An Overview of European Economic Indicators: Great Variety of Data on the Euro Area, Need for More Extensive Coverage of the New EU Member States
This contribution provides an overview of the most common short-term indicators of economic development in the euro area. These indicators are useful when official data are released with long time lags or if they are subject to major revisions. Indicators based on surveys among businesses, households, financial market analysts or forecasters have the advantage of providing detailed and timely information on individual sectors on a monthly basis and largely without later revision. As an additional instrument, composite indicators, which are calculated by combining a variety of measures into a single indicator with the help of regression and factor analysis, offer an attractive tool for drawing conclusions from different, often divergent signals. Even the most reliable economic indicators, however, can only be interpreted as constituent elements of comprehensive economic analysis. With regard to the new EU Member States, coverage is found to be limited as yet. This study also shows that the forecasting quality of the European Commission 's business and consumer surveys for the new Member States is not as high as for the other EU Member States. As the reliability of economic indicators increases as forecasting institutions and respondents gain more experience, coverage of established indicators should be extended early on to this group of countries, in particular as some of the new Member States may soon join the euro area. JEL classification: 0110, 520
Volume (Year): (2005)
Issue (Month): 3 ()
|Contact details of provider:|| Postal: P.O. Box 61, A-1011 Vienna, Austria|
Phone: +43/1/404 20 7405
Fax: +43/1/404 20 7499
Web page: http://www.oenb.at
More information through EDIRC
|Order Information:|| Postal: Oesterreichische Nationalbank, Documentation Management and Communications Services, Otto-Wagner Platz 3, A-1090 Vienna, Austria|
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.:
- Kunst, Robert M., 2003. "Testing for Relative Predictive Accuracy: A Critical Viewpoint," Economics Series 130, Institute for Advanced Studies.
- Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000.
"The Generalized Dynamic-Factor Model: Identification And Estimation,"
The Review of Economics and Statistics,
MIT Press, vol. 82(4), pages 540-554, November.
- Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
- Vanhaelen, J.J. & Dresse, L. & de Mulder, J., 2000. "The Belgian Industrial Confidence Indicator: Leading Indicator of Economic Activity in the Euro Area?," Papers 12, Warwick - Development Economics Research Centre.
- Elliott, Graham & Timmermann, Allan G, 2007.
CEPR Discussion Papers
6158, C.E.P.R. Discussion Papers.
- Rebecca A Emerson & David Hendry, 1994. "An evaluation of forecasting using leading indicators," Economics Papers 5., Economics Group, Nuffield College, University of Oxford.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 20(1), pages 134-44, January.
- Ronald Bewley & Denzil G. Fiebig, 2002. "On the herding instinct of interest rate forecasters," Empirical Economics, Springer, vol. 27(3), pages 403-425.
- Forni, Mario & Lippi, Marco, 2001.
"The Generalized Dynamic Factor Model: Representation Theory,"
Cambridge University Press, vol. 17(06), pages 1113-1141, December.
- Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers 2509, C.E.P.R. Discussion Papers.
- Roy Batchelor, 2001. "How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 225-235.
- Schröder, Michael & Hüfner, Felix P., 2002. "Forecasting economic activity in Germany: how useful are sentiment indicators?," ZEW Discussion Papers 02-56, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
- Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
- Mario Forni & Lucrezia Reichlin, 1998.
"Let's get real: a factor analytical approach to disaggregated business cycle dynamics,"
ULB Institutional Repository
2013/10147, ULB -- Universite Libre de Bruxelles.
- Mario Forni & Lucrezia Reichlin, 1998. "Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 453-473.
- Peter Grasmann & Filip Keereman, 2001. "An indicator-based short-term forecast for quarterly GDP in the euro area," European Economy - Economic Papers 2008 - 2015 154, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
- Massimiliano Marcellino, 2005.
"Leading Indicators: What Have We Learned?,"
286, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Christian Dreger & Christian Schumacher, 2005. "Out-of-sample Performance of Leading Indicators for the German Business Cycle: Single vs. Combined Forecasts," Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2005(1), pages 71-87.
- Thomas J. Sargent & Christopher A. Sims, 1977.
"Business cycle modeling without pretending to have too much a priori economic theory,"
55, Federal Reserve Bank of Minneapolis.
- Tom Doan, . "RATS program to estimate observable index model from Sargent-Sims(1977)," Statistical Software Components RTZ00126, Boston College Department of Economics.
- Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series 90, Board of Governors of the Federal Reserve System (U.S.).
When requesting a correction, please mention this item's handle: RePEc:onb:oenbmp:y:2005:i:3:b:4. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Claudia Kwapil)
If references are entirely missing, you can add them using this form.