Bandeau smcs
UCLouvain > Plate-forme SMCS

Panel-data Analysis using Stata

[3 half days] - [starts on 25-05-2023 at 09:30] - [English] - [Louvain-la-Neuve]

Longitudinal surveys, that follow individuals over several periods of time, are becoming increasingly popular in social sciences. The main reason is that they offer a particular setting that researchers can use to control for some types of unobserved variables bias.

The mixed models are a family of models with both fixed and random effects. They make it possible to take into account the correlation between several observations, in particular the longitudinal aspect of the data.

Training aims

This course provides an introduction to the analysis of panel-data. At the end of the training, participants will be able to use Stata effectively for manipulating and analyzing panel-datasets, to understand the error components model and the issue of unobserved heterogeneity and to implement most commonly used linear panel-data estimators. The last half-day will also include an introduction to estimators for dynamic linear models (which include lagged dependent variables).

By registering for this training, you commit to a level of knowledge equivalent to the following training(s):
Data management and analysis using Stata


We will apply the theoretical content with exercises in Stata.

Louvain-la-Neuve : SOCRATE 068 - Find the location on Google Maps
(This is an air-conditioned room so please cover yourself!)
- Place Cardinal Mercier, 10-12 - Rez-de-chaussée -

Cette formation est accessible à tous moyennant une inscription préalable.

Time slots for training
25-05-2023 from 09:30 to 16:30
26-05-2023 from 09:30 to 12:30

UCLouvain member, UCLouvain student, UCLouvain clinic member : Training available free of charge but registration in advance is required.
Administrative fees will be applied in case of late cancellation.
Non-UCLouvain member : 250 euros per day for a total of 375 euros
Invoice paid by a Belgian university : 170 euros per day for a total of 255 euros

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