For linear regression models with cross-section or panel data, it is natural to assume that the disturbances are clustered in two dimensions. However, the finite-sample properties of two-way cluster-robust tests and confidence intervals are often poor. We discuss several ways to improve...

We provide new and computationally attractive methods, based on jackknifing by cluster, to obtain cluster-robust variance matrix estimators (CRVEs) for linear regres- sion models estimated by least squares. These estimators have previously been com- putationally infeasible except for small...

Cluster-robust inference is widely used in modern empirical work in economics and many other disciplines. The key unit of observation is the cluster. We propose measures of "high-leverage" clusters and "influential" clusters for linear regression models. The measures of leverage and partial...

A regime dependent VAR model is suggested that allows long memory (fractional integration) in each of the observed regime states as well as the possibility of fractional cointegration. The model is motivated by the dynamics of electricity prices where the transmission of power is subject to...

Cointegration imposes restrictions on the frequency domain behavior of a time series at the zero-frequency. We derive these restrictions for a multivariate fractionally cointegrated system. In particular, we consider a p-vector time series integrated of order d with r cointegrating relations,...

We propose a Lagrange Multiplier test of the null hypothesis of cointegration in fractionally cointegrated models. The test statistic utilizes fully modified residuals to cancel the endogeneity and serial correlation biases, and we show that standard asymptotic properties apply under the null...

Fractional cointegration imposes restrictions on the zero-frequency behavior of a time series. In a multivariate time series, integrated of order d epsilon (1/2, 3/2) and cointegrating to order d - b epsilon (-1/2, 1/2), we derive these restrictions in terms of the (reduced) rank of the spectral...