Final assignment (group)

Do this project in groups of 2 people (or if necessary I'll allow one group of three people). There are two deliverable: a short paper and a class presentation. The content is flexible, I'll suggest some ideas at the end--but they are only suggestions. You can pick your own.

  1. Class presentation (last two days of class): You and your partner should give a 10-15 minute in-class presentation of your results. It isn't necessary for each of you to talk, but feel free to do it that way if you like.

    1. You MUST have a one page handout. It is always important to send your audience home with something that has your name on it (and in the real world you should also provide contact information. Otherwise, how can they hire you to consult?)

    2. You may use overheads, chalk, power point or even JMP. But since we don't want to see how you run your numbers, JMP would only be useful for "brushing" or other interactive statistics.

    3. Your primary audience is your fellow students, not me. Putting them to sleep isn't nice!

  2. Write-up: The write-up is due before the end of classes. It might be useful to do the write-up first and give me a copy. (I'm willing to even look over rough drafts or outlines.) If you do that, I will email you your comments (if you provide me with an email address of one of your group members) so you will have a chance to fix things before the presentation. Assume it will take me 48 hours to read and comment.

    1. Think of this as the usual discussion from previous homeworks.

    2. Keep it short! Aim for 2 pages of text and a maximum of 5 pages of appendix. The idea is that the text should carry the primary economic story. It should have graphs that are important to the primary message. For example, you wouldn't put a histogram of the residuals in the main text--instead put it in the appendix. The appendix can include other graphs that support your story. You don't have to have an appendix if don't need one.

    3. Put captions on your figures. Make your figures simple and clear.

    4. If you turn in early, I'll allow a revision as I have on earlier homeworks. If you turn in on the last day of classes, your document is final. I won't force any resubmits. So turning early will not be held against you.

Project ideas

The following is a list of project ideas. It is more of a starting point for discussion with your partner rather than a complete list of possibilities. The basic idea is that you should find some data that is similar to something discussed in class and present it. By similar, I mean statisticially similar rather than substantially similar.

The focus should be on what we learn from the data (namely what interesting economic fact did we learn from the data) and not on the statistical methodology.

  1. Learning curve example: Find data on computer chip manufacturing. You need both the price and the total amount produced. You should take a quick look at Ray Kurzweil's new book. You will need to learn enough about chip manufacturing to understand the process and describe what might have been learned.

  2. Production function: Find data on the number of lines of computer code written by a group of programmers. As you add programmers, their efficiency goes down--so you should find a classic diminishing marginal return to programmer. If you can also find out information on number of managers, you can have two terms in your production function.

  3. Ponzironi data: Look at some successful scheme--be it a mutual fund, a hedge fund, a trading method based on the past 200 day rolling average, or a particular trader (say turtletrader.com). Come to a decision as to whether true excess returns are generated or not. (You will need to read a prospectus or other information to determine what a disaster would be. You will need to think hard about how much search you (and others) did to find this scheme.)

  4. Ponzironi simulation: Look at real instruments (puts, calls, small high volatility stocks, etc) available to say a mutual fund or to a hedge fund. Find a way of converting these instruments into a bet in which you mostly win a little bit, and sometimes lose a lot. If you can find historical data on your instrument, run a "look back" analysis of how well your fund would have performed over the past years. (Say 10/20 years for a mutual fund and 1-5 years for a hedge fund.)

  5. Time series (evaluations): Find some historical predictions (say from the Economist which often puts forecasts on its last page) of a macro-economic variable (say GNP, interest rates, unemployment, etc). Collect 10-20 years of data. Now you have both a forecast and the actual result and so can compute a RMSE. Try a VERY simple model and compute its RMSE. How do the experts do compared to this simple model?

  6. Time series (forecasting): Decide on some macro-economic variable to predict (say interest rates, unemployment, GNP, etc). Think of at least 2 other variables that might be significant drivers of your variable of interest. Build a model on data from 1980-1989 using your variables. DO NOT look at the data from 1990-2000. After you have a model that you are happy with generate predictions for 1990-2000. Compute your RMSE on these 10 years of data. Did you over fit?
  7. Marketing: Find some data relating advertising (or other promotion) to sales. For example, Wharton has scanner data from grocery stores available from WRDS.