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Maize Productivity and Input Subsidies in Malawi: A State-Contingent Stochastic Production Frontier Approach

Author

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  • Holden , Stein

    (School of Economics and Business, Norwegian University of Life Sciences)

  • O’Donnell, Christopher J.

    (School of Economics, The University of Queensland, Australia)

Abstract

We make cross-sectional comparisons of productivity in a risky agricultural setting. To make meaningful comparisons, we find it necessary to define a new productivity index that satisfies important axioms from index number theory (e.g., transitivity). The index can be computed without any information on output or input prices. However, it cannot be computed without an estimate of a state-contingent production frontier. We use maximum likelihood methods to estimate a state-contingent stochastic production frontier that explicitly allows for variations in input quality. We find that differences in productivity are mainly due to differences in environment and scale-mix efficiency. In turn, we conjecture that differences in scale-mix efficiency are partly driven by variations in access to input subsidies. The maximum likelihood estimator appears to do a poor job of disentangling the effects of technical inefficiency and statistical noise.

Suggested Citation

  • Holden , Stein & O’Donnell, Christopher J., 2015. "Maize Productivity and Input Subsidies in Malawi: A State-Contingent Stochastic Production Frontier Approach," Working Paper Series 02-2015, Norwegian University of Life Sciences, School of Economics and Business.
  • Handle: RePEc:hhs:nlsseb:2015_002
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    References listed on IDEAS

    as
    1. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    2. Feder, Gershon, 1985. "The relation between farm size and farm productivity : The role of family labor, supervision and credit constraints," Journal of Development Economics, Elsevier, vol. 18(2-3), pages 297-313, August.
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    Cited by:

    1. Holden, S.T. & Quiggin, J., 2018. "Probability Weighting and Fertilizer Use in a State-Contingent Framework," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277355, International Association of Agricultural Economists.
    2. Holden , Stein T. & Quiggin, John, 2017. "Probability Weighting and Input Use Intensity in a State-Contingent Framework," CLTS Working Papers 8/17, Norwegian University of Life Sciences, Centre for Land Tenure Studies, revised 21 Oct 2019.
    3. Holden , Stein T. & Quiggin, John, 2015. "Climate risk and state-contingent technology adoption: The role of risk preferences and probability weighting," Working Paper Series 15-2015, Norwegian University of Life Sciences, School of Economics and Business.
    4. Holden, Stein T., 2015. "Risk Preferences, Shocks and Technology Adoption: Farmers’ Responses to Drought Risk," CLTS Working Papers 3/15, Norwegian University of Life Sciences, Centre for Land Tenure Studies, revised 11 Oct 2019.

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    More about this item

    Keywords

    agricultural productivity; risky environment; imperfect factor markets; state-contingent analysis; total factor productivity; input subsidies;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General

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