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the claim
Instrumental variables estimators resolve simultaneity bias by isolating exogenous variation correlated with the regressor
the verdict
SUPPORTED
the evidence backs this
refutedsupported
the weight of evidence
3 sources for · 0 against

Instrumental variables estimators are a standard econometric technique used to address simultaneity bias and endogeneity by leveraging exogenous variation correlated with the regressor of interest.

Evidence for · 3
2025 · cited by 3
This study uses an instrumental variable approach (MAIVE) to address endogeneity and improve the reliability of estimates.
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The analysis

The claim states a fundamental econometric definition and function of instrumental variables (IV) estimators: solving simultaneity bias and endogeneity by exploiting exogenous variation. Papers [1], [6], and [7] all explicitly employ instrumental variable techniques for this exact purpose (addressing endogeneity and reverse causality in observational data). The claim is specific, well-established in econometrics, and directly supported by the methodology and use cases in the retrieved literature.

More for · 2
2025 · cited by 0
This paper utilizes generalized spatial two-stage least squares (GS2SLS) models with instrumental variables to successfully address spatial endogeneity.
2026 · cited by 0
This research applies a two-stage residual inclusion instrumental variables approach using county-level average wages to address potential endogeneity and reverse causality.
The paper trail · every fact has a biography
first checked04 Aug 2026
judged → SUPPORTED · 7904 Aug 2026
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