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早期儿童干预收益分布的分位数AI 解读

Summary We investigate the distribution of gains among participants in the Infant Health and Development Program, an understudied randomized controlled trial that targets infants with low birth weight. Our primary focus is on assessing the effects in cognitive and health outcomes within distinct subgroups, which we define based on the outcomes that would occur in the absence of program participation. We propose a strategy to estimate the distribution of gains from the…

Summary When dealing with the estimation of Engel curves, measurement errors in expenditure data and simultaneity are likely sources of endogeneity. In this paper we study identification of the parameters that characterize an Engel curve in the presence of both. We consider specifications where budget shares are polynomials in the logarithm of total expenditure, which is the case frequently encountered in empirical applications. We propose an estimation procedure which is an…

学历误报、多重测量与教育资格的工资回报AI 解读

We consider the identification and estimation of the average wage return to attaining educational qualifications when attainment is potentially measured with error. By exploiting two independent measures of qualifications, we identify the extent of misclassification in administrative and self-reported data on educational attainment. The availability of multiple self-reported educational measures additionally allows us to identify the temporal patterns of individual…

协变量测量误差下的处理效应估计AI 解读

This paper investigates the effect that covariate measurement error has on a treatment effect analysis built on an unconfoundedness restriction in which there is conditioning on error free covariates. The approach uses small parameter asymptotic methods to obtain the approximate effects of measurement error for estimators of average treatment effects. The approximations can be estimated using data on observed outcomes, the treatment indicator and error contaminated…

We study the impact of misreported treatment status on the estimation of causal treatment effects, focusing on applications where no additional information or repeated measurements are available. We first characterize the bias introduced by misclassification on the average treatment effect on the treated (ATT) under a conditional independence assumption, in both a binary and a multiple-treatment setting. We find that the bias of matching-type estimators computed from…

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