Panel data are repeated measures of a large number of units, e.g., individuals or companies. Such longitudinal data is typically collected through surveys, but panel data can also come from other data sources, such as administrative records. The longitudinal nature of the data makes it possible to address research questions, that cannot be analysed with cross-sectional data and can be used to approach causality. However, panel data have a more complex structure and require additional skills for data preparation and data analysis.
In this course, we provide the skills to prepare panel data for analysis and apply regression models with panel data. We will put emphasis on understanding the mechanism behind the different approaches, focussing on their advantages and limitations such that participants will be able to choose and apply the appropriate model.
Workshop contents
This workshop provides an introduction to the structure, data management, and analysis of panel data. Participants will learn how to prepare panel data for different types of research questions specific to this type of data. This includes creating wide data files, long data files, spells, and transitions that can be used for descriptive statistics and for regression models.
For data analysis, we focus on different basic regression models, namely pooled OLS, fixed effects, random effects, and first differences. The aim of this workshop is to understand the within perspective of panel data as opposed to the between perspective of cross-sectional data and to grasp the mechanics of these models.
For careful data analysis, it is important to understand how data has been collected. For panel, difficulties arise, among others, from following of units over time, non-response and attrition, and measurement changes over time (e.g. change of survey modes). We will use real data in the course and discuss the implications of these issues for data analysis. Examples are mainly from the Swiss Household Panel (SHP), which contains data over more than 20 years, covers topics from different social science disciplines and offers different kinds of data files (individual, household, one-time collected information, events). We will also discuss other types of panel data, that have different numbers and types of levels (households, schools, companies) and measurement points.
In the morning sessions, we will present theory and applications and discuss how to do research with panel data. In the afternoon sessions, participants will work on practical exercises either with data prepared by the instructors from the SHP or with panel data of their own choice. One of the instructors is available to discuss and solve individual problems.
Course leader
Oliver Lipps & Ursina Kuhn, FORS
Course aim
This workshop provides an introduction to the structure, data management, and analysis of panel data. Participants will learn how to prepare panel data for different types of research questions specific to this type of data. This includes creating wide data files, long data files, spells, and transitions that can be used for descriptive statistics and for regression models.
Credits info
The Summer School cannot grant credits. We only deliver a Certificate of attendance, i.e. we certify your presence
If you consider using Summer School workshops to obtain credits (ECTS), you will have to investigate at your home institution (contact the person/institute responsible for your degree) to find out whether they recognize the Summer School, how many credits can be earned from a workshop/course with roughly 35 hours of teaching, no graded work, and no exams.
Fee info
CHF 700: Reduced fee: 700 Swiss Francs per weekly workshop for students (requires proof of student status).
CHF 1100: Normal fee: 1100 Swiss Francs per weekly workshop for all others.
For further information, please click the "LINK TO ORIGINAL" button below.