian”; other religious

• Herfindahl index of competitor types (1-Herfindahl)• Robust to other radii of competition• Study sample: schools with competitor within 5 miles

(basically the whole state)

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Competition measures #1

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Competition measures #2

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Competition measures #3

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Competition measures #4

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Within-MSA variation

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Within-MSA variation

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Within-MSA variation

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First-year estimates of voucher effects

Competition measure Math estimated effect Reading estimated effect

Distance 0.017***(0.002)

0.015***(0.002)

Density 0.003***(0.000)

0.003***(0.000)

Diversity 0.011***(0.001)

0.011***(0.001)

Concentration 0.069***(0.008)

0.070***(0.007)

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Adding leads of policy variableCompetition measure

Math: first year

Math: lead Reading: first year

Reading: lead

Distance 0.012***(0.003)

-0.006+(0.003)

0.012***(0.002)

-0.004+(0.002)

Density 0.002***(0.000)

-0.001***(0.000)

0.002***(0.000)

-0.000(0.000)

Diversity 0.006***(0.002)

-0.007***(0.002)

0.009***(0.001)

-0.003**(0.001)

Concentration 0.045**(0.015)

-0.033*(0.015)

0.045***(0.012)

-0.034**(0.012)

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Differences by program eligibilityCompetition measure

Math: ineligibles

Math: difference for eligibles

Reading: ineligibles

Reading: difference for eligibles

Distance 0.014***(0.002)

0.008**(0.003)

0.012***(0.002)

0.010***(0.003)

Density 0.003***(0.000)

-0.001*(0.000)

0.003***(0.000)

-0.001**(0.000)

Diversity 0.012***(0.001)

-0.002*(0.001)

0.013***(0.001)

-0.003**(0.001)

Concentration 0.060***(0.009)

0.022*(0.011)

0.060***(0.008)

0.030**(0.010)

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Effects same for poor vs very poorCompetition measure

Math: reduced price lunch

Math: difference for free lunch

Reading: reduced price lunch

Reading: difference for free lunch

Distance 0.023***(0.003)

-0.002(0.003)

0.019***(0.003)

0.001(0.003)

Density 0.003***(0.000)

0.000(0.000)

0.003***(0.000)

-0.000(0.000)

Diversity 0.010***(0.001)

0.001(0.001)

0.012***(0.001)

0.000(0.001)

Concentration 0.088***(0.009)

-0.012(0.010)

0.083***(0.008)

-0.004(0.011)

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Differences by context (reading; distance measure of competition)

Contextual measure

Average class size in school

2000 school grade District has open enrollment

Competition x post-policy

0.032***(0.001)

0.016***(0.003)

0.008***(0.002)

Interaction with class size

-0.001(0.000)

Interaction with "B" grade

0.005(0.006)

Interaction with "C" grade

-0.003(0.004)

Interaction with "D" grade

0.017(0.011)

Interaction with "F" grade

0.222**(0.072)

Interaction with open enrollment

0.014***(0.004)

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Over-time changes in policy effectsComp.measure (pre-policy)

Lead of program(2000-01)

First year(2001-02)

2002-03 2003-04 2004-05 2005-06 2006-07

Distance -0.008+(0.005)

0.010*(0.004)

0.008+(0.004)

0.014***(0.004)

0.023***(0.004)

0.028***(0.004)

0.023***(0.004)

Density -0.002***(0.000)

0.002***(0.000)

0.001***(0.000)

0.002***(0.000)

0.004***(0.000)

0.004***(0.000)

0.004***(0.000)

Diversity -0.008***(0.002)

0.004*(0.002)

0.003(0.002)

0.008***(0.002)

0.013***(0.002)

0.018***(0.002)

0.016***(0.002)

Concen-tration

-0.040+(0.021)

0.036+(0.019)

0.026(0.018)

0.063***(0.018)

0.104***(0.019)

0.131***(0.019)

0.116***(0.019)

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Bigger differences in “mobility” years

• Competition effect?• Resource effect?• Composition effect?

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Evidence of negative selection

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Evidence of negative selection

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Where do students fall in their prior school’s distribution?

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Where do students fall in their prior school’s distribution?

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Distributions by race/ethnicity

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Distributions by race/ethnicity

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Summing up

• Preliminary conclusions• Limitations/generalizability