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Diagnostic Testing: An Application to the Demand for M1

In: Cointegration


  • Glenn Otto


Diagnostic or specification tests are typically used as a means of indicating model inadequacy or failure. For example in the case of a linear regression model which is estimated by ordinary least squares (OLS), a series of diagnostic tests could be used to indicate whether any of the assumptions required for OLS to be the best linear unbiased estimator (BLUE) appear to be violated. These assumptions include a serially uncorrelated and homoscedastic error term, absence of correlation between the error term and the regressors and correct specification of the conditional mean function, i.e. no omitted variables and appropriate functional form.

Suggested Citation

  • Glenn Otto, 1994. "Diagnostic Testing: An Application to the Demand for M1," Palgrave Macmillan Books, in: B. Bhaskara Rao (ed.), Cointegration, chapter 6, pages 161-184, Palgrave Macmillan.
  • Handle: RePEc:pal:palchp:978-1-349-23529-2_6
    DOI: 10.1007/978-1-349-23529-2_6

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    Cited by:

    1. Chor Foon Tang, 2013. "Evidence on Structural Instability in the Japanese Money Demand Function," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(3), pages 255-272, August.
    2. Tang, Chor Foon, 2007. "The stability of money demand function in Japan: Evidence from rolling cointegration approach," MPRA Paper 19807, University Library of Munich, Germany.


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