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 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.

We estimate a bargaining model of competition between hospitals and managed care organizations (MCOs) and use the estimates to evaluate the effects of hospital mergers. We find that MCO bargaining restrains hospital prices significantly. The model demonstrates the potential impact of coinsurance rates, which allow MCOs to partly steer patients toward cheaper hospitals. We show that increasing patient coinsurance tenfold would reduce prices by 16 percent. We find that a proposed hospital acquisition in Northern Virginia that was challenged by the Federal Trade Commission would have significantly raised hospital prices. Remedies based on separate bargaining do not alleviate the price increases.

The prices of for-profit academic journals have increased rapidly over the past decade (Barbara Albee and Brenda Dingley, 2001). There remains substantial debate as to the explanation for these increases. Among those put forward are the increased concentration of the journal industry (see e.g., McCabe, 2002) and the relatively recent effort by major publishers to bundle print and electronic journals (Aaron S. Edlin and Rubinfeld, 2004). While both explanations are undoubtedly important, what is missing is the significant role of the primary customers of journal publishers—the academic libraries. As agents of college and university faculties, libraries serve the interests of their principals while having only limited information about faculty journal demands. Facing little or no hard budget constraint, faculty are unlikely or unwilling to make difficult allocative choices. As a result, libraries have been making hard choices for years (between journals and books, and among journals), in a world of increasing budgetary pressure. Given that electronic transmission of knowledge is becoming increasingly important, an understanding of the reasons for the increases in journal prices is a vital element in the ongoing discussion of best mechanisms by which scholarly communications can be disseminated. In this paper, we formulate a model of library journal demand and suggest how it can be used to analyze the optimal pricing of journals by publishers. This represents part of a larger project whose long-range goal is to explain the pattern of journal pricing over time, and to

Food purchases differ substantially across countries. We use detailed household-level data from the United States, France, and the United Kingdom to (i) document these differences; (ii) estimate a demand system for food and nutrients; and (iii) simulate counterfactual choices if households faced prices and nutritional characteristics from other countries. We find that differences in prices and characteristics are important and can explain some difference (e.g., United States–France difference in caloric intake) but generally cannot explain many of the compositional patterns by themselves. Instead, it seems an interaction between the economic environment and differences in preferences is needed to explain cross-country differences.