measurement error. Our proposed solution involves deconvolution kernel estimators of the propensity score and the regression …

classical measurement error. Our proposed solution involves deconvolution kernel estimators of the propensity score and the …

wrong answers are given to survey questions that aim to assess competence. We model this source of measurement error and …

While classical measurement error in the dependent variable in a linear regression framework results only in a loss of … precision, non-classical measurement error can lead to estimates which are biased and inference which lacks power. Here, we … consider a particular type of non-classical measurement error: skewed errors. Unfortunately, skewed measurement error is likely …

We examine economic mobility in India while rigorously accounting for measurement error. Such an analysis is imperative …

reviewing the sources of endogeneity—omitted variables, simultaneity, and measurement error—and their implications for inference …

The impact of measurement error in explanatory variables on quantile regression functions is investigated using a small … approximation to investigate the sensitivity of estimates to varying amounts of measurement error. …

We assess the role of measurement error in minimum wage evaluations when the treatment variable - the bite - is … measurement error derived from a record linkage of survey wages and administrative data. On the individual-level treatment effects …, measurement error can cause upward biased treatment effects. Besides aggregation, we discuss two possible remedies: the use of a …

While classical measurement error in the dependent variable in a linear regression framework results only in a loss of … precision, non-classical measurement error can lead to estimates which are biased and inference which lacks power. Here, we … consider a particular type of non-classical measurement error: skewed errors. Unfortunately, skewed measurement error is likely …