Prediction in a Generalized Spatial Panel Data Model with Serial Correlation

Baltagi, Badi H.; Liu, Long

PanelPrediction01152016.pdf (160.76 kB)

Prediction in a Generalized Spatial Panel Data Model with Serial Correlation

journal contribution

posted on 2017-03-10, 10:12 authored by Badi H. Baltagi, Long Liu

This paper considers the generalized spatial panel data model with serial correlation proposed by Lee and Yu (Spatial panels: random components versus fixed effects. International Economic Review 2012; 53: 1369–1412.), which encompasses many of the spatial panel data models considered in the literature, and derives the best linear unbiased predictor (BLUP) for that model. This in turn provides valuable BLUP for several spatial panel models as Special Cases.

Funding

This work received computational support from Computational System Biology Core, funded by the National Institute on Minority Health and Health Disparities (G12MD007591) from the National Institutes of Health.

History

Citation

Journal of Forecasting, 2016, 35 (7), pp. 573-591 (19)

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/Department of Economics

Version

AM (Accepted Manuscript)

Published in

Journal of Forecasting

Publisher

Wiley

issn

0277-6693

eissn

1099-131X

Acceptance date

2016-01-13

Copyright date

2016

Available date

2018-03-21

Publisher DOI

https://doi.org/10.1002/for.2410

Publisher version

http://onlinelibrary.wiley.com/doi/10.1002/for.2410/abstract

Notes

The file associated with this record is under embargo until 24 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

Administrator link

https://leicester.figshare.com/account/articles/10202174

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Keywords

Social Sciences Economics Management Business & Economics prediction panel data fixed effects random effects serial correlation spatial error correlation REMAINDER DISTURBANCES REGRESSION GROWTH

Prediction in a Generalized Spatial Panel Data Model with Serial Correlation

Funding

This work received computational support from Computational System Biology Core, funded by the National Institute on Minority Health and Health Disparities (G12MD007591) from the National Institutes of Health.

History

Citation

Author affiliation

Version

Published in

Publisher

issn

eissn

Acceptance date

Copyright date

Available date

Publisher DOI

Publisher version

Notes

Language

Administrator link

Usage metrics

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Keywords

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