Skip to content

Opening book details…

About this document

Understanding Panel Data Models by MarkWeber is a document available to read on EtoBox.

The document discusses panel data modeling. Panel data, also known as longitudinal or pooled data, involves observing the same cross-sectional units (e.g. individuals, firms) over multiple time periods. There are four main types of data structures: time series data, cross-sectional data, pooled data, and panel data. Panel data modeling has two main approaches - the fixed effects model and random effects model. The fixed effects model accounts for differences between cross-sectional units using dummy variabl

Author
MarkWeber
Language
EN