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Climate Forecasting And Emergency Policies Evidence Of Opportunities From Ceará, Brazil

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  • Ariaster Baumgratz Chimeli
  • Francisco de Assis de Souza Filho
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    Abstract

    We take small steps towards the approximation between economic analysis and the science of climate forecasting in the formulation of policies to alleviate the impact of climatic shocks. We do so by estimating the relationship between climate variables and corn production in Ceará, an important State in the Brazilian semi-arid. Using parametric and non-parametric regression models, we first estimate the relationship between contemporaneous sea surface temperatures (SSTs) for the Pacific and Atlantic oceans and the local rainfed corn market. Next, we investigate the forecasting potential of future corn production conditional on information on current SSTs. We find strong evidence that climate determinants are important in determining current and future corn production, a key indicator of the climatic stress to which a large number of small farmers are subject in the Brazilian semi-arid. Additionally, corn production in the region is negatively correlated with federal government transfers meant to mitigate the impact of local droughts. These resources have been subject to lethargic bureaucracies, corruption and economic inefficiencies in general. The observation and forecasting of corn production can be invaluable in the design of more efficient, expeditious and transparent policies to mitigate the effects of droughts in the region.

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    File URL: http://www.anpec.org.br/encontro2004/artigos/A04A118.pdf
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    Bibliographic Info

    Paper provided by ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics] in its series Anais do XXXII Encontro Nacional de Economia [Proceedings of the 32th Brazilian Economics Meeting] with number 118.

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    Date of creation: 2004
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    Handle: RePEc:anp:en2004:118

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    1. Troy Podbury & Terry C. Sheales & Intizar Hussain & Brian S. Fisher, 1998. "Use of El Ni�o Climate Forecasts in Australia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(5), pages 1096-1101.
    2. John Luke Gallup & Jeffrey D. Sachs, 2000. "Agriculture, Climate, and Technology: Why are the Tropics Falling Behind?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(3), pages 731-737.
    3. Datt, Gaurav & Hoogeveen, Hans, 2003. "El Nino or El Peso? Crisis, Poverty and Income Distribution in the Philippines," World Development, Elsevier, vol. 31(7), pages 1103-1124, July.
    4. James W. Mjelde & Harvey S.J. Hill & John F. Griffiths, 1998. "A Review of Current Evidence on Climate Forecasts and Their Economic Effects in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(5), pages 1089-1095.
    5. Allan D. Brunner, 2002. "El Niño and World Primary Commodity Prices: Warm Water or Hot Air?," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 176-183, February.
    6. Richard M. Adams & Stephen Polasky, 1998. "The Value of El Ni�o Forecasts in the Management of Salmon: A Stochastic Dynamic Assessment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(4), pages 765-777.
    7. Richard M. Adams & Kelly J. Bryant & Bruce A. Mccarl & David M. Legler & James O'Brien & Andrew Solow & Rodney Weiher, 1995. "Value Of Improved Long-Range Weather Information," Contemporary Economic Policy, Western Economic Association International, vol. 13(3), pages 10-19, 07.
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