ESTIMATION AND INFERENCE IN SHORT PANEL VECTOR AUTOREGRESSIONS WITH UNIT ROOTS AND COINTEGRATION

Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and shown to be consistent and asymptotically normally distributed irrespective of the unit root and cointegr...

Vector Autoregressions and Cointegration*

Unit Roots and Cointegration in Panels∗

This paper provides a review of the literature on unit roots and cointegration in panels where the time dimension (T ), and the cross section dimension (N) are relatively large. It distinguishes between the first generation tests developed on the assumption of the cross section independence, and the second generation tests that allow, in a variety of forms and degrees, the dependence that might...

Testing for unit roots in autoregressions with multiple level shifts ∗

The asymptotic distributions of Augmented-Dickey-Fuller (ADF) unit root tests for autoregressive processes with a unit or near-unit root are discussed in the presence of multiple stochastic level shifts of large size occurring independently in time. The distributions depend on a Brownian motion and a Poisson-type jump process. Due to the latter, tests based on standard critical values experienc...

Prior selection for panel vector autoregressions

There is a vast literature that speci…es Bayesian shrinkage priors for vector autoregressions (VARs) of possibly large dimensions. In this paper I argue that many of these priors are not appropriate for multi-country settings, which motivates me to develop priors for panel VARs (PVARs). The parametric and semi-parametric priors I suggest not only perform valuable shrinkage in large dimensions, ...