Estimating non-stationary common factors : implications for risk sharing

In this paper, we analyze and compare the finite sample properties of alternative factor extraction procedures in the context of non-stationary Dynamic Factor Models (DFMs). On top of considering procedures already available in the literature, we extend the hybrid method based on the combination of principal components and Kalman filter and smoothing algorithms to non-stationary models. We show that if the idiosyncratic noises are stationary, procedures based on extracting the factors using the non-stationary original series work better than those based on differenced variables. We apply the methodology to the analysis of cross-border risk sharing by fitting non-stationary DFM to aggregate Gross Domestic Product and consumption of a set of 21 industrialized countries from the Organization for Economic Co-operation and Development (OECD). The goal is to check if international risk sharing is a short- or long-run issue.Financial support from the Spanish Government Projects ECO2015-70331-C2-1-R and ECO2015-70331-C2-2-R (MINECO/FEDER) is gratefully acknowledged. This paper was started while Pilar Poncela was still at Universidad Autónoma de Madrid. We are very grateful for the detailed comments of an anonymous referee which have been very useful to improve the presentation of this paper. The views expressed in this paper are those of the authors and should not be attributed neither to the European Commission nor to INEGI