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Factor Models in Large Cross-Sections of Time Series

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  • Reichlin, Lucrezia

Abstract

This Paper reviews recent econometric work on factor models in large cross-sections of time series. In this literature, traditional factor analysis is adapted to develop parsimonious estimation methods for high dimension time series models. The review covers problems of consistency and rates – as the dimension of the cross-section and the time dimension become large – identification and forecasting. We also review empirical applications on measuring and interpreting business cycles.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 3285.

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Date of creation: Mar 2002
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Handle: RePEc:cpr:ceprdp:3285

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Keywords: business cycles; factor analysis; panel data;

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  33. Forni, Mario & Reichlin, Lucrezia, 1998. "Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 453-73, July.
  34. Filippo Altissimo & Antonio Bassanetti & Riccardo Cristadoro & Mario Forni & Marco Lippi & Lucrezia Reichlin & Giovanni Veronese, 2001. "A real time coincident indicator of the euro area business cycle," Temi di discussione (Economic working papers) 436, Bank of Italy, Economic Research and International Relations Area.
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Citations

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Cited by:
  1. Marlene Amstad & Andreas Fischer, 2005. "Shock Identification of Macroeconomic Forecasts based on Daily Panels," Working Papers 05.02, Swiss National Bank, Study Center Gerzensee.
  2. Thomas Helbling & Tamim Bayoumi, 2003. "Are they All in the Same Boat? the 2000-2001 Growth Slowdown and the G-7 Business Cycle Linkages," IMF Working Papers 03/46, International Monetary Fund.
  3. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "A Dynamic Factor Analysis of Business Cycle on Firm-Level Data," LEM Papers Series 2006/27, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  4. Cimadomo, Jacopo & Bénassy-Quéré, Agnès, 2012. "Changing patterns of fiscal policy multipliers in Germany, the UK and the US," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 845-873.
  5. Daniel Grenouilleau, 2006. "The Stacked Leading Indicators Dynamic Factor Model: A Sensitivity Analysis of Forecast Accuracy using Bootstrapping," European Economy - Economic Papers 249, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission.
  6. Bork, Lasse, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," Finance Research Group Working Papers F-2009-03, University of Aarhus, Aarhus School of Business, Department of Business Studies.
  7. Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.

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