Published Sep 06, 2022
Specification and estimation of the linear regression model. Departures from the Gauss-Markov assumptions include heteroskedasticity, serial correlation, and errors in variables. Advanced topics include generalized least squares, and simultaneous equations/instrumental variables. They may also include nonlinear regression, and limited dependent variable models. Some or all of the problem sets involve working with the computer.
Although we will cover econometric theory in great details, the course focuses more on numerical applications and simulations than on mathematical proofs. Learning how to code is very beneficial to co-op students these days, and it is a skill that can be used in other economics courses as well. However, you do not need any coding background for this course. I will provide you with all the documentations that you need to succeed. You may want to bring your laptop in class to help you follow, because I may present numerical techniques in class from time to time. I will let you know in advance.
In this course, all students are required to use R for the applications and the assignments must be produced using Markdown. You will be trained in the first week on how to create documents with Markdown and throughout the term on how to use R. To be ready before the class starts, intall R from https://www.r-project.org/. You also have to install the RStudio (https://www.rstudio.com/), which is an IDE (Integrated development environment) for R. You will also need to install a Latex compiler. You do not really need to learn Latex, but it is required to create PDF's with Markdown. What you need is MiKTeX (https://miktex.org/) if you are a Windows user or MacTeX (https://www.tug.org/mactex/) if you are a Mac user. You will be ask to test your installation during the first week using a template.
| Understand the small and large sample properties of OLS, IV and GMM estimators. |
| Interpret the coefficients of OLS, IV and GMM estimators. |
| Estimate and interpret models using OLS, IV and GMM methods. |
| Apply bootstrap methods to estimate standard errors and to perform hypothesis tests, using R. |
| Perform and interpret hypothesis tests on coefficients, functions of coefficients and on model specification. |
| Perform simulation studies to analyze the sample sample properties of statistical methods, using R. |
| Analyze data and estimation results using vizualisation techniques. |
We will spend approximately one week on each of the following topics.
| Title / Name | Notes / Comments | Required |
|---|---|---|
| Hansen, Bruce E., Probability and Statistics for Economists | Probability theory. Referred as Prob | Yes |
| Hansen, Bruce E., Econometrics | Econometric theory. Referred as Econ | Yes |
All above textbooks are available for free. Just follow the links:.
I recommend a third one as a reference. It is a guide on how to use R in econometrics.
For most applications, I will post notes on how to use R on the course website.
| Component | Value |
|---|---|
| Assignments: between 4 and 6 | 45% |
| Midterm exam: November 29 from 8:30 AM to 9:50 AM in class. | 20% |
| Take home exam | 35% |
The assignments are a mixture of theory questions, empirical and simulation studies. The take home exam is a small empirical project that may include a simulation study. You have 48 hours to complete it.
Assignments: They must be handed in before the date and time written on the question sheet. Late submissions for assignments will be deducted 20% per day. Assignment submissions more than 3 days late will not be accepted.
Take home exam: You are not allowed to communicate with your classmates during the exam period. Late submissions are not accepted.
Text matching software (Turnitin) will be used to screen assignments in this course. This is being done to verify that use of all material and sources in assignments is documented. In the first week of the term, details will be provided about the arrangements for the use of Turnitin and alternatives in this course. See Administrative Policy below for more information and links.
Students should be aware that this course contains the intellectual property of their instructor, TA, and/or the University of Waterloo.
Intellectual property includes items such as:
Course materials and the intellectual property contained therein, are used to enhance a student’s educational experience. However, sharing this intellectual property without the intellectual property owner’s permission is a violation of intellectual property rights. For this reason, it is necessary to ask the instructor, TA and/or the University of Waterloo for permission before uploading and sharing the intellectual property of others online (e.g., to an online repository).
Permission from an instructor, TA or the University is also necessary before sharing the intellectual property of others from completed courses with students taking the same/similar courses in subsequent terms/years. In many cases, instructors might be happy to allow distribution of certain materials. However, doing so without expressed permission is considered a violation of intellectual property rights.
Please alert the instructor if you become aware of intellectual property belonging to others (past or present) circulating, either through the student body or online. The intellectual property rights owner deserves to know (and may have already given their consent).
All of us need a support system. The faculty and staff in Arts encourage students to seek out mental health support if they are needed.
On Campus
Due to COVID-19 and campus closures, services are available only online or by phone.
Off campus, 24/7
Full details can be found online on the Faculty of Arts website
Download UWaterloo and regional mental health resources (PDF)
Download the WatSafe app to your phone to quickly access mental health support information.
Policy 33, Ethical Behaviour states, as one of its general principles (Section 1), “The University supports academic freedom for all members of the University community. Academic freedom carries with it the duty to use that freedom in a manner consistent with the scholarly obligation to base teaching and research on an honest and ethical quest for knowledge. In the context of this policy, 'academic freedom' refers to academic activities, including teaching and scholarship, as is articulated in the principles set out in the Memorandum of Agreement between the FAUW and the University of Waterloo, 1998 (Article 6). The academic environment which fosters free debate may from time to time include the presentation or discussion of unpopular opinions or controversial material. Such material shall be dealt with as openly, respectfully and sensitively as possible.” This definition is repeated in Policies 70 and 71, and in the Memorandum of Agreement, Section 6
Academic integrity: In order to maintain a culture of academic integrity, members of the University of Waterloo community are expected to promote honesty, trust, fairness, respect and responsibility. [Check the Office of Academic Integrity for more information.]
Grievance: A student who believes that a decision affecting some aspect of their university life has been unfair or unreasonable may have grounds for initiating a grievance. Read Policy 70, Student Petitions and Grievances, Section 4. When in doubt, please be certain to contact the department’s administrative assistant who will provide further assistance.
Discipline: A student is expected to know what constitutes academic integrity to avoid committing an academic offence, and to take responsibility for their actions. [Check the Office of Academic Integrity for more information.] A student who is unsure whether an action constitutes an offence, or who needs help in learning how to avoid offences (e.g., plagiarism, cheating) or about “rules” for group work/collaboration should seek guidance from the course instructor, academic advisor, or the undergraduate associate dean. For information on categories of offences and types of penalties, students should refer to Policy 71, Student Discipline. For typical penalties, check Guidelines for the Assessment of Penalties.
Appeals: A decision made or penalty imposed under Policy 70, Student Petitions and Grievances (other than a petition) or Policy 71, Student Discipline may be appealed if there is a ground. A student who believes they have a ground for an appeal should refer to Policy 72, Student Appeals.
Note for students with disabilities: AccessAbility Services, located in Needles Hall, Room 1401, collaborates with all academic departments to arrange appropriate accommodations for students with disabilities without compromising the academic integrity of the curriculum. If you require academic accommodations to lessen the impact of your disability, please register with AccessAbility Services at the beginning of each academic term.
Turnitin.com: Text matching software (Turnitin®) may be used to screen assignments in this course. Turnitin® is used to verify that all materials and sources in assignments are documented. Students' submissions are stored on a U.S. server, therefore students must be given an alternative (e.g., scaffolded assignment or annotated bibliography), if they are concerned about their privacy and/or security. Students will be given due notice, in the first week of the term and/or at the time assignment details are provided, about arrangements and alternatives for the use of Turnitin in this course.
It is the responsibility of the student to notify the instructor if they, in the first week of term or at the time assignment details are provided, wish to submit alternate assignment.