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Testing for Structural Breaks in the Evaluation of Programs

Author

Listed:
  • Cooper, Suzanne

    (Harvard U)

  • Piehl, Anne Morrison

    (Harvard U)

  • Braga, Anthony

    (Harvard U)

  • Kennedy, David

    (Harvard U)

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 post-program outcomes. Such an approach is not valid, however, when the timing of a potential break is unknown. To evaluate the Boston initiative, we adapt from the macroeconomics literature a test of unknown break point 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 percent) shortly after the intervention was unveiled.

Suggested Citation

  • 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.
  • Handle: RePEc:ecl:harjfk:rwp01-019
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    References listed on IDEAS

    as
    1. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-287, July.
    2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
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    4. Steven D. Levitt & Sudhir Alladi Venkatesh, 2000. "An Economic Analysis of a Drug-Selling Gang's Finances," The Quarterly Journal of Economics, Oxford University Press, vol. 115(3), pages 755-789.
    5. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
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    7. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
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    9. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
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    12. Budd, J.W. & Nho, Y., 1995. "Testing for a Structurak Change in U.S. Wage Determination," Papers 95-03, Minnesota - Industrial Relations Center.
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; 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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