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Exact tests for structural change in first-order dynamic models
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DOI：10.1016/0304-4076(94)01683-6.png)
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摘要
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Several finite-sample tests of parameter constancy against the presence of structural change are proposed for a linear regression model with one lagged dependent variable and independent normal disturbances, The procedures derived include analysis-of-covariance, CUSUM, CUSUM-of-squares, and predictive tests, The approach used to obtain the tests involves the application of three techniques: derivation of an exact confidence set for the autoregressive parameter (based on using an appropriately extended regression), a union-intersection technique, and (when required) randomization. The tests proposed are illustrated with some artificial data and applied to a dynamic trend model of gross private domestic investment in the U.S.
Keyword:
finite-sample tests
exact inference
first-order autoregressive model
randomization
structural change
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