ECON 8080 Introduction to Econometrics Course Syllabus Spring 2010 MW, 930-1045 Sanford 309 INSTRUCTOR Chris Cornwell 534 Brooks Hall [email protected] 706-542-3670 http://www.terry.uga.edu/~cornwl Office hours Friday, 130-330 and by appointment COURSE DESCRIPTION ECON 8080 is our first-year PhD course in econometrics. Its main focus is the specification and estimation of linear regression models, with special attention to estimator properties and hypothesis testing under different statistical assumptions. Ordinary-least-squares, maximum-likelihood and method-of-moments estimators are covered. ECON 8070 is a prerequisite. COURSE OBJECTIVE Students will learn how to specify and estimate linear regression models and test hypotheses about model parameters under different statistical assumptions and understand the small-sample and asymptotic theory underlying each method. COURSE MATERIAL Recommended texts Greene, W., Econometric Analysis, Prentice-Hall, 6e Hayashi, Econometrics, Princeton Wooldridge, J. Econometric Analysis of Cross-section and Panel Data, MIT Press Wooldridge, J., Introductory Econometrics, Thomson, 4e Other useful texts Baltagi, B., Introduction to Econometrics, Springer-Verlag Cameron, C. and P. Trivedi, Microeconometrics Using Stata, Stata Press Davidson, R. and J. MacKinnon, Econometric Theory and Methods, Oxford Goldberger, A., A Course in Econometrics, Harvard Kennedy, P., A Guide To Econometrics, 5e Poirier, D., Intermediate Statistics and Econometrics, MIT Press Ruud, P., Classical Econometric Theory, Oxford PressIn addition, you will be assigned selected from the scholarly literature. See the Course Schedule for details. TOPICAL OUTLINE 1. Statistics review a. Estimation b. Inference 2. Cross-section regression a. Introduction b. Algebra of least squares c. Statistical results of squares d. Units of measurement and functional form e. Dummy variables f. Heteroscedasticity g. Omitted variable bias, measurement error and instrumental variables h. Other data problems 3. Time-series regression a. OLS using time-series data b. Trending series c. Autocorrelation ASSIGNMENTS AND GRADING POLICY Performance will be evaluated on the basis of 3 problem sets and a final exam, weighted as follows: Component Weight problem sets .60 final exam .40 You will be ranked relative to other students in the class according to your overall performance and grades assigned based on your class rank. I will use the plus/minus system to make distinctions within grade categories. Class Attendance Regular class attendance is expected. UGA academic regulations authorize a professor to withdraw students with excessive absences and I will exercise that authority. Also, it will be very difficult to earn credit for class participation if you are not there.Exam Dates & Policies The final exam is scheduled for Monday, May 3 at 800a. Failure to take the final exam at the scheduled time will result in a grade of zero. There are 2 and only 2 exceptions to this rule: (1) if the Office of the Vice-President for Academic Affairs verifies that you have another exam scheduled for the same time or three exams scheduled on the same day, or (2) if you have a documented family emergency or personal illness. In the case of (2), you must resolve the situation as promptly as possible. If you know now that you will not be able to take the final exam at the scheduled time, then you should drop this course. UNIVERSITY HONOR CODE & ACADEMIC HONESTY POLICY As a University of Georgia student, you have agreed to abide by the University’s academic honesty policy, “A Culture of Honesty,” and the Student Honor Code. All academic work must meet the standards described in “A Culture of Honesty” found at: www.uga.edu/honesty. Lack of knowledge of the academic honesty policy is not a reasonable explanation for a violation. Questions related to course assignments and the academic honesty policy should be directed to the instructor. CHANGES TO THE SYLLABUS The syllabus is a general plan for the course; deviations announced to the class by the instructor may be