Impact of Voucher Design on Public School Performance: Evidence from Florida and Milwaukee Voucher Programs

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper examines the impact of vouchers in general and voucher design in particular on public school performance. It argues that all voucher programs are not created equal.There are often fundamental differences in voucher designs that affect public school incentives differently and induce different responses from them. It analyzes two voucher programs in the United States. The 1990 Milwaukee experiment can be looked upon as a "voucher shock" program that suddenly made low-income students eligible for vouchers. The 1999 Florida program can be looked upon as a "threat of voucher" program, in which schools getting an "F" grade for the first time are exposed to the threat of vouchers, but do not face vouchers unless and until they get a second "F" within the next three years. In the context of a formal theoretical model, the study argues that the threatened public schools will unambiguously improve under the Florida-type program, and this improvement will exceed that under the Milwaukee-type program. Using school-level scores from Florida and Wisconsin and a difference-in-differences estimation strategy in trends, it then shows that these predictions are validated empirically. These findings are reasonably robust in that they survive sensitivity checks including correcting for mean reversion and a regression discontinuity analysis.

Measuring Competitive Effects From School Voucher Programs: A Systematic Review

“…The same data later appeared in a 2008 publication by Chakrabarti reviewed by Forster that more thoroughly answers the competitive effects question alluded to in the short 2004 segment (Chakrabarti, 2008a). The second reason I report fewer Florida estimates than Forster is because he counts Chakrabarti (2007), which has since been published and is referred to in this article as Chakrabarti (2012), and Chakrabarti (2008a) as separate estimates. A close investigation of the two datasets used in these separate papers reveals that both studies use the same dataset.…”

“…Although each choice program examined in this review takes place in a unique environment, the DC voucher program was exceptional because it was restricted to a relatively small number of participants in the year this study was conducted. Furthermore, a "holdharmless" provision ensured that public schools were insulated from the financial loss from any students that transferred into private schools with a Chakrabarti, R. (2008a) 1997-1998through 2001-20021993-1994through 2001-20021997-1998through 2001-2002 Grade 5 Positive students in Grades 3-10 take the Florida Comprehensive Assessment Test (FCAT). Results from this state test are used to grade schools on a scale from A to F. If a school receives two F grades in a 4-year period, its students automatically become eligible for vouchers to transfer to alternative private or public schools.…”

“…The unique policy design permitted the use of a regression discontinuity analysis around assignments of grades to schools near the accountability cutoffs, permitting numerous rigorous quasi-experimental analyses. I identify seven estimates of competition effects from the A+ Plan, all of which find positive impacts on math, reading, and writing outcomes (Chakrabarti, 2008a;Figlio & Rouse, 2006;Forster, 2008a;Greene, 2001;Greene & Winters, 2004;Rouse et al, 2013;West & Peterson, 2006).…”

“…A close investigation of the two datasets used in these separate papers reveals that both studies use the same dataset. In order to avoid double-counting studies, I only count this estimate once (the study I refer to in this article is Chakrabarti, 2008a).…”

“…By comparing observations from two similar groups that fall on either side of a prespecified cutoff point, this approach approximates a "gold standard" random-assignment research design. Six of the Florida estimates gathered in this review use this approach, made possible by Florida's unique accountability policy that assigns letter grades to schools and makes voucher availability contingent on these school grades being below a cut-off point (Chakrabarti, 2008a;Figlio & Rouse, 2006;Greene, 2001;Greene & Winters, 2004;Rouse et al, 2013;West & Peterson, 2006).…”