ABSTRACT
Irrigated agriculture for Rhodes Grass and fodder production forms the backbone of many farmers in Al-Batinah and Salalah Plain of Sultanate of Oman. Ecological deterioration and inefficient water resource use have resulted in a significant threat to the livelihoods of those most dependent on agricultural sector. Inefficient water use has led to rising ground water tables and widespread water and soil salinization has resulted. The high water demand in the region for crop production renders farmers vulnerable to the recurrently predicted decrease in water supply.
The government authority stopped the cultivation of Rhodes grass in coastal area and support farmers with incentive systems in order to increase fodder production investment at Najed area. Due to new irrigation water policy regulations, new technical solutions required, underground water availability, fodder investors have little data to help in making investment decisions. In addition, fodder production investments are characterized by much uncertainty due to the nature of the desert farming which is relying on many factors that cannot be controlled. In this study a dynamic evaluation model was formed and developed as a method of analyzing the economic feasibility of fodder cultivation investment project with regard to project profitability under risk environment.
The main objective of this research is to understand capital budgeting techniques for fodder crops re-allocation project. In particular, it analyzes; Net Present Value (NPV) by using conventional approach, Monte Carlo Simulation techniques, and compares these approaches in terms of their treatment of uncertainty variables, their acknowledgement of flexibility, and their usefulness for strategic decision making.
The specific objectives of the research is to determine the profitability of producing Rhodes grass in Najed area, given new fodder crop re-allocation program and new water policy implemented in Najed area. The comparison of new proposed cultivation area to costal area is performed and Risk Premium calculated. Moreover, risk efficient policy and rank alternative risk management strategies are performed to support decision makers for sustainable Rhodes grass farming at new area. The study also determine incentive requirement to compensate risk associated with project location.
Economic feasibility of the investment is evaluated through calculation of the Net Present Value and IRR by using Monte Carlo Simulation models. Our objective is to formulate a dynamic programming simulation model for the investment decision with incorporating risk and uncertainty parameters in a probabilistic manner. To this end, a static, stochastic model was developed to evaluate risk and explore potential risk reducing strategies for farmers, while accounting for the ecological consequences of potential agriculture policies. Worldwide, mathematical modelling has proven to be an effective instrument for increasing the overall understanding of the complexity of water management and determine best combination of risk management strategies for decision makers with alternative preferences for risk aversion and achieve resource-saving alternatives that are both economically and ecologically sustainable.
Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors were found to have unimportant effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end products of the project appraisal such as Internal Rate of Return, Net Present Value, and Benefit Cost Ratios that take forecasting errors into account are feasible decision tools for economic evaluation. The study constructed Monte Carlo Simulation model to perform dynamic stochastic budgeting simulation analysis by using @Risk software that allows the representation of uncertainty as probability distributions.
The sample data generated by Latin hypercube sampling method from Monte Carlo Simulation model has been used to performed stochastic dominance analysis and Stochastic Efficiency with Respect to a Function (SERF) were also used to select the risk-efficient strategies. The analysis shows government investment subsidy reduced risk at new location at Najed but still more support is needed. Minimum Revenue Guarantee, raw material subsidy analysis is performed and could be one of the risk management tool uses in Najed Project.
The study shows dynamic stochastic simulation model are more powerful than deterministic models and could be used to estimate the probability distribution for select key output such as (NPV) and (IRR) of a Rhodes Grass farm production facility in three alternative locations in Oman (Hanfeet, Dawkah and Salalah Plain). The dynamic models used in the study assess the impact of new water policy for each farm location. The study indicates dynamic models are better than conventional analysis and could help policy makers to review water policy to get a sustainable farming in
desert area and achieve positive economic gains and economic sustainability for Najed area. The study also performed SERF analysis and calculate Certainty Equivalents (CE) to rank risky alternatives. Certainty Equivalent value shows the amount of money that the decision maker would have to be paid to be indifferent between the particular scenario and a no risk investment. We also estimated confidence premiums for each alternative and calculate government incentives required for each location. Confidence premium indicates how much a decision maker has to be paid to switch from the preferred strategy (Salalah) location to new area. The results illustrate possible conflicts between risk efficiency and sustainability and risk management strategies, change in water policy with raw material subsidy alternatives could improve risk efficiency and encourage investors to sustain agriculture activates at new developed area at Najed.
MOHAMMED, K (2021). Economic Appraisal Of Fodder Crops Production Under Risk And Uncertainty In Sultanate Of Oman. Afribary. Retrieved from https://tracking.afribary.com/works/economic-appraisal-of-fodder-crops-production-under-risk-and-uncertainty-in-sultanate-of-oman
MOHAMMED, KHEIRY "Economic Appraisal Of Fodder Crops Production Under Risk And Uncertainty In Sultanate Of Oman" Afribary. Afribary, 21 May. 2021, https://tracking.afribary.com/works/economic-appraisal-of-fodder-crops-production-under-risk-and-uncertainty-in-sultanate-of-oman. Accessed 24 Nov. 2024.
MOHAMMED, KHEIRY . "Economic Appraisal Of Fodder Crops Production Under Risk And Uncertainty In Sultanate Of Oman". Afribary, Afribary, 21 May. 2021. Web. 24 Nov. 2024. < https://tracking.afribary.com/works/economic-appraisal-of-fodder-crops-production-under-risk-and-uncertainty-in-sultanate-of-oman >.
MOHAMMED, KHEIRY . "Economic Appraisal Of Fodder Crops Production Under Risk And Uncertainty In Sultanate Of Oman" Afribary (2021). Accessed November 24, 2024. https://tracking.afribary.com/works/economic-appraisal-of-fodder-crops-production-under-risk-and-uncertainty-in-sultanate-of-oman