Panel data, sometimes referred to as longitudinal data, is data that contains observations about different cross sections across time. Panel data exhibits characteristics of both cross-sectional data and time-series data. This blend of characteristics has given rise to a unique branch of time series modeling made up of methodologies specific to panel data structure. This blog offers a complete guide to those methodologies including the nature of panel data series, types of panel data, and panel data models.
Introduction In this blog, we examine one of the fundamentals of panel data analysis, the one-way error component model. Today we will: Explain the theoretical one-way error component model. Consider fixed effects vs. random effects. Estimate models using an empirical example. The theoretical one-way error component model The one-way error-component model is a panel data [...]
Introduction When policy changes or treatments are imposed on people, it is common and reasonable to ask how those people have been impacted. This is a more difficult question than it seems at first glance. In order to truly know how those individuals have been impacted, we need to consider how those individuals would be [...]
Introduction In this blog, we extend last week's analysis of unit root testing with structural breaks to panel data. We will again use the quarterly current account to GDP ratio but focus on a panel of data from five countries: United States, United Kingdom, Australia, South Africa, and India. Using panel data unit roots tests [...]Tagged in