Archive for September, 2020

This paper is a joint effort with prof. Mike Tsionas. It has just been accepted for publication in Econometric Reviews. It really has a new least-squares method to propose that reduces the variance of the estimator in linear regression. And it is very easy to implement.

ABSTRACT. In pursuit of efficiency, we propose a new way to construct least squares estimators, as the minimizers of an augmented objective function that takes explicitly into account the variability of the error term and the resulting uncertainty, as well as the possible existence of heteroskedasticity. We initially derive aninfeasible estimator which we then approximate using Ordinary Least Squares (OLS) residuals from a first-step regression to obtain the feasible “HOLS” estimator. This estimator has negligible bias, is consistent and outperforms OLS in terms of finite-sample Mean Squared Error, but also in terms of asymptotic efficiency, under all skedastic scenarios, including homoskedasticity. Analogous efficiency gains are obtained for the case of Instrumental Variables estimation. Theoretical results are accompanied by simulations that support them.

Download the pre-print and the on-line Appendix.


This has just been approved for publication in Empirical Economics.

ABSTRACT. We revisit the production frontier of a firm and we examine the effects that the firm’s management has on output. In order to estimate these effects using a cross-sectional sample while avoiding the costly requirement of obtaining data on management as a production factor, we develop a two-tier stochastic frontier (2TSF) model where management is treated as a latent variable. The model is consistent with the microeconomic theory of the firm, and it can estimate the effect of management on the output of a firm in monetary terms from different angles, separately from inefficiency. The approach can thus contribute to the cost-benefit analysis related to the management system of a company, and it can facilitate research related to management pay and be used in studies of the determinants of management performance. We also present an empirical application, where we find that the estimates from our latent-variable model align with the results obtained when we use the World Management Survey scores that provide a measure of management.