Department of Economics MIT Fall 2019 14.32 Econometrics Class meets in E52-164 TTh 1-2:30 Recitation meets in E51-376 F 2-3 Inst.: Anna Mikusheva TAs: E52-526 Brandon Enriquez [email protected] [email protected] office hours: Wed 2-3 pm office hours: Wed 4-5:30 Assistant: Emily Gallagher Aaron Goodman [email protected] [email protected] office hours: Mon 2:30-4 1. Course Description and Prerequisites: This course introduces students to multiple regression methods for analyzing data in economics and related disciplines. Extensions include regression with discrete random variables, instrumental variables regression, analysis of random experiments and quasi-experiments, and regression with time-series data. The objective of the course is for the student to learn how to conduct – and how to critique – empirical studies in economics and related fields. The only formal prerequisite is 14.30 or the equivalent, but some familiarity with matrix algebra will be helpful. The course is required for majors 14-1 Economics, 14-2 Mathematical Economics and 6-14 Computer Science, Economics and Data Science. It can be counted towards a minor in Statistics. 2. Texts: The textbook is J.H. Stock and M.W. Watson, Introduction to Econometrics, Addison-Wesley. An optional book, which will not be used in class but which provides a complementary treatment that some students might find helpful, is J.M. Wooldridge, Introductory Econometrics, South-Western College Publishing. 3. Requirements: The final course grade will be based on two exams (midterm- 30%, final-40%), empirical project (10%) and graded problem sets (20%). The last problem set has no due date, will not be graded and is intended for your practice only. The students taking undergraduate version (14.32) are responsible for submitting 5 out of 6 problem sets that have a due date. In case they decided to submit all 6, the top 5 scores will be used for the grade. The students taking graduate version (14.320) are responsible for all 6 problem sets with due date. egular attendance at the recitation is strongly recommended, as the T.A.s will discuss problem sets, clarify lecture material, and provide other useful guidance. The Department of Economics values an inclusive environment. If you need a disability accommodation to access this course, please communicate with us early in the semester. If you have your accommodation letter, please meet with the faculty so that we can understand your needs and implement your approved accommodations. If you have not yet been approved for accommodations, please contact Student Disability Services at <[email protected]> to learn about their procedures. We encourage you to do so early in the term to allow sufficient time for implementation of services/accommodations that you may need. 4. Schedule: The schedule is tentative. All changes will be announced in class. Readings: Class # 1 Date/Day Sept. Topic SW Ch. # 5 Th Introduction and review of probability 2 10 Tue Review of statistics 3 3 12 Th Review of statistics 3 4 17 Tue Bivariate regression I 4 5 19 Th Bivariate regression II 5 6 24 Tue Bivariate regression II 5 7 26 Th Multiple regression I 6 1 Tue Multiple regression II 7 9 3 Th Multiple regression III 7 10 8 Tue Nonlinear regression models I 8 11 10 Th Nonlinear regression models II 8 15 Tue Columbus day- holiday 12 17 Th Nonlinear regression models III 8 13 22 Tue Assessing regression studies 14 24 Th Midterm exam 15 29 Tue 16 31 Problem Sets: Posted Due 1,2 PS#1 PS#2 PS#1 PS#3 PS#2 9 PS#4 PS#3 Binary dependent variable I 11 project Th Binary dependent variable II 11 5 Tue Panel Data I 10 18 7 Th Panel Data II 10 19 12 Tue Instrumental variable regression I 12 20 14 Th Instrumental variable regression II 12 21 19 Tue IV regression III and program evaluation I 22 21 Th Program evaluation II 13 23 26 Tue Program evaluation III 13 28 Th No class- Thanksgiving 3 Tue Time series regression I 15 25 5 Th Time series regression II 16 26 10 Tue Time series regression III 16 8 17 24 Oct Nov Dec PS#5 PS#4 PS#6 PS#5 12,13 PS#6 PS#7 project 14.32 Policies 1. Problem sets are designed to help you learn how to apply the material presented in lectures and recitations. You are permitted to discuss course material, including homework, with other students in the class. However, you must turn in your own individual solutions to each homework set. Discussion with others is intended to clarify ideas, concepts, and technical questions, not to derive group homework set solutions. Identical homework set answers (especially when the steps used to derive answers are not shown or when questions of interpretation are involved) violate this policy and may receive no credit. Also, you are expected to complete the problem sets without consulting old problem set solutions. 2. Handwritten solutions are fine, as long as they are legible and neat. Please remember: if we can’t read it, we can’t grade it. Please, attach your log files to show your computer work. 3. In fairness to students who complete assignments on time, late homework sets will not be accepted. You may turn in assignments during the lecture on the day they are due. After the lecture, assignments may be placed in a designated box that will be set out on the third floor of E52 until 5:00 pm. Do not leave assignments in the T.A.’s office or mailbox. You may e-mail your homework to the TAs, but put 14.32 in the subject line. You may also submit your work electronically through Stellar Grade-Module. 4. The empirical project is somewhat similar to the problem sets, but is more open-ended. It contains less guidance and requires one to use knowledge from the course in a real-life application. This project is in the spirit of MIT Lab requirement. All rules about problem sets described above are applicable to the project as well. The description of the project and the data for it will be posted immediately following the mid-term. The sharp deadline for the project is December 5th. 5. Taking both exams is a requirement of the course. Missing an exam without a valid excuse will result in a failing grade for the entire course. 6. To be considered valid, an excuse must be proffered prior to the exam that is to be missed, if at all possible, the excuse must be in writing, and it must be verifiable. These criteria are necessary, not sufficient, however. We reserve the right to deem an excuse meeting the above criteria invalid. 7. An oral make-up exam will be given in the event of a valid excuse. 8. All requests for regrades must be submitted in writing within one week of the exam being handed back. 9. Cheating or academic dishonesty in any form will not be tolerated and will result in swift punitive action. This includes but is not restricted to copying information from other students’ exams, communicating with other students during exams, failing to follow the rules of the exams regarding notes, calculators, etc., altering an exam for the purpose of a regrade, and producing fraudulent written excuses. Any student found to have cheated or to have behaved unethically or dishonestly will be given a grade of F on the exam involved and referred to the appropriate disciplinary committees within MIT for further action.