Heteroskedasticity is a common issue in regression analysis where the variance of errors is not constant. This can lead to biased estimates and affect hypothesis testing. Learn how to identify, test for, and correct heteroskedasticity using robust estimators and model adjustments to ensure the relia

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Explore the algebra of identification problems in VARs, including Cholesky factorization, timing restrictions, long-run impact restrictions, sign restrictions, and identification through heteroskedasticity. Discover why structural identification is crucial for policy design, economic modeling, and u

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