Solution and Estimation of Dynamic Discrete Choice Structural Models Using Euler Equations

50 Pages Posted: 1 Jun 2016

See all articles by Victor Aguirregabiria

Victor Aguirregabiria

University of Toronto - Department of Economics

Arvind Magesan

University of Calgary

Multiple version iconThere are 2 versions of this paper

Date Written: May 2016

Abstract

This paper extends the Euler Equation (EE) representation of dynamic decision problems to a general class of discrete choice models and shows that the advantages of this approach apply not only to the estimation of structural parameters but also to the computation of a solution and to the evaluation of counterfactual experiments. We use a choice probabilities representation of the discrete decision problem to derive marginal conditions of optimality with the same features as the standard EEs in continuous decision problems. These EEs imply a fixed point mapping in the space of conditional choice values, that we denote the Euler equation-value (EE-value) operator. We show that, in contrast to Euler equation operators in continuous decision models, this operator is a contraction. We present numerical examples that illustrate how solving the model by iterating in the EE-value mapping implies substantial computational savings relative to iterating in the Bellman equation (that requires a much larger number of iterations) or in the policy function (that involves a costly valuation step). We define a sample version of the EE-value operator and use it to construct a sequence of consistent estimators of the structural parameters, and to evaluate counterfactual experiments. The computational cost of evaluating this sample-based EE-value operator increases linearly with sample size, and provides an unbiased (in finite samples) and consistent estimator the counterfactual. As such there is no curse of dimensionality in the consistent estimation of the model and in the evaluation of counterfactual experiments. We illustrate the computational gains of our methods using several Monte Carlo experiments.

Keywords: Dynamic programming discrete choice models; Euler equations; Policy iteration; Estimation; Approximation bias.

JEL Classification: C13, C35, C51, C61

Suggested Citation

Aguirregabiria, Victor and Magesan, Arvind, Solution and Estimation of Dynamic Discrete Choice Structural Models Using Euler Equations (May 2016). Available at SSRN: https://ssrn.com/abstract=2786902

Victor Aguirregabiria (Contact Author)

University of Toronto - Department of Economics ( email )

150 St. George Street
Toronto, Ontario M5S 3G7
Canada
4169784358 (Phone)

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Arvind Magesan

University of Calgary ( email )

2500 University DR NW
Calgary, AB
Canada

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