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Economic bias of weather forecasting: a spatial modeling approach


  • Anbarci, Nejat
  • Floehr, Eric
  • Lee, Jungmin
  • Song, Joon Jin


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.

Suggested Citation

  • Anbarci, Nejat & Floehr, Eric & Lee, Jungmin & Song, Joon Jin, 2008. "Economic bias of weather forecasting: a spatial modeling approach," Economics Series eco_2008_12, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  • Handle: RePEc:dkn:econwp:eco_2008_12

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    More about this item


    Weather Forecasting; Extent of the Market; Forecast Verification; Accuracy; Bias; Spatial Autoregressive Model;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • H4 - Public Economics - - Publicly Provided Goods
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • L8 - Industrial Organization - - Industry Studies: Services


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