IncorporatingCredit in Demand Analysis

Incorporating Credit in Demand Analysis Analysis of consumer demand has evolved along two related but distinct lines of thought. Theorists typically begin with the twin assumptions that individuals choose the consumption bundle that maximizes utility, subject to a budget constraint, and that data are available to test the validity of the results. Attention is focused on restrictions such as Slutsky symmetry and homogeneity that are either implicitly or explicitly imposed. For theoretical economists, imposing these restrictions is what differentiates a model of consumer demand from a mere description of the correlation between the exogenous and endogenous variables (Philips 1974). The second school of thought comprises those who must gather the relevant data and use them to make predictions and to analyze policies. These researchers quickly learn that the data are deficient in both the number of observations and in the definitions employed by the data-collection agency. For this group, imposition of restrictions tends to be a little unsettling because they are often rejected by the data. Restrictions tend to be imposed only when they result in parameters that conform to those predicted by the theory, even when the imposition of the restrictions causes a sign reversal in the estimated parameters. The conformation of estimated results to those predicted by the theory is regarded more as a test of the model than a test of the theory (Chalfant 1987). Where the data are weak, it is more logical to build models that take into account data limitations than to build theoretical models that can never be tested. The example used in this paper is estimation of the impact of credit use on consumer expenditure patterns. There is a fundamental problem with publicly available statistics as they relate to this area. Governments and corporations define expenditures by the date when the consumer agrees to purchase rather than the date when the consumer must find the required funds. The monthly U.S. per capita expenditures on durables, nondurables, services, and savings sum to the per capita disposable income. Yet Americans spend almost 18 percent of their disposable incomes repaying loans, an item that does not appear as an expenditure item (Paquette 1986). If one purchases a new house, the entire value of the transaction is recorded as a one-period increase in housing expenditures. To the individual who has made the purchase, however, it represents an agreement to consign future expected income to a budgetary item called mortgage repayments. Periodically, the government does publish surveys of actual consumer expenditures, but these are useless if it is necessary to examine the impact of changing prices, interest rates, income shocks, and other economic conditions on expenditure patterns because all consumers face the conditions prevalent when the survey was undertaken. The economist has three options. The first is to assume that expenditure figures measure how individuals spend money (rather than measuring sales made by corporations) and estimate a demand system by using available data. This is equivalent to assuming that consumers pay cash for all items. The second option is to assume that correct data exist and to examine the intertemporal optimization decision within a dynamic demand system. The lack of suitable data means that these models can never be tested.1 The third possible option, discussed in this paper, is to begin with a description of data limitations, to discuss which aspects of the theory are relevant to the particular data set, and to estimate the model within the confines of the relevant theory. The test of any hypothesis regarding consumer behavior is, therefore, a joint test of both the underlying theoretical model and of the specified hypothesis itself. Hence, the theory used is an unrestrictive as possible. 1 In fact, most intertemporal demand equations that have been estimated assume that the intertemporal consumer choice can be decentralized. …