A Bunch of Models, a Bunch of Nulls and Inference About Predictive Ability
Inference about predictive ability is usually carried out in the form of pairwise comparisons between two competing forecasting methods. Nevertheless, some interesting questions are concerned with families of models and not just with a couple of forecasting strategies. An example of this would be the question about the predictive accuracy of pure time-series models versus models based on economic fundamentals. It is clear that an appropriate answer to this question requires comparing families of models, which may include a number of different forecasting strategies. Another usual approach in the literature consists of comparing the accuracy of a new forecasting method with a natural benchmark. Nevertheless, unless the econometrician is completely sure about the superiority of the benchmark over the rest of the methods available in the literature, he/she may want to compare the accuracy of his/her new forecasting model, and its extensions, against a broader set of methods. In this article we present a simple methodology to test the null hypothesis of equal predictive ability between two families of forecasting methods. Our approach corresponds to a natural extension of the White (2000) reality check in which we allow for the families being compared to be populated by a large number of forecasting methods. We illustrate our testing approach with an empirical application comparing the ability of two families of models to predict headline inflation in Chile, the US, Sweden and Mexico. With this illustration we show that comparing families of models using the usual approach based on pairwise comparisons of the best ex-post performing models in each family, may lead to conclusions that are at odds with those suggested by our approach.
|Date of creation:||Jan 2011|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (562) 670 2000
Fax: (562) 698 4847
Web page: http://www.bcentral.cl/
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.:
- 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.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Groen, Jan J.J. & Kapetanios, George & Price, Simon, 2009. "A real time evaluation of Bank of England forecasts of inflation and growth," International Journal of Forecasting, Elsevier, vol. 25(1), pages 74-80.
- Kenneth D. West, 1994.
"Asymptotic Inference About Predictive Ability,"
- Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
- Dean Croushore, 2006.
"An evaluation of inflation forecasts from surveys using real-time data,"
06-19, Federal Reserve Bank of Philadelphia.
- Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
- Pincheira, Pablo & García, Álvaro, 2012. "En busca de un buen marco de referencia predictivo para la inflación en Chile," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(313), pages 85-123, enero-mar.
- Raffaella Giacomini & Halbert White, 2003.
"Tests of Conditional Predictive Ability,"
- Raffaella Giacomini & Halbert White, 2003. "Tests of conditional predictive ability," Boston College Working Papers in Economics 572, Boston College Department of Economics.
- Giacomini, Raffaella & White, Halbert, 2003. "Tests of Conditional Predictive Ability," University of California at San Diego, Economics Working Paper Series qt5jk0j5jh, Department of Economics, UC San Diego.
- Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
- West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, Elsevier.
- James H. Stock & Mark W. Watson, 2008.
"Phillips curve inflation forecasts,"
Conference Series ; [Proceedings],
Federal Reserve Bank of Boston, vol. 53.
- Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
- Ghysels, Eric & Osborn, Denise R. & Rodrigues, Paulo M.M., 2006. "Forecasting Seasonal Time Series," Handbook of Economic Forecasting, Elsevier.
When requesting a correction, please mention this item's handle: RePEc:chb:bcchwp:607. 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: (Claudio Sepulveda)
If references are entirely missing, you can add them using this form.