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TESTING HYPOTHESES ABOUT ABSOLUTE CONCENTRATION CURVES AND MARGINAL CONDITIONAL STOCHASTIC DOMINANCE

绝对集中曲线与边际条件随机占优的假设检验

We consider statistical tests concerning various relationships between two absolute concentration curves (ACCs). In particular, we consider tests for determining if the two ACCs coincide, if one is above another in a specified order, or if they do not intersect without specifying which one is above/below the other one. These problems are of interest in the context of marginal conditional stochastic dominance (MCSD). Constructing statistical tests for the MCSD relies on ideas…

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QUANTILE REGRESSION WITH MISMEASURED COVARIATES

协变量测量误差下的分位数回归

This paper establishes that the availability of instrumental variables enables the identification and the consistent estimation of nonparametric quantile regression models in the presence of measurement error in the regressors. The proposed estimator takes the form of a nonlinear functional of derivatives of conditional expectations and is shown to provide estimated quantile functions that are uniformly consistent over a compact set.

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On Casting Random-Effects Models in a Survival Framework

将随机效应模型置于生存分析框架

Summary Logistic random-effects models are often employed in the analysis of correlated binary data. However, fitting these models is challenging, since the marginal distribution of the response variables is analytically intractable. Often, the random effects are treated as missing data for constructing traditional data augmentation algorithms. We create a novel alternative data augmentation scheme that simplifies the likelihood-based inference for logistic random-effects…

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Non-Crossing Non-Parametric Estimates of Quantile Curves

不交叉分位数曲线的非参数估计

Summary Since the introduction by Koenker and Bassett, quantile regression has become increasingly important in many applications. However, many non-parametric conditional quantile estimates yield crossing quantile curves (calculated for various p ∈ (0, 1)). We propose a new non-parametric estimate of conditional quantiles that avoids this problem. The method uses an initial estimate of the conditional distribution function in the first step and solves the problem of…

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Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations

效率分析的非参数无条件分位数估计:美联储支票处理业务应用

This paper examines the technical efficiency of U.S. Federal Reserve check processing offices over 1980–2003. We extend results from Park et al. (2000) and Daouia and Simar (2007) to develop an unconditional, hyperbolic, α-quantile estimator of efficiency. Our new estimator is fully non-parametric and robust with respect to outliers; when used to estimate distance to quantiles lying close to the full frontier, it is strongly consistent and converges at rate root-n, thus…

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Formal and Informal Risk Sharing in LDCs: Theory and Empirical Evidence

欠发达国家的正式与非正式风险分担:理论与经验证据

We develop and estimate a model of dynamic interactions in which commitment is limited and contracts are incomplete to explain the patterns of income and consumption growth in village economies of less developed countries. Households can insure each other through both formal contracts and informal agreements, that is, self-enforcing agreements specifying voluntary transfers. This theoretical setting nests the case of complete markets and the case where only informal…

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Asymptotic Least Squares Estimators for Dynamic Games

This paper considers the estimation problem in dynamic games with finite actions. we derive the equation system that characterizes the markovian equilibria. the equilibrium equation system enables us to characterize conditions for identification. we consider a class of asymptotic least squares estimators defined by the equilibrium conditions. this class provides a unified framework for a number of well-known estimators including those by Hotz and Miller (1993) and by…

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Partial Identification in Monotone Binary Models: Discrete Regressors and Interval Data

单调二元模型的部分识别:离散回归量与区间数据

We investigate identification in semi-parametric binary regression models, y = 1(xβ+υ+ε > 0) when υ is either discrete or measured within intervals. The error term ε is assumed to be uncorrelated with a set of instruments z, ε is independent of υ conditionally on x and z, and the support of −(xβ + ε) is finite. We provide a sharp characterization of the set of observationally equivalent parameters β. When there are as many instruments z as variables x, the bounds of the…

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Comment

评论:博弈中偏好与信念参数的识别

The paper by Andres Aradillas-Lopez and Elie Tamer clari…es how identi…cation can be obtained in games and provides techniques to do so.In other words, it o¤ers constructive ways of analyzing either point or set identi…cation of parameters governing the preferences and beliefs of players in di¤erent games.In this short comment, I am trying to highlight the key issues that are brought out by the paper.First, as sometimes alluded to by the authors, one way of reading their…

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The Identification Power of Equilibrium in Simple Games

简单博弈中均衡假设的识别能力

We examine the identification power that (Nash) equilibrium assumptions play in conducting inference about parameters in some simple games. We focus on three static games in which we drop the Nash equilibrium assumption and instead use rationalizability as the basis for strategic play. The first example examines a bivariate discrete game with complete information of the kind studied in entry models. The second example considers the incomplete-information version of the…

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The Sensitivity of Productivity Estimates

生产率估计对方法选择的敏感性

Researchers interested in estimating productivity can choose from an array of methodologies, each with its strengths and weaknesses. This study compares productivity estimates and evaluates the extent to which the conclusions of three important productivity debates in the economic development literature are sensitive to the choice of estimation method. Five widely used techniques are considered, two nonparametric and three parametric: index numbers, data envelopment…

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A bootstrap procedure for panel data sets with many cross-sectional units

适用于大量截面单位面板数据的自助法程序

This paper considers the issue of bootstrap resampling in panel data sets. The availability of data sets with large temporal and cross-sectional dimensions suggests the possibility of new resampling schemes. We suggest one possibility which has not been widely explored in the literature. It amounts to constructing bootstrap samples by resampling whole cross-sectional units with replacement. In cases where the data do not exhibit cross-sectional dependence but exhibit…

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Survival Analysis With Quantile Regression Models

使用分位数回归模型进行生存分析

Quantile regression offers great flexibility in assessing covariate effects on event times, thereby attracting considerable interests in its applications in survival analysis. But currently available methods often require stringent assumptions or complex algorithms. In this article we develop a new quantile regression approach for survival data subject to conditionally independent censoring. The proposed martingale-based estimating equations naturally lead to a simple…

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Trimmed Comparison of Distributions

分布的修剪比较

This article introduces an analysis of similarity of distributions based on the L2-Wasserstein distance between trimmed distributions. Our main innovation is the use of the impartial trimming methodology, already considered in robust statistics, which we adapt to this setup. Instead of simply removing data at the tails to provide some robustness to the similarity analysis, we develop a data-driven trimming method aimed at maximizing similarity between distributions.…

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Learning Causal Bayesian Network Structures From Experimental Data

从实验数据学习因果贝叶斯网络结构

We propose a method for the computational inference of directed acyclic graphical structures given data from experimental interventions. Order-space Markov chain Monte Carlo, equi-energy sampling, importance weighting, and stream-based computation are combined to create a fast algorithm for learning causal Bayesian network structures.

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Robust and Efficient Adaptive Estimation of Binary-Choice Regression Models

二元选择回归模型的稳健高效自适应估计

The binary-choice regression models, such as probit and logit, are used to describe the effect of explanatory variables on a binary response variable. Typically estimated by the maximum likelihood method, estimates are very sensitive to deviations from a model, such as heteroscedasticity and data contamination. At the same time, the traditional robust (high-breakdown point) methods, such as the maximum trimmed likelihood, are not applicable because, by trimming observations,…

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Two-Sided Estimation of Mate Preferences for Similarities in Age, Education, and Religion

年龄、教育与宗教相似性择偶偏好的双边估计

We propose a two-sided method to simultaneously estimate men's and women's preferences for relative age, education, and religious characteristics of potential mates using cross-sectional data on married couples and single individuals, in conjunction with a behavioral model developed in game theory and discrete choice estimation methods developed for simpler, one-sided choice situations. We use fixed effects to control for characteristics that are observed by the opposite sex…

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Causal Inference in Hybrid Intervention Trials Involving Treatment Choice

包含治疗选择的混合干预试验中的因果推断

Randomized allocation of treatments is a cornerstone of experimental design but has drawbacks when a limited set of individuals are willing to be randomized, or the act of randomization undermines the success of the treatment. Choice-based experimental designs allow a subset of the participants to choose their treatments. We discuss here causal inferences for hybrid experimental designs in which some participants are randomly allocated to treatments and others receive their…

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Estimating Incumbency Advantage and Its Variation, as an Example of a Before–After Study

任职优势及其差异的估计:一项前后比较研究

Incumbency advantage is one of the most widely studied features in American legislative elections. In this article we construct and implement an estimate that allows incumbency advantage to vary between individual incumbents. This model predicts that open-seat elections will be less variable than those with incumbents running, an observed empirical pattern that is not explained by previous models. We apply our method to the U.S. House of Representatives in the twentieth…

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Statistical Treatment Choice

统计辅助的处理方案选择

Choosing among a number of treatments the most suitable for a particular client is an issue of everyday concern. In this article two methodological advances for statistically assisted treatment choice are developed: First, it permits one to combine a dataset on previously treated clients with a dataset on new clients when the regressors available in these two datasets do not coincide. It thereby incorporates additional regressors on previously treated clients that are not…

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Toward Causal Inference With Interference

存在个体间干扰时的因果推断

A fundamental assumption usually made in causal inference is that of no interference between individuals (or units); that is, the potential outcomes of one individual are assumed to be unaffected by the treatment assignment of other individuals. However, in many settings, this assumption obviously does not hold. For example, in the dependent happenings of infectious diseases, whether one person becomes infected depends on who else in the population is vaccinated. In this…

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Statistical modeling of causal effects in continuous time

连续时间因果效应的统计建模

This article studies the estimation of the causal effect of a time-varying treatment on time-to-an-event or on some other continuously distributed outcome. The paper applies to the situation where treatment is repeatedly adapted to time-dependent patient characteristics. The treatment effect cannot be estimated by simply conditioning on these time-dependent patient characteristics, as they may themselves be indications of the treatment effect. This time-dependent confounding…

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