2008
DOI: 10.1002/for.1047
|View full text |Cite
|
Sign up to set email alerts
|

Forecasting with panel data

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. Copyright © 2008 John Wile… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

2
273
0
9

Year Published

2011
2011
2024
2024

Publication Types

Select...
9
1

Relationship

2
8

Authors

Journals

citations
Cited by 464 publications
(284 citation statements)
references
References 82 publications
(92 reference statements)
2
273
0
9
Order By: Relevance
“…In this study, we adopt an extension of Arellano and Bover (1995) by Roodman (2009ab). Instead of employing first differences as instruments, the extension adopts forward orthogonal deviations which have been established in prior literature to limit over-identification and restrict instrument proliferation (see Baltagi, 2008;Love & Zicchino, 2006). A two-step procedure is adopted in place of the one-step process in order to correct for heteroscedasticity.…”
Section: Generalised Methods Of Moments: Specification Identificationmentioning
confidence: 99%
“…In this study, we adopt an extension of Arellano and Bover (1995) by Roodman (2009ab). Instead of employing first differences as instruments, the extension adopts forward orthogonal deviations which have been established in prior literature to limit over-identification and restrict instrument proliferation (see Baltagi, 2008;Love & Zicchino, 2006). A two-step procedure is adopted in place of the one-step process in order to correct for heteroscedasticity.…”
Section: Generalised Methods Of Moments: Specification Identificationmentioning
confidence: 99%
“…In this study, we instead employ the Arellano and Bover (1995) extension by Roodman (2009aRoodman ( , 2009b which uses forward orthogonal deviations instead of first differences because it has been renowned to restrict instrument proliferation and control for cross-sectional dependence (Baltagi, 2008;Love & Zicchino, 2006). A two-step specification procedure is adopted because it controls for heteroscedasticity.…”
Section: Estimation Techniquementioning
confidence: 99%
“…The estimation technique has been documented to: limit the proliferation of instruments or restrict over-identification and control for cross-sectional dependence (see Love and Zicchino 2006;Baltagi 2008). A two-step approach is adopted in the specification because it controls for heteroscedasticity.…”
Section: Estimation Techniquementioning
confidence: 99%