Bandeau SMCS

Treatment Effect Analysis using Stata

[4 demi jours] - [Anglais]

Do you want to assess the causal effect of a treatment or a policy on your interest variable?

Treatment-effect estimators quantify the causal effect of a treatment/policy on an outcome, based on observational or quasi-experimental data. For example, a treatment could be a new drug and the outcome blood pressure or it could be a job training program with employment or wages as outcome, etc.
Causal inference requires the estimation of the outcomes for each treatment level. But one only observes the outcome of each subject (individual, firm, region…) conditional on the received treatment. Experiments may help but can be expensive and sometimes unethical. Fortunately, many things can be done with observational data. But one needs some statistical machinery.

Objectifs de la formation
Equip the participants with the most commonly used methods available in Stata to estimate treatment effects from observational data.


By registering for this training, you commit to a level of knowledge equivalent to a course of intermediate econometrics or biostatistics and to the following training(s):

Data management and analysis using Stata


Outils utilisés durant la formation

Méthodes et familles de méthodes abordées
Regression model

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