Estimating Dynamic Models of Imperfect Competition

Bajari, Patrick; Benkard, C. Lanier; Levin, Jonathan

doi:10.3386/w10450

Cited by 132 publications

(223 citation statements)

References 0 publications

Supporting

Mentioning

222

Contrasting

Order By: Relevance

“…This is especially beneficial if the researcher uses modern econometric techniques (Aguirregabiria and Mira 2007, Bajari et al 2007, Judd and Su 2008, Pesendorfer and Schmidt-Dengler 2008 to estimate the primitives of the game and therefore recovers them with error. In addition, our main stability result lays the foundations for comparative statics.…”

Section: Introductionmentioning

confidence: 99%

A Theory of Regular Markov Perfect Equilibria in Dynamic Stochastic Games: Genericity, Stability, and Purification

Doraszelski

Escobar

2008

SSRN Journal

View full text Add to dashboard Cite

This paper studies generic properties of Markov perfect equilibria in dynamic stochastic games. We show that almost all dynamic stochastic games have a finite number of locally isolated Markov perfect equilibria. These equilibria are essential and strongly stable. Moreover, they all admit purification. To establish these results, we introduce a notion of regularity for dynamic stochastic games and exploit a simple connection between normal form and dynamic stochastic games.Keywords dynamic stochastic games, Markov perfect equilibria, regularity, genericity, finiteness, strong stability, essentiality, purifiability, estimation, computation, repeated games This paper studies generic properties of Markov perfect equilibria in dynamic stochastic games. We show that almost all dynamic stochastic games have a finite number of locally isolated Markov perfect equilibria. These equilibria are essential and strongly stable. Moreover, they all admit purification. To establish these results, we introduce a notion of regularity for dynamic stochastic games and exploit a simple connection between normal form and dynamic stochastic games.

show abstract

Section: Introductionmentioning

confidence: 99%

A Theory of Regular Markov Perfect Equilibria in Dynamic Stochastic Games: Genericity, Stability, and Purification

Doraszelski

Escobar

2008

SSRN Journal

View full text Add to dashboard Cite

show abstract

“…Kawai & Watanabe (2013) simulates market effects in a model of strategic voting that uses moment inequalities to address unobserved beliefs about other voters. Although not strictly moment inequalities, the method of Bajari, Benkard & Levin (2007) uses simulation in the context of a minimum distance estimator based on inequalities to study dynamic oligopoly games. Well-known applications are Ryan (2012) and Fowlie, Reguant & Ryan (2015).…”

Section: Introductionmentioning

confidence: 99%

“…Interestingly, Bajari et al (2007) show in Table 5 that their inequalities estimator may be inferior to an estimator based on moment equalities (as in Pakes, Ostrovsky & Berry, 2007) if one can be implemented. They ascribe this to the non-linearity of the second-stage estimator.…”

Section: Introductionmentioning

confidence: 99%

Moment inequalities in the context of simulated and predicted variables

Kaido¹,

Li²,

Rysman³

2018

View full text Add to dashboard Cite

This paper explores the effects of simulated moments on the performance of inference methods based on moment inequalities. Commonly used confidence sets for parameters are level sets of criterion functions whose boundary points may depend on sample moments in an irregular manner. Due to this feature, simulation errors can affect the performance of inference in non-standard ways. In particular, a (first-order) bias due to the simulation errors may remain in the estimated boundary of the confidence set. We demonstrate, through Monte Carlo experiments, that simulation errors can significantly reduce the coverage probabilities of confidence sets in small samples. The size distortion is particularly severe when the number of inequality restrictions is large. These results highlight the danger of ignoring the sampling variations due to the simulation errors in moment inequality models. Similar issues arise when using predicted variables in moment inequalities models. We propose a method for properly correcting for these variations based on regularizing the intersection of moments in parameter space, and we show that our proposed method performs well theoretically and in practice.

show abstract

“…The researcher would want to have a method for implementing counterfactual experiments that does not require these additional assumptions. 2 In this paper, we consider that the researcher is not willing to impose these restrictions. We propose an approach that imposes minimum conditions on the characteristics of the equilibrium P * .…”

Section: Modelmentioning

confidence: 99%

“…Models with multiple equilibria do not have a unique reduced form, and this indeterminacy poses practical estimation problems. In the context of discrete games with incomplete information, recent papers have proposed two-step and sequential estimators that significantly simplify the estimation of these models (Aguirregabiria and Mira, 2007; Bajari, Benkard and Levin, 2007;and Pesendorfer and Schmidt-Dengler, 2008). Nevertheless, the indeterminacy problem associated with multiple equilibria still remains an issue when the researcher wants to use the estimated model to predict the effects of counterfactual changes in the structural parameters.…”

mentioning

confidence: 99%

A method for implementing counterfactual experiments in models with multiple equilibria

Aguirregabiria

2012

Economics Letters

View full text Add to dashboard Cite

This paper proposes a method for implementing counterfactual experiments in estimated models that have multiple equilibria. The method assumes that the researcher does not know the equilibrium selection mechanism and wants to impose minimum restrictions on it. Our key assumption is that the equilibrium selection function does not jump discontinuously between equilibria as we change marginally the structural parameters of the model. Under this assumption, we show that, although the equilibrium selection function is unknown, the researcher can obtain an approximation of this function in a neighborhood of the estimated values of the structural parameters. Under the additional assumption that the counterfactual equilibrium is stable, this approximation can be combined with iterations in the equilibrium mapping to obtain the exact counterfactual equilibrium. We illustrate the differences between our approach and other methods, such as the selection of a counterfactual equilibrium that is closer to the equilibrium in the data, and equilibrium mapping iterations using the equilibrium in the data as the initial value. We show that, in general, these alternative methods are not consistent with the assumption that the equilibrium selection mechanism is continuous with respect to the structural parameters.

show abstract

Estimating Dynamic Models of Imperfect Competition

Cited by 132 publications

References 0 publications

A Theory of Regular Markov Perfect Equilibria in Dynamic Stochastic Games: Genericity, Stability, and Purification

A Theory of Regular Markov Perfect Equilibria in Dynamic Stochastic Games: Genericity, Stability, and Purification

Moment inequalities in the context of simulated and predicted variables

A method for implementing counterfactual experiments in models with multiple equilibria

Contact Info

Product

Resources

About