TY  - CHAP
AB  - Abstract 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 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.
VL  - 31
SN  - 978-1-78350-052-9/0731-9053
DO  - 10.1108/S0731-9053(2013)0000032001
UR  - https://doi.org/10.1108/S0731-9053(2013)0000032001
AU  - Aguirregabiria Victor
AU  - Magesan Arvind
PY  - 2013
Y1  - 2013/01/01
TI  - Euler Equations for the Estimation of Dynamic Discrete Choice Structural Models
T2  - Structural Econometric Models
T3  - Advances in Econometrics
PB  - Emerald Group Publishing Limited
SP  - 3
EP  - 44
Y2  - 2024/04/26
ER  -