Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors
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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|Date of creation:||Jan 2011|
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Web page: http://www.bu.edu/econ/
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