Industrial Organization

Industrial Organization

Members of the NBER's Industrial Organization Program met February 7-8 at Stanford University. Research Associate Julie H. Mortimer of Boston College and Faculty Research Fellows Christopher Neilson of Princeton University and Michael Sinkinson of Yale University organized the meeting. These researchers' papers were presented and discussed:


Mo Xiao, University of Arizona, and Zhe Yuan, Alibaba Group

License Complementarity and Package Bidder: The U.S. Spectrum Auctions

U.S. spectrum licenses cover geographically distinct areas and often complement each other. A bidder seeking to acquire multiple licenses is then exposed to risks of winning only isolated patches. Xiao and Yuan investigate whether allowing bidders to bid for (predefined) packages of licenses alleviates the exposure problem and improves allocation efficiency. Using Auction 73 bidding data, the researchers model the bidding process as an entry game with interdependent markets and evolving bidder belief. Bidders' decisions on bidding (and not bidding) provide bounds on licenses' stand-alone values and complementarity between licenses. With estimated bidder valuation, the researchers conduct counterfactual analyses to show that the effects of package bidding on bidders' exposure risks depend on package format and package size. More importantly, package bidding increases auction revenue substantially, at the cost of reducing bidder surplus and increasing license allocation concentration.


Thomas R. Covert, University of Chicago and NBER, and Richard Sweeney, Boston College

Relinquishing Riches: Auctions vs Informal Negotiations in Texas Oil and Gas Leasing (NBER Working Paper No. 25712)

Covert and Sweeney compare outcomes from informally negotiated oil and gas leases to those awarded via centralized auction. They focus on Texas, where legislative decisions in the early twentieth century assigned thousands of proximate parcels to different mineral allocation mechanisms. The researchers show that during the fracking boom, which began unexpectedly decades later, auctioned leases generated at least 40 percent larger upfront payments and 60 percent more output than negotiated leases did. These results suggest large potential gains from employing centralized, formal mechanisms in markets that traditionally allocate in an unstructured fashion, including the broader $3 trillion market for privately owned minerals.


Yeon-Koo Che and Dong Woo Hahm, Columbia University, and Yinghua He of Rice University

Leveraging Uncertainties to Infer Preferences: Robust Analysis of School Choice

Recent evidence suggests that market participants make mistakes (even) in a strategically straightforward environment but seldom with significant payoff consequences. Uncertainties arising from the use of lotteries or other sources increase payoff consequences of certain mistakes, and force participants to take care to avoid them. Consequently, uncertainties limit the extent to which certain mistakes are made, thus making it possible for one to infer some preference relations reliably. Che, Hahm, and He propose a novel method of exploiting the uncertainties present in a matching environment to systematically and robustly infer student preferences over schools based on their rank-order lists data. The method consists of three steps: (i) simulating the underlying structure of uncertainties present in the environment, (ii) extracting preference relations revealed under the simulated uncertainties, and then (iii) extending the revealed preference relations via the axiom of transitivity. Depending on the type of uncertainties present, the method rationalizes a variety of procedures, ranging from truthful-reporting assumption at one extreme (full-support uncertainty) to the stability assumption at the other extreme (when there is little uncertainty). Further, the researchers refine their method to strengthen the robustness of the revealed preferences in the presence of participants making even some payoff-relevant mistakes, and explore ways to optimally balance the tradeoff between robustness and efficiency in preference estimation. They apply their methods to estimate student preferences through a Monte Carlo analysis capturing canonical school choice environment with single tie-breaking lotteries. Finally, the researchers apply their methods as well as other existing methods to New York City high school assignment data to explore the implications for preference estimation and counterfactual analysis under a possible policy intervention.


Itai Ater, Tel Aviv University, and Oren Rigbi, Ben-Gurion University

Price Transparency, Media and Informative Advertising

Ater and Rigbi study the effects of a regulation that required Israeli supermarkets to post online the prices of all items sold in their brick-and-mortar stores. Using a differences-in-differences research design and multiple complementary control groups, the researchers show that prices have declined by 4% to 5% after the regulation, primarily in premium chains. Price dispersion has also dropped as chains adopted a uniform pricing strategy, setting similar prices across same-chain stores. To uncover the underlying mechanisms, the researchers test predictions based on Robert and Stahl (1993). Consistent with these predictions they find the following the transparency regulation: (1) hard-discount chains extensively used ads stressing their low prices, (2) to gain credibility these ads referenced to price-comparison surveys which were frequently conducted by the media, (3) the use of media-based ads increased during weeks in which prices declined, (4) price-comparison websites that became available were hardly accessed by consumers. Ater and Rigbi's findings highlight the importance of the media in facilitating informative advertising, and the role of advertising in promoting competition.


Amil Petrin, University of Minnesota and NBER; Emmanuel Dhyne, National Bank of Belgium; and Valerie Smeets and Frederic Warzynski, Aarhus University

Theory for Extending Single-Product Production Function Estimation to Multi-Product Settings

Petrin, Dhyne, Smeets, and Warzynski introduce a new methodology for estimating multi-product production functions. It embeds the seminal contributions of Diewert (1973) and Lau (1976) in a semi-parametric econometric framework following Olley and Pakes (1996). The researchers address the simultaneity of inputs and outputs while allowing for and estimating one unobserved technical efficiency term for each firm-product, each one of which may be freely correlated with inputs and outputs. They show how to translate the structural parameters into the reduced form parameters that give the elasticity of each output with respect to each input. For each output the sum of these input coefficients is the returns to scale for that output. The researchers show how to use these estimates to recover estimates of firm-product marginal costs by extending the Hall (1988) single-product result to their multi-product setting. The main advantage of their framework is that it does not require multi-product production to be a collection of single-product production functions, which rules out the possibility that outputs are substitutes or complements with one another. The researchers' empirical results using panel multi-production production data are largely consistent with their theoretical restrictions and strongly reject the single-product production approximation to multi-product production.


Zach Y. Brown, University of Michigan, and Jihye Jeon, Boston University

Endogenous Information and Simplifying Insurance Choice

Insurance contracts are complicated and individuals may choose how much time and effort to spend understanding and comparing plans. Building on the rational inattention literature, Brown and Jeon develop a parsimonious demand model in which individuals choose how much to research difficult to observe characteristics, affecting the accuracy of their beliefs and subsequent choices. The model predicts that individuals acquire more information when the stakes are higher. Using prescription drug insurance data, the researchers show that the model provides an explanation for behavior that is inconsistent with standard demand models. The researchers estimate an empirical model of insurance demand and find that the marginal cost of acquiring information is higher for older enrollees and those with less previous experience choosing a plan. Counterfactual analysis sheds light on the welfare losses due to information frictions and how policy makers can restrict plan choice or decrease cost sharing to simplify decision-making and raise welfare.


Xing Li and Wesley Hartmann, Stanford University, and Tomomichi Amano, Harvard University

Preference Externality Estimators: A Comparison of Border Approaches and IVs

Li, Hartmann, and Amano document that identification strategies exploiting cross-border differences in treatment are a variant of the preference externality estimator more recently developed in the industrial organization literature. Waldfogel (1999) coined the term preference externality to describe how the aggregate tastes of heterogenous consumers can influence the products made available to one another within a common market. The externality forms the basis for an instrumental variable estimator where, after conditioning on observed preference determinants for a focal consumer type, the aggregate observables within the market, which vary by the preferences of other types, influence the focal type's "treatment" but are excluded from the focal type's outcome equation. Variation in treatment across geographic borders similarly arises from an externality where otherwise comparable individuals near a border face different policies because of different externalities from their respective aggregate regions. The researchers use an advertising application to compare the border and IV implementations of preference externality estimators across three dimensions: i) identifying assumptions, ii) sacrifices in statistical power, and iii) local estimates of heterogenous effects.


Sylvia Hristakeva, University of California, Los Angeles

Vertical Contracts with Endogenous Product Selection: An Empirical Analysis of Vendor-Allowance Contracts

Producers frequently provide retailers with financial incentives to secure distribution of their products. These payments often take the form of vendor allowances: lump-sum transfers to retailers that do not directly depend on quantity sold. Hristakeva studies equilibrium effects of vendor allowances when retailers' product selections are endogenous and vertical contracts are unobserved. The researcher introduces an estimation strategy that uses rich information from observed product selections to inform about lump-sum payments. Vendor allowances are estimated as the payments needed to rationalize observed assortments. For the empirical analysis, estimates imply that these transfers are important for retailers' profitability, corresponding to about 20% of retailers' variable profits. A counterfactual that restricts firms to only contract on wholesale prices predicts that lump-sum payments incentivize retailers to adjust their product selections. In the absence of vendor payments, total surplus increases because previously excluded low-cost products enter the market.


David C. Chan Jr and Matthew Gentzkow, Stanford University and NBER, and Chuan Yu, Stanford University, "Selection with Variation in Diagnostic Skill: Evidence from Radiologists" (NBER Working Paper No. 26467)

Physicians, judges, teachers, and agents in many other settings differ systematically in the decisions they make when faced with similar cases. Standard approaches to interpreting and exploiting such differences assume they arise solely from variation in preferences. Chan, Gentzkow, and Yu develop an alternative framework that allows variation in both preferences and diagnostic skill, and show that both dimensions are identified in standard settings under quasi-random assignment. The researchers apply this framework to study pneumonia diagnoses by radiologists. Diagnosis rates vary widely among radiologists, and descriptive evidence suggests that a large component of this variation is due to differences in diagnostic skill. Their estimated model suggests that radiologists view failing to diagnose a patient with pneumonia as more costly than incorrectly diagnosing one without, and that this leads less-skilled radiologists to optimally choose lower diagnosis thresholds. Variation in skill can explain 44 percent of the variation in diagnostic decisions, and policies that improve skill perform better than uniform decision guidelines. Failing to account for skill variation can lead to highly misleading results in research designs that use agent assignments as instruments.


Pedro Gardete, Nova School of Business and Economics, and Megan Hunter, Stanford University

Guiding Consumers through Lemons and Peaches: Analyzing of the Effects of Search Design Activities

The advent of the Internet age has led to questions about the impact of obfuscation and information provision activities by sellers. Gardete and Hunter estimate the welfare effects of search design activities by an online used car seller, through a dynamic model of search over differentiated offerings. The researchers find that different emphases on product characteristics have a modest impact on consumer welfare (-0.4% to +2.5%) but a relatively high impact on the seller's (-1.9% to +11.3%). Incentives for information provision are found to be largely aligned between supply and demand. Finally, they find no evidence of consumer myopia in learning.


Cailin R. Slattery, Columbia University

Bidding for Firms: Subsidy Competition in the United States

In the US, states compete to attract firms by offering discretionary subsidies, but little is known about how states choose their subsidy offers, and whether such subsidies affect firms' location choices. Slattery uses an oral ascending (English) auction to model the subsidy "bidding" process and estimate the efficiency of subsidy competition. The model allows state governments to value both the direct and indirect (spillover) job creation of firms when submitting bids, and firms to take both subsidies offered and state characteristics into account when choosing their location. To estimate the model, Slattery hand-collects a new and unique dataset on state incentive spending and subsidy deals from 2002-2016. They estimate both the distribution of states' (revealed) valuations for firms that rationalizes observed subsidies, and firms' valuations for state characteristics. In order to allow states to value potential spillovers, they estimate the effect of subsidy-winning firms' locations on the entry decision of smaller firms, using a discrete choice entry model. The researcher provides the first empirical evidence that states use subsidies to help large firms internalize the positive spillovers, in the form of indirect job creation, they have on the states. Moreover, subsidies have a sizable effect on firm locations. In particular, Slattery finds that without subsidies approximately 68% of firms would locate in a different state, and the number of anticipated indirect jobs created would decrease by 32%. With subsidies, total welfare (the sum of state valuations and firm profits) increases by 22%, and this welfare gain is captured entirely by the firms.