Non-Stationary Dynamic Factor Models for Large Datasets

59 Pages Posted: 4 Mar 2016

See all articles by Matteo Barigozzi

Matteo Barigozzi

Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES); London School of Economics and Political Science; University of Bologna

Marco Lippi

Dipartimento di Scienze Economiche (DiSSE); Einaudi Institute for Economics and Finance (EIEF)

Matteo Luciani

Board of Governors of the Federal Reserve System

Multiple version iconThere are 2 versions of this paper

Date Written: March 3, 2016

Abstract

We develop the econometric theory for Non-Stationary Dynamic Factor models for large panels of time series, with a particular focus on building estimators of impulse response functions to unexpected macroeconomic shocks. We derive conditions for consistent estimation of the model as both the cross-sectional size, n, and the time dimension, T, go to infinity, and whether or not cointegration is imposed. We also propose a new estimator for the non-stationary common factors, as well as an information criterion to determine the number of common trends. Finally, the numerical properties of our estimator are explored by means of a MonteCarlo exercise and of a real-data application, in which we study the effects of monetary policy and supply shocks on the US economy.

Keywords: Dynamic Factor models, unit root processes, common trends, impulse response functions

JEL Classification: C0, C01, E0

Suggested Citation

Barigozzi, Matteo and Barigozzi, Matteo and Barigozzi, Matteo and Lippi, Marco and Luciani, Matteo, Non-Stationary Dynamic Factor Models for Large Datasets (March 3, 2016). Available at SSRN: https://ssrn.com/abstract=2741739 or http://dx.doi.org/10.2139/ssrn.2741739

Matteo Barigozzi (Contact Author)

Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES) ( email )

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University of Bologna ( email )

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Marco Lippi

Dipartimento di Scienze Economiche (DiSSE) ( email )

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Einaudi Institute for Economics and Finance (EIEF) ( email )

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Matteo Luciani

Board of Governors of the Federal Reserve System ( email )

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Washington, DC 20551
United States

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