Paneldatenmodellen
Paneldatenmodellen, also known as panel data models or longitudinal models, are statistical models used to analyze data collected from multiple entities (such as individuals, firms, or countries) over multiple time periods. This type of data, called panel data, has both a cross-sectional dimension (the entities) and a temporal dimension (the time periods). Panel data models offer advantages over purely cross-sectional or time-series models because they can account for unobserved heterogeneity across entities and changes over time.
The fundamental idea behind panel data models is to capture variations within entities over time as well
Common types of panel data models include the pooled ordinary least squares (OLS) model, the fixed-effects model,