Using Macro-Financial Variables To Forecast Recessions. An Analysis Of Canada, 1957-2002
AbstractWe employ artificial neural networks using macro-financial variables to predict recessions. We model the relationship between indicator variables and recessions to periods into the future and employ a procedure that penalizes a misclassified recession more than a misclassified non-recession. Our results reveal that among 16 models that we constructed from indicator variables and their combinations, the indicator variables Spread, -year bond rates, -year bond rates, monetary base, industrial production are candidate variables for predicting recessions ranging to periods in the future. However, most indicator variables become candidate for predicting recessions when misclassified recessions are penalized heavily than misclassified non-recessions.
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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Euro-American Association of Economic Development in its journal Applied Econometrics and International Development.
Volume (Year): 6 (2006)
Issue (Month): 3 ()
Contact details of provider:
Web page: http://www.usc.es/economet/eaa.htm
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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.:
- Marimon, Ramon & McGrattan, Ellen & Sargent, Thomas J., 1990. "Money as a medium of exchange in an economy with artificially intelligent agents," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 329-373, May.
- Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
- Allan D. Brunner, 1994.
"On the dynamic properties of asymmetric models of real GNP,"
International Finance Discussion Papers
489, Board of Governors of the Federal Reserve System (U.S.).
- Allan D. Brunner, 1997. "On The Dynamic Properties Of Asymmetric Models Of Real GNP," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 321-352, May.
- James M. Hutchinson & Andrew W. Lo & Tomaso Poggio, 1995.
"A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks,"
NBER Working Papers
4718, National Bureau of Economic Research, Inc.
- Hutchinson, James M & Lo, Andrew W & Poggio, Tomaso, 1994. " A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks," Journal of Finance, American Finance Association, vol. 49(3), pages 851-89, July.
- Khurshid M. Kiani & Prasad V. Bidarkota & Terry L. Kastens, 2005. "Forecast performance of neural networks and business cycle asymmetries," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 1(4), pages 205-210, July.
- Brunner, Allan D, 1992.
"Conditional Asymmetries in Real GNP: A Seminonparametric Approach,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 10(1), pages 65-72, January.
- Allan D. Brunner, 1990. "Conditional asymmetries in real GNP: a semi-nonparametric approach," Finance and Economics Discussion Series 140, Board of Governors of the Federal Reserve System (U.S.).
- Gencay, Ramazan, 1998. "The predictability of security returns with simple technical trading rules," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 347-359, October.
- Frank, Murray & Gencay, Ramazan & Stengos, Thanasis, 1988. "International chaos?," European Economic Review, Elsevier, vol. 32(8), pages 1569-1584, October.
- Beaudry, Paul & Koop, Gary, 1993. "Do recessions permanently change output?," Journal of Monetary Economics, Elsevier, vol. 31(2), pages 149-163, April.
- Simon M. Potter, 1993.
"A Nonlinear Approach to U.S. GNP,"
UCLA Economics Working Papers
693, UCLA Department of Economics.
- Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
- Garcia, Rene & Gencay, Ramazan, 2000.
"Pricing and hedging derivative securities with neural networks and a homogeneity hint,"
Journal of Econometrics,
Elsevier, vol. 94(1-2), pages 93-115.
- René Garcia & Ramazan Gençay, 1998. "Pricing and Hedging Derivative Securities with Neural Networks and a Homogeneity Hint," CIRANO Working Papers 98s-35, CIRANO.
- Norman R. Swanson & Halbert White, 1997.
"A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks,"
The Review of Economics and Statistics,
MIT Press, vol. 79(4), pages 540-550, November.
- Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, EconWPA.
- Swanson, N.R. & White, H., 1995. "A Models Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Papers 04-95-12, Pennsylvania State - Department of Economics.
- Ramsey, James B & Rothman, Philip, 1996.
"Time Irreversibility and Business Cycle Asymmetry,"
Journal of Money, Credit and Banking,
Blackwell Publishing, vol. 28(1), pages 1-21, February.
- Anderson, Heather M. & Vahid, Farshid, 1998. "Testing multiple equation systems for common nonlinear components," Journal of Econometrics, Elsevier, vol. 84(1), pages 1-36, May.
- Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-75, July.
- Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-28, April.
- Khurshid Kiani, 2005. "Detecting Business Cycle Asymmetries Using Artificial Neural Networks and Time Series Models," Computational Economics, Society for Computational Economics, vol. 26(1), pages 65-89, August.
- Bidarkota Prasad V., 1999. "Sectoral Investigation of Asymmetries in the Conditional Mean Dynamics of the Real U.S. GDP," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(4), pages 1-12, January.
- Khurshid M. Kiani & Prasad V. Bidarkota, 2004.
"On Business Cycle Asymmetries in G7 Countries,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 66(3), pages 333-351, 07.
- Gencay, Ramazan, 1999. "Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules," Journal of International Economics, Elsevier, vol. 47(1), pages 91-107, February.
- Khurshid M. Kiani, 2009. "Asymmetries in Macroeconomic Time Series in Eleven Asian Economies," International Journal of Business and Economics, College of Business, and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 8(1), pages 37-54, April.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (M. Carmen Guisan).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.