摘要:

This paper presents a Lagrange multiplier test of the normality assumption underlying the ordered probit model. The test is presented both for the standard ordered probit model and a version in which censoring is present in the dependent variable. The test is then compared to normality tests proposed here compares favorably to tests based on artificial regression techinques.

ISSN:0747-4938    

DOI:10.1080/07474939708800369

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor

摘要:

This paper unifies two seemingly separate approaches to test weak exogeneity in dynamic regression models with Lagrange-mulptiplier statistics. The first class of tests focuses on the orthogonality between innovations and conditioning variables, and thus is related to the Durbin-Wu-Hausman specification test. The second approach has been developed more recently in the context of context of cointegration and error correction models, ad concentrates on the question whether the conditioning variables display error correction behaviour. It is shown that the vital difference between the two approaches stems from the choice of the parmeters of interest. A new test is derived, which encompasses both its predecessors. The test is applied to an error correction model of the demand for money in Switzerland.

ISSN:0747-4938    

DOI:10.1080/07474939708800370

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor

摘要:

This paper addresses the issue of designing finite-sample corrections to information matrix tests. We review a Cornish-Fisher correction that has been propowed elsewhere and propose an alternative, Bartlett-type correction. Simulation results for skewness, excess kurtosis, normality and heteroskedasticity tests are given.

ISSN:0747-4938    

DOI:10.1080/07474939708800371

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor

摘要:

In the framework of the Engle-type (G)ARCH models, I demonstrate that there is a family of symmetric and asymmetric density functions for which the asymptotic efficiency of the semiparametric estimator is equal to the asymptotic efficiency of the maximum likelihood estimator. This family of densities is bimodal (except for the normal). I also chracterize the solution to the problem of minimizing the mean squared distance between the parametric score and the semiparametric score in order to search for unimodal densities for which the semiparametric estimator is likely to perform well. The LaPlace density function emerges as one of these cases.

ISSN:0747-4938    

DOI:10.1080/07474939708800372

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor

摘要:

This paper numerically examines the size robustness of various conditional moment tests in misspecified tobit and probit models. The misspecifications considered include the incorrect exclusion of regressors, ignored heteroskedasticity and false distributional assumptions. An important feature of the experimental design is that it is based on an existing empirical study and is more realistic than many simulation studies. The tests are seen to have mixed performance depending on both the original null hypothesis being tested and type of misspecification encountered.

ISSN:0747-4938    

DOI:10.1080/07474939708800373

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor

摘要:

This paper considers the problem of estimating a nonlinear statistical model subject to stochastic linear constraints among unknown parameters. These constraints represent prior information which originates from a previous estimation of the same model using an alternative database. One feature of this specification allows for the disign matrix of stochastic linear restrictions to be estimated. The mixed regression technique and the maximum likelihood approach are used to derive the estimator for both the model coefficients and the unknown elements of this design matrix. The proposed estimator whose asymptotic properties are studied, contains as a special case the conventional mixed regression estimator based on a fixed design matrix. A new test of compatibility between prior and sample information is also introduced. Thesuggested estimator is tested empirically with both simulated and actual marketing data.

ISSN:0747-4938    

DOI:10.1080/07474939708800374

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor

摘要:

Abstract: The predictor that minimizes mean-squared prediction error is used to derive a goodness-of-fit measure that offers an asymptotically valid model selection criterion for a wide variety of regression models. In particular, a new goodness-of-fit criterion (cr2) is proposed for censored or otherwise limited dependent variables. The new goodness-of-fit measure is then applied to the analysis of duration.

ISSN:0747-4938    

DOI:10.1080/07474939708800375

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor

摘要:

We examine the risk of a pre-test estimator for regression coefficients after a pre-test for homoskedasticity under the Balanced Loss Function (BLF). We show analytically that the two stage Aitken estimator is dominated by the pre-test estimator with the critical value of unity, even if the BLF is used. We also show numerically that both the two stage Aitken estimator and the pre-test estimator can be dominated by the ordinary least squares estimator when “goodness of fit” is regarded as more important than precision of estimation.

ISSN:0747-4938    

DOI:10.1080/07474939708800376

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor

ISSN:0747-4938    

DOI:10.1080/07474939708800368

出版商:Marcel Dekker, Inc.    

年代:1997

数据来源: Taylor