In many industries, consumers choose not only what to purchase but when to purchase. However, economists lack compelling models of aggregate demand for this case and many papers specify static models in industries that clearly have dynamic features. In order to address this problem, this study extends several previous lines of research to specify and estimate the first dynamic random coefficients model of consumer demand designed for aggregate data. This study uses this method to analyze little-studied data sets on two visible consumer electronics industries, digital cameras and DVD players. The principal focus of this study is to develop new methods to estimate the dynamics of consumer demand with aggregate data.
Using these methods, this work studies several important applied questions in these industries. In particular, this research seeks to evaluate why prices fall so dramatically in these industries, a ubiquitous feature of many new durable goods markets. While the typical explanations of intertemporal price discrimination, entry and cost declines have long been recognized, no previous work has provided an empirical evaluation of their relative importance. This study also investigates welfare and price indices in these industries. Standard price indices are problematic when consumers can delay purchase because indices do not handle situations in which quantity expands over time or when consumers use current price changes to predict the optimal purchase time. These features are naturally accounted for in the proposed model and are expected to be important in the data sets under consideration. Thus, another contribution of this study is that it provides answers to these questions, based on theoretically and empirically coherent models.
There are two important broader implications of this study. First, a new methodology for estimating consumer demand is developed. Computer code and algorithms for implementing the methodology will be distributed on the World Wide Web by the authors. The proposed methods can be widely used by other researchers for other industries. Second, the results could have important broader implications for policy makers. For instance, the Coase conjecture suggests that if consumers know prices will fall in the future, a monopolist may have little market power even if it is protected by barriers to entry. Empirical analysis of this issue could be important for merger analysis and other questions faced by a competition authority. Research about how to evaluate price indices are of significant interest to government agencies that create these indices, and these indices impact the economy in a large variety of ways.
