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Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors

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Author Info

  • Pierre Perron

    ()
    (Department of Economics, Boston University)

  • Yohei Yamamoto

    ()
    (University of Alberta School of Business)

Abstract

We consider the problem of estimating and testing for multiple breaks in a single equation framework with regressors that are endogenous, i.e., correlated with the errors. We show that even in the presence of endogenous regressors, it is still preferable to simply estimate the break dates and test for structural change using the usual ordinary least-squares (OLS) framework. In most cases, it delivers estimates of the break dates with higher precision and tests with higher power compared to those obtained using an IV method. Also, the OLS method avoids potential weak identification problems caused by weak instruments. To illustrate the relevance of our theoretical results, we consider the stability of the New Keynesian hybrid Phillips curve. IV-based methods only provide weak evidence of instability. On the other hand, OLS-based ones strongly indicate a change in 1991:1 and that after this date the model looses all explanatory power.

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Bibliographic Info

Paper provided by Boston University - Department of Economics in its series Boston University - Department of Economics - Working Papers Series with number WP2011-053.

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Length: 34 pages
Date of creation: Jan 2011
Date of revision:
Handle: RePEc:bos:wpaper:wp2011-053

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Related research

Keywords: structural change; instrument variables; parameter variations; Phillips Curve.;

References

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  1. Mohitosh Kejriwal & Pierre Perron, 2007. "Testing for Multiple Structural Changes in Cointegrated Regression Models," Boston University - Department of Economics - Working Papers Series wp2008-020, Boston University - Department of Economics, revised Nov 2008.
  2. Perron, Pierre & Qu, Zhongjun, 2006. "Estimating restricted structural change models," Journal of Econometrics, Elsevier, vol. 134(2), pages 373-399, October.
  3. Mohitosh Kejriwal & Pierre Perron, 2006. "The Limit Distribution of the Estimates in Cointegrated Regression Models with Multiple Structural Changes," Boston University - Department of Economics - Working Papers Series WP2006-064, Boston University - Department of Economics.
  4. Tatevik Sekhposyan & Barbara Rossi, 2008. "Has modelsí forecasting performance for US output growth and inflation changed over time, and when?," Working Papers 09-02, Duke University, Department of Economics.
  5. Hall, Alastair R. & Han, Sanggohn & Boldea, Otilia, 2008. "Inference regarding multiple structural changes in linear models estimated via two stage least squares," MPRA Paper 9251, University Library of Munich, Germany, revised 20 Jun 2008.
  6. Boldea, O. & Hall, A.R. & Han, S., 2012. "Asymptotic distribution theory for break point estimators in models estimated via 2SLS," Open Access publications from Tilburg University urn:nbn:nl:ui:12-5241457, Tilburg University.
  7. Pierre Perron & Yohei Yamamoto, 2008. "Estimating and Testing Multiple Structural Changes in Models with Endogenous Regressors," Boston University - Department of Economics - Working Papers Series wp2008-017, Boston University - Department of Economics.
  8. Kurmann, Andre, 2007. "VAR-based estimation of Euler equations with an application to New Keynesian pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(3), pages 767-796, March.
  9. 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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Citations

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Cited by:
  1. Pierre Perron & Yohei Yamamoto, 2011. "Estimating and Testing Multiple Structural Changes in Linear Models Using Band Spectral Regressions," Boston University - Department of Economics - Working Papers Series WP2011-049, Boston University - Department of Economics.
  2. Rasmus Fatum & Yohei Yamamoto, 2012. "Does foreign exchange intervention volume matter?," Globalization and Monetary Policy Institute Working Paper 115, Federal Reserve Bank of Dallas.

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