Tests for serial dependence and other specification analysis in models of markets in disequilibrium

Anil K. Bera, Peter M. Robinson

Research output: Contribution to journalArticlepeer-review


The assumption of serial independence of disturbances is the starting point of most of the work done on analyzing market disequilibrium models. We derive tests for serial dependence given normality and homoscedasticity using the Lagrange multiplier (LM) test principle. Although the likelihood function under serial dependence is very complicated and involves multiple integrals of dimensions equal to the sample size, the test statistic we obtain through the LM principle is very simple. We apply the test to the housing-start data of Fair and Jaffee (1972) and study its finite sample properties through simulation. The test seems to perform quite well in finite samples in terms of size and power. We present an analysis of disequilibrium models that assumes that the disturbances are logistic rather than normal. The relative performances of these distributions are investigated by simulation.

Original languageEnglish (US)
Pages (from-to)343-352
Number of pages10
JournalJournal of Business and Economic Statistics
Issue number3
StatePublished - Jul 1989


  • Finite sample distribution
  • Lagrange multiplier test
  • Logistic distribution
  • Nonnormality
  • Simulation study
  • Size and power of a test

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty


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