Useful matrix transformations for panel data analysis: a survey

B. H. Baltagi

doi:10.1007/BF02925550

Useful matrix transformations for panel data analysis: a survey

B. H. Baltagi

Research output: Contribution to journal › Article

5 Scopus citations

Abstract

This paper surveys some useful matrix transformations which simplify the derivation of GLS as WLS in an error component model. This is particularly important for large panel data applications where brute force inversion of large data matrices may not be feasible. This WLS transformation is known in the literature as the Fuller and Baltese (1974) transformation and its extension to error component models with heteroscedasticity, serial correlation, unbalancedness as well as a set of seemingly unrelated regressions are considered.

Original language	English (US)
Pages (from-to)	281-301
Number of pages	21
Journal	Statistical Papers
Volume	34
Issue number	1
DOIs	https://doi.org/10.1007/BF02925550
State	Published - Dec 1 1993
Externally published	Yes

Keywords

error components models
spectral decomposition
weighted least squares

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

Access to Document

10.1007/BF02925550

Fingerprint Dive into the research topics of 'Useful matrix transformations for panel data analysis: a survey'. Together they form a unique fingerprint.

Cite this

Baltagi, B. H. (1993). Useful matrix transformations for panel data analysis: a survey. Statistical Papers, 34(1), 281-301. https://doi.org/10.1007/BF02925550

@article{ab563d36c2874543b15169ee21468c42,

title = "Useful matrix transformations for panel data analysis: a survey",

abstract = "This paper surveys some useful matrix transformations which simplify the derivation of GLS as WLS in an error component model. This is particularly important for large panel data applications where brute force inversion of large data matrices may not be feasible. This WLS transformation is known in the literature as the Fuller and Baltese (1974) transformation and its extension to error component models with heteroscedasticity, serial correlation, unbalancedness as well as a set of seemingly unrelated regressions are considered.",

keywords = "error components models, spectral decomposition, weighted least squares",

author = "Baltagi, {B. H.}",

year = "1993",

month = dec,

day = "1",

doi = "10.1007/BF02925550",

language = "English (US)",

volume = "34",

pages = "281--301",

journal = "Statistical Papers",

issn = "0932-5026",

publisher = "Springer New York",

number = "1",

}

TY - JOUR

T1 - Useful matrix transformations for panel data analysis

T2 - a survey

AU - Baltagi, B. H.

PY - 1993/12/1

Y1 - 1993/12/1

N2 - This paper surveys some useful matrix transformations which simplify the derivation of GLS as WLS in an error component model. This is particularly important for large panel data applications where brute force inversion of large data matrices may not be feasible. This WLS transformation is known in the literature as the Fuller and Baltese (1974) transformation and its extension to error component models with heteroscedasticity, serial correlation, unbalancedness as well as a set of seemingly unrelated regressions are considered.

AB - This paper surveys some useful matrix transformations which simplify the derivation of GLS as WLS in an error component model. This is particularly important for large panel data applications where brute force inversion of large data matrices may not be feasible. This WLS transformation is known in the literature as the Fuller and Baltese (1974) transformation and its extension to error component models with heteroscedasticity, serial correlation, unbalancedness as well as a set of seemingly unrelated regressions are considered.

KW - error components models

KW - spectral decomposition

KW - weighted least squares

UR - http://www.scopus.com/inward/record.url?scp=0040674009&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0040674009&partnerID=8YFLogxK

U2 - 10.1007/BF02925550

DO - 10.1007/BF02925550

M3 - Article

AN - SCOPUS:0040674009

VL - 34

SP - 281

EP - 301

JO - Statistical Papers

JF - Statistical Papers

SN - 0932-5026

IS - 1

ER -