Abstract
This paper gives a brief survey of forecasting with panel data. It begins with a simple error component regression model and surveys the best linear unbiased prediction under various assumptions of the disturbance term. This includes various ARMA models as well as spatial autoregressive models. The paper also surveys how these forecasts have been used in panel data applications, running horse races between heterogeneous and homogeneous panel data models using out-of-sample forecasts.
Original language | English (US) |
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Pages (from-to) | 153-173 |
Number of pages | 21 |
Journal | Journal of Forecasting |
Volume | 27 |
Issue number | 2 |
DOIs | |
State | Published - Mar 2008 |
Keywords
- BLUP
- Forecasting
- Heterogeneous panels
- Panel data
- Serial correlation
- Spatial dependence
ASJC Scopus subject areas
- Modeling and Simulation
- Computer Science Applications
- Strategy and Management
- Statistics, Probability and Uncertainty
- Management Science and Operations Research