In the standard data analysis framework, is first collected (once for all), and then carried out. Moreover, data-generating process typically assumed to be exogenous. This approach natural when analyst has no impact on how generated. The advancement of digital technology, however, facilitated firms learn from make decisions at same time. As these generate new data, analyst---a business manager ...

Instrumental variable regression (RegIV) provides a means for detecting and correcting parameter bias in causal models. Widely used economics, recently several papers have highlighted its potential utility ecological applications. Little attention has thus far been paid to the fact that IV methods can also be implemented within structural equation models (SEMIV). In this paper I present motivat...

The instrumental variable method consistently estimates the effect of a treatment when there is unmeasured confounding and a valid instrumental variable. A valid instrumental variable is a variable that is independent of unmeasured confounders and affects the treatment but does not have a direct effect on the outcome beyond its effect on the treatment. Two commonly used estimators for using an ...

background and purpose: women with low (high) pre-pregnancy body mass index (bmi) recently delivered infants with approximately normal or close to normal birth weights under the high quality of prenatal care. this study estimated the effect of pre-pregnancy bmi when concerns about the effects of different quality levels of prenatal care and the health status of mothers and their infants existed...

This paper proposes shrinkage methods for instrumental variable estimation to solve the “many instruments” problem. Even though using a large number of instruments reduces the asymptotic variances of the estimators, it has been observed both in theoretical works and in practice that in finite samples the estimators may behave very poorly if the number of instruments is large. This problem can b...

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...

In this article we develop an Instrumental Variable estimation procedure that corrects for possible endogeneity of a variable in a duration model. We assume a Generalized Accelerated Failure Time (GAFT) model. This model is based on transforming the durations and assuming a distribution for these transformed durations. The GAFT model encompasses two competing approaches to duration data; the (M...

We derive a new adaptive filtering algorithm called the Instrumental Variable Affine Projection (IVAP) algorithm and give its fast version (FIVAP algorithm). The IVAP algorithm departs from the AP algorithm and uses an IV. The IV process is generated in a way such that the new algorithm combines between the AP and the Fast Newton Transversal Filter (FNTF) algorithms. Simulations show that the I...