HYPOTHESIS TESTING USING NUMEROUS APPROXIMATING FUNCTIONAL FORMS

F. Bailey Norwood, Jayson L. Lusk () and Peyton Michael Ferrier ()

No 18964, 2001 Conference, April 23-24, 2001, St. Louis, Missouri from NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management

Abstract: While the combination of several or more models is often found to improve forecasts (Brandt and Bessler, Min and Zellner, Norwood and Schroeder), hypothesis tests are typically conducted using a single model approach 1 . Hypothesis tests and forecasts have similar goals; they seek to define a range over which a parameter should lie within a degree of confidence. If it is true that, on average, composite forecasts are more accurate than a single model's forecast, it might also be true that hypothesis tests using information from numerous models are, on average, more accurate in the sense of lower Type I and Type II errors than hypothesis tests using a single model.

Keywords: Research Methods/ Statistical Methods (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://purl.umn.edu/18964 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:ags:ncrone:18964

Access Statistics for this paper

More papers in 2001 Conference, April 23-24, 2001, St. Louis, Missouri from NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management
Series data maintained by AgEcon Search ().