Abstract

This study aims at applying Prior-Posterior decision theory based models to analyze and solve the farmers’ decision problem who are faced with decision of determining among alternatives crops [Sorghum, Rice, Wheat & Corn] the best crop to invest on, that will give a highest yield and profit under the prevailing state of nature on each of a 100 acres land located in Obudu LGA in Cross River State for each of the Farm Settler. However, the study has the following objectives (i) laying bare the usefulness of the theory, (ii) measuring the magnitude of the difference between alternative actions (iii) presenting experimental results for considering decision making under uncertainties, and (iv) evaluating the optimal policy or strategy or action that maximizes the expected yield of cereal crop within the study area. The methodology involves experiments and data were compared to United State Department of Agriculture (USDA). The analysis and presentation of results were based on Simulation of Prior-Posterior decision models, Policy iterations, and Pearson Product Moment Correlation as interaction, validity, reliability tests respectively. Consequently, from the results of prior probabilities of the state of nature and the likelihood of the alternatives courses of action, and applying Prior-Posterior Decision Models to the uncertain system, the following decision were generated: (a)Posterior Probabilities of the States of Nature (b) Marginal Probability of the Course of Action, (c) Maximum Expected Monetary Value[EMV*] (d) Expected Profit in a Perfect Information[EPPI], (e) Expected Value of Perfect Information[EVPI], and (f) Expected Value of System Information[ EVSI]. The results gave a clear indication that Rice has the [EMV*] value of $17,178.21 at 40 th model iteration, making it the most suitable crop for each of the Farmer Settlers to invest on, for maximum yield. EMV* of rice was also observed to be optimized from the 1 st and 40 th model iteration at the value of $14,175.66 and $17,178.21 respectively. The results of the analyses attest to the fact that rice production in Obudu study area is currently the most yielding crop. The performance of Prior-Posterior decision models on the farmers’ decision was evaluated which gave Pearson Product Moment Coefficient(r) of = 1.0. This shows applicability of Prior-Posterior Decision Model Excel Algorithms in River Basin Multi-projects/objectives Planning and Management. Keywords : Prior-Posterior, Modeling, Farm- Settlers -Decision, investment, Optimization. DOI : 10.7176/CER/11-2-07 Publication date :March 31 st 2019

Highlights

  • 1.0 Introduction Farmers in Obudu LGA in Cross River State was confronted with an economic decision of selecting the best cereal crop to invest on, in the area

  • An investment that will bring in the dividend of agriculture as the federal government is clamoring for all to go into agriculture to save Nigerian from food scarcity and as well as gains from foreign exchange earnings through cereal crops exports

  • Details of the solution to the problem is handled step-wisely as you proceed in this paper.In Prior-Posterior decision model, it is difficult to consider decision problems in which the decision maker has no information, either objective or subjective, regarding the probabilities of the states of nature

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Summary

Methodology

(iii) Gives idea to the researcher on the ultimate prior probability that will give each of the Farm Settler the absolute decision i.e. the priority that produces the optimum solution, gives the actual indication of the state of nature. Series data in respect of annual yields (t ha1) of Maize, Rice, Sorghum and Wheat was obtained from the United State Department of Agricultural (USDA); the data on climateis not known[State of Nature], the Prior probability of the climate was estimated based on the crops growth rate. The profit from each crop is strongly dependent on the climate during the growing season per year He has selected four years horizon form 2014-2017 to enable him make optimum decision for higher yield and profit. The conditional probability when divided by the marginal probability result to Posterior Probability

Wheat Corn
Marginal Probability
Expected Value of System Information
Prior Posterior
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