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Subjective Distributions As Econometric Response Data

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  • William E. Griffiths
  • Jock R. Anderson
  • K.B. Hamal

Abstract

Analysis of actual observations of response processes is a routine procedure in applied econometrics but methods of dealing with purely subjective probability distributions as response 'data' have seemingly not hitherto been worked out. The models and methods developed here go some way to filling this void. They are illustrated by using information from a cross-sectional study of sixty Nepalese small-scale farmers. Means and variances of subjective probability distributions for rice paddy yields under different technologies are related to controlled inputs, such as fertiliser levels, and to relevant socio-economic aspects of farmers themselves, such as technological knowledge and farm size.
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Suggested Citation

  • William E. Griffiths & Jock R. Anderson & K.B. Hamal, 1987. "Subjective Distributions As Econometric Response Data," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 31(2), pages 127-141, August.
    • Handle: RePEc:bla:ajarec:v:31:y:1987:i:2:p:127-141
    DOI: j.1467-8489.1987.tb00670.x
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    1. Griffiths, William E., 1986. "A Bayesian Framework For Optimal Input Allocation With An Uncertain Stochastic Production Function," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 30(2-3), pages 1-25, August.
    2. Anderson, Jock R. & Dillon, John L. & Hardaker, Brian, 1977. "Agricultural Decision Analysis," Monographs: Applied Economics, AgEcon Search, number 288652, November.
    3. 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.
    4. Roumasset, James A., 1974. "Estimating The Risk Of Alternate Techniques: Nitrogenous Fertilization Of Rice In The Philippines," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 42(04), pages 1-38, December.
    5. 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.
    6. Amemiya, Takeshi, 1977. "A note on a heteroscedastic model," Journal of Econometrics, Elsevier, vol. 6(3), pages 365-370, November.
    7. 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, August.
    8. 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.
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    Cited by:

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    2. Norris, Patricia E. & Kramer, Randall A., 1990. "The Elicitation of Subjective Probabilities with Applications in Agricultural Economics," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 58(02-03), pages 1-21, December.

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