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Closed Form Estimators for a Class of Semiparametric Multinomial Choice Models

一类半参数多项选择模型的闭式估计量

We consider a semiparametric multinomial choice model that allows for an arbitrary joint distribution of choice specific unobservables that are independent of explanatory variables. This model permits relatively flexible substitution patterns between choices. To minimize computational difficulties, we restrict attention on estimators of the model that can be expressed in closed form. We combine and extend various results from the existing literature to enforce economic…

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Econometrics of insurance with multidimensional types

多维类型保险模型的计量分析

In this paper, we address the identification and estimation of insurance models where insurees have private information about their risk and risk aversion. The model includes random damages and allows for several claims, while insurees choose from a finite number of coverages. We show that the joint distribution of risk and risk aversion is nonparametrically identified despite bunching due to multidimensional types and a finite number of coverages. Our identification…

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Estimation of treatment effects under endogenous heteroskedasticity

内生异方差下的处理效应估计

This paper considers a treatment effect model in which individual treatment effect may be heterogeneous, even among observationally identical individuals. Specifically, by extending the classical instrumental-variables (IV) model with an endogenous binary treatment, the heteroskedasticity of the error disturbance is allowed to vary with the treatment variable so that the treatment generates both mean and variance effect on the outcome. In this endogenous heteroskedasticity…

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TESTING FOR UNOBSERVED HETEROGENEOUS TREATMENT EFFECTS WITH OBSERVATIONAL DATA

利用观测数据检验不可观测的异质处理效应

Unobserved heterogeneous treatment effects have been emphasized in the recent policy evaluation literature (see, e.g., Heckman and Vytlacil (2005, Econometrica 73, 669–738)). This paper proposes a nonparametric test for unobserved heterogeneous treatment effects in a treatment effect model with a binary treatment assignment, allowing for individuals’ self-selection to the treatment. Under the standard local average treatment effects assumptions, i.e., the no defiers…

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Semiparametric estimation of dynamic discrete choice models

动态离散选择模型的半参数估计

We consider the estimation of dynamic binary choice models in a semiparametric setting, in which the per-period utility functions are known up to a finite number of parameters, but the distribution of utility shocks is left unspecified. This semiparametric setup differs from most of the existing identification and estimation literature for dynamic discrete choice models. To show identification we derive and exploit a new recursive representation for the unknown quantile…

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Estimation of Heterogeneous Individual Treatment Effects With Endogenous Treatments

内生处理下异质性个体处理效应的估计

This article estimates individual treatment effects (ITE) and its probability distribution in a triangular model with binary-valued endogenous treatments. Our estimation procedure takes two steps. First, we estimate the counterfactual outcome and hence, the ITE for every observational unit in the sample. Second, we estimate the ITE density function of the whole population. Our estimation method does not suffer from the ill-posed inverse problem associated with inverting a…

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Rationalization and identification of binary games with correlated types

私人类型相关的二元博弈:模型相容性与识别

This paper studies the rationalization and identification of binary games where players have correlated private types. Allowing for type correlation is crucial in global games and in models with social interactions as it represents correlated private information and homophily, respectively. Our approach is fully nonparametric in the joint distribution of types and the strategic effects in the payoffs. First, under monotone pure Bayesian Nash Equilibrium strategy, we…

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Estimation of social-influence-dependent peer pressure in a large network game

大型网络博弈中依赖社会影响力的同伴压力估计

Research on peer effects in sociology has long been focused on social interactions and the associated social influence process. In this paper, we extend a large‐network‐based game model to a model that allows for the dependence of social interactions on social‐influence status. In particular, we use the Katz–Bonacich centrality to measure individuals' social influences, which are obtained directly from the observation of a social network. To solve the computational burden…

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Counterfactual mapping and individual treatment effects in nonseparable models with binary endogeneity

二元内生非可分模型中的反事实映射与个体处理效应

This paper establishes nonparametric identification of individual treatment effects in a nonseparable model with a binary endogenous regressor. The outcome variable may be continuous, discrete, or a mixture of both, while the instrumental variable can take binary values. First, we study the case where the model includes a selection equation for the binary endogenous regressor. We establish point identification of the individual treatment effects and the structural function…

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Estimating a nonparametric triangular model with binary endogenous regressors

含二元内生解释变量的非参数三角模型估计

We consider identification and estimation in a nonparametric triangular system with a binary endogenous regressor and nonseparable errors. For identification, we take a control function approach utilizing the Dynkin system idea. We articulate various trade‐offs, including continuity, monotonicity and differentiability. For estimation, we use the idea of local instruments under smoothness assumptions, but we do not assume additive separability in latent variables. Our…

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Inference in semiparametric binary response models with interval data

区间数据下半参数二元响应模型的推断

This paper studies the semiparametric binary response model with interval data investigated by Manski and Tamer (2002). In this partially identified model, we propose a new estimator based on MT’s modified maximum score (MMS) method by introducing density weights to the objective function, which allows us to develop asymptotic properties of the proposed set estimator for inference. We show that the density-weighted MMS estimator converges at a nearly cube-root-n rate. We…

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Semiparametric identification of binary decision games of incomplete information with correlated private signals

私人信号相关的不完全信息二元决策博弈的半参数识别

This paper studies the identification and estimation of a static binary decision game of incomplete information. We make no parametric assumptions on the joint distribution of private signals and allow them to be correlated. We show that the parameters of interest can be point-identified subject to a scale normalization under mild support requirements for the regressors (publicly observed state variables) and errors (private signals). Following Manski and Tamer (2002), we…

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Estimation of discrete games with correlated types

类型相关的离散博弈估计

In this paper, I focus on the identification and estimation of static games of incomplete information with correlated types. Instead of making the independence assumption on players' types in order to simplify the equilibrium set, I propose an approach that allows me to identify subsets of the space of covariates (i.e. publicly observed state variables in payoff functions), for which there exists a unique pure strategy Bayesian Nash equilibrium (BNE) and the equilibrium…

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Tighter bounds in triangular systems

三角系统中更紧的识别界

We study a nonparametric triangular system with (potentially discrete) endogenous regressors and nonseparable errors. Like in other work in this area, the parameter of interest is the structural function evaluated at particular values. We impose a global exclusion and exogeneity condition, in contrast to Chesher (2005), but develop a rank condition which is weaker than Chesher's. The alternative rank condition can be satisfied for binary endogenous regressors, and it often…

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