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固定效应动态离散选择模型中平均边际效应的识别AI 解读

Abstract In nonlinear panel data models, fixed-effects methods are often criticized because they cannot identify average marginal effects (AMEs) in short panels. In contrast with that criticism, we prove the point identification of different AMEs, including causal effects of changes in the lagged dependent variable or the last choice's duration, in a panel dynamic logit model for T as small as three. Our proofs are constructive and provide simple closed-form expressions for…

结构动态 Logit 模型中未观测异质性的充分统计量AI 解读

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…

动态离散博弈估计中的均衡约束实施AI 解读

Imposing equilibrium restrictions provides substantial gains in the estimation of dynamic discrete games. Estimation algorithms imposing these restrictions have different merits and limitations. Algorithms that guarantee local convergence typically require the approximation of high‐dimensional Jacobians. Alternatively, the Nested Pseudo‐Likelihood (NPL) algorithm is a fixed‐point iterative procedure, which avoids the computation of these matrices, but—in games—may fail to…

参与者信念不处于均衡时动态博弈的识别与估计AI 解读

This article deals with the identification and estimation of dynamic games when players’ beliefs about other players’ actions are biased, that is, beliefs do not represent the probability distribution of the actual behaviour of other players conditional on the information available. First, we show that an exclusion restriction, typically used to identify empirical games, provides testable non-parametric restrictions of the null hypothesis of equilibrium beliefs in dynamic…

多重均衡与不可观测异质性下不完全信息博弈的识别AI 解读

This paper deals with identification of discrete games of incomplete information when we allow for three types of unobservables: payoff‐relevant variables, both players' private information and common knowledge, and nonpayoff‐relevant variables that determine the selection between multiple equilibria. The specification of the payoff function and the distributions of the common knowledge unobservables is nonparametric with finite support (i.e., finite mixture model). We…

美国航空业的动态寡头博弈：估计与政策实验AI 解读

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 game of network competition 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 of the paper, we…

动态离散选择结构模型：综述AI 解读

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 some of the estimation methods are available in a companion web page.

重新审视动态离散决策过程的识别：退休行为应用AI 解读

This article deals with the estimation of behavioral and welfare effects of counterfactual policy interventions using dynamic structural models where all the primitive functions are nonparametrically specified (i.e., preferences, technology, transition rules, and distribution of unobserved variables). It proves the nonparametric identification of agents’ decision rules, before and after the policy intervention, and of the change in agents’ welfare. Based on these results, I…

摘要暂缺

动态离散博弈的序贯估计AI 解读

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…

交换嵌套不动点算法：离散马尔可夫决策模型的一类估计量AI 解读

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…