Threshold Regression with Endogeneity for Short Panels

This paper considers the estimation of dynamic threshold regression models with fixed effects using short panel data. We examine a two-step method, where the threshold parameter is estimated nonparametrically at the N-rate and the remaining parameters are estimated by GMM at the N−−√ -rate. We provide simulation results that illustrate advantages of the new method in comparison with pure GMM estimation. The simulations also highlight the importance of the choice of instruments in GMM estimation.Tue Gørgens’ research was supported in part by Australian Research Council Grant DP1096862

The Effect of Nuisance Parameters on the Power of LM Tests in Logit and Probit Models

In econometrics, most null hypotheses are composite, dividing the parameters into parameters of interest and nuisance parameters. The domain of the nuisance parameters can influence the size-corrected critical value and hence the power of a test. We show that the domain of the nuisance parameters determines which version of the LM test to use in logit and probit models. In these models there are two commonly used ways to construct the LM test: it can be based on the Hessian matrix or the outer product (OP) matrix of the score vectors. For the OP based LM test, the domain of the nuisance parameters strongly influences the size-corrected critical value whereas the same is not true for the Hessian based LM test. A theoretical explanation is developed using large nuisance parameter asymptotics. For empirically relevant domains, the experimental evidence shows that the Hessian based LM test has better finite sample power than the OP based LM test.

Power of Tests in Binary Response Models

Most hypotheses in binary response models are composite. The null hypothesis is usually that one or more slope coefficients are zero. Typically, the sequence of alternatives of interest is one in which the slope coefficients are increasing in absolute value. In this paper, we prove that the power goes to zero for this sequence of alternatives of interest in cases which often occur in practice. The practical implication is that for the sequence of alternatives of interest the power is nonmonotonic. This is true for any non-randomized test with size less than one and for a wide class of binary response models which includes the logit and probit models.

Semiparametric Estimation of the Box-Cox Model Preliminary and Incomplete

This paper investigates the finite sample performance of three semiparametric estimators of the Box-Cox model. Two of the semiparametric estimators are the nonlinear two-stage least squares (NL2SLS) estimator proposed by Amemiya and Powell (1981) and a rescaled version (RNL2SLS) proposed by Powell (1996) to eliminate an inconsistent minimizer of the NL2SLS objective function. These estimators are special cases of the general-method-of-moments (GMM) estimator. The third estimator is one recently proposed by Foster, Tian and Wei (FTW) (2000), which is based on the empirical distribution function of the dependent variable. The Monte Carlo results show that there is no best estimator across the experimental designs considered. The NL2SLS and RN2SLS estimators tend to suffer from near nonidentification due to a flat objective function, and, although the FTW estimator is better than NL2SLS and RNL2SLS for many designs, it can perform badly for certain designs. The results also show that first-order asymptotic theory may provide a poor approximation to the finite sample distributions of the estimators.

Udviklingslinier i Oekonometrien

Recent Developments in Econometrics (In Danish) survey and assess the developments within econometric theory, microeconometrics, time series econometrics, financial econometrics, and latent variables.Econometrics

CAHIER 11-2000 EXACT TESTS FOR CONTEMPORANEOUS CORRELATION OF DISTURBANCES IN SEEMINGLY UNRELATED REGRESSIONS CAHIER 11-2000 EXACT TESTS FOR CONTEMPORANEOUS CORRELATION OF DISTURBANCES IN SEEMINGLY UNRELATED REGRESSIONS

RÉSUMÉ Cet article propose des procédures exactes pour tester la spécification SURE (régressions empilées) dans le contexte des régressions linéaires multivariées, i.e. si les perturbations des différentes équations sont corrélées ou non. Nous appliquons la technique des tests de Monte Carlo (MC

Temperature dependence of estrogen binding: Importance of a subzone in the ligand binding domain of a novel piscine estrogen receptor

10.1016/S0167-4889(99)00128-7Biochimica et Biophysica Acta - Molecular Cell Research14522103-120BAMR