This paper specifies and estimates a dynamic model of consumer preferences for new durable goods with persistent heterogeneous consumer tastes, rational expectations about future products and repeat purchases over time. Most new consumer durable goods, particularly consumer electronics, are characterized by relatively high initial prices followed by rapid declines in prices and improvements in quality. The evolving nature of product attributes suggests the importance of modeling dynamics in estimating consumer preferences. We estimate the model on the digital camcorder industry using a panel data set on prices, sales and characteristics. We find that dynamics are a very important determinant of consumer preferences and that estimated coefficients are more plausible than with traditional static models. We use the estimates to investigate the value of new consumer goods and intertemporal elasticities of demand.

This article examines how product and consumer characteristics moderate the influence of online consumer reviews on product sales using data from the video game industry. The findings indicate that online reviews are more influential for less popular games and games whose players have greater Internet experience. The article shows differential impact of consumer reviews across products in the same product category and suggests that firms’ online marketing strategies should be contingent on product and consumer characteristics. The authors discuss the implications of these results in light of the increased share of niche products in recent years.

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This paper reviews a framework for numerically analyzing dynamic interactions in imperfectly competitive industries. The framework dates back to Ericson & Pakes (1995), but it is based on equilibrium notions that had been available for some time be-fore, and it has been extended in many ways by different authors since. The framework requires as input a set of primitives which describe the institutional structure in the industry to be analyzed. The framework outputs profits and policies for every incum-bent and potential entrant at each possible state of the industry. These policies can be used to simulate the distribution of sample paths for all firms from any initial industry structure. The sample paths generated by the model can be quite different depending on the primitives that are fed into it, and most of the extensions were designed to enable the framework to accommodate empirically relevant cases that required modification of the initial structure. The sample paths possess similar properties to those observed in (the recently made available) panel data sets on industries. These sample paths can be used either for an analysis of the likely response to a policy or an environmental change,

We estimate a model of dynamic oligopoly with durable goods and endogenous innovation to examine the effect of competition on innovation in the PC microprocessor industry. Firms make dynamic pricing and investment decisions while accounting for the dynamic behavior of consumers who anticipate product improvements and price declines. We extend the dynamic oligopoly framework of Ericson and Pakes (1995) to incorporate durable goods. Our alternative approach to bounding the state space yields an endogenous long-run rate of innovation. Counterfactual simulations reveal that although consumer surplus is higher with competition from AMD, innovation is lower.

We present an empirical framework to analyze real-world sales-force compen-sation schemes, and report on a multi-million dollar, multi-year project involv-ing a large contact lens manufacturer at the US, where the model was used to improve sales-force contracts. The model is built on agency theory, and solved using numerical dynamic programming techniques. The model is exi-ble enough to handle quotas and bonuses, output-based commission schemes, as well as ratcheting of compensation based on past performance, all of which are ubiquitous in actual contracts. The model explicitly incorporates the dy-namics induced by these aspects in agent behavior. We apply the model to a rich dataset that comprises the complete details of sales and compensation plans for the …rms US sales-force. We use the model to evaluate pro…t-improving, theoretically-preferred changes to the extant compensation scheme. These rec-ommendations were then implemented at the focal …rm. Agent behavior and output under the new compensation plan is found to change as predicted. The

This paper develops a framework to measure “tipping”—the increase in a firm’s market share dominance caused by indirect network effects. Our measure compares the expected concentration in a market to the hypothetical expected concentration that would arise in the absence of indirect network effects. In practice, this measure requires a model that can predict the counter-factual market concentration under different parameter values capturing the strength of indirect network effects. We build such a model for the case of dynamic standards competition in a market characterized by the classic hardware/software paradigm. To demonstrate its applicability, we calibrate it using demand estimates and other data from the 32/64-bit generation of video game consoles, a canonical example of standards competition with indirect network effects. In our example, we find that indirect network effects can lead to a strong, economically significant increase in market concentration. We also find important roles for beliefs on both the demand side, as consumer’s tend to pick the product they expect to win the standards war, and on the supply side, as firms engage in penetration pricing to invest in growing their networks.

We develop a dynamic model of experience goods pricing with independent private valuations. We show that the optimal paths of sales and prices can be described in terms of a simple dichotomy. In a mass market, prices are declining over time. In a niche market, the optimal prices are initially low followed by higher prices that extract surplus from the buyers with a high willingness to pay. We consider extensions of the model to integrate elements of social rather than private learning and turnover among buyers. I.

We propose and estimate a model of dynamic oligopoly with durable goods and endogenous innovation. Firms make dynamic pricing and investment decisions while taking into account the dynamic behavior of consumers who anticipate the product improvements and price declines. The distribution of currently owned products is a state variable that affects current demand and evolves endogenously as consumers make replacement purchases. Our work extends the dynamic oligopoly framework of Ericson and Pakes (1995) to incorporate durable goods. We propose an alternative approach to bounding the state space that is less restrictive of frontier firms and yields an endogenous steady-state rate of innovation. Using a simulated minimum distance estimator, we estimate the model for the PC microprocessor industry and perform counterfactuals to measure the benefits of competition. Consumer surplus is 4.1 percent higher ($17 billion per year) with AMD than if Intel were a monopolist. Innovation, however, would be higher without AMD. We also show that prices and profits are substantially higher when firms correctly account for the dynamic nature of demand, compared to an alternative scenario in which they mistakenly ignore the effect of current prices on future demand. Finally, equilibrium prices, profits, innovation, and consumer surplus are all increasing in the consumer’s discount factor.

As high-tech markets mature, replacement purchases inevitably become the dominant proportion of sales. Despite the clear importance of replacement, little work examines the separate roles of adoption and replacement. The analysis is complicated by the fact that a consumer’s decision to replace a product is dynamic because high-tech markets undergo both rapid improvements in quality and falling prices. To address these issues, I develop and estimate a dynamic consumer demand model that explicitly accounts for the replacement decision when consumers are uncertain about both future product price and quality. Using a unique data set from the PC processor industry, I show how to combine aggregate data on sales and product ownership to infer replacement behavior. The results reveal substantial variation in replacement behavior over time, and this heterogeneity provides an opportunity for managers to tailor their product introduction and pricing strategies to target the particular segment of consumers that is most likely to replace in the near future.