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Quantifying the Extent and Nature of Risk in Alternative Cropping Patterns in Claveria, Philippines

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  • Abedullah

    (University of Agriculture, Faisalabad, Pakistan.)

  • Mubaraik Ali

    (Asian Vegetable Research and Development Center (AVRDC), Taiwan.)

Abstract

The study develops a formulation to decompose variability in profit into price and production effects. The production effect is further segregated into management and weather effects. The formulation is used to compare and decompose risk in the profit of three existing cropping patterns (corn-corn, corn-fallow, and rice-fallow) in the rainfed areas of Claveria, northern Mindanao, Philippines. High variability and low profitability of the crops in a more risky season (dry in our case) can limit cropping intensities in rainfed areas. However, intensification of the crops during the less risky season (wet in our case) can provide the necessary stake to invest in the risky season crops. Although weather is the dominant factor in explaining total variability, this should not be interpreted as a general rule for all agricultural environments. In an environment where input intensity is high, and input-output markets are inefficient, management and price effects can dominate the weather effect.

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Bibliographic Info

Article provided by Pakistan Institute of Development Economics in its journal The Pakistan Development Review.

Volume (Year): 45 (2006)
Issue (Month): 2 ()
Pages: 261-280

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Handle: RePEc:pid:journl:v:45:y:2006:i:2:p:261-280

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Related research

Keywords: Cropping Pattern; Weather Risk; Management Risk; Price Risk; Profit; Expected Utility;

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References

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  1. Chambers, Robert G. & Quiggin, John C., 2004. "Technological and financial approaches to risk management in agriculture: an integrate approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), June.
  2. Mehra, Shakuntla, 1981. "Instability in Indian agriculture in the context of the new technology:," Research reports 25, International Food Policy Research Institute (IFPRI).
  3. Anderson, Jock R., 1974. "Risk Efficiency in the Interpretation of Agricultural Production Research," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 42(03), September.
  4. Robert G. Chambers & John Quiggin, 2002. "The State-Contingent Properties of Stochastic Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 513-526.
  5. Robert G. Chambers & John Quiggin, 2004. "Technological and financial approaches to risk management in agriculture: an integrated approach ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), pages 199-223, 06.
  6. Mark W. Rosegrant & James A. Roumasset, 1985. "The Effect Of Fertiliser On Risk: A Heteroscedastic Production Function With Measurable Stochastic Inputs," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 29(2), pages 107-121, 08.
  7. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
  8. Anderson, Jock R. & Feder, Gershon, 2007. "Agricultural Extension," Handbook of Agricultural Economics, Elsevier.
  9. Anderson, Jock R. & Griffiths, William E., 1981. "Production Risk And Input Use: Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 25(02), August.
  10. Hans Binswanger, 1980. "Attitudes toward risk: Experimental measurement in rural india," Artefactual Field Experiments 00009, The Field Experiments Website.
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