Econ 107 Winter 22 - ... PDF

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ECON 107 Introductory Econometrics UC Riverside, Winter 2022 : Instructor: Riyad Abubaker, Ph.D. Class Times/Location: MW: 05:00 – 06:20 PM Material Science and Engineering, Room 104 E-mail: [email protected] or [email protected] Office Hours/Location: MW 12pm to 1:30 pm or by appointment.

Sproul Hall # 3121 Phone: 951-758-3857 Course Webpage: Blackboard (https://ilearn.ucr.edu) .

Course materials includes (but not limited to): - Textbook - PowerPoint slides - Additional assigned readings Required Textbook: Wooldridge, J. M.: Introductory Econometrics: A Modern Approach, 7th edition, Cengage. (You may read all the earlier editions as well but need either the 7th or the 6th edition for homework problems.) Course Description: This course will cover an introduction to the basic methods of econometrics. The focus of the course will be on providing a quantitative approach to economics through the linear regression models (conditional means), which are also useful in a large number of applied subjects such as business and finance, sociology, biology, and mathematics, among others. Assumptions, estimation and testing of the regression models will be covered. A good prior knowledge in Economics 101 or equivalent is needed (For a review see Appendix B &C in the Wooldridge’s textbook). Elementary linear algebra and basic calculus are recommended (Also see Appendix A in the text book).

Learning Outcome: By the end of this course, you are expected to be able to: • Establish econometric models, and conduct meaningful econometric analyses using given data sets; • Present your analysis in a clearly written document; • Interpret and critically evaluate econometric analyses conducted by others.

Methods of instruction Econometrics is a hard course. Be prepared to make efforts. Lecture: In lectures, you will be introduced to the basic principles of the course topics. I will provide lecture slides, which is NOT a substitute of the textbook, but only guides you through important topics that are discussed in depth in the textbook. Bottom line is, everything that I show in class, in the slides and/or notes posted on iLearn/Blackboard, in the assignments and solutions, or in the book chapters corresponding to the topics we cover in class is a fair game. Unless I explicitly exclude something, they all could appear in the exams. I will utilize technology, but I have found that the best way to learn econometrics is often to physically take notes. I will post slides and notes on iLearn, but many of the topics we cover will involve graphs and calculations so plan on taking notes. Discussion: Every student must enroll to one discussion session. Watching the discussion session video is mandatory. Get to know your TAs, too. They will be the first person you turn to when you have concerns with the course. The discussion section will be used to review the class lectures, discuss the homework assignments, and/or go over specific problems. Plan to bring additional questions to TAs’ office hour. Lab: Every student must enroll to one lab session. Watching the lab session is mandatory. An important part of the course is learning how to use real data to answer economic questions. In your weekly lab sessions, you will connect the material we discuss in lecture to STATA. Most weeks, your Lab TA will introduce some new commands and tips, and walk you through a few examples of how to use them. Ask your Lab TAs if you have questions about the STATA problems in the assignments. You are encouraged to practice using STATA on your own. UCR provides STATA license for registered students. I posted information on installation and licensing of STATA on iLearn (Announcement). I posted a brief tutorial of Stats on iLearn (Course Materials), you may want to check back to it as the course progresses. Grading Breakdown: Homework Midterm Final Total: 100%

25% 30% 45%

(5 assignments, 5% each.)

__________________________________________ Start working on the homework early and try to submit early, in order to submit on time even when you encounter internet connection problems. Each homework assignments will consist of analytical problems as well as computer problems. They will be posted on iLearn with due dates. Include STATA commands for the key steps (not the whole do file) and STATA outputs, as well as your interpretation of the results, for computer exercises. You can do screen shot of your computer for the commands and the outputs. To submit your homework, upload TWO PDF FILES, one for the analytical part and one for the computer part. Don’t upload many pictures (jpeg, png, etc.). There are many free apps that scan documents to pdf files. Late submission of the assignment is not accepted — no exception. Homework assignments aim to help you understand the materials better, but not to test you. So they will be graded based on whether you made an honest attempt to answer all the problems, not correctness. You are allowed to discuss with other students or TAs, but every student must submit her/his own assignments individually. Any academic misconduct will be reported. It is your responsibility to make sure that you learn by doing the assignments, not the professor’s or the TAs’.

Class expectations: Instructors: Instructors will carefully prepare the videos, come to the office hours prepared, and will be respectful to all students and situations. Instructors will respond to appropriate questions by email in a timely manner. If you do not receive an email back from an instructor or A TA, the answer is probably on this syllabus or the iLearn. Please see me during office hours if you need an accommodation for any disability. Unless there is a mistake in grading, instructors will NOT respond to inquiries regarding individual grades. Students: Econometrics is an advanced and difficult course. Prepared to dedicate considerable time outside of class to this course. Be respectful of your peers and instructors (stay off distracting technology). The more work you put into the course, the better you will perform. Although you may (and should) work in groups, it is imperative that you do all the graded course work by yourself. Academic Integrity: Any violation of academic integrity will be reported. In the past, I have reported multiple cases of academic dishonesty, which resulted in the disciplinary dismissal of two students and disciplinary sanctions for others. Please see the following website regarding Academic Integrity and Procedures: https://conduct.ucr.edu/policies/academic-integrity-policies-and-procedures

University Academic Integrity Definition: “At the University of California, Riverside (UCR) honesty and integrity are fundamental values that guide and inform us as individuals and as a community. The culture of academia requires that each student take responsibility for learning and for producing products that reflect their intellectual potential, curiosity, and capability. Students must represent themselves truthfully, claim only work that is their own, acknowledge their use of others’ words, research results, and ideas, using the methods accepted by the appropriate academic disciplines and engage honestly in all academic assignments. Anything less than total commitment to honesty circumvents the contract for intellectual enrichment that students have with the University to become an educated person, undermines the efforts of the entire academic community, and diminishes the value of an education for everyone, especially for the person who cheats. Both students and faculty are responsible for insuring the academic integrity of the University.” https://conduct.ucr.edu/sites/g/files/rcwecm1511/files/2018-07/aidefinitions.pdf University Definition of an academic integrity violation: “Academic misconduct is any act that improperly distorts (or could distort) a student’s grades or other academic records.” https://conduct.ucr.edu/policies/academic-integrity-policies-and-procedures

TENTATIVE COURSE SCHEDULE Note: The course outline is tentative and subject to change Final Note: You are fully responsible for following up on all the announcements made during the lectures.

Appendix B and C: Introduction. Chapter 1: The Nature of Econometrics and Economic Data.

Chapter 2. The Simple Regression Model.

MIDTERM EXAM: TBD Chapter 3. Multiple Regression Analysis: Estimation. i. Modeling. ii. Omitted variable bias. iii. Adjusted R-square.

Chapter 4. Multiple Regression Analysis: Inference i. T-test ii. F test iii. Linear and nonlinear models.

Chapter 5. Multiple Regression Analysis: OLS Asymptotics.

Chapter 7. Multiple Regression Analysis with Qualitative Information: dummy variables. Chapter 10. Basic Regression Analysis with Time Series Data.

FINAL EXAM( non-cumulative) : Saturday, March 12, 8:00 a.m - 11:00 a.m...