Introduction to Applied Econometrics
Econ 400 (4 Credits), Spring 2024
University of Wisconsin-Madison
This course provides an introduction to econometrics – the statistical methods economists use to evaluate empirical relationships and test economic theory. Because this is an applied course, our emphasis will be on (a) developing the econometric skills necessary to read and understand empirical papers in economics and (b) the application of econometrics to real-world data using modern statistical software. A wide range of statistical techniques will be covered, including: univariate & multiple regression, differences-in-differences, instrumental variables, limited dependent variables, fixed-effects models, and regression discontinuity. Throughout the course, we will be interested in the extent to which statistical models can be used to conduct causal inference.
Note: Our department offers two introductory econometrics courses: Econ 400 and Econ 410. Econ 400 places less emphasis on theory and a correspondingly greater emphasis on applied techniques. Econ 410 takes a more mathematical & theoretical approach, deriving formulas and proving results wherever possible. Econ 400 and 410 are not a sequence. Students take only one of the two. Students doing our math em phasis major, including all those pursuing honors in the major, must take Econ 410.
Lecture is Tuesdays and Thursdays from 11am to 12:15pm in Plant Sciences 108.
My office hours and those of your TA can be found here on our class website.
Required Course Materials
As noted in the Course Guide, this course uses an Engage eText, which is available via our course webpage (see below). Our textbook is: Introduction to Econometrics by James H. Stock and Mark W. Watson, Fourth Edition. There is no need to purchase the textbook from the publisher, since the cost of the eText is already bundled into your tuition bill. For more information, including opt-out instructions, see the Engage eText Frequently Asked Questions.
This course requires frequent use of a computer (Mac or Windows) with Stata installed. Because UW-Madison has a site-license, Stata can be downloaded for free from the Campus Software Library. You will also need a calculator and access to a reliable internet connection.
Your overall grade for the course will be based on the following components:
• Midterm Exams: There will be two midterms, each worth 30% of your overall grade. Midterms will be held in-person during our regularly scheduled lecture on March 7 and May 2. Ensure you are available these dates. If you are unable to take an exam due to a circumstance that is beyond your control, let me know and we will discuss how best to proceed. To qualify for an accommodation, the circumstance must make it impossible for you to complete the midterm at the scheduled time, it must be fully documented, and you must notify me in advance of the midterm.
• Problem sets: There will be weekly problem sets, which together are worth 40% of your overall grade – so completing them will be critical to your success. For full credit, problem sets must be submitted in Canvas before the submission deadline. Late problem sets may be submitted after this deadline, but will receive a 20% per day deduction. In order to provide you with hands-on experience using the methods taught in this course, the computer package Stata will be used extensively on the problem sets. To receive full credit, you must submit your Stata log. To help prepare you for these assignments, Stata will be used during lectures and tutorials will also be provided during discussion section. You are encouraged to form a study group with your classmates, but you must write up your answers independently (meaning that you should not be looking at anyone else’s answer as you write up your own response). Problem sets with identical wording or where free-response answers have been written using artificial intelligence (e.g., ChatGPT) or by an electronic translator (e.g., Google Translate) will not be accepted (i.e., receive zero credit).
Your overall grade for this class will be curved. This curve can help your grade, but cannot hurt it. I achieve this by computing your grade using two different methods. First, I assign grades according to a percentage scale, where A = [92,100], AB = [88,92), B = [82,88), BC = [78,82), C = [70,78), D = [60,70), F = [0,60). (In other words, if you receive a grade in the class of 92% or better, then you’ll receive an A.) Second, I assign grades according to a percentile scale, where A = [80,100], AB = [60,80), B = [40,60), BC = [20,40), C = [6,20), D = [3,6), F = [0,3). (In other words, if you perform bet ter than 80% of the class, then you’ll receive an A). Your overall grade in the class is the higher of these two grades.
I strive to make all of the grading transparent and fair. If you are unhappy with the way a problem has been graded, I encourage you to discuss it with me, but you must bring mthe concern to me within two weeks of when you were first able to view the graded problem set or exam.
Grievance Procedure
The Department of Economics has developed a grievance procedure through which you may register comments or complaints about a course, an instructor, or a teaching assistant. The Department continues to provide a course evaluation each semester in every class. If you wish to make anonymous complaints to an instructor or teaching assistant, the appropriate vehicle is the course evaluation. If you have a disagreement with an instructor or a teaching assistant, we strongly encourage you to try to resolve the dispute with him or her directly. The grievance procedure is designed for situations where neither of these channels is appropriate.
If you wish to file a grievance, you should go to room 7238 Social Science and request a Course Comment Sheet. When completing the comment sheet, you will need to pro vide a detailed statement that describes what aspects of the course you find unsatisfactory. You will need to sign the sheet and provide your student identification number, your address, and a phone where you can be reached. The Department plans to investigate comments fully and will respond in writing to complaints.
Your name, address, phone number, and student ID number will not be revealed to the instructor or teaching assistant involved and will be treated as confidential. The De partment needs this information, because it may become necessary for a commenting student to have a meeting with the department chair or a nominee to gather additional information. A name and address are necessary for providing a written response.
Academic integrity is critical to maintaining fair and knowledge based learning at UWMadison. Academic dishonesty is a serious violation: it undermines the bonds of trust and honesty between members of our academic community, degrades the value of your degree, and defrauds those who may eventually depend upon your knowledge and integrity.
Examples of academic misconduct include, but are not limited to: cheating on an ex amination (copying from another student's paper, referring to materials on the exam other than those explicitly permitted, continuing to work on an exam after the time has expired, turning in an exam for regrading after making changes to the exam), copying the homework of someone else, submitting for credit work done by someone else, stealing examinations or course materials, tampering with the grade records or with another student's work, or knowingly and intentionally assisting another student in any of the above. Students are reminded that online sources, including anonymous or unat tributed ones like Wikipedia, still need to be cited like any other source; and copying from any source without attribution is considered plagiarism.
The Dept. of Economics will deal with these offenses harshly following UWS14 procedures (http://students.wisc.edu/saja/misconduct/UWS14.html):
1. The penalty for misconduct in most cases will be removal from the course and a failing grade,
2. The department will inform the Dean of Students as required and additional sanctions may be applied.
3. The department will keep an internal record of misconduct incidents. This information will be made available to teaching faculty writing recommendation letters and to admission offices of the School of Business and Engineering.