Green shoots and double dips in the euro area: A real time measure

International Journal of Forecasting

Volumn 30, Issue 3, 2014, Pages 520-535

  Camacho, Maximo ^a   Perez Quiros, Gabriel ^b,c   Poncela, Pilar ^d  

^a UNIVERSITY OF MURCIA   (Spain)

^b BANCO DE ESPAÑA   (Spain)

^c CEPR   (United Kingdom)

^d UNIVERSIDAD AUTÓNOMA DE MADRID   (Spain)

Author keywords

Business cycles; Output growth; Time series

Indexed keywords

EID: 84902258615     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2013.01.006     Document Type: Article

References (23)

1. Aruoba B., Diebold F., Scotti C. Real-time measurement of business conditions. Journal of Business and Economic Statistics 2009, 7:417-427.
2. Aruoba, B., Diebold, F., & Scotti, C. (2009b). Updates on ADS index calculations. Mimeo. Available at. http://www.philadelphiafed.org.
3. Anas J., Billio M., Ferrara L., Lo Duca M. A turning point chronology for the Euro-zone classical and growth cycle. Growth and cycle in the Euro-zone 2006, Palgrave-MacMillan, New-York. G.L. Mazzi, G. Savio (Eds.).
4. Camacho M., Perez Quiros G. Jump-and-rest effect of U.S. business cycles. Studies in Nonlinear Dynamics and Econometrics 2007, 11(4). article 3.
5. Camacho M., Perez-Quiros G. Introducing the Euro-STING: short term indicator of Euro area growth. Journal of Applied Econometrics 2010, 25:663-694.
6. Camacho, M., Perez-Quiros, G., & Poncela, P. (2012a). Extracting nonlinear signals from several economic indicators. Bank of Spain Working Paper 1202.
7. Camacho, M., Perez-Quiros, G., & Poncela, P. (2012b). Markov-switching dynamic factor models in real time. Bank of Spain Working Paper 1205.
8. Chauvet M. An economic characterization of business cycle dynamics with factor structure and regime switches. International Economic Review 1998, 39:969-996.
9. Chauvet M., Hamilton J. Dating business cycle turning points in real time. Nonlinear time series analysis of business cycles 2006, 1-54. Elsevier Science, Amsterdam. C. Milas, P. Rothman, D. Van Dijk (Eds.).
10. Chauvet M., Piger J. A comparison of the real-time performance of business cycle dating methods. Journal of Business and Economic Statistics 2008, 26:42-49.
11. Coenen C., Levin A., Wieland V. Data uncertainty and the role of money as an information variable for monetary policy. European Economic Review 2005, 49:975-1006.
12. Diebold F., Mariano R. Comparing predictive accuracy. Journal of Business and Economic Statistics 1995, 13:253-263.
13. European Commission, (2006). The joint harmonized EU programme of business and consumer surveys. Special Report No. 5/2006.
14. Evans M. Where are we now? Real time estimates of the macroeconomy. International Journal of Central Banking 2005, 1:127-175.
15. Hamilton J. Calling recessions in real time. International Journal of Forecasting 2011, 27:1006-1026.
16. Kim C. Dynamic linear models with Markov-switching. Journal of Econometrics 1994, 60:1-22.
17. Kim C., Nelson C. Business cycle turning points, a new coincident index, and tests of duration dependence based on a dynamic factor model with regime switching. Review of Economics and Statistics 1998, 80:188-201.
18. Kim M., Yoo J. New index of coincident indicators: A multivariate Markov switching factor model approach. Journal of Monetary Economics 1995, 36:607-630.
19. Mariano R., Murasawa Y. A new coincident index of business cycles based on monthly and quarterly series. Journal of Applied Econometrics 2003, 18:427-443.
20. Perez-Quiros G., Timmermann A. Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities. Journal of Econometrics 2001, 103:259-306.
21. Stark T., Croushore D. Forecasting with a real-time data set for macroeconomists. Journal of Macroeconomics 2002, 24:507-531.
22. Stock J., Watson M. A probability model of the coincident economic indicators. Leading economic indicators: new approaches and forecasting records 1991, Cambridge University Press. K. Lahiri, G. Moore (Eds.).
23. Stock J., Watson M. Dynamic factor models. Oxford handbook of forecasting 2011, Oxford University Press. M. Clements, D. Hendry (Eds.).