Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. AbstractWe study the nonparametric identification of gross output production functions under the en vironment of the commonly employed proxy variable methods. We show that applying these methods to gross output requires additional sources of variation in the demand for flexible in puts (e.g., prices). Using a transformation of the firm's first-order condition, we develop a new nonparametric identification strategy for gross output that can be employed even when additional sources of variation are not available. Monte Carlo evidence and estimates from Colombian and Chilean plant-level data show that our strategy performs well and is robust to deviations from the baseline setting. * We would like to thank

We consider the invertibility of a nonparametric nonseparable demand system. Invertibility of demand is important in several contexts, including identification of demand, estimation of demand, testing of revealed preference, and economic theory requiring uniqueness of market clearing prices. We introduce the notion of "connected substitutes" and show that this structure is sufficient for invertibility. The connected substitutes conditions require weak substitution between all goods and sufficient strict substitution to necessitate treating them in a single demand system. These conditions are satisfied in many standard models, have transparent economic interpretation, and allow us to show invertibility without functional form restrictions, smoothness assumptions, or strong domain restrictions.

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This paper analyzes the effects of mergers between firms competing by simultaneously choosing price and location. Products combined by a merger are repositioned away from each other to reduce cannibalization, and non-merging substitutes are, in response, repositioned between the merged products. This repositioning greatly reduces the merged firm's incentive to raise prices and thus substantially mitigates the anticompetitive effects of the merger. Computation of, and selection among, equilibria is done with a novel technique known as the stochastic response dynamic, which does not require the computation of first-order conditions.

In this paper we introduce a new approach to estimating differentiated product demand system that allows for error in market shares as measures of choice probabilities. In particular, our approach allows for products with zero sales in the data, which is a frequent phenomenon that arises in product differentiated markets but lies outside the scope of existing demand estimation techniques. Although we find that error in market shares generally undermine the standard point identification of discrete choice models of demand, we exploit shape restrictions on demand implied by discrete choice to generate a system of moment inequalities that partially identify demand parameters. These moment inequalities are fully robust to the variability in market shares yet are also adaptive to the information revealed by market shares in a way that allows for informative inferences. In addition, we construct a profiling approach for parameter inference with moment inequalities, making it feasible to study models with a large number of parameters (as typically required in demand applications) by focusing attention on a profile of the parameters, such as the price coefficient. We use our approach to study consumer demand from scanner data using the Dominick's Finer Foods database, and find that even for the baseline logit model, demand elasticities nearly double when the full error in market shares is taken into account.

This paper studies belief heterogeneity in a benchmark competitive asset market: a market for Arrow-Debreu securities. We show that differences in agents' beliefs lead to a systematic pricing pattern, the favorite longshot bias (FLB): securities with a low payout probability are overpriced while securities with high probability payout are underpriced. We apply demand estimation techniques to betting market data, and find that the observed FLB is explained by a two-type population consisting of canonical traders, who hold virtually correct beliefs and are the majority type in the population (70%); and noise traders exhibiting significant belief dispersion. Furthermore, using formal model comparisons and also exploiting variation in public information across markets in our dataset, we show that our belief heterogeneity model empirically outperforms existing preference-based explanations of the FLB, such as risk-loving or prospect theory.JEL Classification: C13, C51, D40, G13, L00.

We consider the invertibility (injectivity) of a nonparametric nonseparable demand system. Invertibility of demand is important in several contexts, including identi…cation of demand, estimation of demand, testing of revealed preference, and economic theory exploiting existence of an inverse demand function or (in an exchange economy) uniqueness of Walrasian equilibrium prices. We introduce the notion of "connected substitutes" and show that this structure is su¢ cient for invertibility. The connected substitutes conditions require weak substitution between all goods and su¢ cient strict substitution to necessitate treating them in a single demand system. The connected substitutes conditions have transparent economic interpretation, are easily checked, and are satis…ed in many standard models. They need only hold under some transformation of demand and can accommodate many models in which goods are complements. They allow one to show invertibility without strict gross substitutes, functional form restrictions, smoothness assumptions, or strong domain restrictions. When the restriction to weak substitutes is maintained, our su¢ cient conditions are also "nearly necessary" for even local invertibility.

We show how to nonparametrically identify the distribution of unobservables, such as random coefficients, that characterizes the heterogeneity among consumers in multinomial choice models. We provide general identification conditions for a class of nonlinear models and then verify these conditions using the primitives of the multinomial choice model. We require that the distribution of unobservables lie in the class of all distributions with finite support, which under our most general assumptions, resembles a product space where some of the product members are function spaces. We show how identification leads to the consistency of a nonparametric estimator.