Forecasting with approximate dynamic factor models: The role of non-pervasive shocks

Matteo Luciani

International Journal of Forecasting, 2014, vol. 30, issue 1, 20-29

Abstract: This paper studies the role of non-pervasive shocks when forecasting with factor models. To this end, we first introduce a new model that incorporates the effects of non-pervasive shocks, an Approximate Dynamic Factor Model with a sparse model for the idiosyncratic component. Then, we test the forecasting performance of this model both in simulations, and on a large panel of US quarterly data. We find that, when the goal is to forecast a disaggregated variable, which is usually affected by regional or sectorial shocks, it is useful to capture the dynamics generated by non-pervasive shocks; however, when the goal is to forecast an aggregate variable, which responds primarily to macroeconomic, i.e. pervasive, shocks, accounting for non-pervasive shocks is not useful.

Keywords: Dynamic factor models; Penalized regressions; Local factors; Bayesian shrinkage; Forecasting (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (36)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207013000769
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Forecasting with Approximate Dynamic Factor Models: the Role of Non-Pervasive Shocks (2011)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:30:y:2014:i:1:p:20-29

DOI: 10.1016/j.ijforecast.2013.05.001

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().