Economic bias of weather forecasting: a spatial modeling approach

Nejat Anbarci (), Eric Floehr, Jungmin Lee and Joon Jin Song

Working Papers from Deakin University, Department of Economics

Abstract: 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.

Keywords: Weather Forecasting; Extent of the Market; Forecast Verification; Accuracy; Bias; Spatial Autoregressive Model (search for similar items in EconPapers)
JEL-codes: C21 H4 L1 L8 (search for similar items in EconPapers)
Date: 2008-08-01
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Persistent link: https://EconPapers.repec.org/RePEc:dkn:econwp:eco_2008_12

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