Instrumental Variable Estimation with a Stochastic Monotonicity Assumption
نویسندگان
چکیده
منابع مشابه
Instrumental Variable Estimation with a Stochastic Monotonicity Assumption
The instrumental variables (IV) method provides a way to estimate the causal effect of a treatment when there are unmeasured confounding variables. The method requires a valid IV, a variable that is independent of the unmeasured confounding variables and is associated with the treatment but which has no effect on the outcome beyond its effect on the treatment. An additional assumption often mad...
متن کاملCensored Quantile Instrumental Variable Estimation with Stata
Many applications involve a censored dependent variable and an endogenous independent variable. Chernozhukov et al. (2015) introduced a censored quantile instrumental variable estimator (CQIV) for use in those applications, which has been applied by Kowalski (2016), among others. In this article, we introduce a Stata command, cqiv, that simplifes application of the CQIV estimator in Stata. We s...
متن کاملEmpirical Example: Instrumental Variable Estimation
So on average, a woman with more than two kids works 6 weeks fewer than her counterpart with fewer than 2 kids. The result changes a little after we include age as the regressor. The question is, does this correlation imply causality? So the key regressor is morekids. The main concern is that morekids may be endogenous, i.e., correlated with the error term, due to simultaneity or omitted variab...
متن کاملInstrumental variable estimation in a survival context.
Bias due to unobserved confounding can seldom be ruled out with certainty when estimating the causal effect of a nonrandomized treatment. The instrumental variable (IV) design offers, under certain assumptions, the opportunity to tame confounding bias, without directly observing all confounders. The IV approach is very well developed in the context of linear regression and also for certain gene...
متن کاملCharacterizing the Instrumental Variable Identifying Assumption as Sample Selection Conditions
Characterizing the Instrumental Variable Identifying Assumption as Sample Selection Conditions We build on Rosenzweig and Wolpin (2000) and Keane (2010) and show that in order to fulfill the Instrumental variable (IV) identifying moment condition, a policy must be designed so that compliers and non-compliers either have the same average error term, or have an error term ratio equal to their rel...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical Science
سال: 2017
ISSN: 0883-4237
DOI: 10.1214/17-sts623