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"instrumental variable" is a correct phrase to use in written English, and it is often used in academic research papers.
An instrumental variable is a type of variable used in statistical analysis to estimate a causal relationship between two variables, despite the presence of confounding variables. For example, a researcher might use public school budget as an instrumental variable when trying to estimate the effect of class size on student achievement, even though poverty and other factors may ultimately be confounding the results.
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Although the above discussion uses a binary instrumental variable, we observe a multi-valued instrument.
When comparing OLS and instrumental variable biases, researchers should account for the instrument strength.
Results following matching and instrumental variable strategies are very similar.
To understand this relationship better, we implement a standard econometric technique called an instrumental variable analysis.
To establish causality, we use a difference-in-differences approach and an instrumental variable approach.
We correct for this problem by employing an instrumental variable estimation method.
To deal with such endogeneity concerns, we employ instrumental variable techniques.
These findings were confirmed using propensity score matched and instrumental variable analysis.
Potential bias of instrumental variable analyses for observational comparative effectiveness research.
"Mostly Harmless Econometrics" also emphasizes the importance of validating an instrumental variable.
For ex post evaluation, the following estimation methods are discussed: traditional regression methods, matching, control function methods, instrumental variable and local instrumental variable (LIV) methods, and regression-discontinuity.
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