Changes in Predictive Ability with Mixed Frequency Data
Abstract
This paper proposes a new regression model - a smooth transition mixed data sampling (STMIDAS) approach - that captures recurrent changes in the ability of a high frequency variable in predicting a low frequency variable. The STMIDAS regression is employed for testing changes in the ability of financial variables in forecasting US output growth. The estimation of the optimal weights for aggregating weekly data inside the quarter improves the measurement of the predictive ability of the yield curve slope for output growth. Allowing for changes in the impact of the short-rate and the stock returns in future growth is decisive for finding in-sample and out-of-sample evidence of their predictive ability at horizons longer than one year.Download Info
If 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 Info
Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 595.Length:
Date of creation: May 2007
Date of revision:
Handle: RePEc:qmw:qmwecw:wp595
Contact details of provider:
Postal: London E1 4NS
Phone: +44 (0) 20 7882 5096
Fax: +44 (0) 20 8983 3580
Web page: http://www.econ.qmul.ac.uk
More information through EDIRC
Related research
Keywords: Smooth transition; MIDAS; Predictive ability; Asset prices; Output growth;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
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-05-19 (All new papers)
- NEP-ECM-2007-05-19 (Econometrics)
- NEP-ETS-2007-05-19 (Econometric Time Series)
- NEP-FOR-2007-05-19 (Forecasting)
- NEP-MAC-2007-05-19 (Macroeconomics)
References
References listed on IDEASPlease 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.:
- Pesaran, M Hashem & Timmermann, Allan G, 2004.
"Small Sample Properties of Forecasts From Autoregressive Models Under Structural Breaks,"
CEPR Discussion Papers
4401, C.E.P.R. Discussion Papers.
- Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
- Pesaran, M.H. & Timmermann, A., 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," Cambridge Working Papers in Economics 0331, Faculty of Economics, University of Cambridge.
- Allan Timmermann & M. Hashem Pesaran, 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," CESifo Working Paper Series 990, CESifo Group Munich.
- Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005.
"Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination,"
International Journal of Forecasting,
Elsevier, vol. 21(4), pages 755-774.
- Teräsvirta, Timo & van Dijk, Dick & Medeiros, Marcelo, 2004. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," Working Paper Series in Economics and Finance 561, Stockholm School of Economics, revised 04 Nov 2004.
- Timo Teräsvirta & Dick van Dijk & Marcelo Cunha Medeiros, 2004. "Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination," Textos para discussão 485, Department of Economics PUC-Rio (Brazil).
- Hodrick, Robert J, 1992.
"Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement,"
Review of Financial Studies,
Society for Financial Studies, vol. 5(3), pages 357-86.
- Tom Doan, . "OLSHODRICK: RATS procedure to compute Hodrick standard errors," Statistical Software Components RTS00147, Boston College Department of Economics.
- Mittelhammer,Ron C. & Judge,George G. & Miller,Douglas J., 2000. "Econometric Foundations Pack with CD-ROM," Cambridge Books, Cambridge University Press, number 9780521623940.
- Arturo Estrella & Frederic S. Mishkin, 1999.
"Predicting U.S. Recessions: Financial Variables as Leading Indicators,"
NBER Working Papers
5379, National Bureau of Economic Research, Inc.
- Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
- Arturo Estrella & Frederic S. Mishkin, 1996. "Predicting U.S. recessions: financial variables as leading indicators," Research Paper 9609, Federal Reserve Bank of New York.
- Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
- Massimiliano Marcellino & James Stock & Mark Watson, 2005.
"A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series,"
Working Papers
285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
- Marcellino, Massimiliano & Stock, James H & Watson, Mark W, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
- Galbraith, John W. & Tkacz, Greg, 2000.
"Testing for asymmetry in the link between the yield spread and output in the G-7 countries,"
Journal of International Money and Finance,
Elsevier, vol. 19(5), pages 657-672, October.
- John W. Galbraith & Greg Tkacz, 1999. "Testing For Asymmetry In The Link Between The Yield Spread And Output In The G-7 Countries," Departmental Working Papers 1999-02, McGill University, Department of Economics.
- Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor and Francis Journals, vol. 24(4), pages 369-404.
- 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.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Andrew Ang & Monika Piazzesi & Min Wei, 2003.
"What does the yield curve tell us about GDP growth?,"
Proceedings,
Federal Reserve Bank of San Francisco, issue Mar.
- Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
- Andrew Ang & Monika Piazzesi & Min Wei, 2004. "What Does the Yield Curve Tell us about GDP Growth?," NBER Working Papers 10672, National Bureau of Economic Research, Inc.
- Arturo Estrella & Gikas A. Hardouvelis, 1989.
"The term structure as a predictor of real economic activity,"
Research Paper
8907, Federal Reserve Bank of New York.
- Estrella, Arturo & Hardouvelis, Gikas A, 1991. " The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-76, June.
- Inoue, Atsushi & Kilian, Lutz, 2003.
"On the Selection of Forecasting Models,"
CEPR Discussion Papers
3809, C.E.P.R. Discussion Papers.
- Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 130(2), pages 273-306, February.
- Lutz Kilian & Atsushi Inoue, 2003. "On the selection of forecasting models," Working Paper Series 214, European Central Bank.
- Clements, Michael P & Galvão, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data : Forecasting US output growth and inflation," The Warwick Economics Research Paper Series (TWERPS) 773, University of Warwick, Department of Economics.
- Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003.
"How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States,"
The Review of Economics and Statistics,
MIT Press, vol. 85(3), pages 629-644, August.
- Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2000. "How stable is the predictive power of the yield curve? evidence from Germany and the United States," Staff Reports 113, Federal Reserve Bank of New York.
- Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
- Strikholm, Birgit & Teräsvirta, Timo, 2005. "Determining the Number of Regimes in a Threshold Autoregressive Model Using Smooth Transition Autoregressions," Working Paper Series in Economics and Finance 578, Stockholm School of Economics, revised 11 Feb 2005.
- Ang, Andrew & Bekaert, Geert, 2002.
"Regime Switches in Interest Rates,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 20(2), pages 163-82, April.
- Andrew Ang & Geert Bekaert, 1998. "Regime Switches in Interest Rates," NBER Working Papers 6508, National Bureau of Economic Research, Inc.
- 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.
- Valkanov, Rossen, 2003. "Long-horizon regressions: theoretical results and applications," Journal of Financial Economics, Elsevier, vol. 68(2), pages 201-232, May.
Citations
Lists
This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.Statistics
Access and download statisticsCorrections
When requesting a correction, please mention this item's handle: RePEc:qmw:qmwecw:wp595For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nick Vriend).
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.

