In this paper we propose a new test statistic that considers multiple structural breaks to analyse the non-stationarity of a panel data set. The methodology is based on the common factor analysis in an attempt to allow for some sort of dependence across the individuals. Thus allowing for...

The paper proposes statistics to test the null hypothesis of no cointegration in panel data when common factors drive the cross sectional dependence. We consider both the case in which regressors are independent of the common factors and the case in which regressors are correlated with the...

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...

We consider the situation when there is a large number of series, $N$, each with $T$ observations, and each series has some predictive ability for the variable of interest, $y$. A methodology of growing interest is to first estimate common factors from the panel of data by the method of...