# One Instrument to Rule Them All: The Bias and Coverage of Just-ID IV

@inproceedings{Angrist2021OneIT, title={One Instrument to Rule Them All: The Bias and Coverage of Just-ID IV}, author={Joshua David Angrist and M. Koles{\'a}r}, year={2021} }

Two-stage least squares estimates in heavily over-identified instrumental variables (IV) models can be misleadingly close to the corresponding ordinary least squares (OLS) estimates when many instruments are weak. Just-identified (just-ID) IV estimates using a single instrument are also biased, but the importance of weak-instrument bias in just-ID IV applications remains contentious. We argue that in microeconometric applications, just-ID IV estimators can typically be treated as all but…

## One Citation

## References

SHOWING 1-10 OF 35 REFERENCES

Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak

- Mathematics
- 1995

Abstract We draw attention to two problems associated with the use of instrumental variables (IV), the importance of which for empirical work has not been fully appreciated. First, the use of…

A Practical Guide to Weak Instruments

- 2021

We provide a simple survey of the literature on weak instruments, aimed at giving practical advice to applied researchers. It is well-known that 2SLS has poor properties if instruments are exogenous…

Instrumental Variables Regression with Weak Instruments

- 1994

This paper develops asymptotic distribution theory for instrumental variable regression when the partial correlation between the instruments and a single included endogenous variable is weak, here…

Weak Instruments in Instrumental Variables Regression: Theory and Practice

- MathematicsAnnual Review of Economics
- 2019

When instruments are weakly correlated with endogenous regressors, conventional methods for instrumental variables (IV) estimation and inference become unreliable. A large literature in econometrics…

Estimating Outcome Distributions for Compliers in Instrumental Variables Models

- Economics
- 1997

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…

Unbiased Instrumental Variables Estimation under Known First-Stage Sign

- Mathematics
- 2015

We derive mean-unbiased estimators for the structural parameter in instrumental variables models with a single endogenous regressor where the sign of one or more first stage coecients is known. In…

Unbiased Instrumental Variables Estimation Under Known First-Stage Sign

- 2015

We derive mean-unbiased estimators for the structural parameter in instrumental variables models with a single endogenous regressor where the sign of one or more first stage coefficients is known. In…

Valid t-ratio Inference for IV

- Economics, Mathematics
- 2020

In the single IV model, current practice relies on the first-stage F exceeding some threshold (e.g., 10) as a criterion for trusting t-ratio inferences, even though this yields an anti-conservative…

Judging Instrument Relevance in Instrumental Variables Estimation

- Psychology, Economics
- 1994

Recent research has emphasized the poor finite-sample performance of the instrumental variables estimator when the instruments are weakly correlated with the regressors. The authors show how the…

Two-Stage Least Squares Estimation of Average Causal Effects in Models with Variable Treatment Intensity

- Mathematics
- 1995

Abstract Two-stage least squares (TSLS) is widely used in econometrics to estimate parameters in systems of linear simultaneous equations and to solve problems of omitted-variables bias in…