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Population and income sensitivity of private and public weather forecasting

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  • Anbarci, Nejat
  • Boyd III, John
  • Floehr, Eric
  • Lee, Jungmin
  • Song, Joon Jin

Abstract

Accurate weather forecasts have substantial economic value. We examine the provision of accurate forecasts both theoretically and empirically. Theoretically, we use a simple Neo-Hotelling model. In that model, the public forecaster, the National Weather Service (NWS), tries to achieve socially-efficient forecast accuracy operating under a per capita tax constraint; on the other hand, the private providers compete against each other for profits by choosing their optimal level of forecast accuracy in a monopolistically competitive market in which each private provider caters to a market niche while co-existing with the NWS. Empirically, we use a unique data set on daily maximum temperature forecasts for 704 U.S. cities and estimate the nearest neighbor matching and the state fixed effect (FE) models. Our empirical findings are consistent with the predictions of our simple public good model: we find that forecast accuracy is sensitive to economic variables such as population and average household income in that the accuracy increases in these economic variables. Our most surprising theoretical and empirical finding is that population and income sensitivity is found not only for private forecasters but also for the public forecaster, the NWS.

Suggested Citation

  • Anbarci, Nejat & Boyd III, John & Floehr, Eric & Lee, Jungmin & Song, Joon Jin, 2011. "Population and income sensitivity of private and public weather forecasting," Regional Science and Urban Economics, Elsevier, vol. 41(2), pages 124-133, March.
  • Handle: RePEc:eee:regeco:v:41:y:2011:i:2:p:124-133
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    References listed on IDEAS

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    2. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
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    Cited by:

    1. L. Zirulia, 2015. "Should I stay or should I go? : Weather forecasts and the economics of short breaks," Working Papers wp1034, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Paolo Figini & Simona Cicognani & Lorenzo Zirulia, 2023. "Booking in the Rain. Testing the Impact of Public Information on Prices," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(3), pages 1329-1364, November.
    3. Lorenzo Zirulia, 2016. "‘Should I stay or should I go?’," Tourism Economics, , vol. 22(4), pages 837-846, August.

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