This paper studies estimation of panel co-integration models with cross-sectional dependence Generated by unobserved global stochastic trends. The standard least squares estimator is, in General, inconsistent owing to the spuriousness induced by the unobservable i(1) trends. We propose two...

Most of the existing literature on panel data cointegration assumes cross-sectional independence, an assumption that is difficult to satisfy. This paper studies panel cointegration under cross-sectional dependence, which is characterized by a factor structure. We derive the limiting distribution...

This paper develops a new methodology that makes use of the factor structure of large dimensional panels to understand the nature of non-stationarity in the data. We refer to it as PANIC - a 'Panel Analysis of Non-stationarity in Idiosyncratic and Common components'. PANIC consists of univariate...