EconPapers    
Economics at your fingertips  
 

Estimation and prediction in the random effects model with AR(p) remainder disturbances

Badi Baltagi and Long Liu

International Journal of Forecasting, 2013, vol. 29, issue 1, 100-107

Abstract: This paper considers the problem of estimation and forecasting in a panel data model with random individual effects and AR(p) remainder disturbances. It utilizes a simple exact transformation for the AR(p) time series process derived by Baltagi and Li (1994) and obtains the generalized least squares estimator for this panel model as a least squares regression. This exact transformation is also used in conjunction with Goldberger’s (1962) result to derive an analytic expression for the best linear unbiased predictor. The performance of this predictor is investigated using Monte Carlo experiments and illustrated using an empirical example.

Keywords: Prediction; Panel data; Random effects; Serial correlation; AR(p) (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207012000891
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Estimation and Prediction in the Random Effects Model with AR(p) Remainder Disturbances (2012) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:29:y:2013:i:1:p:100-107

DOI: 10.1016/j.ijforecast.2012.07.001

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:intfor:v:29:y:2013:i:1:p:100-107