A Note on the Role of the Propensity Score for Estimating Average Treatment Effects

Hahn [Hahn, J. (1998). On the role of the propensity score in efficient semiparametric estimation of average treatment effects. Econometrica 66:315-331] derived the semiparametric efficiency bounds for estimating the average treatment effect (ATE) and the average treatment effect on the treated (ATET). The variance of ATET depends on whether the propensity score is known or unknown. Hahn attributes this to “dimension reduction.” In this paper, an alternative explanation is given: Knowledge of the propensity score improves upon the estimation of the distribution of the confounding variables.     

Direct and Indirect Causal Effects via Potential Outcomes*

Abstract. The use of the concept of ‘direct’ versus ‘indirect’ causal effects is common, not only in statistics but also in many areas of social and economic sciences. The related terms of ‘biomarkers’ and ‘surrogates’ are common in pharmacological and biomedical sciences. Sometimes this concept is represented by graphical displays of various kinds. The view here is that there is a great deal of imprecise discussion surrounding this topic and, moreover, that the most straightforward way to clarify the situation is by using potential outcomes to define causal effects. In particular, I suggest that the use of principal stratification is key to understanding the meaning of direct and indirect causal effects. A current study of anthrax vaccine will be used to illustrate ideas.     

《天龙八部》中的因果之说

《天龙八部》是金庸作品中和佛教关系最紧密的一部小说。金庸通过三位主角引出了芸芸众生相以及纷繁复杂的故事发展,而这一切到最后,全部都是有因可循的。通过分析主角及配角的经历和结局,来揭示《天龙八部》中所体现的因果之说。     

Double robust estimator in general treatment regimes based on Covariate-balancing

Double robust estimators have double the chance of being a consistent estimator of a causal effect in binary treatments cases. In this paper, we proposed an estimator of a causal effect for general treatment regimes based on covariate-balancing. Under parametrical situation, our estimator has double robustness.     

Research Design Meets Market Design: Using Centralized Assignment for Impact Evaluation

A growing number of school districts use centralized assignment mechanisms to allocate school seats in a manner that reflects student preferences and school priorities. Many of these assignment schemes use lotteries to ration seats when schools are oversubscribed. The resulting random assignment opens the door to credible quasi‐experimental research designs for the evaluation of school effectiveness. Yet the question of how best to separate the lottery‐generated randomization integral to such designs from non‐random preferences and priorities remains open. This paper develops easily‐implemented empirical strategies that fully exploit the random assignment embedded in a wide class of mechanisms, while also revealing why seats are randomized at one school but not another. We use these methods to evaluate charter schools in Denver, one of a growing number of districts that combine charter and traditional public schools in a unified assignment system. The resulting estimates show large achievement gains from charter school attendance. Our approach generates efficiency gains over ad hoc methods, such as those that focus on schools ranked first, while also identifying a more representative average causal effect. We also show how to use centralized assignment mechanisms to identify causal effects in models with multiple school sectors.     

我国教育投入与经济增长关系的实证研究

利用协整分析和Granger因果检验方法研究1952-2002期间,我国教育投入和经济增长之间的相互关系,证实我国经济增长教育的投入,且教育投入与国内生产总值间互为因果关系,增加教育投入有助于促进我国实际经济总量的增长,同时,经济和增长和发展水平决定着教育投入的规模.     

Causal inferences on the effectiveness of complex social programs: Navigating assumptions,sources of complexity and evaluation design challenges

This paper explores avenues for navigating evaluation design challenges posed by complex social programs (CSPs) and their environments when conducting studies that call for generalizable, causal inferences on the intervention’s effectiveness. A definition is provided of a CSP drawing on examples from different fields, and an evaluation case is analyzed in depth to derive seven (7) major sources of complexity that typify CSPs, threatening assumptions of textbook-recommended experimental designs for performing impact evaluations. Theoretically-supported, alternative methodological strategies are discussed to navigate assumptions and counter the design challenges posed by the complex configurations and ecology of CSPs. Specific recommendations include: sequential refinement of the evaluation design through systems thinking, systems-informed logic modeling; and use of extended term, mixed methods (ETMM) approaches with exploratory and confirmatory phases of the evaluation. In the proposed approach, logic models are refined through direct induction and interactions with stakeholders. To better guide assumption evaluation, question-framing, and selection of appropriate methodological strategies, a multiphase evaluation design is recommended.     

Comparison of causal effect estimators under exposure misclassification

Over the past decades, various principles for causal effect estimation have been proposed, all differing in terms of how they adjust for measured confounders: either via traditional regression adjustment, by adjusting for the expected exposure given those confounders (e.g., the propensity score), or by inversely weighting each subject's data by the likelihood of the observed exposure, given those confounders. When the exposure is measured with error, this raises the question whether these different estimation strategies might be differently affected and whether one of them is to be preferred for that reason. In this article, we investigate this by comparing inverse probability of treatment weighted (IPTW) estimators and doubly robust estimators for the exposure effect in linear marginal structural mean models (MSM) with G-estimators, propensity score (PS) adjusted estimators and ordinary least squares (OLS) estimators for the exposure effect in linear regression models. We find analytically that these estimators are equally affected when exposure misclassification is independent of the confounders, but not otherwise. Simulation studies reveal similar results for time-varying exposures and when the model of interest includes a logistic link.     

玩忽职守罪的因果关系法律问题研究

目前,玩忽职守犯罪在职务性犯罪中呈现出高发态势,严重影响了国家机关的公信力,也给国家和人民造成了重大损失。但目前司法实践中对玩忽职守罪因果关系认定比较难。玩忽职守罪因果关系本质与其归责在国内外刑法学界至今争论不已,本文以案例作为出发点,对各种理论和观点进行分析批判基础上提出客观归责理论并予以论证,同时对玩忽职守罪因果关系相关问题进行探讨。