论文信息 - Coincident and leading indicators for the Euro area

Coincident and leading indicators for the Euro area

This paper proposes a new way to compute a coincident and a leading indicator of economic activity. Our methodology, based on Forni, Hallin, Lippi and Reichlin (2000), reconciles dynamic principal components analysis with dynamic factor analysis. It allows us to extract indicators from a large panel of economic variables (many variables for many countries). The procedure is used to estimate coincident and leading indicators for the EURO area. Unlike other methods used in the literature, the procedure takes into consideration the cross-country as well as the within-country correlation structure and exploit all information on dynamic cross-correlation.(This abstract was borrowed from another version of this item.)

[1] Lucrezia Reichlin,et al. Federal policies and local economies: Europe and the US , 2001 .

[2] Marco Lippi,et al. The Generalized Factor Model: Identification and Estimation , 2000 .

[3] D. Brillinger. Time series - data analysis and theory , 1981, Classics in applied mathematics.

[4] Richard A. Davis,et al. Time Series: Theory and Methods , 2013 .

[5] Clive W. J. Granger,et al. Spectral Analysis for Economic Time Series , 1964 .

[6] J. Stock,et al. Diffusion Indexes , 1998 .

[7] Victor Zarnowitz. Business Cycles: Theory, History, Indicators, and Forecasting , 1992 .

[8] V. Zarnowitz,et al. Business Cycles: Theory, History, Indicators and Forecasting , 1993 .

[9] L. Hurwicz,et al. Measuring Business Cycles. , 1946 .

[10] M. Rothschild,et al. Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets , 1983 .

[11] Thomas J. Sargent,et al. Business cycle modeling without pretending to have too much a priori economic theory , 1976 .

[12] J. Stock,et al. Macroeconomic forecasting in the Euro area: Country specific versus area-wide information , 2003 .

[13] M. Rothschild,et al. Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets , 1982 .