Analysis of distributed lag models with applications to consumption function estimation

TLDR: In this paper, the authors present maximum likelihood and Bayesian estimation procedures for estimating the parameters of a typical distributed lag model under four alternative sets of assumptions regarding disturbance terms' properties.

Abstract: SINCE KOYCK'S pioneering work, distributed lag models have come to play an important role in econometrics and much work has been done to develop methods for analyzing them-see eg Koyck [15], Klein [12], Solow [20], Fuller and Martin [5], Malinvaud [18], Hannan [9], Liviatan [17], Amemiya and Fuller [1], Zellner and Park [25], Thornber [21], Waud [23], Dhrymes [3], and Griliches [7] In the present paper we present maximum likelihood and Bayesian estimation procedures for estimating the parameters of a typical distributed lag model under four alternative sets of assumptions regarding disturbance terms' properties Then these procedures and assumptions are employed in analyses of a sample of United States quarterly consumption data to illustrate their application and to show the sensitivity of inferences to the assumptions made about disturbance terms' properties We also compute posterior probabilities associated with four alternative models The plan of the paper is as follows In Section 2, the model to be analyzed is described and alternative assumptions about disturbance terms are introduced Section 3 contains a discussion of maximum likelihood techniques and application of them in the analysis of US quarterly consumption data Then in Sections 4 and