• Corpus ID: 244527084

On Recoding Ordered Treatments as Binary Indicators

@inproceedings{Rose2021OnRO,
  title={On Recoding Ordered Treatments as Binary Indicators},
  author={Evan K. Rose and Yotam Shem-Tov},
  year={2021}
}
Researchers using instrumental variables to investigate the effects of ordered treatments (e.g., years of education, months of healthcare coverage) often recode treatment into a binary indicator for any exposure (e.g., any college, any healthcare coverage). The resulting estimand is difficult to interpret unless the instruments only shift compliers from no treatment to some positive quantity and not from some treatment to more—i.e., there are extensive margin compliers only (EMCO). When EMCO… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 47 REFERENCES

Coarsening Bias: How Coarse Treatment Measurement Upwardly Biases Instrumental Variable Estimates

Political scientists increasingly use instrumental variable (IV) methods, and must often choose between operationalizing their endogenous treatment variable as discrete or continuous. For theoretical

Understanding Instrumental Variables in Models with Essential Heterogeneity

This paper examines the properties of instrumental variables (IV) applied to models with essential heterogeneity, that is, models where responses to interventions are heterogeneous and agents adopt

Estimating Outcome Distributions for Compliers in Instrumental Variables Models

In Imbens and Ingrist (1994), Angrist, Imbens and Rubin (1996) and Imbens and Rubin (1997), assumptions have been outlined under which instrumental variables estimands can be given a causal

USING INSTRUMENTAL VARIABLES FOR INFERENCE ABOUT POLICY RELEVANT TREATMENT PARAMETERS

We propose a method for using instrumental variables (IV) to draw inference about causal effects for individuals other than those affected by the instrument at hand. The question of policy relevance

Identification and Estimation of Local Average Treatment Effects

We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify

Testing Instrument Validity for LATE Identification Based on Inequality Moment Constraints

Abstract We derive testable implications of instrument validity in just identified treatment effect models with endogeneity and consider several tests. The identifying assumptions of the local

Judging Judge Fixed Effects

We propose a nonparametric test for the exclusion and monotonicity assumptions invoked in instrumental variable (IV) designs based on the random assignment of cases to judges. We show its asymptotic

Inference on Causal and Structural Parameters using Many Moment Inequalities

This article considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by $p$, is possibly much larger than the sample size $n$. There is a variety

A Test for Instrument Validity

The strongest testable implication for instrument validity is given by the condition for non- negativity of point-identi…able complier's outcome densities using a variance-weighted Kolmogorov-Smirnov test statistic.

Bounds on Treatment Effects from Studies with Imperfect Compliance

Abstract This article establishes nonparametric formulas that can be used to bound the average treatment effect in experimental studies in which treatment assignment is random but subject compliance