In the robust statistics literature, a wide variety of models has been developed to cope with outliers in a rather large number of scenarios. Nevertheless, a recurrent problem for the empirical implementation of these estimators is that optimization algorithms generally do not perform well when...

In a 2012 article in the Journal of Business & Economic Statistics, Arthur Lewbel presents the theory of allowing the identification and estimation of "mismeasured and endogenous regressor models" by exploiting heteroskedasticity. These models include linear regression models customarily...

This presentation shows a somewhat complex automatization scheme in Stata that was developed during preparation of two papers using firm-level data and applying the propensity score matching techniques to distill the direct effects of the presence of foreign investors on various indicators from...

In this presentation, the author presents a procedure and an illustrative application of a user-written Allocation Model(AE) in Stata. AE measures allocative efficiency and economic efficiency as well as technical efficiency when price and cost information of production are available. This model...

Estimating the density of a distribution from a finite number of data points is an important tool in the statistician's and data analyst's toolbox. In their recent paper, Bernacchia and Pigolotti (JRSS-B, 2011) introduce a new non-parametric method for the density estimation of univariate...

This talk illustrates how results from various Stata commands can be processed efficiently for inclusion in customized reports. A two-step procedure is proposed in which results are gathered and archived in the first step and then tabulated in the second step. Such an approach disentangles the...

This session offers an introduction to spatial econometrics using some user-written Stata commands. I will discuss the estimation and interpretation of the parameters in the cross-sectional spatial-autoregressive model. Data management issues pertaining to spatial-weighting matrices used in the...

Abstract not available.

Missing data is a pervasive issue in epidemiological, clinical, social, and economic studies. This presentation offers a brief overview of the conceptual issues raised by missing data, followed by an overview of some of the principled statistical methods of handling missing data that are...

Hierarchical datasets are commonly a product of the popular CSPro system developed by the U.S. Census Bureau. CSPro became widely popular and a de facto standard for data collection in many countries; some agencies supply data exclusively in CSPro format. While CSPro can export the data into...