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ECON 399:
INTRODUCTORY ECONOMETRICS
COURSE OUTLINE1 Section: B2 Term: Spring 2017
Class Time: Tuesday and Thursday from 2PM to 3:20 PM Class Room: T B 70
Lab Time: H3 (T): 10AM-10:50AM and H4 (R): 4PM-4:50PM Lab Room: T B 39
Web Page: eClass
Instructor: Andrew McGee Office: Tory 7-18
Office Hours: Tuesday from 1PM to 1:50PM Thursday from 3:30PM to 4PM E-mail2: [email protected]
Course Description: “Intermediate between mathematics, statistics, and economics; we find a new discipline which for a lack of a better name may be called Econometrics. Econometrics has as its aim to subject abstract laws of theoretical political economy of “pure” economics to experimental and numerical verification and thus to turn pure economics, as far as possible, into a science in the strict sense of the world.” Ragnar Frisch (1926).3
Course Goals: At the end of the course, the students will have developed skills needed for estimating and testing economic relationships. The course will prepare students for conducting independent research projects; i.e., throughout the course the students will learn to identify testable predictions by drawing from economic theory, identify data to test the predictions, and carry through empirical tests.
Course Prerequisites: ECON 281, ECON 282, STAT 141, and ECON 299 (or equivalent). Important: The Department may cancel your registration if you do not have the required courses as prerequisites. Students who do not meet the requirements should contact the instructor as soon as possible.
Required Text: Wooldridge, J.M. (2016): Introductory Econometrics: A Modern Approach, Sixth Edition, Thomson South-Western. ISBN: 9781305270107. By purchasing the book you also obtain access to datasets and Student Solution manual on-line (http://1pass.thomson.com). Those who purchased a used book can obtain on-line access for an additional fee.
Access to Software (STATA): During the course you will learn how to use statistical software STATA (attending lab sessions is encouraged). You will be expected to use the software to complete some of the course’s requirements (i.e., homework assignments). There are two ways you can obtain access to STATA outside of scheduled lab sessions:
You can access STATA in any of the labs on campus that have it installed (to check which labs apply go to https://ist.ualberta.ca/services/labs-classrooms/lab-bookings and select STATA as “Software”).4
1 Policy about course outlines can be found in 23.4(2) of the University Calendar.
2 When sending an e-mail indicate in the subject line of the e-mail “ECON 399.”
3 Ragnar Frisch is a recipient of the first Nobel Prize to be awarded for contributions to the field of economics in 1969 (shared with Jan Tinbergen).
4 A few options are: Tory B-39, Rutherford 2-05A, Rutherford 2-03, General Services 866, General Services 217, Business B-24.
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You can purchase a 6-month license for $38 (see https://www.stata.com/order/new/edu/
gradplans/student-pricing/).
Other Course Materials: (1) Data sets, sample midterm, sample final exam, sample Stata programs and other materials will be posted on the course page on eclass. A sample midterm and final exam will each be posted at least 3 weeks ahead of the respective scheduled testing dates.
Course Performance Evaluation: Final course grades are determined according to the University calendar
§23.4(2): Grades reflect judgments of student achievement made by instructors. These judgments are based on a combination of absolute achievement and relative performance in a class.
Type of evaluation Date(s) Weight
Lab exercises (5 assignments) TBA (schedule depends on when a lab assistant is assigned)
10%
Homework assignments (2 assignments) Tentative due dates February
17 and March 17 20%
Research report Due in class on April 11 20%
Midterm Exam (1-hour long exam) February 28th, 2017 (in class) 20%
Final Exam (2-hour long exam) April 21st, 2017 30%
Lab Sessions should provide sufficient instructions to the program’s use for successful completion of either homework assignments or research paper. Thus, lab attendance is highly encouraged! A teaching assistant will demonstrate the use of various methods learnt in class with the STATA software. Lab assignments can be completed during the lab sessions or may be submitted at the start of the next lab session. Details will be provided as assignments are distributed.
Lab and Homework Assignments will require students to learn the statistical software STATA. Instructions on how to use the software will be provided during the lab sessions. Late assignments will not be accepted unless appropriate documentation is provided (see last page).
The research report will be a 5-8 page report (not including tables and figures) identifying a research question, formulating a hypothesis, testing the hypothesis empirically, and describing findings. The research report will be discussed in greater detail following the midterm.
Midterm exam will take place in-class on February 28th, 2017. Please refer to the last page of the course outline for policies regarding the absence from the examination and appropriate documentation.
Final exam will take place on April 21st (Friday), 2017, at 2PM. This will be a two-hour exam. While the exam is COMPREHENSIVE, the emphasis will be on the material covered in the second half of the semester.
Other: Department of Economics General Office (Tory 8-14) is CLOSED from 12-1PM.
Topics and reading outline (following Wooldridge, 2016):
Chapter 1: The nature of econometrics and economic data Chapter 2: The simple regression model
Chapter 3: Multiple regression analysis: Estimation Chapter 4: Multiple regression analysis: Inference Chapter 5: Multiple regression analysis: OLS asymptotics Chapter 6: Multiple regression analysis: Further issues
Chapter 7: Multiple regression analysis with qualitative information: Binary (or dummy) variables
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Chapter 8: Heteroskedasticity
Chapter 9: More on specification and data problems Chapter 10: Basic regression analysis with time series data Chapter 11: Further issues in using OLS with times series data
Chapter 12: Serial correlation and heteroskedasticity in time series regressions Chapter 19: Carrying out an empirical project
Academic Integrity
“The University of Alberta is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect. Students are particularly urged to familiarize themselves with the provisions of the Code of Student Behavior (at http://www.governance.ualberta.ca/en/CodesofConductandResidenceCommunityStandards/CodeofStudentBehaviour.as px) and avoid any behavior that could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts and/or participation in an offence. Academic dishonesty is a serious offence and can result in suspension or expulsion from the University.”
Learning and working environment
The Faculty of Arts is committed to ensuring that all students, faculty and staff are able to work and study in an environment that is safe and free from discrimination and harassment. It does not tolerate behavior that undermines that environment. The department urges anyone who feels that this policy is being violated to:
• Discuss the matter with the person whose behavior is causing concern; or
• If that discussion is unsatisfactory, or there is concern that direct discussion is inappropriate or threatening, discuss it with the Chair of the Department.
For additional advice or assistance regarding this policy you may contact the student ombudservice:
(http://www.ombudservice.ualberta.ca/). Information about the University of Alberta Discrimination and Harassment Policy and Procedures can be found in the GFC Policy Manual, section 44 available at http://gfcpolicymanual.ualberta.ca/.
Plagiarism and Cheating:
All students should consult the “Truth-In-Education” handbook or Website (http://www.uofaweb.ualberta.ca/TIE/) regarding the definitions of plagiarism and its consequences when detected. Students involved in language courses and translation courses should be aware that on-line “translation engines” produce very dubious and unreliable translations.”
Students in language courses should be aware that, while seeking the advice of native or expert speakers is often helpful, excessive editorial and creative help in assignments is considered a form of “cheating” that violates the code of student conduct with dire consequences. An instructor or coordinator who is convinced that a student has handed in work that he or she could not possibly reproduce without outside assistance is obliged, out of consideration of fairness to other students, to report the case to the Associate Dean of the Faculty. Before unpleasantness occurs consult
http://www.uofaweb.ualberta.ca/TIE/; also discuss this matter with any tutor(s) and with your instructor.
Recording of Lectures:
Audio or video recording of lectures, labs, seminars or any other teaching environment by students is allowed only with the prior written consent of the instructor or as a part of an approved accommodation plan. Recorded material is to be used solely for personal study, and is not to be used or distributed for any other purpose without prior written consent from the instructor.
Attendance, Absences, and Missed Grade Components:
Regular attendance is essential for optimal performance in any course. In cases of potentially excusable absences due to illness or domestic affliction, notify your instructor by e-mail within two days. Regarding absences that may be excusable and procedures for addressing course components missed as a result, consult sections 23.3(1) and 23.5.6 of the
University Calendar. Be aware that unexcused absences will result in partial or total loss of the grade for the “attendance and participation” component(s) of a course, as well as for any assignments that are not handed-in or completed as a result.
