Assessing Aggregate Comovements in France, Germany and Italy. Using a Non Stationary Factor Model of the Euro Area
AbstractThe objective of the paper is to investigate to what extent business cycles co-move in Germany, France and Italy. We use a large-scale database of non-stationary series for the euro area in order to assess the effect of common versus idiosyncratic shocks, as well as transitory versus permanent shocks, across countries over the 1980:Q1 to 2003:Q4 period. We apply the method-ology proposed by Bai (2004) and Bai and Ng (2004) to construct a coincident indicator of the euro area business cycle to which national developments appear to be increasingly correlated at business cycle frequencies (8 to 32 quarters), while more significant différences appear at lower frequencies which measures potential growth. The indicator is also shown to be related to extra euro area economic developments.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Banque de France in its series Working papers with number 145.
Length: 30 pages
Date of creation: 2006
Date of revision:
Factor models ; Non-stationary panel data models ; Euro area business cycles.;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
- Jushan Bai & Serena Ng, 2002.
"Determining the Number of Factors in Approximate Factor Models,"
Econometric Society, vol. 70(1), pages 191-221, January.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
- Tom Doan, . "BAING: RATS procedure to estimate factors in a factor model using Bai-Ng formulas," Statistical Software Components RTS00012, Boston College Department of Economics.
- Victor Zarnowitz, 1992. "Business Cycles: Theory, History, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number zarn92-1, December.
- Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2002. "Tracking Greenspan: Systematic and Unsystematic Monetary Policy Revisited," CEPR Discussion Papers 3550, C.E.P.R. Discussion Papers.
- Eickmeier, Sandra, 2005. "Common stationary and non-stationary factors in the euro area analyzed in a large-scale factor model," Discussion Paper Series 1: Economic Studies 2005,02, Deutsche Bundesbank, Research Centre.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marie-Christine Petit-Djemad).
If references are entirely missing, you can add them using this form.