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Opportunities and challenges to the sustainable development of cattle raising in Brazil, 1970-2005

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  • Eustaquio Reis

    (IPEA, Rio de Janeiro, Brazil)

Abstract

The paper provides historical and analytical perspectives for the assessment of the challenges and opportunities of cattle raising activities in the transition toward a low-carbon agriculture in Brazil. It is organized as follows. The first section poses the problem. The second presents long run historical perspectives on the development of cattle raising in Brazil. The third section analyzes the patterns of growth of cattle raising in Brazil based upon municipal panel data of Agricultural Census from 1975 to 2006. The fourth section uses a framework analogous to Hayami and Ruttan (1985) to estimate growth convergence equations for major aspects of cattle raising activities, namely the stocking ratio, the specialization in cattle and farm expansion. The report concludes with a discussion of policy options for a transition toward sustainable cattle raising in Brazil

Suggested Citation

  • Eustaquio Reis, 2017. "Opportunities and challenges to the sustainable development of cattle raising in Brazil, 1970-2005," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 17(1), pages 18-39.
    • Handle: RePEc:anp:econom:v:18:y:2017:1:18_39
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    More about this item

    Keywords

    Panel data; Arrellano-Bond; Agricultural economics; Land use; Cattle ranching; Deforestation;
    All these keywords.

    JEL classification:

    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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