ECON 7818-001 Econometrics I
ECON 7818 Syllabus Graduate Econometrics Seminar Fall 2002 Professor: Jose J. Canals-Cerda. Office: Econ 103 Phone/Voicemail: 303-492-7869 E-mail: [email protected] Class meets on Tuesday and Thursday 12:30 p.m. to 1:45 p.m. Classroom: Econ 11 7 (The information in this syllabus is subject to change). Course Objectives. The course is designed as a rigorous introduction to advanced statistics and econometrics. Additional Information. Please send me a brief email message containing your name and with the subject "ECON7818 Student". Be aware that most of the course announcements will be done using e-mail. Therefore, it is important that you send this email to me as soon as possible. How to contact me. Office Hours: My office hours are Tuesdays and Thursays from 11 :00 a.m. to 12:00 p.m. I will be in my office Tuesdays and Thursays most of the day, you can talk to me these days at any time if I am available. At any other time, it is best if you make an appointment (by e-mail or phone). Students with Disabilities. This University abides by Section 504 of the Rehabilitation Act of 1973, which stipulates that no student shall be denied the benefits of an education "solely by reason of a handicap." Disabilities covered by law include but are not limited to learning disabilities and hearing, sight or mobility impairments. If you have specific physical, psychiatric, or learning disabilities and require accommodations, please let me know early in the semester so that your learning needs may be appropriately met. You will need to provide documentation of your disability to the Disability Services Office in Willard 322 (phone 303-492-8671). The course paper. · One of the requirements of this class is a paper. The course paper will replicate published research. This work will require the use of statistical or econometrics computer packages. You are not required to use a specific package. You can access computer packages like LIMDEP, GAUSS or SAS. You can buy some of this products and additional ones, like STATA or SAS, from the University at a reasonable student price. During the semester we will spend some time teaching SAS. You should plan to get started on your paper as soon as possible. You may be required to present the paper in class. The quality of your presentation will be an important determinant of your grade, this applies also to the programs. The final draft of the paper will consist of an introduction describing and motivating the interest of the paper in a simple way, as well as a road map with a short description of the different sections of your paper. The paper should have a section describing the data, a section describing the econometric methodology, a section with results and a final section presenting the conclusions. If necessary, the paper may include one or several appendixes. In particular, the programs used for the statistical work should be included in an appendix. Quizes and Exams. There will be several quizes administered during the semester and one final exam. I will also provide you with problem sets but they will not be graded. I encourage you to work in groups. Grading. The grade for this class is based on your performance in quizes, a final exam, the research proposal and the research paper. Quizes: 20% Final Exam: 50% Research Paper: 25% Texts and Other Materials. Recommended books: Rice, John A. : "Mathematical Statistics and Data Analysis." Wadsworth & Brooks/Cole Advanced Books & Software Pacific Grove, California. Amemiya, Takeshi (1994): "Introduction to Statistics and Econometrics." Harvard University Press. Cody and Smith: "Applied Statistics and the SAS Programming Language." Prentice Hall Ed. (4th edition). (This is a book for learning sas). Course Outline. What follows represent a tentative list of subjects to be covered in class. Introduction to Regression analysis. Introduction to regression analysis. Omitted variables. Endogeneity. Linear probability model. Probability Theory. Introduction. Axioms of Probability. Conditional Probability and Independence. Random variables and probability distributions. Definitions. Discrete Random Variables. Continuous Random Variables. Distribution Function. Change of Variables. Normal Random Distribution. Moments. Expected Value. Higher Moments. The Moment Generating Function. Covariance and Correlation. Conditional Mean and Variance. Large sample theory Modes of convergence. Laws of Large Numbers and Central Limit Theorems. Point Estimation Introduction. Properties of Estimators. Least Squares Estimators. Maximum Likelihood Estimation and Method of moments estimation. Introduction. Properties of Maximum Likelihood and Method of Moments Estimation. Interval Estimation and Test of Hypothesis. Introduction. Confidence Intervals. Test of Hypothesis. Constrained Least Squares Estimators. Test of Hypothesis in the Linear Regression Framework. Advanced econometric models. Generalized Least Square. Nonlinear Regression model. Qualitative Response Models.