Industrial organization.

• Author: Rose, Nancy L.
• Position: Program Report

The NBER's Program on Industrial Organization (IO) begins its third decade with a core of 60 program members, including 15 whose primary affiliations are in another NBER Program. The Program's meetings attract submissions from a large and diverse set of researchers, and are lively sessions with 75 to 90 scholars typically in attendance. The IO Program produces important applied research on a broad range of industries and topics, increasingly at the intersection with such other NBER Programs as Environmental and Energy Economics, Productivity, and Health Care. That commonality is recognized with frequent joint program meetings and contiguous Summer Institute sessions with other NBER groups. In 2012, IO Program members Aviv Nevo and Ariel Pakes delivered the annual Summer Institute Methods Lectures, focusing on the econometrics of demand estimation and related methodologies.

This report describes work in just three of the Program's areas: modeling consumer choice; the industrial organization of the digital economy; and lessons for designing government auctions. Readers interested in exploring the broader range of NBER work in IO are encouraged to visit https://www.nber.org/papersbyprog/IO.html

Consumer Choice

Empirical economists in the field of IO have devoted substantial attention to modeling the determinants of demand across a variety of settings. For some time, NBER researchers have been active in the design, innovation, and evaluation of methods to estimate demand based on neoclassical theories of consumer utility maximization. Nevo and Pakes discussed this in their 2012 Methods Lectures (1) and dozens of NBER Working Papers have been published in this area. (2) In recent years, empirical researchers increasingly have turned their attention to analyzing the underpinnings of individual choice, for example characterizing the implications of deviations from standard neoclassical models of optimization behavior and the role of information in markets.

Consumer Behavior

The detailed microdata that are the mainstay of much empirical IO research have proved useful for identifying departures from conventional models of consumer utility maximization. A body of work in this area has looked at automobile purchases, one of the most significant consumer purchase decisions for most households. Meghan Busse, Florian Zettlemeyer, and co-author Duncan Simester (13140) document consumer responses to "price cues" in the context of a Big Three automaker "Employee Discount Pricing" promotion in the summer of 2005. They find that consumers responded to this promotion with unprecedented increases in new car purchases, even though prices during the promotion were not substantially lower than immediately prior to it. Indeed, sales increased even for some models with higher prices during the promotion. While the researchers point out that this behavior can be consistent with rational reliance on (noisy) price signals, their results are cautionary for those who would model consumers as responding primarily to observed prices. In another paper on auto purchases, Nicola Lacetera, Devin Pope, and Justin Sydnor (17030) look at heuristic information processing in used car purchases. They find that sale prices drop discontinuously at exactly 10,000 mile odometer readings, consistent with customers focusing on the leftmost digit of the odometer reading rather than incorporating the full odometer reading into their valuation. They estimate $2.4 billion of mispricing as a result. Busse and Pope and their co-authors (18212) use a sample of 40 million vehicle purchases and 4 million house purchases to explore the role of projection bias -- the tendency to over-predict the degree to which one's future tastes will resemble one's current tastes -- in purchasing behavior. They find that weather at the time of purchase overly influences purchase decisions for these major durables. They meticulously explore alternative explanations for this finding, and their results rule out explanations grounded in neoclassical utility maximization. For example, spring or fall days that are unusually warm and sunny induce additional convertible sales, which are not merely timeshifted. Moreover, the convertibles purchased on such days are more likely to be traded in quickly, consistent with misestimating future tastes.

Justine Hastings and Jesse Shapiro (18248) analyze "mental accounting" in household purchases of gasoline. Their results consistently reject the null hypothesis that households treat spending on gasoline as fungible with other income. Instead, when gasoline prices rise, consumers disproportionately substitute to (less expensive) lower octane gasoline, far more than the substitution that occurs for similar income effects from non-gasoline price sources; the converse is true when gas prices rise. This complements work that Hastings has done with other collaborators (13614) on how households adjust grocery purchases when gasoline prices change. Andrei Shleifer and his collaborators (17947) develop a model of context-dependent consumer choice focused on "salient attributes" that is consistent with this mental accounting behavior, and use their model to study discounts in a variety of settings.

Better understanding of consumer choice is an important input to modeling firm decisions. Julio Rotemberg (13754) models the implications for firms and policymakers of consumers who do not make effective use of price information, and then suffer ex post regret or anger as a...