Buyers in many markets face multiple-discrete choices: they can purchase multiple-units as well as multiple-brands at the same time. This paper presents a multiple-discrete choice model for the analysis of differentiated products demand. Users maximize profits by choosing the number of units of each brand they purchase. The author estimates the model using micro-level data on the demand for personal computers. He uses the estimated demand structure to assess the welfare gains from computerization and technological innovation in peripherals. The estimated return on investment in personal computers is 92 percent. Moreover, a 10 percent increase in the performance-to-price ratio of microprocessors leads to a 22 percent gain in the estimated user surplus.

Temporary price reductions (sales) are common for many goods and naturally result in large increases in the quantity sold. Demand estimation based on temporary price reductions may mismeasure the long run responsiveness to prices. In this paper we quantify the extent of the problem and assess its economic implications. We structurally estimate a dynamic model of consumer choice using two years of scanner data on the purchasing behavior of a panel of households. The results suggest that static demand estimates, which neglect dynamics: (i) overestimate own price elasticities by 30 percent; (ii) underestimate cross-price elasticities to other products by up to a factor of 5; and

We study intertemporal price discrimination when consumers can store for future consumption needs. We offer a simple model of demand dynamics, which we estimate using market-level data. Optimal pricing involves temporary price reductions that enable sellers to discriminate between price sensitive consumers, who stockpile for future consumption, and less price-sensitive consumers, who do not stockpile. We empirically quantify the impact of intertemporal price discrimination on profits and welfare. We find that sales (i) capture 25–30 percent of the gap between non-discriminatory profits and (unattainable) third-degree price discrimination profits, (ii) increase total welfare, and (iii) have a modest impact on consumer welfare.

We present a dynamic model of adverse selection to examine the interactions between new and used goods markets. We find that the used market never shuts down, the volume of trade can be large, and distortions are lower than previously thought. New cars prices can be higher under adverse selection than in its absence. An extension to several brands that differ in reliability leads to testable predictions of the effects of adverse selection. Unreliable brands have steeper price declines and lower volumes of trade. We contrast these predictions with those of a model where brands physically depreciate at different rates.

Leasing contracts are extensively used in durable goods markets. These contracts specify a rental rate and an option price at which the used good can be bought on termination of the lease. This option price cannot be controlled when the car is sold. We show that in a world in which quality is observable, this additional control variable is ineffective. Under adverse selection instead, leasing contracts affect equilibrium allocations in a way that matches observed behavior in the car market. Consistent with the data, our model predicts that leased cars have a higher turnover and that off‐lease used cars are of higher quality. Moreover, the model predicts that the recent increase in leasing can be explained by the observed increase in car durability. We show that leasing contracts can improve welfare but that they are imperfect tools. We also show that a producer with market power can benefit from leasing contracts for two reasons: market segmentation and better pricing of the option. Moreover, despite the fact that lessors could structure contracts to prevent adverse selection, we show that this is not in their interest.

We discuss a class of markets for durable goods where efficiency (or approximate efficiency) is obtained despite the presence of information asymmetries. In the model, the number of times a good has changed hands (the vintage of the good) is an accurate signal of its quality, each consumer self-selects into obtaining the vintage that the social planner would have assigned to her, and consumers' equilibrium trading behaviour in secondary markets is not subject to adverse selection. We show that producers have the incentive to choose contracts that lead to the efficient allocation, and to supply the efficient output. We also provide a contrast between leasing contracts, resale contracts, and different kinds of rental contracts. Resale contracts do not lead to the efficient allocation. A specific kind of rental contract provides the appropriate incentives to consumers.

Does the Secondary Life Insurance Market Threaten Dynamic Insurance? by Glenn Daily, Igal Hendel and Alessandro Lizzeri. Published in volume 98, issue 2, pages 151-56 of American Economic Review, May 2008

We study dynamic monopoly pricing of storable goods in an environment where demand changes over time. The literature on durables has focused on incentives to delay purchases. Our analysis focuses on a different intertemporal demand incentive. The key force on the consumer side is advance purchases or stockpiling. In the case of storable goods, the stockpiling motive has recently been documented empirically. We show that, in this environment, if the monopolist cannot commit, then prices are higher in all periods, and social welfare is lower, than in the case in which the monopolist can commit. This is in contrast with the analysis in the literature on the Coase conjecture.

This paper studies regulated health insurance markets known as exchanges, motivated by the increasingly important role they play in both public and private insurance provision. We develop a framework that combines data on health outcomes and insurance plan choices for a population of insured individuals with a model of a competitive insurance exchange to predict outcomes under different exchange designs. We apply this framework to examine the effects of regulations that govern insurers' ability to use health status information in pricing. We investigate the welfare implications of these regulations with an emphasis on two potential sources of inefficiency: (i) adverse selection and (ii) premium reclassification risk. We find substantial adverse selection leading to full unraveling of our simulated exchange, even when age can be priced. While the welfare cost of adverse selection is substantial when health status cannot be priced, that of reclassification risk is five times larger when insurers can price based on some health status information. We investigate several extensions including (i) contract design regulation, (ii) self‐insurance through saving and borrowing, and (iii) insurer risk adjustment transfers.

We compare house sales on a For-Sale-By-Owner (FSBO) platform to Multiple Listing Service (MLS) sales and find that FSBO precommission prices are no lower, but that FSBO is less effective in terms of time to sell and probability of a sale. We do not find direct evidence of the importance of network size as a reason for the lower effectiveness of FSBO. We do find evidence of endogenous platform differentiation: patient sellers use FSBO while patient buyers transact more often on the MLS (where they avoid patient sellers). We discuss the implications for platform competition, two-sided markets, and welfare.