Pols 603-600: Spring 2003 Quantitative Political Analysis II
B. Dan Wood		Time: 7:00-10:50 p.m. Tuesday
Office: 2098 Bush Academic Building		Room: 2064 Bush Academic Building
Phone: 845-1610		Office Hours: 4:10-4:30 p.m Tuesday

Purpose- This course provides a more advanced treatment of statistical methods for evaluating social science phenomena. The major topics to be discussed include probability and distribution theory, statistical inference and hypothesis testing, the General Linear Regression Model, the Restricted General Linear Regression Model, analysis of covariance, heteroskedasticity and autocorrelation, stochastic regressors, simultaneous equations and other disturbance related regressions, multicollinearity, limited dependent variables, and selected time series topics. The emphasis will be on both statistical theory and application.

Course Grade- The final grade will be based on four components. Weekly homework assignments will count one fourth of the grade. Homework must be handed in on time or no credit will be given. A midsemester and end of semester examination will each count one fourth of the grade. The examinations will test your skill in doing and understanding statistical methods. The remaining one fourth will be based on an empirical paper which utilizes one or more of the methods taught in this course. You should discuss with me the paper topic sometime before the midsemester examination. The paper is due on the last class day before the final examination.

Prerequisites- Prior to entering the course you should have reviewed the basic principles of probability, and also gained some background in basic linear algebra and calculus. Good sources for these materials are the following.

Recommended texts-

Dowling, Edward T. 2001. Introduction to Mathematical Economics, Third Edition. New York: McGraw-Hill. (see especially chapters 1 through 12, 14 and 15)

Spiegel, Murray, John Schiller, and R. Alu Srinivasan. 2000. Probability and Statistics. Second Edition. New York: McGraw-Hill. (see especially chapters 1 through 7)

Required texts-
Greene, William H. 2003. Econometric Analysis, Fifth Edition. New York: Prentice-Hall.
Kennedy, Peter. 2003. A Guide to Econometrics. Cambridge, Ma: MIT Press.

Topics, Readings, and Materials

Following is the order of the subjects taught in this course. Note that there are only 12 headings, which implies that some may be given multiple week treatments, while others may receive less than a week. I do not attach dates to allow flexibility in timing.

1. Introduction to Statistical Models- Greene, chapter 1; Kennedy, chapter 1; DO: Fundamentals of LIMDEP. Click to download Example.dat. Click here for Assignment 1.

2. Mathematics for Statistical Analysis- Greene, Appendix A. DO: Handout problems and computer Assignment 2.

3. Probability and Distribution Theory- Greene, Appendix B; Kennedy, Appendix A, B, and C. Do: Handout problems. Explore the probability distribution spreadsheets that comprise computer Assignment 3.

4. Statistical Inference, Estimation, and Hypothesis Testing- Greene, Appendix C and D; Kennedy, chapter 2. Do: Handout problems and computer Assignment 4.

5. The General Linear Statistical Model- Greene, chapters 2, 3, 4, and 5; Kennedy, chapter 3. Do: Greene, Chapter 3, Questions 4, 5, 10, 11, 12, 13 and Chapter 4, Questions 7 and 11 and computer Assignment 5.

6. Hypothesis Tests with the General Linear Statistical Model- Greene, chapters 6, 7, 8; Kennedy, chapter 4. Do: Greene, Chapter 6, Questions 1 and 9, Chapter 7, Question 7, and Chapter 8, Questions 3 and 4 and computer Assignment 6 .

7. Violating the Assumptions of the General Linear Statistical Model, misspecification and non-linear models- Greene, chapters 7, 8, 9; Kennedy, chapters 6, 7, and 14. Exam week. No homework.

8. Violating the Assumptions, multicollinearity, missing observations, influential observations, and measurement error- Greene, chapters 4.9, 5.6; Kennedy, chapters 9, 11, and 20. Recuperation week. Do computer Assignment 7.

9. Violating the Assumptions, heteroskedasticity and autocorrelation- Greene, chapters 10, 11, 12; Kennedy, chapter 8. Do: Greene, Chapter 11, Question 5 and Chapter 12, Questions 3 and 5 and computer Assignment 8 and Assignment 9.

10. Models with Discrete Dependent Variables- Greene, chapter 21; Kennedy, chapter 15. No written assignments after this date to work on papers. Do computer assignments Assignment 10 and Assignment 11.

11. Violating the Assumptions, stochastic regressors and simultaneity- Greene, chapter 15; Kennedy, chapters 9 and 10.

12. Time Series Topics- Greene, chapter 19, 20; Kennedy, chapters 9.4, 10.5, 17.