Full- and limited-information identification-robust methods are proposed for structural systems, notably DSGE models, which are valid whether identification is weak or strong, theory-intrinsic or data-specific. The proposed methods are applied to a standard New Keynesian system for the U.S....

We propose exact simulation-based procedures for: (i) testing mean-variance efficiency when the zero-beta rate is unknown; (ii) building confidence intervals for the zero-beta rate. On observing that this parameter may be weakly identified, we propose likelihood-ratio-type tests as well as...

We provide evidence on two alternative mechanisms of interaction between returns and volatilities: the leverage ef fect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and implied volatility and find that implied volatilities are...

Usual inference methods for stable distributions are typically based on limit distributions. But asymptotic approximations can easily be unreliable in such cases, for standard regularity conditions may not apply or may hold only weakly. This paper proposes finite-sample tests and confidence sets...

Two linear estimators for stationary invertible vector autoregressive moving average (VARMA) models in echelon form — to achieve parameter unicity (identification) — with known Kronecker indices are studied. It is shown that both estimators are consistent and asymptotically normal with...

A homogeneous random process on the circle {X(P): P[set membership, variant]S} is a process whose mean is zero and whose covariance function depends only on the angular distance [theta] between the points, i.e. E{X(P)}[reverse not equivalent]0 and E{X(P)X(Q)}=R([theta]). We assume that the...