We produce Monte Carlo evidence on the size and power of the RESET, a heteroscedasticity test, and a test for autocorrelation applied to realistic distributed-lag models. We find that the autocorrelation test has the correct size and high power to detect not only autocorrelation (given a correct model), but also the erroneous omission of several lags of an explanatory variable, whereas the RESET and heteroscedasticity tests are oversized in the presence of positive disturbance autocorrelation, especially when the regressors are also positively autocorrelated, and have no power to detect such misspecification errors. In large samples, size distortion may be avoided by using autocorrelation-robust methods.
Size Power Simulation RESET Diagnostic tests
C15 C22 C52
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Godfrey LG (1988) Misspecification tests in econometrics: the Lagrange multiplier principle and other approaches. Cambridge University Press, New YorkGoogle Scholar
Godfrey LG, McAleer M, McKenzie CR (1988) Variable addition and Lagrange multiplier tests for linear and logarithmic regression models. Rev Econ Stat 70:492–503CrossRefGoogle Scholar
Godfrey LG, Orme CD (1994) The sensitivity of some general checks to omitted variables in the linear model. Int Econ Rev 35:489–506zbMATHCrossRefGoogle Scholar