What are the consequences of using weak instrumental variables?

What are the consequences of using weak instrumental variables?

Weak instruments—instruments that are only marginally valid—can cause many problems, including: Biased estimates for independent variables, Hypothesis tests with large size distortions (Stock & Yogo, 2002)

How do you choose a good instrumental variable?

The three main conditions that define an instrumental variable are: (i) Z has a casual effect on X, (ii) Z affects the outcome variable Y only through X (Z does not have a direct influence on Y which is referred to as the exclusion restriction), and (iii) There is no confounding for the effect of Z on Y.

What is weak instrument problem?

With regard to the weak-instruments problem, the instruments are called weak instruments if the instruments are only weakly correlated with the endogenous variable. In such a case, the 2SLS estimator behaves very poorly.

What is weak instrument bias?

This bias, known as ‘weak instrument bias’, is in the direction of the confounded observational association between phenotype and outcome, and depends on the strength of the instrument [13]. Weak instruments are also associated with underestimated confidence intervals and poor coverage properties [14].

Why are IV estimates larger than OLS?

Since the IV estimate is unaffected by the measurement error, they tend to be larger than the OLS estimates. It’s possible that the IV estimate to be larger than the OLS estimate because IV is estimating the local average treatment effect (ATE). OLS is estimating the ATE over the entire population.

Are instrumental variables biased?

Instrumental variables (IV) are used to draw causal conclusions about the effect of exposure E on outcome Y in the presence of unmeasured confounders. For example, a weak association between the instrument and exposure can lead to biased results or large standard error6.

What is an instrumental variable in econometrics?

An instrumental variable (sometimes called an “instrument” variable) is a third variable, Z, used in regression analysis when you have endogenous variables—variables that are influenced by other variables in the model. In other words, you use it to account for unexpected behavior between variables.

What is an instrument in econometrics?

An instrument is a variable that does not itself belong in the explanatory equation but is correlated with the endogenous explanatory variables, conditionally on the value of other covariates. The instrument must be correlated with the endogenous explanatory variables, conditionally on the other covariates.

What is weak identification?

Weak identification occurs when a parameter is weakly regular, i.e., when it is locally homogeneous of degree zero. When this happens, consistent or equivariant estimation is shown to be impossible. While this parameter is not unique, concepts of sufficiency and minimality help pin down a desirable one.

How do you prevent instrument bias?

Increasing the F-statistic The bias from weak instruments depends on the strength of the instrument through the F-statistic. As the F-statistic depends on the sample size, then bias can be reduced by increasing sample size.

What is the difference between OLS and IV?

Whereas OLS estimates rely on all of the natural variation that exists across the entire sample, IV estimates are derived only from the variation attributable to the (exogenous) instrument—in this case, parents who were induced by the experiment to use care arrangements they would not have otherwise used.

What is the difference between OLS and 2SLS?

2SLS is used as an alternative approach when we face endogenity Problem in OLS. When explanatory variable correlate with error term then endogenity problem occurs. then we use 2SLS where we use instrumental variable. The result will be different as if there is endogenity in the model OLS will show biased outcome.

What are instrumental variables in statistics?

In statistics, econometrics, epidemiology and related disciplines, the method of instrumental variables ( IV) is used to estimate causal relationships when controlled experiments are not feasible or when a treatment is not successfully delivered to every unit in a randomized experiment.

What is the importance of OLS assumptions in econometrics?

This is because a lack of knowledge of OLS assumptions would result in its misuse and give incorrect results for the econometrics test completed. The importance of OLS assumptions cannot be overemphasized.

When is an instrument said to satisfy the exclusion restriction?

The instrument cannot be correlated with the error term in the explanatory equation, conditionally on the other covariates. In other words, the instrument cannot suffer from the same problem as the original predicting variable. If this condition is met, then the instrument is said to satisfy the exclusion restriction.