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二元治疗选择中的概率预测：聚焦个性化医疗AI 解读

This paper extends my research applying statistical decision theory to treatment choice with sample data, using maximum regret to evaluate the performance of statistical treatment rules. The specific new contribution is to study as-if optimization using estimates of illness probabilities in a class of medical decisions. Beyond its specifics, the paper sends a broad message. Statisticians and computer scientists have addressed conditional prediction for decision making in…

预期存在缺失数据时的最小最大遗憾样本设计：面板应用AI 解读

Missing data problems are ubiquitous in data collection. In surveys, these problems may arise from unit response, item nonresponse, and panel attrition. Building on the Dominitz and Manski (2017) study of choice between two or more sampling processes that differ in cost and quality, we study minimax-regret sample design in anticipation of missing data, where the collected data will be used for prediction under square loss of the values of functions of two variables. The…

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…

社会互动下处理反应的识别AI 解读

This paper studies identification of potential outcome distributions when treatment response may have social interactions. Defining a person's treatment response to be a function of the entire vector of treatments received by the population, I study identification when non‐parametric shape restrictions and distributional assumptions are placed on response functions. An early key result is that the traditional assumption of individualistic treatment response is a polar case…

存在社会互动时处理响应的识别AI 解读

This paper develops a formal language for study of treatment response with social interactions, and uses it to obtain new findings on identification of potential outcome distributions. Defining a person's treatment response to be a function of the entire vector of treatments received by the population, I study identification when shape restrictions and distributional assumptions are placed on response functions. An early key result is that the traditional assumption of…

单调工具变量的进一步分析AI 解读

Econometric analyses of treatment response often use instrumental variable (IV) assumptions to identify treatment effects. The traditional IV assumption holds that mean response is constant across the sub-populations of persons with different values of an observed covariate. Manski and Pepper (2000) introduced monotone instrumental variable assumptions, which replace equalities with weak inequalities. This paper presents further analysis of the monotone instrumental variable…

过街还是等待？行人过街决策的实证分析AI 解读

Abstract We examine the behaviour of pedestrians wishing to cross a stream of traffic at signalized intersections. We model each pedestrian as making a discrete crossing choice by comparing the gaps between vehicles in traffic to an individual‐specific ‘critical gap’ that characterizes the individual's minimal acceptable gap. We propose both parametric and nonparametric approaches to estimate the distribution of critical gaps in the population of pedestrians. To estimate the…

An important objective of empirical research on treatment response is to provide decision makers with information useful in choosing treatments. Manski (2000, 2002, 2003) showed how identification problems generate ambiguity about the identity of optimal treatment choices. This paper studies treatment choice using sample data. I consider a planner who must choose among alternative statistical treatment rules, these being functions that map observed covariates of population…

解释变量或结果具有区间数据时的回归推断AI 解读

This paper examines inference on regressions when interval data are available on one variable, the other variables being measured precisely. Let a population be characterized by a distribution P(y, x, v, v0, v1), where y∈R1, x∈Rk, and the real variables (v, v0, v1) satisfy v0≤v≤v1. Let a random sample be drawn from P and the realizations of (y, x, v0, v1) be observed, but not those of v. The problem of interest may be to infer E(y|x, v) or E(v|x). This analysis maintains…

单调工具变量：教育回报的应用AI 解读

Econometric analyses of treatment response commonly use instrumental variable (IV) assumptions to identify treatment effects.Yet the credibility of IV assumptions is often a matter of considerable disagreement.There is therefore good reason to consider weaker but more credible assumptions.To this end, we introduce monotone instrumental variable (MIV) assumptions and the important special case of monotone treatment selection (MTS).We study the identifying power of MIV…

协变量和结局缺失的随机实验非参数分析AI 解读

Analysis of randomized experiments with missing covariate and outcome data is problematic, because the population parameters of interest are not identified unless one makes untestable assumptions about the distribution of the missing data. This article shows how population parameters can be bounded without making untestable distributional assumptions. Bounds are also derived under the assumption that covariate data are missing completely at random. In each case the bounds…

摘要暂缺

单调处理响应AI 解读

This paper investigates what may be learned about treatment response when it is assumed that response functions are monotone, semimonotone, or concave-monotone. Nothing is assumed about the process of treatment selection and cross-individual restrictions on response are not imposed. The idea is to determine, for every member of the population, the response functions that pass through the realized (treatment, outcome) pair and that are consistent with the assumption imposed.…

青少年时期家庭结构对高中毕业影响的不同估计AI 解读

Many studies have reported significant empirical associations between family structure during childhood and children's outcomes later in life. It may be that living in a nonintact family has adverse consequences for children. On the other hand, it may be that some unobserved process jointly determines family structure and children's outcomes. How then should one interpret the empirical evidence on the relationship between family structure and children's outcomes? The answer…

二元反应模型的识别AI 解读

This article studies identification of the threshold-crossing model of binary response. Most research on binary response has considered specific estimators and tests. The study of identification exposes the foundations of binary response analysis by making explicit the assumptions needed to justify different methods. It also clarifies the connections between reduced-form and structural analyses of binary response data. Assume that the binary outcome z is determined by an…

基于二元面板数据的随机效应线性模型半参数分析AI 解读

Andersen_(1970) considered the problem of inference on random effects linear models from binary response panel data, and showed that inference is possible if the disturbances for each panel member are known to be white noise with the logistic distribution. The present paper shows that inference remains possible if the disturbances are known only to be time-stationary. A conditional version of the maximum score estimator consistently estimates the parameters up to scale.…

基于选择结果抽样的选择概率估计AI 解读

Ti-H CONCERN of this paper is the estimation of the parameters of a probabilistic choice model when choices rather than decision makers are sampled. Existing estimation methods presuppose an exogeneous sampling process, that is one in which a sequence of decision makers are drawn and their choice behaviors observed. In contrast, in choice based sampling processes, a sequence of chosen alternatives are drawn and the characteristics of the decision makers selecting those…