Victor Aguirregabiria | University of Toronto (original) (raw)

Papers by Victor Aguirregabiria

Econometrics, 2005

This paper presents a method to estimate the effects of a counterfactual policy intervention in t... more This paper presents a method to estimate the effects of a counterfactual policy intervention in the context of dynamic structural models where all the structural functions (i.e., preferences, technology, transition probabilities, and the distribution of unobservable variables) are nonparametrically specified. We show that agents' behavior, before and after the policy intervention, and the change in agents' utility are nonparametrically identified. Based on this result we propose a nonparametric procedure to estimate the behavioral and welfare effects of a general class of counterfactual policy interventions. We illustrate this method with Monte Carlo experiments in a model of capital replacement.

This paper studies the contribution of demand, costs, and strategic factors to the adoption of hu... more This paper studies the contribution of demand, costs, and strategic factors to the adoption of hub-and-spoke networks in the US airline industry. Our results are based on the estimation of a dynamic oligopoly game of network competition that incorporates three groups of factors that may explain hub-and-spoke networks: (1) travelers may value the services associated with the scale of operation of an airline in the hub airport; (2) operating costs and entry costs in a route may decline with the airline's scale of operation in the origin and destination airports (e.g., economies of scale and scope); and (3) a hub-and-spoke network may be an effective strategy to deter the entry of other carriers. We estimate the model using data from the Airline Origin and Destination Survey with information on quantities, prices, and entry and exit decisions for every airline company in the routes between the 55 largest US cities. As methodological contributions, we propose and apply a method to reduce the dimension of the state space in dynamic games, and a procedure to deal with the problem of multiple equilibria when using a estimated model to make counterfactual experiments. We find that the most important factor to explain the adoption of hub-and-spoke networks is that the cost of entry in a route declines importantly with the scale of operation of the airline in the airports of the route. For some of the larger carriers, strategic entry deterrence is the second most important factor to explain hub-and-spoke networks.

RePEc: Research Papers in Economics, Mar 14, 2012

This paper deals with the identification and estimation of dynamic games when players' b... more This paper deals with the identification and estimation of dynamic games when players' be-liefs about other players' actions may not be in equilibrium, ie, they do not represent the actual behavior of other players. This type of model applies naturally to competition in oligopoly indus- ...

RePEc: Research Papers in Economics, Apr 19, 2005

RePEc: Research Papers in Economics, Jun 17, 2004

This paper studies the estimation of dynamic discrete games of incomplete information. Two main e... more This paper studies the estimation of dynamic discrete games of incomplete information. Two main econometric issues appear in the estimation of these models: the indeterminacy problem associated with the existence of multiple equilibria, and the computational burden in the solution of the game. We propose a class of pseudo maximum likelihood (PML) estimators that deals with these problems and we study the asymptotic and finite sample properties of several estimators in this class. We first focus on two-step PML estimators which, though attractive for their computational simplicity, have some important limitations: they are seriously biased in small samples; they require consistent nonparametric estimators of players' choice probabilities in the first step, which are not always feasible for some models and data; and they are asymptotically inefficient. Second, we show that a recursive extension of the two-step PML, which we call nested pseudo likelihood (NPL), addresses those drawbacks at a relatively small additional computational cost. The NPL estimator is particularly useful in applications where consistent nonparametric estimates of choice probabilities are either not available or very imprecise, e.g., models with permanent unobserved heterogeneity. Finally, we illustrate these methods in Montecarlo experiments and in an empirical application to a model of firm entry and exit in oligopoly markets using Chilean data from several retail industries.

RePEc: Research Papers in Economics, Mar 1, 1999

This paper proposes a procedure for the estimation of discrete Markov decision models and studies... more This paper proposes a procedure for the estimation of discrete Markov decision models and studies its statistical and computational properties. Our Nested Pseudo-Likelihood method (NPL) is similar to Rust's Nested Fixed Point algorithm (NFXP), but the nesting of the two algorithms is swapped. First, we prove that on convergence NPL produces a root of the likelihood equations. Our procedure requires fewer policy iterations at the expense of more likelihood-climbing iterations. We focus on a class of in¯nite-horizon, partial likelihood problems for which NPL can deliver large computational gains. Second, based on this algorithm we de¯ne a class of consistent and asymptotically equivalent Sequential Policy Iteration (PI) estimators, which encompasses both Hotz-Miller's CCP estimator and the partial Maximum Likelihood estimator. This presents the researcher with a "menu" of sequential estimators re°ecting a trade-o® between¯nite-sample precision and computational cost. Using actual and simulated data we compare the relative performance of these estimators. In all our experiments the bene¯ts in terms of precision of using a 2-stage PI estimator instead of 1-stage (i.e., Hotz-Miller) are very signi¯cant. More interestingly, the bene¯ts of MLE relative to 2-stage PI are small.

arXiv (Cornell University), Jul 9, 2023

This paper investigates the impact of decentralizing inventory decision-making in multiestablishm... more This paper investigates the impact of decentralizing inventory decision-making in multiestablishment firms using data from a large retail chain. Analyzing two years of daily data, we find significant heterogeneity among the inventory decisions made by 634 store managers. By estimating a dynamic structural model, we reveal substantial heterogeneity in managers' perceived costs. Moreover, we observe a correlation between the variance of these perceptions and managers' education and experience. Counterfactual experiments show that centralized inventory management reduces costs by eliminating the impact of managers' skill heterogeneity. However, these benefits are offset by the negative impact of delayed demand information.

Social Science Research Network, 1998

Social Science Research Network, 2005

Advances in econometrics, Dec 13, 2013

We derive marginal conditions of optimality (i.e., Euler equations) for a general class of Dynami... more We derive marginal conditions of optimality (i.e., Euler equations) for a general class of Dynamic Discrete Choice (DDC) structural models. These conditions can be used to estimate structural parameters in these models without having to solve for or approximate value functions. This result extends to discrete choice models the GMM-Euler equation approach proposed by Hansen and Singleton (1982) for the estimation of dynamic continuous decision models. We first show that DDC models can be represented as models of continuous choice where the decision variable is a vector of choice probabilities. We then prove that the marginal conditions of optimality and the envelope conditions required to construct Euler equations are also satisfied in DDC models. The GMM estimation of these Euler equations avoids the curse of dimensionality associated to the computation of value functions and the explicit integration over the space of state variables. We present an empirical application and compare estimates using the GMM-Euler equations method with those from maximum likelihood and two-step methods.

The Review of Economic Studies, Mar 6, 2019

This paper deals with the identification and estimation of dynamic games when players' beliefs ab... more This paper deals with the identification and estimation of dynamic games when players' beliefs about other players' actions are biased, i.e., beliefs do not represent the probability distribution of the actual behavior of other players conditional on the information available. First, we show that a exclusion restriction, typically used to identify empirical games, provides testable nonparametric restrictions of the null hypothesis of equilibrium beliefs. Second, we prove that this exclusion restriction, together with consistent estimates of beliefs at several points in the support of the special state variable (i.e., the variable involved in the exclusion restriction), is sufficient for nonparametric point-identification of players' payoff and belief functions. The consistent estimates of beliefs at some points of support may come either from an assumption of unbiased beliefs at these points in the state space, or from available data on elicited beliefs for some values of the state variables. Third, we propose a simple two-step estimation method and a sequential generalization of the method that improves its asymptotic and finite sample properties. We illustrate our model and methods using both Monte Carlo experiments and an empirical application of a dynamic game of store location by retail chains. The key conditions for the identification of beliefs and payoffs in our application are the following: (a) the previous year's network of stores of the competitor does not have a direct effect on the profit of a firm, but the firm's own network of stores at previous year does affect its profit because the existence of sunk entry costs and economies of density in these costs; and (b) firms' beliefs are unbiased in those markets that are close, in a geographic sense, to the opponent's network of stores, though beliefs are unrestricted, and potentially biased, for unexplored markets which are farther away from the competitors' network. Our estimates show significant evidence of biased beliefs.

Journal of Industrial Economics, Dec 1, 2016

We propose a dynamic model of an oligopoly industry characterized by spatial competition between ... more We propose a dynamic model of an oligopoly industry characterized by spatial competition between multi-store retailers. Firms compete in prices and decide where to open or close stores depending on demand and cost conditions, the number of competitors at different locations, and on location-specific private-information shocks. The model distinguishes multiple forces in the spatial configuration of store networks, such as cannibalization of revenue between stores of the same retail chain, economies of density, competition, consumer transportation costs, or positive demand spillovers from other stores. We develop an algorithm to approximate a Markov Perfect Equilibrium in our model, and propose a procedure for the estimation of the parameters of the model using panel data on number of stores, prices, and quantities at multiple geographic locations within a city. We also present a numerical example to illustrate the model and algorithm. I. INTRODUCTION RETAIL CHAINS ACCOUNT FOR MORE THAN 60% OF SALES IN U.S. RETAILING (see Hollander and Omura [1989], and Jarmin, Klimek and Miranda [2009]). Geographic location is in many cases the most important source of product differentiation for these firms. It is also a forward looking decision with significant non-recoverable entry costs, mainly due to capital investments which are both firm and location specific. Thus, the sunk cost of setting up a new store, and the dynamic strategic behavior associated with them, is a potentially important force behind the configuration of the spatial market structure that we observe in retail markets. Despite its relevance, there have been very few studies analyzing spatial competition as a dynamic oligopoly game. Existent models of industry

Social Science Research Network, 2007

This paper reviews methods for the estimation of dynamic discrete choice structural models and di... more This paper reviews methods for the estimation of dynamic discrete choice structural models and discusses related econometric issues. We consider single agent models, competitive equilibrium models and dynamic games. The methods are illustrated with descriptions of empirical studies which have applied these techniques to problems in different areas of economics. Programming codes for the estimation methods will be available in a companion web page.

arXiv (Cornell University), May 8, 2022

This paper studies identification and estimation of a dynamic discrete choice model of demand for... more This paper studies identification and estimation of a dynamic discrete choice model of demand for differentiated product using consumer-level panel data with few purchase events per consumer (i.e., short panel). Consumers are forward-looking and their preferences incorporate two sources of dynamics: last choice dependence due to habits and switching costs, and duration dependence due to inventory, depreciation, or learning. A key distinguishing feature of the model is that consumer unobserved heterogeneity has a Fixed Effects (FE) structure-that is, its probability distribution conditional on the initial values of endogenous state variables is unrestricted. I apply and extend recent results to establish the identification of all the structural parameters as long as the dataset includes four or more purchase events per household. The parameters can be estimated using a sufficient statistic-conditional maximum likelihood (CML) method. An attractive feature of CML in this model is that the sufficient statistic controls for the forward-looking value of the consumer's decision problem such that the method does not require solving dynamic programming problems or calculating expected present values.

Journal of Econometrics, May 1, 2012

This paper studies the contribution of demand, costs, and strategic factors to the adoption of hu... more This paper studies the contribution of demand, costs, and strategic factors to the adoption of hub-and-spoke networks in the US airline industry. Our results are based on the estimation of a dynamic oligopoly game of network competition that incorporates three groups of factors that may explain hub-and-spoke networks: (1) travelers may value the services associated with the scale of operation of an airline in the hub airport; (2) operating costs and entry costs in a route may decline with the airline's scale of operation in the origin and destination airports (e.g., economies of scale and scope); and (3) a hub-and-spoke network may be an effective strategy to deter the entry of other carriers. We estimate the model using data from the Airline Origina n dD e s t i n a t i o nS u r v e yw i t hi n f o r m a t i o n on quantities, prices, and entry and exit decisions for every airline company in the routes between the 55 largest US cities. As methodological contributions, we propose and apply a method to reduce the dimension of the state space in dynamic games, and a procedure to deal with the problem of multiple equilibria when using a estimated model to make counterfactual experiments. We find that the most important factor to explain the adoption of hub-and-spoke networks is that the cost of entry in a route declines importantly with the scale of operation of the airline in the airports of the route. For some of the larger carriers, strategic entry deterrence is the second most important factor to explain hub-and-spoke networks.

arXiv (Cornell University), May 10, 2018

We study the identification and estimation of structural parameters in dynamic panel data logit m... more We study the identification and estimation of structural parameters in dynamic panel data logit models where decisions are forward-looking and the joint distribution of unobserved heterogeneity and observable state variables is nonparametric, i.e., fixed-effects model. We consider models with two endogenous state variables: the lagged decision variable, and the time duration in the last choice. This class of models includes as particular cases important economic applications such as models of market entry-exit, occupational choice, machine replacement, inventory and investment decisions, or dynamic demand of differentiated products. The identification of structural parameters requires a sufficient statistic that controls for unobserved heterogeneity not only in current utility but also in the continuation value of the forward-looking decision problem. We obtain the minimal sufficient statistic and prove identification of some structural parameters using a conditional likelihood approach. We apply this estimator to a machine replacement model.

Econometrica, Jul 1, 2002

This paper proposes a procedure for the estimation of discrete Markov decision models and studies... more This paper proposes a procedure for the estimation of discrete Markov decision models and studies its statistical and computational properties. Our Nested Pseudo-Likelihood method (NPL) is similar to Rust's Nested Fixed Point algorithm (NFXP), but the order of the two nested algorithms is swapped. First, we prove that NPL produces the Maximum Likelihood Estimator under the same conditions as NFXP. Our procedure requires fewer policy iterations at the expense of more likelihood-climbing iterations. We focus on a class of in…nite-horizon, partial likelihood problems for which NPL results in large computational gains. Second, based on this algorithm we de…ne a class of consistent and asymptotically equivalent Sequential Policy Iteration (PI) estimators, which encompasses both Hotz-Miller's CCP estimator and the partial Maximum Likekihood estimator. This presents the researcher with a "menu" of sequential estimators re ‡ecting a trade-o¤ between …nite-sample precision and computational cost. Using actual and simulated data we compare the relative performance of these estimators. In all our experiments the bene…ts in terms of precision of using a 2-stage PI estimator instead of 1-stage (i.e., Hotz-Miller) are very signi…cant. More interestingly, the bene…ts of MLE relative to 2-stage PI are small.

Econometrica, 2007

Quantitative marketing and economics, Jun 14, 2014

This paper addresses a fundamental identification problem in the structural estimation of dynamic... more This paper addresses a fundamental identification problem in the structural estimation of dynamic oligopoly models of market entry and exit. Using the standard datasets in existing empirical applications, three components of a firm's profit function are not separately identified: the fixed cost of an incumbent firm, the entry cost of a new entrant, and the scrap value of an exiting firm. We study the implications of this result on the power of this class of models to identify the effects of different comparative static exercises and counterfactual public policies. First, we derive a closed-form relationship between the three unknown structural functions and the two functions that are identified from the data. We use this relationship to provide the correct interpretation of the estimated objects that are obtained under the 'normalization assumptions' considered in most applications. Second, we characterize a class of counterfactual experiments that are identified using the estimated model, despite the non-separate identification of the three primitives. Third, we show that there is a general class of counterfactual experiments of economic relevance that are not identified. We present a numerical example that illustrates how ignoring the non-identification of these counterfactuals (i.e., making a 'normalization assumption' on some of the three primitives) generates sizable biases that can modify even the sign of the estimated effects. Finally, we discuss possible solutions to address these identification problems.

The RAND Journal of Economics, Jul 27, 2016

The 1994 Riegle Neal (RN) Act removed interstate banking restrictions in the US. The primary moti... more The 1994 Riegle Neal (RN) Act removed interstate banking restrictions in the US. The primary motivation was to permit geographic risk diversification (GRD). Using a factor model to measure banks' geographic risk, we show that RN expanded GRD possibilities in small states, but that few banks took advantage. Using our measure of geographic risk and a revealed preference approach, we identify preferences towards GRD separately from the contribution of other factors to branch network configuration. Risk has a negative effect on bank value, but this has been counterbalanced by economies of density/scale, reallocation/merging costs, and concerns for local market power.

Econometrics, 2005

RePEc: Research Papers in Economics, Mar 14, 2012

RePEc: Research Papers in Economics, Apr 19, 2005

RePEc: Research Papers in Economics, Jun 17, 2004

RePEc: Research Papers in Economics, Mar 1, 1999

arXiv (Cornell University), Jul 9, 2023

Social Science Research Network, 1998

Social Science Research Network, 2005

Advances in econometrics, Dec 13, 2013

The Review of Economic Studies, Mar 6, 2019

Journal of Industrial Economics, Dec 1, 2016

Social Science Research Network, 2007

arXiv (Cornell University), May 8, 2022

Journal of Econometrics, May 1, 2012

This paper studies the contribution of demand, costs, and strategic factors to the adoption of hu... more This paper studies the contribution of demand, costs, and strategic factors to the adoption of hub-and-spoke networks in the US airline industry. Our results are based on the estimation of a dynamic oligopoly game of network competition that incorporates three groups of factors that may explain hub-and-spoke networks: (1) travelers may value the services associated with the scale of operation of an airline in the hub airport; (2) operating costs and entry costs in a route may decline with the airline's scale of operation in the origin and destination airports (e.g., economies of scale and scope); and (3) a hub-and-spoke network may be an effective strategy to deter the entry of other carriers. We estimate the model using data from the Airline Origina n dD e s t i n a t i o nS u r v e yw i t hi n f o r m a t i o n on quantities, prices, and entry and exit decisions for every airline company in the routes between the 55 largest US cities. As methodological contributions, we propose and apply a method to reduce the dimension of the state space in dynamic games, and a procedure to deal with the problem of multiple equilibria when using a estimated model to make counterfactual experiments. We find that the most important factor to explain the adoption of hub-and-spoke networks is that the cost of entry in a route declines importantly with the scale of operation of the airline in the airports of the route. For some of the larger carriers, strategic entry deterrence is the second most important factor to explain hub-and-spoke networks.

arXiv (Cornell University), May 10, 2018

Econometrica, Jul 1, 2002

This paper proposes a procedure for the estimation of discrete Markov decision models and studies... more This paper proposes a procedure for the estimation of discrete Markov decision models and studies its statistical and computational properties. Our Nested Pseudo-Likelihood method (NPL) is similar to Rust's Nested Fixed Point algorithm (NFXP), but the order of the two nested algorithms is swapped. First, we prove that NPL produces the Maximum Likelihood Estimator under the same conditions as NFXP. Our procedure requires fewer policy iterations at the expense of more likelihood-climbing iterations. We focus on a class of in…nite-horizon, partial likelihood problems for which NPL results in large computational gains. Second, based on this algorithm we de…ne a class of consistent and asymptotically equivalent Sequential Policy Iteration (PI) estimators, which encompasses both Hotz-Miller's CCP estimator and the partial Maximum Likekihood estimator. This presents the researcher with a "menu" of sequential estimators re ‡ecting a trade-o¤ between …nite-sample precision and computational cost. Using actual and simulated data we compare the relative performance of these estimators. In all our experiments the bene…ts in terms of precision of using a 2-stage PI estimator instead of 1-stage (i.e., Hotz-Miller) are very signi…cant. More interestingly, the bene…ts of MLE relative to 2-stage PI are small.

Econometrica, 2007

Quantitative marketing and economics, Jun 14, 2014

The RAND Journal of Economics, Jul 27, 2016