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The finite-sample properties of matching and weighting estimators, often used for estimating average treatment effects, are analyzed. Potential and feasible precision gains relative to pair matching are examined. Local linear matching (with and without trimming), k-nearest-neighbor matching, and particularly the weighting estimators performed worst. Ridge matching, on the other hand, leads to an approximately 25% smaller MSE than does pair matching. In addition, ridge…

何时应控制协变量？处理效应估计的面板式渐近分析AI 解读

The problem of when to control for continuous or high-dimensional discrete covariate vectors arises in both experimental and observational studies. Large-cell asymptotic arguments suggest that full control for covariates or stratification variables is always efficient, even if treatment is assigned independently of covariates or strata. Here, we approximate the behavior of different estimators using a panel-data-type asymptotic sequence with fixed cell sizes and the number…

使用匹配、工具变量与控制函数估计经济选择模型AI 解读

This paper investigates four topics. (1) It examines the different roles played by the propensity score (the probability of selection into treatment) in matching, instrumental variable, and control function methods. (2) It contrasts the roles of exclusion restrictions in matching and selection models. (3) It characterizes the sensitivity of matching to the choice of conditioning variables and demonstrates the greater robustness of control function methods to misspecification…

Recently there has been a surge in econometric work focusing on estimating average treatment effects under various sets of assumptions. One strand of this literature has developed methods for estimating average treatment effects for a binary treatment under assumptions variously described as exogeneity, unconfoundedness, or selection on observables. The implication of these assumptions is that systematic (for example, average or distributional) differences in outcomes…

多工具变量下的随机效应估计量AI 解读

In this paper we propose a new estimator for a model with one endogenous regressor and many instrumental variables. Our motivation comes from the recent literature on the poor properties of standard instrumental variables estimators when the instrumental variables are weakly correlated with the endogenous regressor. Our proposed estimator puts a random coefficients structure on the relation between the endogenous regressor and the instruments. The variance of the random…

临时解雇与分群总体模型AI 解读

Abstract This paper develops and estimates a split population model for the duration of temporary layoffs in the German labour market; the population being split according to whether a layoff is temporary or permanent. A flexible piecewise constant hazard is employed and the recall propensity is used to condition the duration of a temporary layoff. The distinction between factors that influence the recall propensity and factors that influence the duration of a temporary…

统计模型与生物恐怖袭击AI 解读

In the fall of 2001 an outbreak of inhalational anthrax occurred in the United States that was the result of bioterrorism. Letters contaminated with anthrax spores were sent through the postal system. In response to the outbreak, public health officials treated over 10,000 persons with antibiotic prophylaxis in the hopes of preventing further morbidity and mortality. No persons receiving the antibiotics subsequently developed disease. The question arises as to how many cases…

异方差样本选择模型的半参数估计AI 解读

This paper considers estimation of a sample selection model subject to conditional heteroskedasticity in both the selection and outcome equations. The form of heteroskedasticity allowed for in each equation is multiplicative, and each of the two scale functions is left unspecified. A three-step estimator for the parameters of interest in the outcome equation is proposed. The first two stages involve nonparametric estimation of the “propensity score” and the conditional…

因果模型中对百分位不变性随机偏离的处理AI 解读

Summary Consider a clinical trial in which participants are randomized to a single-dose treatment or a placebo control and assume that the adherence level is accurately recorded. If the treatment is effective, then good adherers in the treatment group should do better than poor adherers because they received more drug; the treatment group data follow a dose–response curve. But, good adherers to the placebo often do better than poor adherers, so the observed…

使用广义结构均值模型进行因果推断AI 解读

Summary We estimate cause–effect relationships in empirical research where exposures are not completely controlled, as in observational studies or with patient non-compliance and self-selected treatment switches in randomized clinical trials. Additive and multiplicative structural mean models have proved useful for this but suffer from the classical limitations of linear and log-linear models when accommodating binary data. We propose the generalized structural mean model to…

环境规制对制造业工厂新设的影响：倾向得分匹配估计的证据AI 解读

This study examines the effects of air quality regulation on economic activity. Anecdotal evidence and some recent empirical studies suggest that an inverse relationship exists between the stringency of environmental regulations and new plant formations. Using a unique county-level data set for New York State from 1980 to 1990, we revisit this conjecture using a seminonparametric method based on propensity score matching. Our empirical estimates suggest that…

因果推断中的一致一致性AI 解读

There is a long tradition of representing causal relationships by directed acyclic graphs (Wright, 1934). Spirtes (1994), Spirtes et al. (1993) and Pearl & Verma (1991) describe procedures for inferring the presence or absence of causal arrows in the graph even if there might be unobserved confounding variables, and/or an unknown time order, and that under weak conditions, for certain combinations of directed acyclic graphs and probability distributions, are asymptotically,…

持续期模型中处理效应的非参数识别AI 解读

This paper analyzes the specification and identification of causal multivariate duration models. We focus on the case in which one duration concerns the point in time a treatment is initiated and we are interested in the effect of this treatment on some outcome duration. We define “no anticipation of treatment” and relate it to a common assumption in biostatistics. We show that (i) no anticipation and (ii) randomized treatment assignment can be imposed without restricting…

同伴能力是否影响学生成绩？AI 解读

Abstract Empirical analysis of peer effects on student achievement has been open to question because of the difficulties of separating peer effects from other confounding influences. While most econometric attention has been directed at issues of simultaneous determination of peer interactions, we argue that issues of omitted and mismeasured variables are likely to be more important. We control for the most important determinants of achievement that will confound peer…

潜变量框架下处理效应参数的简便估计量AI 解读

This note derives simply computed closed-form expressions for the average treatment effect, the effect of treatment on the treated, the local average treatment effect, and the marginal treatment effect in a latent-variable framework for both normal and nonnormal models. Asymptotic standard errors for versions of these parameters that average over observed characteristics are also obtained. The performances of the derived estimators are also evaluated in Monte Carlo…

对 Neuberg《因果性》书评的评论AI 解读

I am grateful to Professor Neuberg for taking the time to study my book Causality and for summarizing its main ideas in a language familiar to readers of Econometric Theory . I will comment on several issues that I believe warrant further discussion. First, I will summarize in my own style what economists can learn from Causality , and, second, I will correct several inaccuracies in the summary of Professor Neuberg.

利用估计倾向得分高效估计平均处理效应AI 解读

We are interested in estimating the average effect of a binary treatment on a scalar outcome. If assignment to the treatment is exogenous or unconfounded, that is, independent of the potential outcomes given covariates, biases associated with simple treatment-control average comparisons can be removed by adjusting for differences in the covariates. Rosenbaum and Rubin (1983) show that adjusting solely for differences between treated and control units in the propensity score…

塔科马的气味AI 解读

A variant of the average derivative estimator is developed to construct an index measuring the effects of a copper smelter on house prices in Tacoma, Washington. The estimated average derivative index is smooth and has lower standard errors than regression coefficients estimated separately across discrete time periods. The dataset spans the time of initial rumors of Superfund site designation, the closing of the smelter, Superfund site designation, and the start of cleanup…

存在未识别参数时的结果增益预测分布AI 解读

distributions of outcome gains in the framework of a standard latent variable selection model. Although most previous work has focused on estimation of mean treatment parameters as the method for characterizing outcome gains from program participation, we show how the entire distributions associated with these gains can be obtained in certain situations. Although the out-of-sample outcome gain distributions depend on an unidentified parameter, we use the results of Koop and…

公共研发补贴对企业创新活动的影响AI 解读

This study analyzes the effects of public R&D policy schemes on the innovation activities of firms in Eastern Germany. The main question in this context is whether public funds stimulate R&D activities or simply crowd out privately financed R&D. Empirically, we investigate the average causal effects of all public R&D schemes in Eastern Germany using a nonparametric matching approach. Compared to the case in which no public financial means are provided, it turns out that…

未控制混杂与应答偏差的先验分布对推断的影响AI 解读

This article examines the potential for misleading inferences from conventional analyses and sensitivity analyses of observational data, and describes some proposed solutions based on specifying prior distributions for uncontrolled sources of bias. The issues are illustrated in a sensitivity analysis of confounding in a study of residential wire code and childhood leukemia and in a pooled analysis of 12 studies of magnetic-field measurements and childhood leukemia. Both…

利用因果图选择协变量以估计控制方案的因果效应AI 解读

Summary Consider a case where cause–effect relationships between variables can be described by a causal path diagram and the corresponding linear structural equation model. The paper proposes a graphical selection criterion for covariates to estimate the causal effect of a control plan. For designing the control plan, it is essential to determine both covariates that are used for control and covariates that are used for identification. The selection of covariates used for…

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