Academic journal article Economic Inquiry

Demand for Differentiated Durable Products: The Case of the U.S. Computer Printer Market

Academic journal article Economic Inquiry

Demand for Differentiated Durable Products: The Case of the U.S. Computer Printer Market

Article excerpt

I. INTRODUCTION

This paper aims to provide a theoretical and empirical description of consumer behavior in a dynamic market for differentiated durable goods. The computer hardware industry serves as an example of the type of market we consider. Markets for computer systems and components, as well as for many other high-technology products, exhibit some striking similarities that are of particular concern for an empirical economist as follows:

* Products are differentiated in multiple dimensions in addition to price.

* Products are durable yielding consumption services over multiple periods.

* Product quality rapidly improves over time.

Empirical work on estimating differentiated product demand systems has been dominated by static discrete choice models with random utility (see Berry, Levinsohn, and Pakes 1995; Goldberg 1995; and Nevo 2001, among others). However, markets for durable goods exhibit several features at odds with their assumption of myopic consumer behavior.

First, traditional static discrete choice models implicitly assume that consumers participate in the market every period, choosing one of the available products or an outside option. Thus, the fraction of consumers who do not buy any product in a given period could only be explained by the high value they assign to the outside alternative. For durable goods, however, purchases are made infrequently and result in a consumer's exiting the market for a significant period of time. Hence, the model needs to account for consumers' outflow from the market arising from their purchase decisions.

Second, a static framework may give a misleading picture of the aggregate sales time pattern in a dynamic industry. In many markets for durable products it is not uncommon to see rapidly improving product quality and falling prices. Given any reasonable set of consumer preferences over the product characteristics space, static discrete choice models for such an industry will tend to predict an upward trend in aggregate sales. This fails to account for a variety of patterns commonly seen in the data.

Third, the evolution of product quality leads to the possibility of intertemporal demand substitution. By forgoing a current purchase, the consumer retains the option to buy a potentially better product in the future. Hence, the decision of when to buy may be just as important for consumers as the decision of what to buy. This trade-off cannot be accounted for in the static framework.

The purpose of this paper is to remedy these shortcomings of static discrete choice models in durable goods markets, with particular attention paid to technological change and the dynamics of new products adoption.

The paper presents a dynamic model of consumer demand for differentiated durable products that explicitly accounts for consumers' expectations of future product quality and consumers' outflow from the market that arises endogenously from their purchase decisions. In this model, the consumer faces a sequence of static discrete choice problems over a non-stationary choice set. We show that for a subclass of random utility models (which include the multinomial logit and the McFadden 1978 generalized extreme value [GEV] model) there exists a scalar-valued sufficient statistic that determines the value of the option to postpone the purchase. This allows us to model industry evolution over a vastly reduced state space and to formalize the consumer's decision of when to buy as an optimal stopping problem. A solution to that problem defines the hazard rate of product adoptions, while the nested discrete choice model determines the alternative-specific purchase probabilities. Integrating individual decisions over the population distribution generates rich dynamics of aggregate and product level sales.

The paper proceeds to present Monte Carlo evidence that ignoring the time dimension of consumer choice will induce a downward bias in the estimates of consumer preferences over quality, sometimes reversing the sign of the coefficients. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.