Will Aviation Biofuels Fly?
@RISK Helps Assess Two Different Government
Policies in Purdue University Study
Developing biofuels for aircraft is a risky endeavor, as transforming plant material into liquid fuel is still very expensive compared to the price of fossil fuels. Dr. Wallace Tyner and his colleagues at Purdue University in Indiana used @RISK to conduct a cost-benefit analysis of building an aviation biofuel plant, and to determine the potential impacts of two different government policies to jump-start this technology: reverse auction and capital subsidy. They found that both policies reduced risk in investment of aviation biofuels, however a reverse-auction policy reduced the risk of this investment more.
Researchers Amanda Bittner, Dr. Wallace Tyner, and Xin Zhao at the Agricultural Economics Department at Purdue University used a discounted cash flow (DCF) model to find the net present value (NPV) of a theoretical aviation biofuel plant. They incorporated four variables that have a large impact on the non-risk adjusted breakeven fuel price: capital cost, feedstock cost, final fuel yield, and hydrogen cost (the price of hydrogen input used in producing biofuels). They created empirical distributions for each variable from literature and/or experts, and then used @RISK to incorporate uncertainty into the variables using a PERT distribution. The researchers created projections to forecast what the fuel prices would be in the future, and what the breakeven biofuel price would have to be in two different situations: one in which the fuel price has no overall trend, and one case in which the fuel price has an increasing trend.
The researchers next wanted to investigate what kind of government policy would be most effective in reducing the risks around investing in aviation biofuels, and at what point in the probability distribution would investment firms be willing to place a bid.
Then, they examined which lowers risk more: reverse auction or capital subsidy. They looked at each under three different contract lengths: 5-year, 10-year, and 15-year, to see how contracts of increasing duration would impact the probability of financial loss for investors. “At those different contract lengths, the numbers are pretty startling,” says Dr. Tyner.
Dr. Tyner uses @RISK for research, as well as for teaching his course in benefit cost analysis.
» Read the full case study
I use [@RISK] to teach all my students
to introduce uncertainty into project
evaluation. It’s been a tool in my
portfolio for a long, long time. You can
do something with much less expense
and much easier with @RISK today
compared to what I painstakingly did
Dr. Wallace Tayner
Professor of Agricultural Economics
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Optimizing Channel Conflicts
Excerpted from Chapter 61 Financial Models Using Simulation and Optimization,
by Wayne Winston, published by Palisade Corporation
An important problem in marketing is how to set prices in different channels in order to maximize a company's profitability. Selling in different channels opens up a vast number of potential sales as it exposes the product to different consumers, however, a company must realize that charging a low price in one channel can and will cannibalize sales in another channel. Download the example model and step-by-step instructions to see how Solver and Evolver are used to determine the demand curves of each channel, and the optimal price for each channel so that profitability is maximized despite the conflict between channels.
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Number of Bins in a Histogram
Q: How does @RISK choose the number of bars when making a histogram? In other words, how many bins or intervals does @RISK divide the data range into? Can I change this?
By default, @RISK determines the number of bins from the number of iterations or data points n, as follows:
|Less than 25|| ||5|
|25 to 100|| ||Nearest integer to n/5|
|More than 100|| ||Largest integer below 10 x log(n)|
If you want to change this for a particular histogram, right-click the graph and select Graph Options. On the Distribution tab, the lower section lets you specify a number of bins (bars), as well as a minimum (left edge of the first bar). "Automatic" uses the calculation shown above, but you can specify a number from 2 to 200.
» View other Techniques and Tips here
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» Will Aviation Biofuels Fly?
@RISK Helps Assess Two
Policies in Purdue U Study
» Licensing Options
» Teaching Tips &
Optimizing Channel Conflicts
» Tech Tip
Number of Bins in a
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