Syllabus SP 26

This is the second course in the quantitative methods sequence for graduate students in public policy. The sequence exposes students to the main empirical methods used in policy analysis. Our goal is to improve your ability to understand causal claims, critically consume empirical evidence, and communicate that evidence to policy audiences. The first half of this course will develop and extend your regression and data analysis skills. The second half will introduce experimental and quasi-experimental strategies for measuring policy impacts.

A byproduct of these objectives is to elevate the student’s skill in deductive reasoning and critical thinking. Specifically, we want students to feel confident about consuming complicated information and help them make a decisions based on that information.

Prerequisite: This course assumes a solid foundation in descriptive and inferential statistics, including probability, estimation, and hypothesis testing. LPPA 6150 is required.

This class will help you develop your quantitative toolkit. While we hope you find these tools valuable immediately, their full benefits may not become apparent for some time. Even if your future job doesn’t explicitly require statistics, the ability to analyze data and discuss evidence will enhance your performance no matter what path you choose.

We will try to minimize technical demands, relying on the minimum math and programming skills required to achieve course objectives. Still, some students will find the course’s analytical approach challenging.

Books

The following books are the main books for this class and available in the UVA Bookstore. Though they are not required, they will substantial help in your understanding of what we see in lecture. The lectures will draw a lot from these books so they will be super helpful.

• Bailey, M.A. Real Stats: Using Econometrics for Political Science and Public Policy. New York: Oxford University Press. (B).
• There are two editions of this book. You are welcome to use either the first or second edition.
• Angrist, J. & Pischke, J-S. (2014). Mastering Metrics: The Path from Cause to Effect.

Princeton, NJ: Princeton University Press. (A&P)

You should first visit the books above for concepts and exercises. The Real-Stats book has questions and some answers in the back. However:

• If you have a concept that you need more or different perspectives on a particular concept
• If you need to see example coding
• If you need to see more “exercises” or “walk-through” examples.

Here are other books I recommend checking

• Gugerty, Mary Kay, and Dean Karlan. The Goldilocks Challenge: Right-fit Evidence for the Social Sector. Oxford University Press, 2018. (GK)
• This book is not made for “students” it is made for non-profits. They go over the concepts and importance of monitoring, when to monitor, and how to monitor and collect data for your non-profit. In addition, it suggest what to do when you cannot do an RCT.
• Stock, J.H. & Watson, M.W. Introduction to Econometrics. Boston: Addison-Wesley. (SW)
• An optional text for students interested in a more technical treatment of the course

material

• Cunningham, Scott. Causal Inference: The Mixtape V. 1.7. Obtain free at: https://mixtape.scunning.com. (C)
• This book is free and a great resource that combines intuition with higher-level math. This book is a bit more dense than the two required, but it is more fun too and has “different” examples. It also has some coding examples in STATA and R!
• Hernán MA, Robins JM (2019). Causal Inference. Boca Raton: Chapman & Hall/CRC. Obtain free at https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ (H)
• Huntington-Klein, Nick. The Effect: An Introduction to Research Design and Causality (E) https://theeffectbook.net

Software

We will use Stata extensively in this course. Stata is available on the Hive virtual desktop. You can also purchase discounted versions using the Stata Corporation Campus GradPlan program. There are a number of good STATA resources online. UCLA, in particular, maintains a wealth of tutorials, FAQs, and videos.

Check out the resources page for more.

The course objective is not to teach you how to code, so this class is not designed to appropriately “teach coding”. We use coding as a way for the student to understand what’s happening with the data and how does one achieve the goals of causal inference. STATA is a user-friendly software that can quickly get everyone on board to understand what’s happening. Having said that, the student is welcome to use any other coding language to solve their homework, whether that’s R or Python, etc. The answer key and support from the instructors will be on STATA and that will be the course’s coding language.

Much of the course will be in lecture format. We will frequently ask individuals to volunteer their thoughts, and we will also call on students to do so.

In general, you will not need cell phones during lecture. The available research suggests that they impede student learning both for computer users and their classmates.

When we use STATA examples during lecture, we will share the STATA files on the class website so that you may replicate the analysis on your own after class.

You should bring your computers to discussion sections, however. Those sessions will emphasize Stata and computer skills. If you believe your circumstances warrant an exception to these policies, please provide us with sufficient detail to evaluate your request.

Lastly, a note on notation: we will sometimes use different notation than the textbooks. This is intentional. Different authors use different notation, and we want you to be familiar with the alternatives.

How to approach lectures and course work?

To maximize learning, you should approach lectures as “review”. That means studying the concepts before coming to class through readings of Real Stats or Mastering Metrics, and then using lectures to review the concepts you’ve learned, and get to ask questions to understand better.

Each week students will have quizzes which will not factor in students grades to help with retention of the material. The goal of the quizzes are not to be evaluative, but to provide a way to practice active recall.

From time to time students will have worksheets. These are not required to be completed, but are a great way for the students to “touch” and play with the data to understand the methods that are being used.

Homework will be used to evaluate the student on how they are applying concepts and they will also serve as a didactic material to teach concepts.

Exams will mainly be used to evaluate progress and learning. However studying for exams has shown as a great tool to help student review the material.

Over the years students have asked for keys for success to improve their learning and retention of the concepts learned in class. The following are a list of “tips” that different students have used:

• Read the assigned material before class. Lectures will cover difficult material and prior exposure will help. We will often assume that you understand basic background information from readings even if we do not cover that content in the lecture. You will almost surely want to re-read the assigned material after class, especially if you found it difficult on a first read.
• Practice active reading. The best way to process the readings is with pen and paper. Econometrics is like reading math not history. But what should you write about? The usual is to make a summary of what you are reading. This is helpful because it helps with “retention” but copying and pasting concepts on paper will only be so helpful. The best type of summary notes are the ones in which your brain is processing the information. For example, instead of reading and taking notes as you read. Read the material and take very little notes. Then after you are done reading, try to summarize and organize the material in your own words without accessing the material, just from notes. A second tip when reading the material, is not to write a summary, but write a question that you need to know and then the answer. Then when you go back to notes, you can only see the question (Without the answer) and this can help with active recall.
• Practice active recall. Retention of the material is one of the hardest thing to achieve. This is because our brain are not designed for storage, they are designed to have ideas. You should aim to only retain core concepts and tools and then practice applying the basics on different problems. How to retain these core concepts? Active Recall is a tool to help with retention. The idea is to have a prompt (usually a question) for which you answer from what you remember and then you can see the answer. Here is a video explaining active recall and how to apply it.
• Apply things over and over. In order to understand your deficiencies you can apply concepts that you learn in class to your other classes, current events, and the policy questions that most interest you. This will help with (a) retention and (b) thinking about questions you have about the material. You can also use the materials we share from lecture and section to run analyses of your own. Come up with other applications for the tools that we cover. The Internet provides an unlimited supply of interesting data to explore.
• Weekly or biweekly review. Every week or two, make summary notes that highlight the key points from the lectures and relevant readings. Summary notes force you to make connections between material and assess what you don’t understand before exam crunch time hits.
• Allow yourself to struggle independently on assignments. Learn to seek out resources online to troubleshoot the Stata challenges that you encounter. Data skills and software are constantly evolving, so learning how to teach yourself new tools is more important than memorizing the ins and outs of any one program right now. A corollary: start assignments early. If you wait ’til the 11th hour, you will be tempted to cut corners and short change your own learning.
• Seek help sooner rather than later. There are many resources available to support your success in this course. Recall that when you seek help, try to figure out what exactly you need help with? Is it there readings? is it the applications? is it retention? What are you struggling with, and why?
• Check out the resources page for more resources!

Your grade will depend on homework and exams. The weighting scheme will be the following:

Homework

There will be approximately seven-ish homework assignments. Some will emphasize the readings and statistical tools we cover in the lecture. Others will require more substantial data analysis. For each assignment, we will specify whether you are permitted to work in groups or required to complete problems on your own. When group work is permitted, the group will turn in one assessment to be graded on.

The homework grade for the class grade will be calculated by adding the points from each individual homework assignment and then dividing them by the total possible points. This means that each individual homework won’t have a grade assigned (though each student is welcome to calculate that by dividing the points over the total points of each homework).

Exams

There will be two exams. Missed exams will receive zero credit, except when a documented medical issue prevents you from taking the exam. Each exam's grade will be self-contained, that is, it will have a grade over 100.

Re-grading

A request for a re-grade shall be done within the next 5 days following receiving the assignment and answer key. Please check the answer key and submit in an email a description of why the regrade needs to occur. The re-grade will activate a re-grade of the entire assignment. It’s a simple process design for ease for the students.

Example of someone’s grading

Monica grade’s are the following

Therefore Monica’s grade for the class will be calculated by the following

Monica’s Homework points: 282

Total possible Homework points: 297

Monica’s exam 1 grade would be $\frac{45}{50}=0.90$

Monica’s exam 2 grade would be $\frac{63}{67}=0.94$

Monica’s final grade would be $\\ 0.95\times0.60\\+\ 0.90\times0.20\\+\ 0.94\times0.20=0.93806\approx0.94$

The mapping from numerical grade to letter grade will follow the standard assignment of As (with + and -) are in the 90s range, Bs in the 80s, etc. The final thresholds will be assigned at the end of the course.

Quizzes and the “progress boost.”

Each week, a quiz will be available for students to practice the concepts learned that past week. These quizzes are not graded and do not factor into the final grade. However, suppose a student manages to get above 60% on their overall quiz grades (calculated by the total number of correct questions over the total number of questions). In that case, that student can use a “progress boost.”

The “progress boost” works the following way, the student will get 0.50 points of the positive difference between Exam 2 - Exam 1. In other words, if a student has shown improvement over their exam, they can get points back on their first exam. This policy would only benefit students and not punish students (For example, if Exam 2 < Exam 1).

Example. Let’s use the example above to see how this would change Monica’s grade. In Exam 1, the grade was 90, and in Exam 2, 94. This means the improvement was 4 points. Monica will get half of those points back into Exam 1, so the new final grade for Exam 1 would be 92 instead of 90.

You will notice that this policy kicks more points back the larger the student's progress. This tends to benefit people who didn’t do so well on midterm 1 and show great improvement in midterm 2.

Policy on Late Assignments

Late assignments will be accepted, but each late day will reduce your potential points by 10 percent — e.g., if you submit your homework three days late, you will receive 70 percent of the points you would have earned had you turned it in on time. Assignments submitted 10 or more days after the due date receive no credit.

Use it wisely. When you plan to use it, email your TA that you want your two-day-no-penalty to be used.

Intellectual honesty is vital to any academic community to safeguard student learning and the fair evaluation of student work. Unless explicitly stated by the Professor in the syllabus or in assignments, the use of Generative AI tools (e.g. ChatGPT, Bing, Claude, Bard, etc.) is prohibited throughout the assignment process. The use of generative AI tools without express permission from the Professor may result in a failing grade on the assignment and may also be reported to the University Honor Committee.

AI Policy for this course:

In the most ideal world, you wouldn't use AI for any of this stuff, as many students have done in the past. However, if you have a question, here is a short answer on our AI policy. If further clarification is necessary, please speak with a member of the teaching team.

The Frank Batten School of Leadership and Public Policy embraces and upholds the University of Virginia’s Honor Code principles that mandate that students will not lie, cheat, or steal, and we will not tolerate the actions of those who do. Acting in a manner consistent with the principles of Honor benefits every member of the Batten School community.

We expect every student to comply fully with all provisions of the UVA Honor System. By enrolling in this course, you agree to abide by and uphold the Honor Code System of the University of Virginia. The following applies to your Batten course work and requirements, and unless otherwise specified by your instructors:

• All graded assignments must be pledged.
• Students may not access any notes, study outlines, problem sets, old exams, answer keys, or collaborate with other students without explicit permission.
• When given permission to collaborate with others, students will not copy answers from another student.
• Students should always cite any resources or individuals they have consulted to complete an assignment. If in doubt, sources should be cited. If in doubt please review https://honor.virginia.edu/plagiarism-supplement.
• Suspected violations will be forwarded to the Honor Committee, and, at the discretion of the instructor, students may receive “no credit” for the assignment in question, independent of the actions taken by the Honor Committee.
• Any questions about what is or is not permitted on an assignment should be clarified by students with their instructors prior to the completion of their work.

If you believe you may have committed an Honor Offense, you may wish to file a Conscientious Retraction (“CR”). For your retraction to be considered valid, it must, among other things, be filed with the Honor Committee before you are aware that the Act in question has come under suspicion by anyone. Please contact Batten Honor Representatives if you have questions regarding the Honor System, believe you may have committed an Honor Offense, or would like to report your suspicion of an Honor offense. More information can be found at www.virginia.edu/honor and https://honor.virginia.edu/plagiarism-supplement. Please direct any further questions regarding the course Honor policy to your professor.

Plagiarism

Because of misunderstandings among students about the definition of academic fraud, instructors are encouraged to address this subject in their classes and in their syllabi. Please distribute these standards in writing to the class and post in your course Collab site. You can find some good information about the honor system at UVA and resources for faculty and TAs here: https://honor.virginia.edu/faculty. The Batten School feels very strongly about academic fraud and enforcing the University honor code standards within our School. Faculty should take note that Batten supports the Honor Code and you.

The Frank Batten School has a grade normalization practice, with an emphasis on a well-distributed range of grades. Batten courses aim to have a mean grade that does not exceed a 3.5 grade point average. 

UVA is committed to creating a learning environment that meets the needs of its diverse student body. If you anticipate or experience any barriers to learning in this course, please feel welcome to discuss your concerns with me. If you have a disability, or think you may have a disability, you may also want to meet with the UVA Student Disability Access Center (SDAC), to request an official accommodation. You can find more information about SDAC, including how to apply online, through their website at www.studenthealth.virginia.edu/SDAC. If you have already been approved for accommodations through SDAC, please make sure to send me your accommodation letter and meet with me so we can develop an implementation plan together.

Additional exam time is not given automatically to students whose first language is not English. Dictionaries are permitted, at the discretion of the faculty member.

If you are feeling overwhelmed, stressed, or isolated, several individuals at Batten are ready and want to help. Amanda Crombie, Assistant Dean for Academic Programs, Heather Downs, Director of Academic Operations, and Nicolo Porto, Staff Psychotherapist, are available to support all Batten Students. They are readily accessible during walk-in hours or by setting up an appointment. Additionally, all Batten faculty and staff take student health and safety very seriously. Therefore, as part of their duty to care for distressed individuals, faculty and staff will refer students who threaten self-harm or suicide to appropriately qualified personnel at the earliest opportunity.

Alternatively, there are also other University of Virginia resources available. The Student Health Center offers Counseling and Psychological Services (CAPS) for its students. Call 434-243-5150 (or 434-972-7004 for after hours and weekend crisis assistance) to get started and schedule an appointment. If you prefer to speak anonymously and confidentially over the phone, call Madison House’s HELP Line at any hour of any day: 434-295-8255. Additionally, as part of the student comprehensive health fees, you have 24/7 virtual care through the TimelyCare app.

If you or someone you know is struggling with gender, sexual, or domestic violence, there are many community and University of Virginia resources available. The Office of the Dean of Students, Sexual Assault Resource Agency (SARA), Shelter for Help in Emergency (SHE), and UVA Women’s Center are ready and eager to help.

Policy on infants in the classroom

You are welcome to bring your infant to the classroom as long as they are not distractive to others. Please consult me about a plan on infants.

Pronouns

If you have a preferred pronoun that I may not be aware of, please let me know.

Class Decorum

I aim to create an inclusive environment. If there is something about this environment that makes you feel not-welcomed. Let me know. I expect that you will attend class, having read all the assigned readings. A successful classroom community exists when we all come to class prepared and contribute to the class discussion in a thoughtful, critical, and active manner. Carefully listening to your classmates and building on their contributions will help facilitate a constructive, interactive classroom experience.

Please be respectful of your classmates’ thoughts and opinions. In this course we will explore a variety of socially sensitive topics. We will engage these topics directly but respectfully in order to explore important mechanisms and theories that underlie beliefs and behaviors with respect to policy domains. Consequently, this course will have an emotional impact on many of us. It will require an ability to listen and think, sometimes with as much dispassion as can be mustered. If you are willing to assume that everyone’s perspective is likely to have some merit, however, it is my belief that you will leave this course equipped with strategies for thinking about important and complex social issues.

In addition, please be professional in your communications. Be especially mindful of this over email, where tone is difficult to ascertain (e.g., sending me an email with “hey, I need the lecture slides” is not appropriate).

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