2.1 Net Return
The evaluation of dairy cow farming profitability depends on estimation income generated from raw milk and other products sales and cost values of feed and other expenses. The net return of this business is calculated with uncertain outcome and cost given the stochastic yields, price and variable cost. The probability range of net return with relative preference and utilities of decision makers are considered to calculate economic evaluation of different feeding strategies. The proposal of market access promotion on milk production and income sustainability is tested.
Six stochastic simulation models were used to incorporate risk of uncertain variable in the model and reduce all possible risky alternatives to small number of alternatives. The Net Return for each model is calculated by identifying key parameters and variables and subtracting the variable and fixed cost from the revenue.
2.2 Monte Carlo Simulation
Monte Carlo simulation model is designed to evaluate the variability or stochastic of input variables in the model. It can be used to study the effects of key variables on the Net Return of a given proposal. The process involves identification and assessment of the key variables. For each key variable, we fit a probability density function that best describes the range of uncertainty around the expected value.
The model including variables is calculated using randomly generated input values taken from the underlying probabilistic distribution function. The computer model combines these inputs to generate an estimated outcome value for (NR) and process is repeated (ten thousand times). Monte Carlo simulation model is used to evaluate goat farming systems risk efficiency and sustainability in Oman, Kheiry (2016). The study used @Risk 8.0 from (Palisade Corporation, Ithaca, New York) and Simetar Program to calculate the stochastic nature of key variables in the simulation model. The first scenario represents present livestock farmers situation with informal marketing channels and current feeding cost (Rhodes Grass and concentrate) and low milk production level. The local Dhofari cow breed average milk yield is 6.9 Liter, The State of Animal Genetic Resources in Oman (2014). The main parameters and feeding cost used in six models are presented in Table (1). The second scenarios models represent Government market promotion support and Alfalfa forage crop feed ratio. Six models parameters presented in Table (2).
Table (1) : Dairy cow low feeding strategies and milk production with informal market promotion :
Variable | Formal Market Access Promotion | Informal Market Access Situation |
| LF20 (1) | LF15 (2) | LF12 (3) | LF10 (4) | LF8 (5) | LF6 (6) |
Milk Production Litr | 20 | 15 | 12 | 10 | 8 | 6 |
Alfalfa/kg | - | - | - | - | - | - |
Rhodes Hay/kg | 5 | 5 | 5 | 8 | 6 | 7.5 |
Maize Silage/kg | 5 | 3 | 3 | - | - | - |
Concentrate/kg | 5.67 | 5.60 | 5.94 | 3.03 | 3.32 | 4.87 |
Feeding Cost RO | 1.489 | 1.364 | 1.406 | 1.160 | 1.000 | 1.341 |
Table (2) : Dairy cow high feeding strategies and milk production with formal marketing promotion :
Variable | Maize Silage and Rhodes Grass Forage | Alfalfa and Rhodes Grass Forage |
| LF20 (1) | LF15 (2) | LF12 (3) | HF20 (4) | HF15 (5) | HF12 (6) |
Milk Production Litr | 20 | 15 | 12 | 20 | 15 | 12 |
Alfalfa/kg | - | - | - | 3 | 1 | 1 |
Rhodes Hay/kg | 5 | 5 | 5 | 6 | 6 | 6 |
Maize Silage/kg | 5 | 3 | 3 | - | - | - |
Concentrate/kg | 5.67 | 5.60 | 5.94 | 3.58 | 4.78 | 4.95 |
Feeding Cost RO | 1.489 | 1.364 | 1.406 | 1.501 | 1.340 | 1.360 |
2.3 Data collection
Data collected to perform dairy cow stochastic budget analysis for alternatives feeding risk management strategies. The operational data for each group performance parameters such as milk yield, feeding cost and other expenses for each model were collected from Dhofar Cattle Feed enterprise dairy farm data record and livestock farmers survey. Following Salim Bahashwan et al. (2017), (2018) and Shaver (2013), the data was supplemented with information from the literature and expert knowledge at MAF. Economic budget data and forage nutrient content data are collected and used to form alternative feed strategy models.
The modeling process began by defining dairy cow feed risk management strategies and inputs parameters effecting business income and net return. The other operational cost such as AI, vaccination and medicine cost, labour cost, deprecation, finance cost and utility cost were obtained and recorded for each model.
Market information such as raw milk price and other income revenue, milk production level, payment method and other marketing cost for each model were collected from market. The study used Monte Carlo Simulation analysis to identified stochastic variables to be incorporated in the model such as yields, input cost, and output prices. The study also identified the probability distributions of the risky uncertain input variables and normal distribution is used to estimate Cumulative Distribution Function (CDF) of the output (NR) for each model.
The study also performed Stochastic Efficiency with Respect to a Function (SERF) analysis to evaluate different dairy cow feed strategies and generates Certainty Equivalent (CEs) to rank alternatives according to risk-efficient within different risk aversion level. The Certainty Equivalent (CEs) value used to calculate risk premium need to be paid to livestock farmers for policy evaluation.
2.4 Model Structure
The stochastic budgeting model structure in this study aim to understand the two main points. The first scenario models represent dairy cow feeding strategy in term of feed cost risks management strategy and it is effect on margin risk. The qualitative risk analysis is used to provide a high level of understanding of each cow feeding risk management strategies. The scenario models represent the effect of introduction and organizing formal marketing channels to the area through building Milk Collection Centers and government raw milk price support which announced recently by Regional Government.
The models in the first scenario are named by forage quality and milk yield obtained for each group (LF20 = Low forage quality 20 Liters/day). The dairy cow milk yield 20 liters, 15 liters and 12 liters per day are considered to represent yield can be obtain with new formal market channels facilities, whereas dairy cow yield of 10 liters, 8 liters and 6 liters per day represent present milk production level within informal market channels.
The second scenario models represent the effect of introduction of new Alfalfa forage crop which introduced recently to the area as high forage quality crop in comparison with Maize Silage and Rhodes Grass forage crop which has been used as a main source of energy and protein in the area since long time. The study investigate economic sustainability for Government policies announced recently to support livestock farmers income and improve dairy business bottom line and mitigate margin risk. The models in the second scenario are named by forge quality and milk yield obtained for each group (HF20 = high forage quality 20 Liters/day), (HF15 = High forage quality 15 Liters/day). The high forage quality models represent Alfalfa crop, Rhodes Grass hay and concentrate. Whereas, low forage quality models represent Maize Silage, Rhodes Grass hay and concentrate.
The simulation model is presented below :
N˜R = (˜Ya* ˜Pa + Yb* ˜Pb + ….) – FC − V˜C
Where :
N˜R Probability distribution for net return.
˜Ya Stochastic yield for raw milk yield.
˜Pa Stochastic raw milk price.
Yb number of bulls sold as meat.
˜Pb Stochastic price for meat.
FC Fixed operation cost (Labour, medicine, housing, depreciation, interest, ..…)
V˜C Stochastic operation variable cost (forage crop alfalfa, maize silage and Rhodes grass hay, concentrate ,…. ).
2.5 Stochastic Efficiency with Respect to a Function (SERF)
Simulation model is used to investigate dairy cow feeding alternatives strategies, and formal marketing channels supports policy introduced by Government and Dhofar Region. The risk management failure could be measured in financial terms of getting a negative Net Return (Hansen and Jones, 1996).
A stochastic efficiency model performed to compare the Net Return for two scenarios and six models for each scenario. Stochastic efficiency with respect to a function (SERF) is used to rank the risky alternatives simultaneously with different risk aversion preferences. Risk Premium is also calculated by subtracting CE Certainty equivalent for less preferred dairy cow feeding alternative from dominant alternative. Given a utility function u(0), a random wealth variable X, and an initial level of wealth w0, the certainty equivalent equation used in the models is :
CE = u − 1{E[u(X + w0)]} − w0,
The risk premium measure the minimum amount of money needs to be paid to decision maker to justify a switch from present feed management strategy to other less risky alternative. The model simulated the costs and returns for keeping and maintaining dairy cow under different feed strategy. The Net Return is calculated and probability distributions generated by the simulation model. The model used to rank the best alternative policy across a full range of RACs. The study finally performed CE analysis to estimate premium price should be given to livestock farmers to keep their dairy cow business at a less risky farming system and utilize farm resources in a sustainable manner.