Applied Panel Data Analysis

About

Workshop contents and objectives

We introduce the properties of panel data as a special case of pooled cross-sectional data and discuss how to prepare panel data for panel analysis. We then present different analysis methods, focusing on identifying causal effects. Participants will learn to understand the mechanism behind the different approaches and to assess the advantages and limitations of different panel models, given their specific research questions and data.

Workshop design

In both the morning and the afternoon sessions, we first present theory and application examples using presentation mode (ppt) and provide prepared hands-on exercises. Alternatively, students can work with their own data. As there are two instructors, there will be time available to discuss and solve individual problems.

Detailed lecture plan (daily schedule)

Day 1.
Morning: Introducing Panel data and example data (based on the Swiss Household Panel).
Afternoon: Panel data preparation, explore data, descriptive analysis, attrition analysis, variance decomposition.

Day 2.
Morning: Regression models with panel data: Pooled OLS, pooled logistic regression, change-score models.
Afternoon: Approaching causality with panel data using Fixed Effects and First Difference models.

Day 3.
Multilevel models with panel data: Random effects, Hybrid model.

Day 4.
Morning: Multilevel model for growth.
Afternoon: Possibility for participants to present and discuss their research project, or data analysis in the group.

Day 5.
Morning: Outlook to additional panel models: Cross-lagged models, dynamic models, missing data.
Afternoon: Wrap-up and discussion/question round.

Class materials

The compendium “Stata Data Management”, which provides an introduction into panel data analysis based on data from the Swiss Household Panel.
Prepared student data sets with example syntax and exercises. Power Point presentations.
A selection of application examples of panel data analysis from scientific journals in social science (sociology, psychology, economics and political science).

Prerequisites

We will use the Stata software and assume some knowledge of Stata with cross-sectional data. For students not sufficiently proficient in Stata we offer an online two-day preparatory course shortly before the workshop introducing Stata. We will also provide syntax for R users for those who wish to work with R, but we will only discuss syntax in Stata.

Course leader

Oliver Lipps & Ursina Kuhn

Target group

graduate students, doctoral researchers, early career researchers, experienced researchers

Fee info