Robust Inference in Models Identified via Heteroskedasticity

Daniel Lewis

The Review of Economics and Statistics, 2022, vol. 104, issue 3, 510-524

Abstract: Identification via heteroskedasticity exploits variance changes between regimes to identify parameters in simultaneous equations. Weak identification occurs when shock variances change very little or multiple variances change close to proportionally, making standard inference unreliable. I propose an

Date: 2022
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Working Paper: Robust inference in models identified via heteroskedasticity (2018)
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