Encompassing Tests When No Model Is Encompassing
This paper considers regression-based tests for encompassing, when none of the models under consideration encompasses all the other models. For both in- and out-of-sample applications, I derive asymptotic distributions and propose feasible procedures to construct confidence intervals and test statistics. Procedures that are asymptotically valid under the null of encompassing (e.g., Davidson and MacKinnon (1981)) can have large asymptotic and finite sample distortions. Simulations indicate that the proposed procedures can work well in samples of size typically available, though the divergence between actual and nominal confidence interval coverage sometimes is large.
|Date of creation:||Jun 2000|
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|Publication status:||published as West, Kenneth D. "Tests For Forecast Encompassing When Forecasts Depend On Estimated Regression," Journal of Business and Economic Statistics, 2001, v19(1,Jan), 29-33.|
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