Panel Data Inference in Finance : Least-Squares vs Fama-MacBeth Panel Data Inference in Finance : Least-Squares vs Fama-MacBeth

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is…

This paper focuses on inference based on the usual panel data estimators of a one-way error component regression model when the true specification is a spatial error component model. Among the estimators considered, are pooled OLS, random and fixed…

In this paper, I consider generalized least squares (GLS) estimation in fixed effects panel and multilevel models with autocorrelation. The presence of fixed effects complicates implementation of GLS as estimating the fixed effects will typically…

To answer substantive questions regarding individual change, it is necessary to collect information from each subject multiple times. For decades, political scientists have col- lected a great deal of panel data, relating to mass behavior,…

This paper develops methods of Bayesian inference in a cointegrating panel data model. This model involves each cross-sectional unit having a vector error correction representation. It is flexible in the sense that different cross-sectional units…

This article provides the large sample distribution of the iterated feasible generalized least-squares (IFGLS) estimator of an augmented dynamic panel data model. The regressors in themodel include lagged values of the dependent variable and may…

In corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms or across time, and OLS standard errors can be biased. Historically,…

In this chapter, we study the asymptotic distributions for ordinary least squares (OLS), fully modified OLS (FMOLS), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FMOLS, and DOLS estimators…

Least Squares (LS) and its minimum variance counterpart, Weighted Least Squares (WLS), have become very popular when estimating the Diffusion Tensor (DT), to the point that they are the standard in most of the existing software for diffusion MRI.…

Using very small, well-conditioned systems of equations, the performance of least-squares solutions has been compared to the performance of the maximum likelihood solution for Poisson data. It is shown that, at count rates normally encountered in…