Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-30T17:12:16.713Z Has data issue: false hasContentIssue false

Forecasting the impacts of climate variability: lessons from the rainfed corn market in Ceará, Brazil

Published online by Cambridge University Press:  01 April 2008

ARIASTER B. CHIMELI
Affiliation:
Ohio University, Department of Economics, Bentley Hall Annex, Athens, OH 45701. Email: [email protected]
FRANCISCO DE ASSIS DE SOUZA FILHO
Affiliation:
International Research Institute for Climate and Society, Columbia University
MARCOS COSTA HOLANDA
Affiliation:
Instituto de Pesquisa e Estratégia Econômica do Ceará
FRANCIS CARLO PETTERINI
Affiliation:
Instituto de Pesquisa e Estratégia Econômica do Ceará

Abstract

A number of studies show that climatic shocks have significant economic impacts in several regions of the world, especially in, but not limited to, developing economies. In this paper we focus on a drought-related indicator of well-being and emergency spending in the Brazilian semi-arid zone – rainfed corn market – and estimate aggregate behavioral and forecast models for this market conditional on local climate determinants. We find encouraging evidence that our approach can help policy makers buy time to help them prepare for drought mitigating actions. The analysis is applicable to economies elsewhere in the world and climatic impacts other than those caused by droughts.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Brunner, A.D. 2002, ‘El Niño and world primary commodity prices: warm water or hot air?’, Review of Economics and Statistics 84: 176183.CrossRefGoogle Scholar
Datt, G. and Hoogeveen, H. 2003, ‘El Niño or El Peso? crisis, poverty and income distribution in the Philippines’, World Development 31: 11031124.CrossRefGoogle Scholar
Deaton, A. 1992a, ‘Household saving in LDCs: credit, markets, insurance and welfare’, Scandinavian Journal of Economics 94: 253273.CrossRefGoogle Scholar
Deaton, A. 1992b, Understanding Consumption, New York: Oxford University Press.CrossRefGoogle Scholar
Fafchamps, M. and Lund, S. 2003, ‘Risk-sharing networks in rural Philippines’, Journal of Development Economics 71: 261287.CrossRefGoogle Scholar
Friedman, J.H. 1984, ‘A variable span smoother’, Technical Report 5, Laboratory for Computational Statistics, Department of Statistics, Stanford.CrossRefGoogle Scholar
Gallup, J.L. and Sachs, J.D. 2000, ‘Agriculture, climate and technology: why are the tropics falling behind?’, American Journal of Agricultural Economics 82: 731737.CrossRefGoogle Scholar
Glantz, M.H. 2001, Currents of Change: Impacts of El Niño and La Niña on Climate and Society, second edn, Cambridge University Press.Google Scholar
Hastenrath, S. 1984, ‘Predictability of northeast Brazil drought’, Nature 307: 531533.CrossRefGoogle Scholar
Hoerling, M. 2002, ‘The symmetry issue’, in Glantz, M. (ed.), La Niña and its Impacts: Facts and Speculation, United Nations University Press.Google Scholar
Instituto Brasileiro de Geografia e pesquisa, ‘Demographic Census 2000’, http://www.ibge.gov.br/english/estatistica/populacao/censo2000/Google Scholar
King, J. 2001, ‘Trade reform and the corn market: prospects for the World Trade Organization negotiations on agriculture’, Review of Agricultural Economics 23: 4767.CrossRefGoogle Scholar
Lemos, M.C., Finan, T.J., Fox, R.W., Nelson, D.R., and Tucker, J. 2002, ‘The use of seasonal climate forecasting in policymaking: lessons from northeast Brazil’, Climatic Change 55: 479507.CrossRefGoogle Scholar
Magalhães, A.R. 1991, Respostas Governamentais às Secas: A Experiência de 1987 no Nordeste, Governo do Estado do Ceará, Secretaria de Planejamento e Coordenação, Imprensa Oficial do Ceará (in Spanish).Google Scholar
Mjelde, J.W., Hill, H.S.J., and Griffiths, J.F. 1998, ‘A review of current evidence on climate forecasts and their economic effects in agriculture’, American Journal of Agricultural Economics 80: 1098–1095.CrossRefGoogle Scholar
Moura, A.D. and Shukla, J. 1981, ‘On the dynamics of droughts in northeast Brazil: observations, theory and numerical experiments with a general circulation model’, Journal of the Atmospheric Sciences 38: 2653–2675.2.0.CO;2>CrossRefGoogle Scholar
Quinn, W.H. 1992, ‘A study of southern oscillation-related climate activity for A.D. 620–1990 incorporating Nile River flood data’, in Diaz, H.F, and Markgraf, V. (eds), El Niño: Historical and Paleoclimatic Aspects of the Southern Oscillation, Cambridge University Press.Google Scholar
Ropelewski, C.F. and Halpert, M.S. 1987, ‘Global and regional scale precipitation patterns associated with the El Niño/southern oscillation’, Monthly Weather Review 115:16061626.2.0.CO;2>CrossRefGoogle Scholar
Santana, C.S., Folhes, M.T., Mayorga, M.I.O., and Mayorga, R.D. 1999, ‘O Programa a Hora de Plantar Sob a Ótica dos Agricultores Beneficiados no Estado do Ceará’, Annals of the XXXVII Congresso Brasileiro de Economia e Sociologia Rural, Sociedade Brasileira de Economia e Sociologia Rural (in Spanish).Google Scholar
Souza-Filho, F.A. and Lall, U. 2003, ‘Seasonal to interannual streamflow forecasts for Ceara, Brazil: applications of a multivariate, semiparametric algorithm’, Water Resources Research 39 (11).CrossRefGoogle Scholar
Tendler, J. 1998, Good Governance in the Tropics, Johns Hopkins University Press.Google Scholar
World Bank 2000, Brazil. Poverty Reduction, Growth, and Fiscal Stability in the State of Ceará: A State Economic Memorandum, Volumes I and II, Brazil Country Management Unit, Report No. 19217-BR.Google Scholar