HARVARD UNIVERSITY ECON S - 1123: Introduction to Econometrics Preliminary Syllabus and Course Outline (Summer 2007) Instructors: Daniela Kolusheva¸ Can Erbil Email: danielak@brandeis.edu, cerbil@brandeis.edu Office hours: TBA Course web site: TBA Location and time: TBA Course Description and Objectives The objective of the course is to teach students how to use econometric methods to quantify economic relations. In addition to providing the basic tools to do your own empirical analysis, ECON S 1123 will help you to become a more sophisticated consumer of economic and financial research done by others. The emphasis will be on applying econometrics to real-world problems. We will start with some probability basics: random variables, probability distributions, estimation, hypothesis testing and confidence intervals in the simplest bivariate models. We will then extend our analysis to the multivariate paradigm and enrich it with nonlinear regression functions, dummy variables and interaction terms. Then we will introduce regressions with a binary dependent variable and use MLE to estimate probit and logit models. In the second half of the course we will cover some panel data methods (fixed effects) and instrumental variables (applications in dealing with measurement error, simultaneity and omitted variable bias; as well as what valid instruments are). The course will conclude with an overview of time series (forecasting, stationarity and non-stationarity, dynamic causal effects). Prerequisites: Pass proficiency examination, Statistics 100 Required Textbook and Software: Stock and Watson, Introduction to Econometrics Addison-Wesley, 2nd edition. For empirical exercises we will use STATA (available on the FAS server). Evaluation: weekly problem sets (25%); midterm (30%) and a comprehensive final exam (45%) Problem sets will be assigned each week and will be due at the beginning of class. Late submissions will receive only partial credit. The assignments are designed to help you explore the issues introduced in the lectures. They are crucial to understanding and digesting the course material. You will have to use an econometric software package in order to complete them. Students are encouraged to work in small groups on their problem sets, but each student must write his or her answers separately. Both exams are closed- book. HARVARD UNIVERSITY ECON S - 1123: Introduction to Econometrics Course Outline: Week 1: Introduction, syllabus overview; review of probability and statistics (SW Chap 2, 3) Week 2: Bivariate (SW Chap 4, 5) and multivariate regression models (SW Chap 6) Week 3: Multivariate regression models – hypothesis testing, nonlinearities, dummy variables, interaction terms (SW Chap 7, 8, 9) Week 4: Regressions with binary dependent variables, introduction to MLE in the context of probit and logit models (SW Chap 11); Midterm Exam Week 5: Panel data (SW Chap 10) Week 6: Instrumental variables regression (SW Chap 12) Week 7: Intro to time series, AR and ADL processes, stationarity/non-stationarity, basic forecasting, dynamic causal effects (SW Chap 14, 15)