| Registro completo |
| Provedor de dados: |
AgEcon
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| País: |
United States
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| Título: |
HYPOTHESIS TESTING USING NUMEROUS APPROXIMATING FUNCTIONAL FORMS
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| Autores: |
Norwood, F. Bailey
Lusk, Jayson L.
Ferrier, Peyton Michael
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| Data: |
2001-06-13
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| Ano: |
2001
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| Palavras-chave: |
Research Methods/ Statistical Methods
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| Resumo: |
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.
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| Tipo: |
Conference Paper or Presentation
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| Idioma: |
Inglês
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| Identificador: |
2869
http://purl.umn.edu/18964
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| Editor: |
AgEcon Search
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| Relação: |
NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management>2001 Conference, St. Louis, MO, April 23-24, 2001
2001 Conference, St. Louis, MO, April 23-24, 2001
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| Formato: |
19
application/pdf
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