Selecting the best linear regression model. A classical approach

Donald Lien, Quang H. Vuong

    Research output: Contribution to journalArticlepeer-review


    In this paper, we apply the model selection approach based on likelihood ratio (LR) tests developed in Vuong (1986) to the problem of choosing between two normal linear regression models which are non-nested. We explicitly derive the procedure when the competing linear models are both misspecified. Some simplifications arise when the models are contained in a larger correctly specified linear regression model, or when one computing linear model is correctly specified.

    Original languageEnglish (US)
    Pages (from-to)3-23
    Number of pages21
    JournalJournal of Econometrics
    Issue number1
    StatePublished - May 1987

    ASJC Scopus subject areas

    • Economics and Econometrics


    Dive into the research topics of 'Selecting the best linear regression model. A classical approach'. Together they form a unique fingerprint.

    Cite this