: identification strategies based on heteroskedasticity and strategkes based on non-Gaussianity more generally. I outline the seminal …Identification based on higher moments has drawn increasing theoretical attention and been widely adopted in empirical … identification results and discuss recent extensions, parametric and non-parametric implementations, and prominent empirical …

single perceived shock that closely aligns with observed inflation surprises. The time-varying impulse responses indicate a … significant decline in the perceived persistence of this shock, suggesting that inflation expectations have become more "anchored …

covariates and heteroskedasticity. Our results are obtained using high-dimensional approximations, where the number of covariates … are allowed to grow as fast as the sample size. We find that all of the usual versions of Eicker-White heteroskedasticity … heteroskedasticity consistent standard error formula that is fully automatic and robust to both (conditional) heteroskedasticity of …

inference methods that allow for many covariates and heteroskedasticity. Our results are obtained using high … versions of Eicker-White heteroskedasticity consistent standard error estimators for linear models are inconsistent under this … asymptotics. We then propose a new heteroskedasticity consistent standard error formula that is fully automatic and robust to both …

and price elasticities, and thus supply and demand curves, have changed in those 11 markets in recent years. The shock …, identification assumptions in empirical work, and modeling exercises. …

structural vector autoregression (SVAR): imposing 'narrative restrictions' (NR) on the shock signs in an otherwise setidentified … SVAR; and casting the information about the shock signs as a discretevalued 'narrative proxy' (NP) to point-identify the … impulse responses. The NP is likely to be 'weak' given that the sign of the shock is typically known in a small number of …