Testing for Structural Breaks in the Evaluation of Programs
AbstractA youth homicide reduction initiative in Boston in the mid-1990s poses particular difficulties for program evaluation because it did not have a control group and the exact implementation date is unknown. A standard methodology in program evaluation is to use time series variation to compare pre- and postprogram outcomes. Such an approach is not valid, however, when the timing of program implementation or effect is unknown. To evaluate the Boston initiative, we adapt from the time series literature an unknown-breakpoint test to test for a change in regime. Tests for parameter instability provide a flexible framework for testing a range of hypotheses commonly posed in program evaluation. These tests both pinpoint the timing of maximal break and provide a valid test of statistical significance. We evaluate the results of the estimation using the asymptotic results in the literature and with our own Monte Carlo analyses. We conclude there was a statistically significant discontinuity in youth homicide incidents (on the order of 60%) shortly after the intervention was unveiled. © 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.
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Bibliographic InfoArticle provided by MIT Press in its journal Review of Economics and Statistics.
Volume (Year): 85 (2003)
Issue (Month): 3 (August)
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Web page: http://mitpress.mit.edu/journals/
Other versions of this item:
- Anne Morrison Piehl & Suzanne J. Cooper & Anthony A. Braga & David M. Kennedy, 1999. "Testing for Structural Breaks in the Evaluation of Programs," NBER Working Papers 7226, National Bureau of Economic Research, Inc.
- Cooper, Suzanne & Piehl, Anne Morrison & Braga, Anthony & Kennedy, David, 2001. "Testing for Structural Breaks in the Evaluation of Programs," Working Paper Series rwp01-019, Harvard University, John F. Kennedy School of Government.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
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