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内生误报下的处理效应估计AI 解读

Participation in social programs is often misreported in survey data, complicating the estimation of treatment effects. We propose a model to estimate treatment effects under endogenous participation and endogenous misreporting. We present an expression for the asymptotic bias of both OLS and IV estimators and discuss the conditions under which sign reversal may occur. We provide a method for eliminating this bias when researchers have access to information regarding…

无排除限制的处理效应估计：学校早餐计划应用AI 解读

SUMMARY The increase in childhood obesity has garnered the attention of many in policymaking circles. Consequently, school nutrition programs such as the School Breakfast Program (SBP) have come under scrutiny. The identification of the causal effects of such programs, however, is difficult owing to non‐random selection into the program and the lack of exclusion restrictions. Here, we propose two new estimators aimed at addressing this situation. We compare our new…

倾向得分模型的设定：贸易政策分析中的应用AI 解读

The use of propensity score methods for program evaluation with nonexperimental data typically requires that the propensity score be estimated, often with a model whose specification is unknown. Although theoretical results suggest that estimators using more flexible propensity score specifications perform better, this has not filtered into applied research. Here we provide Monte Carlo evidence indicating benefits of overspecifying the propensity score that are robust across…

大量非负约束绑定时的高维需求系统估计AI 解读

Two econometric issues arise in the structural estimation of consumer or producer demand systems in the presence of many binding non-negativity constraints. Firstly, most existing methods entail the evaluation of multivariate probability integrals. Secondly, the issue of statistical coherency must be addressed. We circumvent both of these issues using Gibbs' Sampling, along with data augmentation and rejection sampling. We illustrate our method using several simulated data…