Economics is the study of choice under scarcity; Statistics is the language of science. Econometrics is a child of Economics and Statistics. This course introduces statistical and regression analysis for economics and finance. It covers probability and statistics theory for linear regressions, descriptive data analysis, and regression models and applications (specification, estimation, inference, and forecast). Students will learn how to combine economics and statistics to perform econometric study. Throughout the course, students are required to solve computer-aid assignments, conduct a research project, and complete two exams. Extra credit will be available for students participating in a special topic debate or an individual project or teaching assistantship.
This course places applied econometrics in the context of Machine Learning, challenges students to develop a "right" way of doing econometrics, and examines the limitations of applied econometrics.
As a coordinated course, the required text is Stock and Watson, Introduction to Econometrics, Package for Baruch College, 3rd Custom Edition, ISBN 13: 978-1-269-90829-0 ©2014 • Pearson. Another highly recommended textbook is Hill, Griffiths, and Lim, Principles of Econometrics, 5th Edition, ISBN 13: 978-1-118-45227-1 ©2018 • Wiley.
Objectives
Understand the fundamental concepts and distribution models in probability and statistics
Master OLS linear regression theory: its assumptions, models, estimation, hypothesis testing, and inference
Interpret regression results, perform robustness check, detect and correct violations of regression assumptions
Develop basic computer skills in data and regression analysis (Excel, Python, or R)
Apply economic theory to direct quantitative research and complete a project
It is important for students to provide feedback in time throughout the course to ensure positive learning and teaching experience. If students have trouble keeping up with the class material or the workload, please feel free to contact the instructor. It is the instructor's responsibility to support students to make progress and succeed in the course. Students are encouraged to 1) raise questions and participate in the lecture; 2) provide feedback and suggestions regarding teaching and course organization; 3) solve the problem sets and conduct research together; 4) improve the learning and teaching process. Special accommodations will be given to students with disabilities.
Last day to withdraw with a "W" grade from courses. April 16, 2018.
Student Tutoring Center at Baruch College