In this article we extend the class of non-negative, asymmetric kernel density estimators and propose Birnbaum-Saunders (BS) and lognormal (LN) kernel density functions. The density functions have bounded support on [0,1). Both BS and LN kernel estimators are free of boundary bias, non-negative,...

We show that asset pricing models of return with risk factors that entail either shares or dividends are logically circular simultaneities and thus are fallacious, meaningless, non-interpretable, indeterminate and not valid when tested and estimated by scientific statistical methods. This...

Lee (2003) proposed for spatial autoregressive (SAR) model the best spatial two-stage least squares estimator (BS2SLSE) as an improvement on Kelejian and Prucha (1998)¡¯s S2SLSE. In this paper, we show that one more step iteration based on BS2SLSE gives a spatial counterpart of the three-stage...

This paper compares recently developed semiparametric estimators of Type-3 Tobit model using Monte Carlo simulations. In particular, we examine the finite sample performance of the recently proposed method by Li and Wooldridge and compare it to some alternative semiparametric estimators....

A sampling plan that may find applications in economics, biomedical research, reliability and life testing consists of putting kn units on test in groups of k each and observing the minimum value of each group. Thus, the observations are sampled minima and they are to be used to do inference...

In this paper we propose a test statistic to discriminate between models with finite variance and models with infinite variance. The test statistic is the ratio of the sample standard deviation and the sample interquartile range. Both asymptotic and finite sample properties of the test statistic...

This paper develops a consistent test for the correct hazard rate specification within the context of random right hand censoring of the dependent variable. The test is based on comparing a parametric estimate with a kernel estimate of the hazard rate. We establish the asymptotic distribution of...

This paper considers the problem of estimating a partially linear semiparametric fixed effects panel data model with possible endogeneity. Using the series method, we establish the root N normality result for the estimator of the parametric component, and we show that the unknown function can be...

This paper proposes a semiparametric approach to the estimation of ¡®generalized¡¯ binary choice models. A ¡®generalized¡¯ binary choice model is one with separate indices for each conditioning variable which constitutes a generalization of the standard single-index approach typically...

Lee (2003) develops a n-consistent estimator of the parametric component of a partially linear quantile regression model, which is used to obtain his one-step semiparametric efficient estimator. As a result, how well the efficient estimator performs depends on the quality of the initial...