ECON 351 - Introductory Econometrics

Queen’s University, Department of Economics

Location: Jeffrey, Room 126Times: Monday @ 4-5:20pm & Wednesday @ 2:30-3:50pmWebsite: http://www.econ.queensu.ca/econ351

Instructor: Maggie Jones (jonesm@econ.queensu.ca)Office: Dunning Hall, Rm 345Office Hours: Wednesday @ 4-5:30pm & Thursday @ 8:30-10am

Teaching Assistant: Sergei Shibaev (shibaevs@econ.queensu.ca)Office: MAC 425Office Hours: Tuesday @ 2:30-3:30pm

Teaching Assistant: Justin Quinton (quintonj@econ.queensu.ca)Office: MAC 425Office Hours: Monday @ 1-2pm

Description

This course introduces students to regression methods for analyzing data in economics and re-lated fields. We will cover techniques for estimating regression models as well as problems thatarise in estimating such models related to inference, specification, and interpretation.The ma-jority of the course will be spent developing the theory for the ordinary least squares estimator;extensions will include panel data methods and difference-in-difference. The goal of the courseis to teach the basics of the theory and practice of econometrics as well as provide exposure toestimating econometric models with actual data. Students will be expected to draw on materialcovered in ECON 250, and the appropriate mathematics prerequisites in the course catalogue.

Course Goals

The course goals are threefold. By the end of the course students should be able to:

1. Work through the mathematical derivations and theory behind the econometric methodspresented.

2. Use Stata to conduct econometric analysis to address a variety of economic questions.

3. Interpret, analyze and critique basic econometric principles in economic journal articlesand news articles.

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Readings

The required textbook is Introductory Econometrics: A Modern Approach, 6th edition, byJeffrey Wooldridge. Other journal articles that we will be touching on will be listed belowaccording to the section in which they appear.

Additional references that are not required but that you may find helpful include:

1. Mostly Harmless Econometrics: An Empiricist’s Companion - Joshua D. Angrist andJorn-Steffen Pischke

2. Microeconometrics Using Stata - A. Colin Cameron and Pravin K. Trivedi

Software

This course will rely heavily on the use of Stata, a statistical software used frequently ineconomics. You may purchase a copy of Stata online at http://www.stata.com/order/new/

edu/gradplans/course-pricing/ between September 12th, 2016 and December 21st, 2016using the GradPlan ID: AWG15. Please note that if you must purchase the Stata/IC version orabove, as lower versions are not able to handle some of the datasets we will be using. If you donot wish to purchase a copy of Stata, the computer room in Dunning 350 (open Monday-Friday8:30am-10:00pm) is equipped with several machines with Stata.

Tutorials

During the second week of classes (Sept 19th-23rd) there are tutorials scheduled in the computerlab (Dunning 350) each day from 10:00-11:30am. You can choose which day to attend based onyour own schedule. The purpose of these tutorials will be to introduce students to Stata andto go through the coding format required for the assignments.

Grading Scheme

All components of this course will receive numerical percentage marks. The final grade youreceive for the course will be derived by converting your numerical course average to a lettergrade according to the Queens Official Grade Conversion Scale (i.e., numbers in, letters out).

Note that late work will not be accepted. Accommodations can be made in the event of a med-ical emergency with the provision of a Verification of Illness Note from a medical professional.

The following weighting will be used to determine grades. If an assignment or the midterm ismissed for legitimate reasons the percentage will be transferred to the final.

1. Assignments 5 @ 6% each = 30% total

2. Midterm @ 25%: The midterm will be (tentatively) held on October 19th and will covereverything from Sept 12th-Oct 17th (keep in mind Oct 17th will be a review class)

3. Final @ 45%

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Course Outline

1. Introduction and Review of Statistics Sept 12th-21st

• Topics: What is econometrics and why is it useful? Review of tools from calculus,probability distributions, law of large numbers, central limit theorem

• Readings: Wooldridge Chapter 1 and Appendices A, B, C

2. Ordinary Least Squares (Estimation and Inference) Sept 26th-Oct 12th

• Topics: Simple regression model, deriving OLS estimates, multiple regression anal-ysis, functional form, properties of OLS estimators, inference in regression analysis

• Readings: Wooldridge Chapters 2-4

3. Midterm Review and Midterm Oct 17th-19th

4. Additional Issues with Ordinary Least Squares Oct 24th-Nov 9th

• Topics: OLS asymptotics, functional form, goodness of fit, regression analysis withqualitative information, heteroskedasticity

• Readings: Wooldridge Chapter 5-8

5. Advanced Topics in Econometrics Nov 14th-23rd

• Topics: Panel data estimation, instrumental variables, program evaluation

• Readings: Wooldridge Chapters 13-15

6. Introduction to Time Series Nov 28th

• Topics: What is time series data, methods of analyzing, etc

• Readings: Wooldridge Chapter 10

7. Final Exam Review Nov 30th

Academic Integrity

Academic integrity is constituted by the five core fundamental values of honesty, trust, fairness,respect and responsibility (see Academic Integrity). These values are central to the building,nurturing and sustaining of an academic community in which all members of the community willthrive. Adherence to the values expressed through academic integrity forms a foundation forthe “freedom of inquiry and exchange of ideas” essential to the intellectual life of the University(see the Senate Report on Principles and Priorities).

Students are responsible for familiarizing themselves with the regulations concerning academicintegrity and for ensuring that their assignments conform to the principles of academic integrity.Information on academic integrity is available in the Arts and Science Calendar (see AcademicRegulation 1), on the Arts and Science website (see Academic Integrity Policy), and from theinstructors.

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Departures from academic integrity include plagiarism, use of unauthorized materials, facilita-tion, forgery and falsification, and are antithetical to the development of an academic communityat Queen’s. Given the seriousness of these matters, actions which contravene the regulation onacademic integrity carry sanctions that can range from a warning or the loss of grades on anassignment to the failure of a course to a requirement to withdraw from the university. Alsoyou may wish to review the information on the Arts and Science website for students.

Course Website

Please note that the material for this course is copyrighted and is for the sole use of studentsregistered in Economics 351. The material for this course may be downloaded for a registeredstudent’s personal use, but shall not be distributed or disseminated to anyone other than stu-dents registered in Economics 351. Failure to abide by these conditions is a breach of copyright,and may also constitute a breach of academic integrity under the University Senate’s AcademicIntegrity Policy Statement.

Accessibility Statement

Queens is committed to an inclusive campus community with accessible goods, services, andfacilities that respect the dignity and independence of persons with disabilities. Course materialsare available in an accessible format or with appropriate communication supports upon request.

Accommodation Statement

Queens University is committed to achieving full accessibility for persons with disabilities. Partof this commitment includes arranging academic accommodations for students with disabilitiesto ensure they have an equitable opportunity to participate in all of their academic activities. Ifyou are a student with a disability and think you may need accommodations, you are stronglyencouraged to contact Queen’s Student Accessibility Services (QSAS) and register as early aspossible. For more information, including important deadlines, please visit the QSAS website.

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