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Using Moment Constraints in GME Estimation

In: Applied Methods for Agriculture and Natural Resource Management

Author

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  • Richard E. Howitt

    (University of California)

  • Siwa Msangi

    (International Food Policy Research Institute)

Abstract

In this contribution, we explore the sensitivity of parameter estimates derived through the generalized maximum entropy (GME) approach under alternative specifications of the width of the error term supports. Although many recommend a “three-sigma” rule for setting the width of this term, there can be noticeable differences in the results if it is expanded beyond that, as others in the literature have suggested. We use a Monte Carlo analysis to see how imposing a moment-based condition into the GME problem, as an additional constraint, affects the results. We find that it removes the sensitivity of the parameter estimates to the width of the supports for the error term and that this remains robust even when the data is ill-conditioned. Based on this, we recommend that researchers impose this condition when doing GME-based estimation, to improve the performance of the estimator.

Suggested Citation

  • Richard E. Howitt & Siwa Msangi, 2019. "Using Moment Constraints in GME Estimation," Natural Resource Management and Policy, in: Siwa Msangi & Duncan MacEwan (ed.), Applied Methods for Agriculture and Natural Resource Management, chapter 0, pages 129-144, Springer.
    • Handle: RePEc:spr:nrmchp:978-3-030-13487-7_8
    DOI: 10.1007/978-3-030-13487-7_8
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    Cited by:

    1. Zamani, Omid & Grundmann, Philipp & Libra, Judy A. & Nikouei, Alireza, 2019. "Limiting and timing water supply for agricultural production – The case of the Zayandeh-Rud River Basin, Iran," Agricultural Water Management, Elsevier, vol. 222(C), pages 322-335.

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