IDEAS home Printed from https://ideas.repec.org/p/ags/iaaeo5/197677.html
   My bibliography  Save this paper

Normative Supply Response Analysis under Production Uncertainty: Irrigated Multicrop Farming Sector of Sudan

Author

Listed:
  • Hassan, Rashid M.
  • D'Silva, Brian
  • Hallam, A.

Abstract

Sudan's irrigated subsector is the largest in sub-Saharan Africa. Farming is practised under a scheme-mandated rotation with highly centralized decision making. Under this system, labour is the major input for which the tenant has allocation flexibility both during the season and across the three crops grown, sorghum, ootton, and groundnuts. This paper analyzes the risk attributes of the production technology and measures farmer's attitudes towards risk in the irrigation schemes of Sudan. Stochastic production functions are specified where risk increasing and risk reducing input effects are allowed. Single-equation and systems procedures are employed to estimate the parameters of the first two moments of the distribution of crop yields. The analysis supports the existence of aggregate indices for weeding and harvesting labour for oonon and sorghum, while the hypothesis of separability in hired and family labour is rejected. Tue form of labour contract for hired labour is found to have significant implications on its production risk effects. When hired labour is paid in cash, production risks increase, as is the case with cotton and sorghum. When sharecropping takes place, as in groundnuts, production risks decrease with increased labour use. Supply behaviour of the tenant farmers under production uncertainty is simulated using a farm programming model.

Suggested Citation

  • Hassan, Rashid M. & D'Silva, Brian & Hallam, A., 1989. "Normative Supply Response Analysis under Production Uncertainty: Irrigated Multicrop Farming Sector of Sudan," 1989 Occasional Paper Series No. 5 197677, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaaeo5:197677
    DOI: 10.22004/ag.econ.197677
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/197677/files/agecon-occpapers-1989-019_1_.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.197677?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Batra, Raveendra N & Ullah, Aman, 1974. "Competitive Firm and the Theory of Input Demand under Price Uncertainty," Journal of Political Economy, University of Chicago Press, vol. 82(3), pages 537-548, May/June.
    2. Gallant, A. Ronald & Jorgenson, Dale W., 1979. "Statistical inference for a system of simultaneous, non-linear, implicit equations in the context of instrumental variable estimation," Journal of Econometrics, Elsevier, vol. 11(2-3), pages 275-302.
    3. Wallace, T D & Hussain, Ashiq, 1969. "The Use of Error Components Models in Combining Cross Section with Time Series Data," Econometrica, Econometric Society, vol. 37(1), pages 55-72, January.
    4. Gallant, A. Ronald, 1977. "Three-stage least-squares estimation for a system of simultaneous, nonlinear, implicit equations," Journal of Econometrics, Elsevier, vol. 5(1), pages 71-88, January.
    5. 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.
    6. Amemiya, Takeshi, 1974. "The nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 2(2), pages 105-110, July.
    7. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 192-201, July.
    8. Amemiya, Takeshi, 1977. "The Maximum Likelihood and the Nonlinear Three-Stage Least Squares Estimator in the General Nonlinear Simultaneous Equation Model," Econometrica, Econometric Society, vol. 45(4), pages 955-968, May.
    9. Jock R. Anderson, 1973. "Sparse Data, Climatic Variability, and Yield Uncertainty in Response Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 55(1), pages 77-82.
    10. ZELLNER, Arnold & KMENTA, Jan & DREZE, Jacques H., 1966. "Specification and estimation of Cobb-Douglas production function models," LIDAM Reprints CORE 12, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Amemiya, Takeshi, 1983. "Non-linear regression models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 6, pages 333-389, Elsevier.
    2. Peter E. Rossi, 1984. "Stochastic Specification of Cost and Production Relationships," Discussion Papers 616, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    3. Antle, John M., 1981. "Implications Of Sequential Decision Making For Specification And Estimation Of Production Models," Working Papers 225694, University of California, Davis, Department of Agricultural and Resource Economics.
    4. Phoebe Koundouri, 2004. "Current Issues in the Economics of Groundwater Resource Management," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 703-740, December.
    5. Wooldridge, Jeffrey M., 1996. "Estimating systems of equations with different instruments for different equations," Journal of Econometrics, Elsevier, vol. 74(2), pages 387-405, October.
    6. Hassan, Rashid M. & Hallam, Arne & D'Silva, B., 1988. "Stochastic Technology in a Programming Framework: A Generalized E. V. Model," 1988 Annual Meeting, August 1-3, Knoxville, Tennessee 270212, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Griffiths, William E. & Anderson, Jock R. & Hamal, K.B., 1987. "Subjective Distributions As Econometric Response Data," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 31(2), pages 1-15, August.
    8. Antle, John, 1987. "Technology and Uncertainty: Evidence from Egypt," 1987 Occasional Paper Series No. 4 197406, International Association of Agricultural Economists.
    9. Rosegrant, Mark W. & Roumasset, James A., 1985. "The Effect Of Fertiliser On Risk: A Heteroscedastic Production Function With Measurable Stochastic Inputs," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 29(2), pages 1-15, August.
    10. Hennessy, David A., 1997. "Stochastic technologies and the adoption decision," Journal of Development Economics, Elsevier, vol. 54(2), pages 437-453, December.
    11. Celine Nauges & Phoebe Koundouri & Vangelis Tzouvelekas, 2004. "Endogenous Technology Adoption Under Production Risk: Theory and Application to Irrigation Technology," Working Papers 0411, University of Crete, Department of Economics.
    12. Tsai, Grace Yueh-Hsiang, 1989. "A dynamic model of the U.S. cotton market with rational expectations," ISU General Staff Papers 1989010108000012168, Iowa State University, Department of Economics.
    13. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    14. Ian Domowitz, 1985. "New Directions in Non-linear Estimation with Dependent Observations," Canadian Journal of Economics, Canadian Economics Association, vol. 18(1), pages 1-27, February.
    15. Elizabeth Nolan & Paulo Santos, 2019. "Genetic modification and yield risk: A stochastic dominance analysis of corn in the USA," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-10, October.
    16. Nolan, Elizabeth & Santos, Paulo, 2012. "Insurance premiums and GM traits," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125942, International Association of Agricultural Economists.
    17. Love, H. Alan & Buccola, Steven T., 1989. "Risk Aversion, Input Use, And Heteroskedastic Supply," 1989 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, April 9-12, 1989, Sanibel Island, Florida 271525, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    18. B. A. Larson & H. Vroomen, 1991. "Nitrogen, Phosphorus And Land Demands At The Us Regional Level: A Primal Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 42(3), pages 354-364, September.
    19. R. M. Hassan & A. Hallam, 1990. "Stochastic Technology In A Programming Framework: A Generalised Mean‐Variance Farm Model," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(2), pages 196-206, May.
    20. Muktar Geleto & Mohammed Essa, 2022. "Analysis of Red Pepper Production Risk Adjusted Technical Efficiency: The Case Of Lanfuro District In Siltie Zone, Southern Ethiopia," International Journal of Business and Management, International Institute of Social and Economic Sciences, vol. 10(1), pages 30-58, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:iaaeo5:197677. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iaaeeea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.