Econ 382: Introduction to Econometrics Winter 2023
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Econ 382: Introduction to Econometrics
Winter 2023
Course Pages:
• https://canvas.uw.edu/courses/1622861
Office Hours: Tuesday 8:30–9:30, Thursday 11:30– 12:30, Savery 334. I am also available by email, and if you want to schedule office hours at a different time or schedule a Zoom meeting, please just let me know. Please wear a mask if you come to my office.
TA Sections: Wednesdays, 2:30–3:20, Smith 102. TA sections are a requirement of this class. In these sections, you will learn how to use R and RStudio for econometrics.
Main Reference:
• A.H. Studenmund, Using Econometrics: A Practical Guide, Pearson, 7th ed., 2017. Resources are available at https://media.pearsoncmg.com/ph/bp/bridgepages/teamsite/studenmund/
Secondary References: You may also find much of the following reference to be useful as well.
• Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer, Introduction to Econo- metrics with R, econometrics-with-r.org
Required Software: R (r-project.org) and RStudio (rstudio.com) are required for this course. Both are available for free, and will be used throughout the course.
Course Description: Economics 382 is a course in economic statistics and econometrics. Econometrics is distinguished by the unification of economic theory and statistical methodology. It is concerned with estimating economic relationships, confronting economic theory with facts, and testing hypotheses involving economic behavior. Specific topics addressed in this course include mathematical statistics, single and multiple variable regression analysis, the Gauss – Markov Theorem, hypothesis testing, model specification, multicollinearity, dummy variables, heteroskedasticity, serial correlation, and distributed lag models.
As a course in applied econometrics, we will frequently use these methods with real world financial and economic data. Students will be introduced to data and regression analysis in R. Given the applied nature of much of the coursework, some mathematical, statistical, and computer proficiency will be assumed.
Once you have finished this course, you will be able to:
• Interpret and implement multiple regression and related statistical techniques
• Identify the limitations and pitfalls of regression methods
• Write a focused explanation of the findings of a statistical investigation, clearly and concisely
Prerequisites: A minimum grade of 2.0 in Econ 300 is required to take this course.
Grading Policy: Problem Sets (25%), Midterm (25%), Project (25%), Final Exam (25%).
Problem Sets: Short problem sets will be assigned most weeks, and are due at 11:59 PM Pacific Time on the following Tuesday. Solutions will be posted after the assignments are due for help studying. The two lowest homework scores will be dropped from your grade.
Project: There will be one project that must be turned in by the last day of class that will test your ability to apply the course material to real-world econometric questions and using real-world data. More information about this project will be on the course website on Canvas.
Attendance Policy: Attendance at lecture and the TA section is recommended whenever possible. At- tendance for exams is mandatory. If you are unable to attend an exam due to circumstances beyond your control, please contact me as soon as this issue arises, and prior to the beginning of the scheduled exam period.
Exceptions will be made for health, religious, and academic reasons, and accommodations may be possible for those with other challenges.
No late assignments will be accepted.
Accommodations: Should you require disability accommodations, please contact Disability Resources for Students at http://depts.washington.edu/uwdrs/ or 206-543-8924.
Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accomodation, is available at Religious Accom- modations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.
Academic Misconduct: All students are expected to know and to abide by the University’s Academic Mis- conduct policies as defined at http://www.washington.edu/admin/rules/policies/SGP/SPCH209.html# 7 summarized at https://depts.washington.edu/grading/pdf/AcademicResponsibility.pdf. In par- ticular, while you are encouraged to study with each other, all assignments for this course must be completed on one’s own. Exams are closed-book must be completed without accessing outside information, whether from“cheatsheets,” cellphones, your computer, or other sources. Failure to abide by these policies is likely to result in failing this course, and may result in further sanctions as described by the policy. If I believe you have cheated on an assignment, you will receive a “zero”grade for that assignment.
Table 1: Tentative Outline
Date Topic Reading
|
1/3 |
Introduction to Econ 382, Review of Regression Analysis |
Syllabus, Chapter 1 |
|
1/5, 1/10 |
Statistical Principles |
|
|
1/12, 1/17 |
Ordinary Least Squares I |
Chapter 2 |
|
1/17 |
Ordinary Least Squares II |
Chapter 3 |
|
1/19, 1/24 |
Classical Regression Model |
Chapter 4 |
|
1/26, 1/31 |
Hypothesis Testing |
Chapter 5 |
|
2/2 |
Model Specification |
Chapter 6 |
|
2/7 |
Midterm Exam |
Chapters 1 – 5, 17 |
|
2/9 |
Model Specification |
Chapters 7 – 8 |
|
2/14, 2/16 |
Heteroskedasticity |
Chapter 10 |
|
2/21, 2/23 |
Serial Correlation |
Chapter 9 |
|
2/28 |
Panel Data |
Chapter 16 |
|
3/2 |
Time-Series Models |
Chapter 12 |
|
3/7 |
Time-Series Models and Project due |
Chapter 12 |
|
3/9 |
Final Exam |
Chapters 6 – 10, 12, 16 |
2023-03-02