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Mata, the missing manual
William W. Gould, President

Mata is Stata’s matrix programming language. StataCorp provides detailed documentation on it, but so far has failed to give users—and especially users who add new features to Stata—any guidance in when and how to use the language. In this talk, I provide what has been missing. In practical ways, I show how to include Mata code in Stata ado-files, reveal when to include Mata code and when not to, and provide an introduction to the broad concepts of Mata—the concepts that will make the Mata Reference Manual approachable.

Filtering and decomposing time series in Stata
David M. Drukker, Director of Econometrics

In this talk, I provide an introduction to methods for filtering and decomposing time series and I show how to implement them in Stata. I provide an underlying framework for understanding and comparing the different methods. I also present a framework for interpreting the parameters.

Estimating treatment effects by matching
David M. Drukker, Director of Econometrics

In this talk, I provide an introduction to estimating the effect of a treatment using the matching-on-covariates estimator derived by Abadie and Imbens (2006, Econometrica 74: 235–267) and discussed by Abadie, et al. (2004, Stata Journal 4: 290–311). I also provide an introduction to the potential outcome model that underlies this estimator, give some intuition for how the standard errors are estimated, and discuss what happens when this estimator is used to match on previously estimated propensity scores.

Graphics tricks for models
Bill Rising, Director of Educational Services

Visualizing interactions and response surfaces can be difficult. In this talk, I will show how to do the former by graphing adjusted means and the latter by showing how to roll together contour plots. I will demonstrate this for both linear and nonlinear models.