When doing two-way fixed effects OLS estimations, both the variances and covariance of the fixed effects are biased. A formula for a bias correction is known, but in large datasets it involves inverses of impractically large matrices. We detail how to compute the bias correction in this case.

This is an exploratory study that attempts to identify and provide empirical evidence on the possible determinants of the market capitalisation of the Harare Stock Exchange (HSE) with the view of understanding the development prospects of the HSE and other similar markets. The study used...

OLS is as efficient as GLS in the linear regression model with long-memory errors as the long-memory parameter approaches the boundary of the stationarity region_ provided the model contains a constant term. This generalizes previous results of Samarov Taqqu (Journal of Time Series Analysis 9...

The most part of the paper is about modeling (or approximating) nonstochastic regressors. Examples of regressors which are (not) L2-approximable are given. Applications to central limit theory and OLS estimator asymptotics are provided.

A wide range of tests for heteroskedasticity have been proposed in the econometric and statistics literature. Although a few exact homoskedasticity tests are available, the commonly employed procedures are quite generally based on asymptotic approximations which may not provide good size control...

When dealing with the presence of outliers in a dataset, the problem of choosing between the classical ordinary least squares and robust regression methods is sometimes addressed inadequately. In this article, we propose using a Hausman-type test to determine whether a robust S- estimator is...

In the presence of outliers in a dataset, a least squares estimation may not be the most adequate choice to get representative results. Indeed estimations could have been excessively infuenced even by a very limited number of atypical observations. In this article, we propose a new Hausman-type...

Central limit theorems are developed for instrumental variables estimates of linear and semiparametric partly linear regression models for spatial data. General forms of spatial dependence and heterogeneity in explanatory variables and unobservable disturbances are permitted. We discuss...

Strong consistency of least squares estimators of the slope parameter in simple linear regression models is established for predetermined stochastic regressors. The main result covers a class of models which falls outside the applicability of what is presently available in the literature. An...

Changes in tastes and preferences in importing countries as well as the need to keep the environment safe, especially in developed markets, has contributed to a rising trend in the demand for sanitary and phytosanitary measures for quality products. However, the stringency and the preponderance...