A Probability Model of The Coincident Economic Indicators
AbstractThe Index of Coincident Economic Indicators, currently compiled by the U.S. Department of Commerce, is designed to measure the state of overall economic activity. The index is constructed as a weighted average of four key macroeconomic time series, where the weights are obtained using rules that dare to the early days of business cycle analysis. This paper presents an explicit rime series model (formally, a dynamic factor analysis or "single index" model) that implicitly defines a variable that can be thought of as the overall state of the economy. Upon estimating this model using data from 1959-1987, the estimate of this unobserved variable is found to be highly correlated with the official Commerce Department series, particularly over business cycle horizons. Thus this model provides a formal rationalization for the traditional methodology used to develop the Coincident Index. Initial exploratory exercises indicate that traditional leading variables can prove useful in forecasting the short-run growth in this series.
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 National Bureau of Economic Research, Inc in its series NBER Working Papers with number 2772.
Date of creation: Nov 1988
Date of revision:
Publication status: published as G. Moore and K. Lahiri, editors. The Leading Economic Indicators: New Approaches and Forecasting Records. Cambridge University Press, 1990.
Contact details of provider:
Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Web page: http://www.nber.org
More information through EDIRC
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.:
- Friedman, Benjamin M, 1988. "Monetary Policy without Quantity Variables," American Economic Review, American Economic Association, vol. 78(2), pages 440-45, May.
- Kling, John L, 1987. "Predicting the Turning Points of Business and Economic Time Series," The Journal of Business, University of Chicago Press, vol. 60(2), pages 201-38, April.
- Koch, Paul D & Rasche, Robert H, 1988. "An Examination of the Commerce Department Leading-Indicator Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 167-87, April.
- Beatrice N. Vaccara & Victor Zarnowitz, 1978. "Forecasting with the Index of Leading Indicators," NBER Working Papers 0244, National Bureau of Economic Research, Inc.
- Diebold, Francis X & Rudebusch, Glenn D, 1989.
"Scoring the Leading Indicators,"
The Journal of Business,
University of Chicago Press, vol. 62(3), pages 369-91, July.
- Auerbach, Alan J, 1982. "The Index of Leading Indicators: "Measurement without Theory," Thirty-Five Years Later," The Review of Economics and Statistics, MIT Press, vol. 64(4), pages 589-95, November.
- James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
- Neftici, Salih N., 1982. "Optimal prediction of cyclical downturns," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 225-241, November.
- Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
- 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.
- F.Javier FERNANDEZ MACHO & Andrew C. HARVEY & James H. STOCK, 1987. "Forecasting and Interpolation Using Vector Autoregressions with Common Trends," Annales d'Economie et de Statistique, ENSAE, issue 6-7, pages 279-287.
- Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: ().
If references are entirely missing, you can add them using this form.