Money demand revisited: An operational subjective approach

Abstract

SUMMARY This paper proposes a method of data analysis founded on the philosophy and understanding of uncertain knowledge developed by Bruno de Finetti. Specifically, the paper investigates the informational content of interest rates for the prediction of Ml. This empirical application replicates that of Cooley and Leroy (1981) and McAleer, Pagan, and Volker (1985), but the procedures and their interpretation follow the operational subjective approach. The issue of an autocorrelated error structure is recast in the operational subjective context. Methods are developed to assess the interest sensitivity of the demand for money in this context. This paper illustrates an operational method of data analysis in the context of linear models. The procedures advocated are founded on the subjective theory of probability originated by Bruno deFinetti (1974, 1975) and enhanced by L. J. Savage (1954). This foundational position denies the existence of a 'true' model and its concomitant parameters. The function of a model is its assistance in generating predictive distributions of observable unknown quantities. A model's performance at prediction is empirically observable. This proposed method of econometric analysis is illustrated with an applied example taking advantage of a previous, well-known application confronting the appropriateness of econometric practices. The example concerns money demand as measured by Ml with particular emphasis on the informational content of interest rates for the forecasting distribution of Ml. Cooley and Leroy (1981) examined the estimation of money demand, employing the Bayesian method of extreme bounds analysis developed in Leamer (1978). Although Bayesian in approach the method focuses on parameter estimation and retains the conviction of standard techniques in the reality of the model and in the reality of the model parameters. McAleer, Pagan, and Volker (1985) re-examine the same model and data from a frequentist approach, yielding an appropriate example with which to contrast the method presented here and its interpretation.