Replication Data for: Profiling Compliers and Non-compliers for Instrumental-Variable Analysis
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Instrumental-variable (IV) estimation is an essential method for applied researchers across the social and behavioral sciences who analyze randomized control trials marred by non-compliance or leverage partially exogenous treatment variation in observational studies. The potential outcomes framework is a popular model to motivate the assumptions underlying the identification of the local average treatment effect (LATE), and to stratify the sample into compliers, always-takers, and never-takers. However, applied research has thus far paid little attention to the characteristics of compliers and non-compliers. Yet profiling compliers and non-compliers is necessary to understand what subpopulation the researcher is making inferences about, and an important first step in evaluating the external validity (or lack thereof) of the LATE estimate' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["2SLS","complier","encouragement design","instrumental variable","two-stage least squares"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Instrumental-variable (IV) estimation is an essential method for applied researchers across the social and behavioral sciences who analyze randomized control trials marred by non-compliance or leverage partially exogenous treatment variation in observational studies. The potential outcomes framework is a popular model to motivate the assumptions underlying the identification of the local average treatment effect (LATE), and to stratify the sample into compliers, always-takers, and never-takers. However, applied research has thus far paid little attention to the characteristics of compliers and non-compliers. Yet profiling compliers and non-compliers is necessary to understand what subpopulation the researcher is making inferences about, and an important first step in evaluating the external validity (or lack thereof) of the LATE estimate' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Instrumental-variable (IV) estimation is an essential method for applied researchers across the social and behavioral sciences who analyze randomized control trials marred by non-compliance or leverage partially exogenous treatment variation in observational studies. The potential outcomes framework is a popular model to motivate the assumptions underlying the identification of the local average treatment effect (LATE), and to stratify the sample into compliers, always-takers, and never-takers. However, applied research has thus far paid little attention to the characteristics of compliers and non-compliers. Yet profiling compliers and non-compliers is necessary to understand what subpopulation the researcher is making inferences about, and an important first step in evaluating the external validity (or lack thereof) of the LATE estimate
2SLS; complier; encouragement design; instrumental variable; two-stage least squares