Secretary: Kathleen Madsen, CS3-110M, 585-275-8127
E-Mail: madsenka@simon.rochester.edu
You have to compete with other managers, some of whom have a lot of experience, others are well trained, etc. Your advantage as a Simon School graduate is that you approach business decision-making from the standpoint of getting the analysis right. When you make a decision, you ask yourself: What is the logic of the situation? What does it tell me are the relevant facts to focus on? Do I have this information or where can I get it? What is the reliability of the information I have or can acquire? The skills you learned in GBA 412, and that will be further developed in APS 425, are an integral part of the set of tools you will come to rely on to succeed in a competitive business environment.
Also, determining the right decision is only the beginning of a process. A sound factual basis for the decision is a major component of getting it implemented, but the effectiveness of this will be much enhanced if it is communicated well. Thus, one other facet of the class is the effective communication of your argument in favor of a decision. Therefore, in class discussions, assignments, exams, and on the project, there will be a premium for avoidance of unnecessary terminology and effective managerial-style presentation.
One warning -- statistical analysis is no substitute for thinking. It can help to clarify, to sort out which of a number of plausible arguments best fits the facts, and so on. But it cannot tell you what the relevant things to think about are, or obviate the need for experience and good judgment.
Moreover, it is not the kind of material that one learns by listening and reading. It is like riding a bicycle -- everyone can do it, but there is no substitute for getting on the bike as a way to do so. This is why there are a lot of assignments, a serious project, etc.
APS 425 is a lot of work and very cumulative. This is the wrong course to get behind in. This is going to be a hard course, but the reason for this is that you are going to learn a lot. There is little point to coming to the School for years and not leaving a lot different than you arrived!
At the same time I can assure you that there is nothing really deep in this course. It is a course that responds well to effort.
It is a good idea to keep this in mind because about two thirds of the way through the class a lot of you will be feeling pretty anxious. We will have covered a lot of ground, and by that stage it will not have “come together.” But I can tell you that if you keep at it, once you have cranked through the assignments and done your project, it will come together.
To reiterate, this is a hard course, but it is material that is worth learning, and you will learn it if you try.
There will be several homework assignments that are group responsibilities. Homework grades will count 20% of your final grade. Also, there will be a major project due on the last day of your class (3/11/2008) that is also a group assignment worth 20% of your course grade. The project report should be less than 2,000 words (about 10 double-spaced pages) describing your analysis of an interesting dataset. You may include well-documented tables and figures as appendices as long as they are referred to in the report. The report should be written as if you were giving it to your boss (who took a regression course many years ago, but does not use it in his everyday work). Thus, you should not rely on statistical jargon to explain your analysis, but you should also not spend time explaining regression to him (i.e., me). You should start early in the quarter to plan and begin work on your project - last minute efforts are likely to produce poor results.
On the last day of class (3/11/2008), each group will turn in their grade-allocation sheet containing:
Damodar Gujarati, Basic Econometrics, 4th edition, 2003, McGraw-Hill, ISBN 0-07-247852-7 (henceforth DG)
The recommended text for this course is:
Francis X. Diebold, Elements of Forecasting, 4th ed., 2007, Southwestern, ISBN 0-324-32359-X (henceforth FD).
I will generally not lecture from these books. Rather, I think of them as references. In addition, the Eviews Users Guide (henceforth EV) contains some useful discussion that relates the topics we will discuss in class to the options available in Eviews.
DG, Chap. 7, Chap. 8 (pp. 248-265).
DG, Chap. 6.2-6.8 (pp. 169-190), Chap. 8.11.
[Wine price data; temporary assistance data]
DG, Chap. 10 (pp. 341-356), Chap. 9 (pp. 297-319), Chap. 13 (pp. 507-523).
EV, Chap. 15, pp. 165-168; Chap. 13, pp. 295-314, 320-326 (some techniques that are beyond the scope of this course).
[Golf performance data]
EV, Chap. 12, pp. 271-274; Chap. 15, pp. 362-363.
DG, Chap. 15 (pp. 580-594). Skim pp. 595-615.
EV, Chap. 17, pp. 405-422 (techniques that are beyond the scope of this course).
[Epidural data]
FD, Chapter 4.
*Nelson, Charles R. and H. Kang, "Pitfalls in the Use of Time as an Explanatory Variable in Regression," Journal of Business and Economic Statistics, 2 (1984) 73-82.
Cowden, Dudley J., "The Perils of Polynomials", Management
Science, (July 1963) 542-550.
B. Seasonality
FD, Chap. 5, review Chap. 9.
FD, Chap. 7, 6, 8.
*Nelson, Charles R., "The Interpretation of R2 in Autoregressive-Moving Average Time Series Models," The American Statistician, 30 (1976) 175-180.
FD, Chap. 12.
Nelson, Charles R. and Charles I. Plosser, "Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications," Journal of Monetary Economics, 10 (1982) 139-162.
Plosser, Charles R. and G. William Schwert, "Estimation of a Noninvertible Moving Average Process: The Case of Overdifferencing", Journal of Econometrics, (September 1977) 199-224.
Schwert, G. William, "Effects of Model Specification on Tests for Unit Roots in Macroeconomic Data," Journal of Monetary Economics, 20 (1987) 73-103.
FD, Chap. 11.3, 10.6-10.9.
*Nelson, Charles R. and G. William Schwert, "On Testing the Hypothesis That the Real Rate of Interest Is Constant," American Economic Review, 67 (1977) 478-486.
Fama, Eugene F., "Short Term Interest Rates as Predictors of Inflation", American Economic Review, (June 1975) 269-282.
Plosser, Charles I. and G. William Schwert, "Money, Income and Sunspots: Measuring Economic Relationships and the Effects of Differencing," Journal of Monetary Economics, 4 (1978) 637-660.
Engle, Robert F. and C. W. J. Granger, "Co-Integration and Error Correction: Representation, Estimation, and Testing," Econometrica, 55 (1987) 251-276.
[Stock price and inflation data]
Schwert, G. William, "Why Does Stock Market Volatility Change Over Time?" Journal of Finance, 44 (December 1989) 1115-1153.
French, Kenneth R., G. William Schwert, and Robert F. Stambaugh, "Expected
Stock Returns and Volatility," Journal of Financial Economics, 19
(September 1987) 3-29.
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