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Testing for Structural Breaks in the Evaluation of Programs

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  • Anne Morrison Piehl

    (John F. Kennedy School of Government, Harvard University)

  • Suzanne J. Cooper

    (John F. Kennedy School of Government, Harvard University)

  • Anthony A. Braga

    (John F. Kennedy School of Government, Harvard University)

  • David M. Kennedy

    (John F. Kennedy School of Government, Harvard University)

Abstract

A 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 Info

Article provided by MIT Press in its journal Review of Economics and Statistics.

Volume (Year): 85 (2003)
Issue (Month): 3 (August)
Pages: 550-558

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Handle: RePEc:tpr:restat:v:85:y:2003:i:3:p:550-558

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  1. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
  2. Jushan Bai, 1995. "Estimating Multiple Breaks One at a Time," Working papers 95-18, Massachusetts Institute of Technology (MIT), Department of Economics.
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  4. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
  5. Simon M. Potter, 1993. "A Nonlinear Approach to U.S. GNP," UCLA Economics Working Papers 693, UCLA Department of Economics.
  6. Steven D. Levitt & Sudhir Alladi Venkatesh, 1998. "An Economic Analysis of a Drug-Selling Gang's Finances," NBER Working Papers 6592, National Bureau of Economic Research, Inc.
  7. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  8. Cooper, Suzanne J, 1998. "Multiple Regimes in U.S. Output Fluctuations," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 92-100, January.
  9. Anindya Banerjee & Robin L. Lumsdaine & James H. Stock, 1990. "Recursive and Sequential Tests of the Unit Root and Trend Break Hypothesis: Theory and International Evidence," NBER Working Papers 3510, National Bureau of Economic Research, Inc.
  10. Budd, J.W. & Nho, Y., 1995. "Testing for a Structurak Change in U.S. Wage Determination," Papers 95-03, Minnesota - Industrial Relations Center.
  11. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
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