Economic bias of weather forecasting: a spatial modeling approach

Anbarci, Nejat, Floehr, Eric, Lee, Jungmin and Song, Joon Jin 2008, Economic bias of weather forecasting: a spatial modeling approach, Deakin University, School of Accounting, Economics and Finance, Geelong, Vic..

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Title Economic bias of weather forecasting: a spatial modeling approach
Author(s) Anbarci, NejatORCID iD for Anbarci, Nejat
Floehr, Eric
Lee, Jungmin
Song, Joon Jin
Publication date 2008-08
Series School Working Paper - Economics Series ; SWP 2008/12
Total pages 22
Publisher Deakin University, School of Accounting, Economics and Finance
Place of publication Geelong, Vic.
Keyword(s) C21
Weather Forecasting
Extent of the Market
Forecast Verification
Spatial Autoregressive Model
Summary The value of accurate weather forecast information is substantial. In this paper we examine competition among forecast providers and its implications for the quality of forecasts. A simple economic model shows that an economic bias geographical inequality in forecast accuracy arises due to the extent of the market. Using the unique data on daily high temperature forecasts for 704 U.S. cities, we find that forecast accuracy increases with population and income. Furthermore, the economic bias gets larger when the day of forecasting is closer to the target day; i.e. when people are more concerned about the quality of forecasts. The results hold even after we control for location-specific heterogeneity and difficulty of forecasting.
Language eng
HERDC Research category CN.1 Other journal article
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