On the Estimation of Dynamic Demand Functions

Abstract

RECENT years have seen considerable progress toward an integration of the theory of consumer's choice with empirical demand analysis. Theory has been extended so as to bring dynamic adjustment and the effects of past expenditure decisions (primarily through the introduction of certain state variables) into its purview,1 while on the empirical side there now exist a number of studies whose demand functions respect to a letter the restrictions imposed by classical theory.2 Unlike the demand theorist, content to assume the existence of continuous partial derivatives through the second order and to specify the signs of first derivatives, the applied analyst must go considerably further and specify the actual analytical form of the utility function. Herein, however, lies one of the major obstacles to the continued progress in applied demand analysis, for the list of functions which are rich enough to incorporate the restrictions imposed by theory, but yet sufficiently simple to be estimated with the data and techniques at hand is not lengthy. Included in this list are: (1). The additive quadratic utility function used by Houthakker and Taylor (1970) and also by Phlips (1971); (2). The linear-expenditure system based on the Geary-Samuelson utility function employed by Stone and his associates (1954, 1965) and most recently by Phlips (1972); and (3). The Rotterdam system of demand functions developed by Barten and Theil.3 The present work was motivated initially by a desire to devise a better method of estimating the additive quadratic model (AQM) than that used by Houthakker and Taylor. In particular, H and T observed a tendency for the estimated marginal utility of income to decrease sharply at the very end of the sample period, and averred that this probably reflected a defect in the method of estimation (p. 230). However, once we began exploring this, it became clear that the defect was in the quadratic utility function itself. Accordingly, we then undertook a critical look at the appropriateness of the AQM as a tool for empirical research, and in so doing decided to do the same with the linear expenditure system (LES).