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条件矩不等式推断中的加权 KS 统计量AI 解读

This paper proposes set estimators and conservative confidence regions for the identified set in conditional moment inequality models using Kolmogorov–Smirnov statistics with a truncated inverse variance weighting with increasing truncation points. The new weighting differs from those proposed in the literature in two important ways. First, this paper shows that estimators based on KS statistics with the proposed weighting function converge to the identified set at a faster…

SUMMARY A new estimator is proposed for linear triangular systems, where identification results from the model errors following a bivariate and diagonal GARCH(1,1) process with potentially time‐varying error covariances. This estimator applies when traditional instruments are unavailable. I demonstrate its usefulness on asset pricing models like the capital asset pricing model and Fama–French three‐factor model. In the context of a standard two‐pass cross‐sectional…

动态二元选择模型中的半参数推断AI 解读

We introduce an approach for semiparametric inference in dynamic binary choice models that does not impose distributional assumptions on the state variables unobserved by the econometrician. The proposed framework combines Bayesian inference with partial identification results. The method is applicable to models with finite space of observed states. We demonstrate the method on Rust's model of bus engine replacement. The estimation experiments show that the parametric…

二元结果的工具变量随机系数模型AI 解读

In this paper, we study a random‐coefficients model for a binary outcome. We allow for the possibility that some or even all of the explanatory variables are arbitrarily correlated with the random coefficients, thus permitting endogeneity. We assume the existence of observed instrumental variables Z that are jointly independent with the random coefficients, although we place no structure on the joint determination of the endogenous variable X and instruments Z, as would be…

基于条件矩不等式的非参数推断AI 解读

This paper develops methods of inference for nonparametric and semiparametric parameters defined by conditional moment inequalities and/or equalities. The parameters need not be identified. Confidence sets and tests are introduced. The correct uniform asymptotic size of these procedures is established. The false coverage probabilities and power of the CS’s and tests are established for fixed alternatives and some local alternatives. Finite-sample simulation results are given…

计量经济模型中有限混合分布的部分识别AI 解读

We consider partial identification of finite mixture models in the presence of an observable source of variation in the mixture weights that leaves component distributions unchanged, as is the case in large classes of econometric models. We first show that when the number J of component distributions is known a priori, the family of mixture models compatible with the data is a subset of a J(J−1)-dimensional space. When the outcome variable is continuous, this subset is…

收入—闲暇偏好的识别与所得税政策评估AI 解读

The merits of alternative income tax policies depend on the population distribution of preferences for income and leisure. Standard theory, which supposes that persons want more income and more leisure, does not predict how they resolve the tension between these desires. Empirical studies of labor supply have imposed strong preference assumptions that lack foundation. This paper examines anew the problem of inference on income–leisure preferences and considers the…

反事实均值的非参数推断：偏差修正、置信集与弱工具变量AI 解读

This paper supplements Manski (1990) and Manski and Pepper (2000) and contributes to the literature by introducing the concept of weak IV for the partially identified mean counterfactual outcomes when an instrumental variable (IV) or a monotone instrumental variable (MIV) is available (IV or MIV assumption respectively); developing asymptotically uniformly valid confidence sets for the counterfactual mean outcomes and average treatment effects under the assumptions;…

检验矩不等式的实用两步法AI 解读

This paper considers the problem of testing a finite number of moment inequalities. We propose a two‐step approach. In the first step, a confidence region for the moments is constructed. In the second step, this set is used to provide information about which moments are “negative.” A Bonferonni‐type correction is used to account for the fact that, with some probability, the moments may not lie in the confidence region. It is shown that the test controls size uniformly over a…

数据组合下处理效应的识别AI 解读

We consider the identification of counterfactual distributions and treatment effects when the outcome variables and conditioning covariates are observed in separate datasets. Under the standard selection on observables assumption, the counterfactual distributions and treatment effect parameters are no longer point identified. However, applying the classical monotone re-arrangement inequality, we derive sharp bounds on the counterfactual distributions and policy parameters of…

凸矩不等式模型的渐近有效估计AI 解读

This paper examines the efficient estimation of partially identified models defined by moment inequalities that are convex in the parameter of interest. In such a setting, the identified set is itself convex and hence fully characterized by its support function. We provide conditions under which, despite being an infinite dimensional parameter, the support function admits √n‐consistent regular estimators. A semiparametric efficiency bound is then derived for its estimation,…

基于模拟的熵式潜变量积分AI 解读

This paper introduces a general method to convert a model defined by moment conditions that involve both observed and unobserved variables into equivalent moment conditions that involve only observable variables. This task can be accomplished without introducing infinite‐dimensional nuisance parameters using a least favorable entropy‐maximizing distribution. We demonstrate, through examples and simulations, that this approach covers a wide class of latent variables models,…

选择性进入拍卖中的识别AI 解读

This paper considers nonparametric identification of a two‐stage entry and bidding game we call the Affiliated‐Signal (AS) model. This model assumes that potential bidders have private values, observe signals of their values prior to entry, and then choose whether to undertake a costly entry process, but imposes only minimal structure on the relationship between signals and values. It thereby nests a wide range of entry processes, including in particular the Samuelson (1985)…

扩张自助法AI 解读

We propose a methodology for combining several sources of model and data incompleteness and partial identification, which we call Composition Theorem. We apply this methodology to the construction of confidence regions with partially identified models of general form. The region is obtained by inverting a test of internal consistency of the econometric structure. We develop a dilation bootstrap methodology to deal with sampling uncertainty without reference to the…

结构 VAR 模型中脉冲响应函数的推断AI 解读

Skepticism toward traditional identifying assumptions based on exclusion restrictions has led to a surge in the use of structural VAR models in which structural shocks are identified by restricting the sign of the responses of selected macroeconomic aggregates to these shocks. Researchers commonly report the vector of pointwise posterior medians of the impulse responses as a measure of central tendency of the estimated response functions, along with pointwise 68% posterior…

使用无效工具变量时局部平均处理效应的部分识别AI 解读

We derive nonparametric bounds for local average treatment effects (LATE) without imposing the exclusion restriction assumption or requiring an outcome with bounded support. Instead, we employ assumptions requiring weak monotonicity of mean potential and counterfactual outcomes within or across subpopulations defined by the values of the potential treatment status under each value of the instrument. The key element in our derivation is a result relating LATE to a causal…

部分识别拍卖模型的单点决策AI 解读

This article proposes a decision-theoretic method to choose a single reserve price for partially identified auction models, such as Haile and Tamer (2003 Haile, P. A. and Tamer, E. 2003. “Inference With an Incomplete Model of English Auctions,”. Journal of Political Economy, 111: 1–51. [Crossref], [Web of Science ®] , [Google Scholar]), using data on transaction prices from English auctions. The article employs Gilboa and Schmeidler (1989 Gilboa, I. and Schmeidler, D. 1989.…

多项离散选择的工具变量模型AI 解读

This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and…

利用面板数据进行稳健企业定价AI 解读

Firms often have imperfect information about demand for their products. We develop an integrated econometric and theoretical framework to model firm demand assessment and subsequent pricing decisions with limited information. We introduce a panel data discrete choice model whose realistic assumptions about consumer behavior deliver partially identified preferences and thus generate ambiguity in the firm pricing problem. We use the minimax-regret criterion as a…

预测者偏好的可恢复性AI 解读

We study the problem of identifying a forecaster’s loss function from observations on forecasts, realizations, and the forecaster’s information set. Essentially different loss functions can lead to the same forecasts in all situations, though within the class of all continuous loss functions, this is strongly nongeneric. With the small set of exceptional cases ruled out, generic nonparametric preference recovery is theoretically possible, but identification depends…

欧氏显示偏好：空间投票模型的检验AI 解读

SUMMARY In the spatial model of voting, voters choose the candidate closest to them in the ideological space. Recent work by Degan and Merlo in 2009 shows that it is falsifiable on the basis of individual voting data in multiple elections. We show how to tackle the fact that the model only partially identifies the distribution of voting profiles and we give a formal revealed preference test of the spatial voting model in three national elections in the USA, and strongly…

利用数据组合评估处理分配规则AI 解读

In real life, individuals are often assigned to binary treatments according to existing treatment protocols. Such protocols, when designed with “taste-based” motives, would be productively inefficient in that the expected returns to treatment for a marginal treatment recipient would vary across covariates and be larger for discriminated groups. This cannot be directly tested if assignment is based on more covariates than the researcher observes, because then the marginal…

二元响应半参数结构模型：形状限制与部分识别AI 解读

I study the partial identifying power of structural single-equation threshold-crossing models for binary responses when explanatory variables may be endogenous. The sharp identified set of threshold functions is derived for the case in which explanatory variables are discrete, and I provide a constructive proof of sharpness. There is special attention to a widely employed semiparametric shape restriction, which requires the threshold-crossing function to be a monotone…

样本选择概率未知但有界时总体均值的区间估计AI 解读

Applying concepts from partial identification to the domain of finite population sampling, we propose a method for interval estimation of a population mean when the probabilities of sample selection lie within a posited interval. The interval estimate is derived from sharp bounds on the Hajek (1971) estimator of the population mean. We demonstrate the method's utility for sensitivity analysis by applying it to a sample of needles collected as part of a syringe tracking and…