In this paper we use the approximate bias expressions developed in Yu (2012) and Bao et al. (2013) to improve the … testing of the ordinary least squares or quasi-maximum likelihood estimator of the mean reversion parameter in continuous time … models. We follow the approach given in Iglesias and Phillips (2005) and Chambers (2013), where if we bias correct the …

-squares (OLS). To explore these conjectures, we derive an expression for OLS omitted variable bias in a univariate model with … conventional omitted variables bias. Moreover, we show that spatial dependence in the regressor exacerbates the usual bias that …

We examine evidence on omitted-ability bias in estimates of the economic return to schooling, using proxies for …

We examine evidence on omitted-ability bias in estimates of the economic return to schooling, using proxies for …

-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than … in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias …

In this paper I discuss three issues related to bias of OLS estimators in a general multivariate setting. First, I … discuss the bias that arises from omitting relevant variables. I offer a geometric interpretation of such bias and derive … sufficient conditions in terms of sign restrictions that allows us to determine the direction of bias. Second, I show that …