A brief survey of clustered errors, focusing on estimating cluster–robust standard errors: when and why to use the cluster option (nearly always in panel regressions), and implications. Additional topics may include using svyset to specify clustering, multidimensional clustering, clustering in...

Using loops and macros in Stata can hold many advantages, mainly reducing the length of your do files, allowing errors to be tracked and fixed quickly and efficiently, faster running do files and providing us with re-usable programs which can be used in subsequent data analyses with similar...

We will take a quick tour of the graph editor, covering the basic concepts: adding text, lines, and markers; changing the defaults for added objects; changing properties; working quickly by combining the contextual toolbars with the more object dialogs; and using the object browser effectively....

One of Stata’s great strengths is its data management abilities. When either building or sharing datasets, 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 datasets were self-contained, i.e., if...

Describing batches of data in terms of their order statistics or quantiles has long roots, but remains underrated in graphically-based exploration, data reduction and data reporting. Hosking in 1990 proposed L-moments based on quantiles as a unifying framework for summarizing distribution...

The cendif module is part of the somersd package, and calculates confidence intervals for the Hodges–Lehmann median difference between values of a variable in two subpopulations. The traditional Lehmann formula, unlike the formula used by cendif, assumes that the two subpopulation...

In an attempt to learn Mata I have translated the LARS package, written for R by Trevor Hastie and Brad Efron, into Mata. The LARS package is an efficient implementation of an entire lasso sequence with the cost of a single least-squares estimation. Mata and R/S+ are incredibly similar in terms...

Distributive analysis typically consists in estimating summary measures capturing aspects of the distribution of sample points beyond central tendency. Stochastic dominance analysis is also central for comparisons of distributions. Unfortunately, data contamination, and extreme data more...

This article presents a Stata program (sensatt) that implements the sensitivity analysis for matching estimators proposed by Ichino, Mealli and Nannicini (2007). The analysis simulates a potential confounder in order to assess the robustness of the estimated treatment effects with respect to...

Three different methods have been suggested in the econometrics literature to deal with the initial conditions problem in dynamic Probit models for panel data. Heckman (1981) suggest to approximate the reduced form marginal probability of the initial state with a Probit model and allow free...