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A state space approach to evaluate multi-horizon forecasts


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Goodwin, T and Tian, J 2017 , A state space approach to evaluate multi-horizon forecasts.

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We propose a state space modeling framework to evaluate a set of forecasts that target
the same variable but are updated along the forecast horizon. The approach decomposes
forecast errors into three distinct horizon-specific processes, namely, bias, rational error
and implicit error, and attributes forecast revisions to corrections for these forecast errors.
We derive the conditions under which forecasts that contain error that is irrelevant
to the target can still present the second moment bounds of rational forecasts. By evaluating
multi-horizon daily maximum temperature forecasts for Melbourne, Australia, we
demonstrate how this modeling framework analyzes the dynamics of the forecast revision
structure across horizons. Understanding forecast revisions is critical for weather forecast
users to determine the optimal timing for their planning decision.

Item Type: Report (Discussion Paper)
Authors/Creators:Goodwin, T and Tian, J
Keywords: Rational forecasts, implicit forecasts, forecast revision structure, weather forecasts
Publisher: University of Tasmania
Additional Information:

JEL classification: C32; C53

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