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Assignment -

You recently joined Magna Enterprise, a commercial real estate developer, and have been given a position working directly for Evelyn Kemme, Magna's CEO. When you meet Evelyn for the first time, she gives you a project she wants you to complete by the end of the week.

Evelyn explains that Magna is thinking about leasing a parcel of land to build a shopping center. Magna would own and operate the shopping center and generate revenue by renting space to retailers. Evelyn would like you do some work on the project. Specifically, she would like you to complete the following tasks.

1. Determine the optimal size of the shopping center (to the nearest 100 square meters) based on existing estimates of the demand for retail space.

2. Determine the most Magna should be willing to pay to lease the land for the expected life of the project.

3. Calculate the profit under each possible demand curve with the optimum size of the shopping center.

4. Determine if it is worth hiring a local consultant, David Smith, to do some additional market research that would provide a better estimate of the demand for retail space.

5. Write a short report summarizing the results of your analysis and any recommendations.

Evelyn tells you that Martin Bernetson, a former Magna employee, did some preliminary work on the project, but left the organization before wrapping things up. Evelyn says that you should have complete confidence in any work Martin did on the project and that you should use his findings and assumptions as a starting point for your analysis. In fact, Evelyn has reviewed Martin's notes and quickly summarizes the key information she thinks you'll need for your analysis.

Specifically, she tells you that:

  • Martin thought the shopping center would take one year to build and would last 20 years. He estimated that it would cost $100 per square meter to build and that the annual operations and maintenance costs would be $1 per square meter of floor space.
  • Martin thought that the parcel of land would be large enough to build a shopping center with as much as 60,000 square meters of retail space. He also thought that Magna should make a onetime upfront payment to lease the parcel of land for the expected 20-year life of the project.
  • Martin thought the amount retailers in the shopping center would be willing to pay per square meter of floor space would be a decreasing function of the total size of the shopping center. Martin did some initial work estimating the likely relationship between what tenants would be willing to pay for retail space and the size of the shopping center. Specifically, he thought there was a 50% chance the true relationship would be: r = 60 - 0.001s and a 50% chance that the true relationship would be r = 50 - 0.001s, where r is the rental rate per square meter of floor space and s is the total size of the shopping center in square meters. Furthermore, Martin was going to assume that once the shopping center had been built, the realized relationship between r and s would remain unchanged for the next 20 years.
  • Martin was planning to ignore discount rates and the time value of money in his initial evaluation of the project. He was going to treat all of the project's costs and benefits equally no matter when they occurred in the life of the project; that is, he was going to treat a$1 cost incurred (or revenue received) at the start of the project the same as a $1 cost incurred (or revenue received) during any other year of the project's life. At this point, you tell Evelyn that doing this could lead to misleading conclusions about the real value of the project and how much Magna should be willing to pay to lease the land. Evelyn agrees, but says she thinks this approach is good enough for a preliminary evaluation. (HINT: Do not try to account for the time value of money in your analysis. Simply treat all costs incurred [or revenues received] as equivalent no matter when they occur. Doing so means you can calculate the total costs over the life of the project by simply summing the costs incurred in each year. Similarly, you can calculate the total revenues received over the life of the project by simply summing the revenues received in each year.)
  • Martin had contacted a local consultant, David Smith, who could do some additional market research to accurately forecast which of the demand curves (i.e., r = 60 - 0.001s or r = 50 - 0.001s) would actually be realized if the shopping center was built. Martin was trying to find out if it was worth hiring David at all, and if he could be hired then what was the maximum consulting fee that Magna should offer. (HINT: In the first scenario, if Magna were to hire David, Magna would build a shopping center that is sized optimally for the demand curve that David identifies in his report. For example, if David's report says that the demand curve will be r = 60 -0.001s then Magna will build a shopping center that is optimally sized for that demand curve. Similarly, if David's report says that the demand curve will be r = 50 - 0.001s, then Magna will build a shopping center that is optimally sized for that demand curve. Nonetheless, a decision to hire David does not affect the fact that there is still a 50% chance that the demand will actually turn out to be r = 60 - 0.001s and a 50% chance that the demand curve will actually turn out to be r = 50 - 0.001s)

After briefing you on Martin's findings, Evelyn wishes you luck and says she looks forward to reading your report in a week's time. She tells you that the main body of the report must be short (i.e., 1000words at most excluding the title page, table of contents and any appendices), to the point, and not overly technical. Nevertheless, your conclusions and recommendations must be based on a rigorous analysis of the available information and you should provide a concise summary of any technical details in an appendix. Evelyn also tells you to be explicit about any important limitations your analysis might have. Finally, Evelyn tells you that she likes her reports to be broken up into sections with sensible and self-explanatory headings.

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