Testing linear and loglinear error components regressions against Box-Cox alternatives

Badi H. Baltagi

doi:10.1016/S0167-7152(96)00110-1

Testing linear and loglinear error components regressions against Box-Cox alternatives

Badi H. Baltagi

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

This paper derives Lagrange multiplier tests based on double-length artificial regressions for testing linear and loglinear error component regressions against Box-Cox alternatives. These tests are easy to implement and should prove useful in panel data regressions.

Original language	English (US)
Pages (from-to)	63-68
Number of pages	6
Journal	Statistics and Probability Letters
Volume	33
Issue number	1
DOIs	https://doi.org/10.1016/S0167-7152(96)00110-1
State	Published - Apr 15 1997
Externally published	Yes

Keywords

Box-cox transformation
Double-length regressions
Error components
Lagrange multiplier

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/S0167-7152(96)00110-1

Cite this

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title = "Testing linear and loglinear error components regressions against Box-Cox alternatives",

abstract = "This paper derives Lagrange multiplier tests based on double-length artificial regressions for testing linear and loglinear error component regressions against Box-Cox alternatives. These tests are easy to implement and should prove useful in panel data regressions.",

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KW - Box-cox transformation

KW - Double-length regressions

KW - Error components

KW - Lagrange multiplier

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JO - Statistics and Probability Letters

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Testing linear and loglinear error components regressions against Box-Cox alternatives

Abstract

Keywords

ASJC Scopus subject areas

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