This course offers an introduction to econometrics, a powerful suite of analytical tools that can help us to analyze data and uncover causal relationships in economics. Through a blend of theoretical knowledge and hands-on experience with statistical programming, you will learn to construct and interpret econometric models. Economists and other practitioners use these models for testing economic hypotheses, modeling complex relationships, and making informed forecasts. In this course, we will focus on regression analysis, learning how and when regressions can be used to identify causal relationships in data. By the end of the course, you will apply these skills to develop a research paper on a topic of your choice, demonstrating your ability to translate data into meaningful insights.

The textbook for this course is Real Econometrics, 2nd edition, by Michael Bailey. For this course, I will be using the “Inclusive Access Course Materials” so that you have access to the materials from day one. You should have received an email from the bookstore regarding detailed instructions on how to access the materials on Canvas. For more questions please visit: https://store.suu.edu/inclusive-access-info or send an email to the bookstore: bookstore@suu.edu.

Upon successful completion of this course, students should be able to:

• Identify situations in which econometrics can provide insights, explaining its use and limitations
• Evaluate which econometric approach should be taken to analyze a real-world problem, and provide justification
• Implement key econometric analyses independently using Stata and interpret the results
• Execute a simple research project including collecting and/or cleaning data, conducting an analysis, and sharing findings with diverse audiences

This course has two midterm exams, each worth 15% of the final grade. Any material covered in class lectures, class discussions, weekly assignments, or in the textbook may be included in the midterms. The exams may be in any format including, but not limited to, questions requiring mathematical calculations, short- and long-form essay questions, code reading or writing, questions requiring data analysis, and multiple-choice questions. You will be notified in advance of the formats. Each midterm will be 75 minutes long.

Weekly Assignments: After each class session, you are expected to review the relevant chapter of the textbook and work on a weekly assignment. The due dates are listed below. The weekly assignments form 15% of the final grade. No late assignments will be accepted without prior notification. You are welcome to discuss or work on Weekly Assignments with your classmates as long as you submit your own work – meaning everything is in your own words, with code (if applicable) that you wrote yourself.

Research Paper and Presentation: In this course, you will write a research paper with a partner/partners (group size: 4 members) demonstrating some of the econometric techniques that you have learned. The final research paper is worth 20% of your final grade. You will also give a brief presentation on your work to the rest of the class in which all partners will speak, worth 15% of your final grade.

At the end of the semester, you will submit feedback on the contributions of each partner to the research project. Partners may receive different grades on the final paper and/or final presentation based on this feedback.

To help you in the research paper writing process, the final research paper is scaffolded into research deliverables. You will submit research deliverables prior to the submission of your final paper. The research deliverables are graded on effort and completion, worth 15% of your final grade.

Because the research deliverables are discussed in class, late or missed research deliverables negatively impact the class’s learning experience and therefore are typically not accepted for any reason.

The research paper process in total is thus worth 50% of your final grade in and should represent a significant effort.

In your research papers, citations are required for any quotes, facts, or key ideas taken from the work of any other individual or entities.

• Course Schedule: The course schedule is tentative and subject to change. The professor reserves the right to deviate from this plan as needed, including changing the order of the chapters covered, eliminating chapters, or adding other chapters or modules to the list below.
  Textbook chapters that we will cover in class:
  • Appendix: Math and probability background
  • Chapter 1: The quest for causality
  • Chapter 2: Stats in the Wild: Good Data Practices
  • Chapter 3: Bivariate OLS: The Foundation of Econometric Analysis
  • Chapter 4: Hypothesis Testing and Interval Estimation: Answering Research Questions
  • Chapter 5: Multivariate OLS: Where the Action Is
  • Chapter 6: Dummy Variables: Smarter than You Think
  • Chapter 7: Specifying Models
• Time permitting, we will briefly cover the following concepts as well. These are some of the causal methods and will be primarily taught in Advanced Econometrics: Difference-in differences, instrumental variables, and regression discontinuity.

Class Policies:

• Late/missed exams: The midterms must be taken on the day they are administered. If you have a valid reason for missing an exam, this needs to be cleared with the professor BEFORE the exam is administered, and any accommodation is at the discretion of the professor.
• Arriving late to class: Out of respect to your fellow students and the professor, please arrive before class begins. In case I don’t show up before class time, please wait 10 minutes before you disperse.
• Communication: You are responsible for monitoring your SUU email and the course website on Canvas regularly for updates regarding the course.

Late Work and Extensions Policy: All weekly assignments, research deliverables, peer reviews, and required readings are due at the beginning of the class period on the date published on the syllabus. All assignments in this class will be discussed in class or used for class activities, so generally no late work can be accepted or extensions granted. The research paper deadline is final, meaning this is the absolute latest date you can submit the work.

This is an interactive course in which you are expected to actively participate and learn from your peers. Although attendance is not mandatory, my experience suggests that you will soon realize that the opportunity cost of missing a class for this course is quite high! If you do miss a class, it is your responsibility to arrange with classmates to catch up on any missed notes or work.