Approximation bias in linearized Euler equations

Sydney Ludvigson, Christina H. Paxson

    Research output: Contribution to journalArticlepeer-review


    A wide range of empirical applications rely on linear approximations to dynamic Euler equations. Among the most notable of these is the large and growing literature on precautionary saving that examines how consumption growth and saving behavior are affected by uncertainty and prudence. Linear approximations to Euler equations imply a linear relationship between expected consumption growth and uncertainty in consumption growth, with a slope coefficient that is a function of the coefficient of relative prudence. This literature has produced puzzling results: estimates of the coefficient of relative prudence (and the coefficient of relative risk aversion) from linear regressions of consumption growth on uncertainty in consumption growth imply estimates of prudence and risk aversion that are unrealistically low. Using numerical solutions to a fairly standard intertemporal optimization problem, our results show that the actual relationship between expected consumption growth and uncertainty in consumption growth differs substantially from the relationship implied by a linear approximation. We also present Monte Carlo evidence that shows that the instrumental-variables methods that are commonly used to estimate the parameters correct some, but not all, of the approximation bias.

    Original languageEnglish (US)
    Pages (from-to)242-256
    Number of pages15
    JournalReview of Economics and Statistics
    Issue number2
    StatePublished - May 2001

    ASJC Scopus subject areas

    • Social Sciences (miscellaneous)
    • Economics and Econometrics


    Dive into the research topics of 'Approximation bias in linearized Euler equations'. Together they form a unique fingerprint.

    Cite this