Uncertainty Scenario: Sale or Keep the Cattle for Oncoming Drought

UNCERTAINTY SCENARIO: TO KEEP OR SELL CATTLE FOR

ONCOMING DROUGHT

I’m using the keeping of cattle for a large scale business-farm relying on natural rain for pasture and water in prospect of the oncoming drought. The drought is due to the usual annual rain failures that cause severe loss between the months of November to February, though if well planned, escaping the loss (cattle deaths) ultimately bring huge profits afterwards. In consideration of the accurate decision making on whether to sell before the drought or risk to keep through the drought, the previous records at the ministry of livestock showed the four months, November, December, January and February having the most miserable period that significantly affect the ranching business enterprise.

The government is intervening to help the entrepreneurs in the sector by issuing drought insurance at a fee of 20% of the total value of the cattle one owns. The government will refund the cattle but not the fee if the drought kills the cattle.

The entrepreneurs have to decide whether to keep the cattle and not worry about the drought, which risks the loss of the cattle, or keep the cattle and spend extra money in purchasing the drought insurance, which affects my financial budget for the cattle upkeep, or sell the cattle before the drought, which can be at a loss, and miss out on huge profits after the drought.

Research

For making the decision in the uncertainty of my ranching enterprise, I researched data set from the National Livestock Statistics and the Ministry of Livestock. I also considered the statistics on climate and weather condition over the past 5 years from the Meteorological Department. The statistics on weather condition changes specified the date and duration of droughts spreading between November and February of each year. Thus, my research for decision making on the uncertainty of the business concentrated on this period. This helped me on forecasting and statistically using the data...