This paper presents a Stata program ("sensatt") that implements the sensitivity analysis for propensity-score matching estimators proposed by Ichino, Mealli and Nannicini (2005). The proposed analysis builds on Rosenbaum and Rubin (1983) and Rosenbaum (1987), and simulates a potential confounder...

xtabond2 may hold the record among user-written Stata modules for the most confused users (and perhaps the most-confused too). In this presentation, I motivate and describe, in pedagogic fashion, the Arellano-Bond and Blundell-Bond linear GMM dynamic panel estimators, drawing lessons from a...

I will give a brief overview of modern statistical methods for estimating treatment effects that have recently become popular in social and biomedical sciences. These methods are based on the potential outcome framework developed by Donald Rubin. The specific methods discussed include regression...

In many applications of conditional logit models the choice set and the characteristics of that set are identical for groups of decision makers. In that case is possible to obtain a more computationally efficient estimation of the model by grouping the data and employing a new user-written...

I will present a set of routines to conduct a one-factor confirmatory factor analysis in Stata. The use of Mata in programming will be highlighted. Corrections for non-normality, as common in the structural equation modeling literature, will be demonstrated. Indications for further development...

Seasonal effects are dominant in many environmental time series and important or at least notable in many economic or biomedical time series, to name only a few application areas represented in the Stata user community. In several fields it seems rare to use anything other than basic line graphs...

One of Stata's great strengths is its data management abilities. When either building or sharing data sets, some of the most time-consuming activities are validating the data and writing documentation for the data. Much of this futility could be avoided if data sets were self-contained, i.e. if...

The assumptions of the ordered logit/probit models estimated by ologit and oprobit are often violated. When an ordinal regression model incorrectly assumes that error variances are the same for all cases, the standard errors are wrong and (unlike OLS regression) the parameter estimates are...

After introducing time-series data management in Stata, the talk discusses estimation, inference, and interpretation of ARMA models, ARCH/GARCH models, VAR models, and SVAR models in Stata. The talk briefly introduces each model discussed.

This presentation reviews methods for summarizing and comparing income distributions, together with the related literature about variance estimation for a range of summary measures. Although the focus is on income and the perspective is that of an economist, the methods have been widely applied...