The Strategic Timing Incentives of Commercial Radio Stations: An Empirical Analysis Using Multiple Equilibria

Sweeting, Andrew

doi:10.3386/w14506

Cited by 49 publications

(125 citation statements)

References 25 publications

(54 reference statements)

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“…Finally, the emphasis on inequality conditions derived from revealed preference arguments and the speci…c decomposition of the errors into structural and non-structural components draws upon the recent moment inequality literature 2 There is a wide and growing literature on discrete games in both economics and marketing. Notable examples include Aguirregabiria and Mira (2007), Bajari, Benkard, and Levin (2007), Berry (1992), Pakes, Ostrovsky, and Berry (2007), Draganska, Mazzeo, andSeim (2009), Hartmann (2010), Ho (2009), Orhun (2006, Pesendorfer and Schmidt-Dengler (2007), Sweeting (2009), Vitorino (2007, and . provide an overview of this rapidly expanding …eld.…”

Section: Introductionmentioning

confidence: 99%

Enriching interactions: Incorporating outcome data into static discrete games

Ellickson

Misra

2011

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When modeling the behavior of …rms, marketers and micro-economists routinely confront complex problems of strategic interaction. In competitive environments, …rms make strategic decisions that not only depend on the features of the market, but also on their beliefs regarding the reactions of their rivals. Structurally modeling these interactions requires formulating and estimating a discrete game, a task which, until recently, was considered intractable. Fortunately, two-step estimation methods have cracked the problem, fueling a growing literature in both marketing and economics that tackles a host of issues from the optimal design of ATM networks to the choice of pricing strategy. However, most existing methods have focused on only the discrete choice of actions, ignoring a wealth of information contained in post-choice outcome data and severely limiting the scope for performing informative counterfactuals or identifying the deep structural parameters that drive strategic decisions. The goal of this paper is to provide a method for incorporating post-choice outcome data into static discrete games of incomplete information. In particular, our estimation approach adds a selection correction to the two-step games approach, allowing the researcher to use revenue data, for example, to recover the costs associated with alternative actions. Alternatively, a researcher might use R&D expenses to back out the returns to innovation.The authors would like to thank participants at the 2007 Choice Symposium at the University of Pennsylvania and the 2007 QME conference at the University of Chicago. The authors have bene…tted from conversations with Patrick Bajari, Jeremy Fox, Han Hong, and Harikesh Nair and would also like to thank the editors and two anonymous referees for many helpful comments. All remaining errors are our own.

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Section: Introductionmentioning

confidence: 99%

Enriching interactions: Incorporating outcome data into static discrete games

Ellickson

Misra

2011

Quant Mark Econ

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“…In this case one would need to normalize 0 or, as in our example, assume it is known, in order to identify : If on the other hand two equilibria are played in the data then we can pinpoint the (logit) curve that passes through these points and identify both 0 and . Sweeting (2009) discusses this identi…cation in more formal detail.…”

Section: Parameter Identi…cation Given Equilibrium Probabilitiesmentioning

confidence: 99%

“…Most empirical work (see e.g. Bajari et al 2010;Sweeting 2009) assumes (as we do) that there is a single equilibrium played in any given market. This helps alleviate problems related to the third point, albeit not completely.…”

Section: An Illustrative Examplementioning

confidence: 99%

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Markov chain Monte Carlo for incomplete information discrete games

Misra

2012

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This paper outlines a Bayesian approach to estimating discrete games of incomplete information. The MCMC routine proposed features two changes to the traditional Metropolis-Hastings algorithm to facilitate the estimation of games. First, we propose a new approach to sample equilibrium probabilities using a probabilistic equilibrium selection rule that allows for the evaluation of the parameter posterior. Second, we propose a di¤erential evolution based MCMC sampler which is capable of handling the unwieldy posterior that only has support on the equilibrium manifold. We also present two applications to demonstrate the feasibility of our proposed methodology.

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“…Aradillas-López (2010), Durlauf (2001, 2007), Seim (2006), Sweeting (2009)). We retain the notation introduced in Section 3, but we substitute Assumption 3.1 with the following one, which is fairly standard in the literature.…”

Section: Application Ii: Entry Games Of Incomplete Informationmentioning

confidence: 99%

Sharp identification regions in models with convex moment predictions

Beresteanu¹,

Molchanov²,

Molinari³

2010

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We provide a tractable characterization of the sharp identi…cation region of the parameters in a broad class of incomplete econometric models. Models in this class have set valued predictions that yield a convex set of conditional or unconditional moments for the observable model variables. In short, we call these models with convex moment predictions. Examples include static, simultaneous move …nite games of complete and incomplete information in the presence of multiple equilibria; best linear predictors with interval outcome and covariate data; and random utility models of multinomial choice in the presence of interval regressors data. Given a candidate value for ; we establish that the convex set of moments yielded by the model predictions can be represented as the Aumann expectation of a properly de…ned random set. The sharp identi…cation region of ; denoted I ; can then be obtained as the set of minimizers of the distance from a properly speci…ed vector of moments of random variables to this Aumann expectation. Algorithms in convex programming can be exploited to e¢ ciently verify whether a candidate is in I : We use examples analyzed in the literature to illustrate the gains in identi…cation and computational tractability a¤orded by our method.

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The Strategic Timing Incentives of Commercial Radio Stations: An Empirical Analysis Using Multiple Equilibria

Cited by 49 publications

References 25 publications

Enriching interactions: Incorporating outcome data into static discrete games

Enriching interactions: Incorporating outcome data into static discrete games

Markov chain Monte Carlo for incomplete information discrete games

Sharp identification regions in models with convex moment predictions

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