BU5562: Empirical Methods in Energy Economics – Tornado chart for Oil Price – Economic Assessment Help

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Subject Code: BU5562

Economic Assessment Help

After initial exploration and appraisal, a major oil company has estimated the reserves in a new oil field which it plans to develop as 100 million barrels. The oil company plans to develop this field over the next five years (starting 2019) with production starting in 2024 and decommissioning of the field expected in 2040.

The government of the country in which the oil field is being developed is currently charging a Resource Rent Tax with a threshold IRR of 20% and a tax rate of 50% In the Excel file BU5562-oilfield-data.xlsx (available on the MyAberdeen) you will
find information and assumptions about the development of the hypothetical field. In the appendix below is further information on the data in the excel file.

Assignment Task
a) Using the information in BU5562-oilfield-data.xlsx, construct a Spreadsheet model to obtain the Pre and Post Tax NPV, Government Tax plus any other metrics you think useful associated with the development of the oil field for the resource rent tax regime. You should undertake this part of the task under the assumption all input values are known with certainty. Specifically, you should assume that the oil price is known and will grow at 3% per year for the duration of the project.
b) Construct a Tornado chart for Oil Price, Total Field Production, Development Expenditure per barrel, and Abandonment Cost per barrel.
c) Undertake a Monte Carlo Simulation Analysis on the Oil Price. (You must undertake this analysis explicitly by adapting your spreadsheet model following the Computer workshops, i.e. you must not use any Excel Add-Ins that may automate the Simulation.) As you are very concerned about the oil price modeling specifications, in particular about the effect of different
distributional assumptions, use the following three models: (1) a simple log- normally distributed oil price. (2) an oil price random walk. (3) an oil price random walk plus a long-term cycle. Include all three modeling assumptions in your report in order to illustrate how this affects your analysis. Try to make sure that the simulated oil prices, on average, take the same value.

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