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To investigate whether secondary markets aid or harm durable goods manufacturers, we build a dynamic model of durable goods oligopoly with transaction costs in the secondary market. Calibrating model parameters using data from the US automobile industry, we find the net effect of opening the secondary market is to decrease new car manufacturers' profits by 35 percent. Counterfactual scenarios in which the size of the used good stock decreases, such as when products become less durable, when the number of firms decreases, or when firms can commit to future production levels, increase the profitability of opening the secondary market.

We introduce a measure of the severity of violations of the revealed preference axioms, themoney pump index(MPI). The MPI is the amount of money one can extract from a consumer who violates the axioms. It is also a statistical test for the hypothesis that a consumer is rational when behavior is observed with error. We present an application using a panel data set of food expenditures. The data exhibit many violations of the axioms. Mostly, the MPI for these violations is small. The MPI indicates that the hypothesis of consumer rationality cannot be rejected.

This article establishes a general equivalence between discrete choice and rational inattention models. Matějka and McKay (2015) showed that when information costs are modeled using the Shannon entropy, the choice probabilities in the rational inattention (RI) model take the multinomial logit form. We show that, for one given prior over states, RI choice probabilities may take the form of any additive random utility discrete choice model (ARUM) when the information cost is a Bregman information, a class defined in this article. The prior information of the rationally inattentive agent is summarized in a constant vector of utilities in the corresponding ARUM.

We measure the welfare distortions from endogenous quality choice in imperfectly competitive markets. For US cable television markets between 1997–2006, prices are 33 percent to 74 percent higher and qualities 23 percent to 55 percent higher than socially optimal. Such quality overprovision contradicts classic results in the literature and our analysis shows that it results from the presence of competition from high-end satellite TV providers: without the competitive pressure from satellite companies, cable TV monopolists would instead engage in quality degradation. For welfare, quality overprovision implies cable customers would prefer smaller, lower-quality cable bundles at a lower price, amounting to a twofold increase in consumer surplus for the average consumer.

We show how the equilibrium restrictions implied by standard search models can be used to estimate search-cost distributions using price data alone. We consider both sequential and non-sequential search strategies, and develop estimation methodologies that exploit equilibrium restrictions to recover estimates of search-cost heterogeneity that are theoretically consistent with the search models. We illustrate the method using online prices for several economics and statistics textbooks.

Exploiting a rich panel data set on anti-ulcer drug prescriptions, we measure the effects of uncertainty and learning in the demand for pharmaceutical drugs. We estimate a dynamic matching model of demand under uncertainty in which patients learn from prescription experience about the effectiveness of alternative drugs. Unlike previous models, we allow drugs to have distinct symptomatic and curative effects, and endogenize treatment length by allowing drug choices to affect patients' underlying probability of recovery. We find that drugs' rankings along these dimensions differ, with high symptomatic effects for drugs with the highest market shares and high curative effects for drugs with the greatest medical efficacy. Our results also indicate that while there is substantial heterogeneity in drug efficacy across patients, learning enables patients and their doctors to dramatically reduce the costs of uncertainty in pharmaceutical markets.

The impact of digital platforms on the implementation of the United Nations’ (UN) Sustainable Development Goals (SDGs), especially the business sustainability of micro, small and medium-sized enterprises (MSMEs), under different containment policies during and after the COVID-19 pandemic has not yet been studied in detail. Using detailed administrative data from Alibaba Group’s online on-demand food delivery platform, we found that the digital platform contributed to the food security, wellbeing, employment and business sustainability of MSMEs both during and after the pandemic. We uncovered merchants’ heterogeneous responses to the COVID-19 pandemic during and after the implementation of different containment policies in China. On the extensive margin, the period of complete lockdown left long-term scarring on online merchants by decreasing the number of entrants, especially in the cooked food industry. In contrast, on the intensive margin, chain stores, especially those with large chain networks or multiapp stores, exhibited stronger resilience than their counterparts during and after lockdown. Thus, specialization (at the outlet level) and wider coverage (at the network level) emerged as key factors that enable business sustainability under challenging economic circumstances.

We assess empirically the effects of the winner's curse which, in common-value auctions, counsels more conservative bidding as the number of competitors increases. First, we construct an econometric model of an auction in which bidders' preferences have both common- and private-value components, and propose a new monotone quantile approach which facilitates estimation of this model. Second, we estimate the model using bids from procurement auctions held by the State of New Jersey. For a large subset of these auctions, we find that median procurement costs rise as competition intensifies. In this setting, then, asymmetric information overturns the common economic wisdom that more competition is always desirable.

We examine the informational effects of M&As by investigating whether bank mergers improve banks' ability to screen borrowers. By exploiting a data set in which we observe a measure of a borrower's default risk that the lenders observe only imperfectly, we find evidence of these informational improvements. Mergers lead to a closer correspondence between interest rates and individual default risk: after a merger, risky borrowers experience an increase in the interest rate, while nonrisky borrowers enjoy lower interest rates. These informational benefits appear to derive from improvements in information processing resulting from the merger, rather than from explicit information sharing on individual customers among the merging parties. Our evidence suggests that part of these informational improvements stem from the consolidated banks using \"hard\" information more intensively.

This paper proposes a new semi-parametric identification and estimation approach to multinomial choice models in a panel data setting with individual fixed effects. Our approach is based on cyclic monotonicity, which is a defining convex-analytic feature of the random utility framework underlying multinomial choice models. From the cyclic monotonicity property, we derive identifying inequalities without requiring any shape restrictions for the distribution of the random utility shocks. These inequalities point identify model parameters under straightforward assumptions on the covariates. We propose a consistent estimator based on these inequalities.