# Questions tagged [instrumental-variables]

Instrumental variables (IV) are used for causal inference with observational data in the presence of endogeneity when standard regression methods yield biased and inconsistent estimates.

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### Why does the IV estimator fail to attenuate the EIV bias in a two-stage FM regression?

In Jegadeesh et al. (2019), they proposed to use the instrumental variables (IVs) estimation approach to attenuate the errors-in-variables (EIV) bias, which is inherent to a two-stage Fama-MacBeth (FM,...
1 vote
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### When does the Instrumental Variable (IV) method fail?

Consider the following ARMAX model: $$y[k]=\alpha y[k-1]+\beta u[k-1]+e[k]-0.7e[k-1]$$ where $e[k]$ is a white noise. One can see that $e[k]-0.7e[k-1]$ is a filtered noise and thus using ordinary ...
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### Show that the IV estimator is equal to ( ̄y1 − ̄y0)/( ̄x1 − ̄x0) [closed]

I am stuck at solving this question. Thank you and please feel free to ask any questions!
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### Categorical IV with probit second stage

In a panel setting, I have a binary endogenous variable $X_{ijt}$ where $i$ indexes the individual, $j$ indexes the region, and $t$ indexes the year. I have a set of mutually exclusive binary ...
1 vote
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### Why not simply use your instrumental variable as your independent variable?

I'm a little confused as to why we need to go through an entire two-stage regression process to capture the effect of our instrumental variable on our independent variable, and then only use this ...
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### Why is ignoring prediction error not a concern in instrumental variables?

In his book, Statistical Rethinking (2nd edition, p. 137), Richard McElreath states that including parameters with unobserved values, such as residuals, and treating them as if they were perfectly ...
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### How to treat dummy variables and their interactions terms with an endogenous variable in a IV context?

I have the following regression function: # fictitious regression function Y = α1 + α2*X + α3*W + α4*D + α5*(D*X) Y is the dependent variable, X is the main ...
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### In large sample, does IV fit better than OLS?

This is taken from Hansen's econometrics textbook. Take the linear model: $$Y = Z\beta + e$$ Let the residuals in an IV regression be $\tilde e$ and in an OLS regression $\hat e$. If X is indeed ...
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### How to think about exclusion restriction in an over-identified IV setup?

If I have more instruments than endogenous regressors, let’s say two instruments for one endogenous regressor, my IV set up is ‘over-identified’. What does the exclusion restriction imply with more ...
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### Using IV when regressor is not endogenous

Suppose I have a single regressor model and the regressor itself is uncorrelated with the error term. If I were to use IV estimation to estimate the coefficient, would the estimate be incorrect, and ...
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### Fixed effect instrumental variable (IV) regression with available diagnostic tests

May I please know an R package and code to run fixed effect instrumental variable (IV) regression with available diagnostic tests (e.g., weak instrument test, exogeneity test (using Wu-Hausman), ...
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### Interpretation of bias with an endogenous variable

I am running an analysis of impacts of immigration on natives' votes to anti-immigration parties, across municipalities. The concern in this type of analysis is that location decisions of immigrants ...
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### Instrument validity: does a positive and significant coefficient on Z in a regression of Y on X and Z pose a problem?

I have an initial regression of Y on X and Z. Both of my coefficients on X and Z are non-zero and strongly statistically significant. X and Z are correlated but I am told collinearity shouldn't be an ...
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### Difference-in-differences on compliers

I'm trying to estimate a generalized DID (two periods three groups)'s local average treatment effect on Stata. The DID code used was: ...
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### Which type of correlation is used when IV has four categories?

I am working on parenting styles (IV) that is a categorical variable with 4 categories. My DVs are personality traits and quality of life. I have created dummy variables (IV) for regression analysis. ...