Double-length regressions for linear and log-linear regressions with AR(1) disturbances

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4 Scopus citations

Abstract

This paper derives Lagrange Multiplier tests based on double-length artificial regressions (DLR) for testing linear and log-linear regressions with AR(1) disturbances against Box-Cox alternatives. These DLR tests are easier to compute than the corresponding likelihood ratio tests, and are easily generalized to test jointly for functional form and serial correlation. Two illustrative examples are given to show the importance of jointly testing for functional form and serial correlation.

Original languageEnglish (US)
Pages (from-to)199-209
Number of pages11
JournalStatistical Papers
Volume40
Issue number2
DOIs
StatePublished - Apr 1999
Externally publishedYes

Keywords

  • Box-Cox transformation
  • Double-Length Regressions
  • Lagrange Multiplier
  • Serial Correlation

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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