论文信息 - On choosing the optimal level of significance for the Durbin-Watson test and the Bayesian alternative

On choosing the optimal level of significance for the Durbin-Watson test and the Bayesian alternative

Abstract This paper critically evaluates the usual ad hoc selection of the level of significance in the Durbin-Watson test and compares this procedure to the Bayesian alternative. The results of Monte Carlo experiments indicate that an α-level substantially larger than that normally used may be appropriate. The Bayesian estimator performed better than all preliminary test estimates in terms of MSE.

Thomas B. Fomby | David K. Guilkey | T. Fomby | D. Guilkey

[1] A. P. J. Abrahamse,et al. On the Power of the Blus Procedure , 1968 .

[2] Takeshi Hiromatsu,et al. Minimax Regret Significance Points for a Preliminary Test in Regression Analysis , 1973 .

[3] A. Zellner. An Introduction to Bayesian Inference in Econometrics , 1971 .

[4] T. Wallace,et al. Optimal Critical Values for Pre-Testing in Regression , 1976 .

[5] J. Mehta,et al. Efficient method of estimating the level of a stationary first-order autoregressive process , 1974 .

[6] H. Thornber. Finite Sample Monte Carlo Studies: An Autoregressive Illustration , 1967 .

[7] J. Durbin,et al. Testing for serial correlation in least squares regression. II. , 1950, Biometrika.

[8] Arnold Zellner,et al. BAYESIAN ANALYSIS OF THE REGRESSION MODEL WITH AUTOCORRELATED ERRORS. , 1964 .

[9] Paul N. Rappoport,et al. Relative efficiencies of some simple Bayes estimators of coefficients in dynamic models — I , 1975 .

[10] Zvi Griliches,et al. Small-Sample Properties of Several Two-Stage Regression Methods in the Context of Auto-Correlated Errors , 1969 .

[11] T. Wallace,et al. Estimation of variance after a preliminary test of homogeneity and optimal levels of significance for the pre-test , 1975 .