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NEW YORK UNIVERSITY
ROBERT F. WAGER GRADUATE SCHOOL OF PUBLIC SERVICE

PADM-GP 2902: MULTIPLE REGRESSION AND INTRODUCTION TO ECONMETRICS
SPRING 2023

INTSTRUCTOR INFORMATION
Kaitlyn O’Hagan
Email: koh210@nyu.edu
Office Hours: By Appointment, please email
LECTURES: Thursday, 10:00AM – 11:40AM
LOCATION: 238 Thompson Street, Room 269
Matías Morales
Email: mim313@nyu.edu
Office Hours: By Appointment, please email
LECTURES: Thursday, 6:45PM-8:25PM
LOCATION: GCASL, Room 361

TEACHING COLLEAGES (TC)
Lydia Ruddick-Schulman
Email: lbr2544@nyu.edu
Recitation: Mondays 12:30PM-1:30PM
Office Hours: Tuesdays 12PM-1PM
(every other week)
Adelaide Currin
Email: acc7905@nyu.edu
Recitation: Tuesdays 8:35-9:35PM
Office Hours: Fridays 1PM-2PM
(every other week)
TC-led recitations and office hours are virtual.
COURSE DESCRIPTION
Multiple regression is the core econometric technique used by policy and financial analysts. In
this course, you learn how to use and interpret this critical statistical method. Specifically, you
learn how to build and estimate multiple regression models, how to evaluate whether regression
coefficients are biased, whether standard errors (and thus t statistics) are valid, and whether
regressions used in policy and finance studies support causal arguments.
In addition, employing one consistent dataset for all your computer exercises, you perform
statistical analyses discussed in class using Stata, an econometric statistical package, and you see
how the results reflect econometric concepts. Finally, with a group of your classmates and project
datasets provided by your professor, you do a project that involves estimating your own
regression model and applying the techniques we learn in class.
PREREQUISITE: CORE-GP 1011 or equivalent
COURSE LEARNING OBJECTIVES
• Understand what an Ordinary Least Squares (OLS) regression does and why it is useful.
• Write and interpret mathematical equations representing various regression models.
• Interpret regression results as they are typically represented in statistical software
packages, policy and finance papers, and academic articles.
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• Use Stata and regression techniques to suggest answers to important policy questions.
• Think critically about the assumptions underlying your (or another analyst’s)
interpretation of regression output and test whether these assumptions hold.
• Conduct a research project in which you formulate, estimate, write about, and present an
econometric model.
• Understand the statistics that underlie research in your field of interest.
RECITATIONS (Virtual):
Attendance is optional by highly recommended. In these sessions you:
• review the answers to the problem set and computer exercises due the previous week
• discuss the learning objectives of the problem set and computer exercises due the
following class
The TCs also offer one hour of office hours per week (see course schedule).
There are no problem sets or computer exercises due in the first week of class, so the first week
of classes there will be a STATA tutorial/refresher during the recitation on Monday January 23
(12:30-1:30PM) and during TC office hours on Friday January 27 (1:00-2:00PM).
COURSE MATERIALS
REQUIRED: A.H. Studenmund, Using Econometrics: A Practical Guide. ISBN: 9780134182742
• Unfortunately, the text is not available electronically from NYU Libraries (though you can
ask them to scan a limited number of pages/chapters for you).
REQUIRED: STATA/BE. You can purchase this and install it on your personal computer or use it
from NYU’s virtual lab.
• Purchase: Use this link to obtain a student discount. The least expensive option is a 6-
month license. If you are planning to take Estimating Impact, Advanced Empirical
Methods, or the Research Capstone you may want to consider an annual or perpetual
license. https://www.stata.com/order/new/edu/profplus/student-pricing/
• Virtual Lab: You can log into NYU’s virtual computer lab (VCL) here:
https://www.nyu.edu/life/information-technology/instructional-technology-
support/instructional-technology-tools-and-services/virtual-computer-lab.html
o Here’s a review on how to use STATA on the VCL:
https://nyu.app.box.com/s/zp39zryd56u1rbnxxit61ylpqiez3yuq
REQUIRED: NYU BRIGHTSPACE. All announcements and class-related documents (lecture power
points, datasets for the final project, problem sets, computer exercises, assignment solutions,
STATA review materials, and exam review materials) are available on Brightspace. Problem sets
and computer exercises are to be submitted via Assignments in Brightspace.
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COURSE REQUIREMENTS AND GRADING
• 20% Problem Sets and Computer Exercises
• 35% Midterm Exam
• 45% Regression Project
Students are expected to attend all of the lectures and actively participate. Please email your
instructor if you are unable to attend class due to extenuating circumstances.
PROBLEM SETS AND COMPUTER EXERCISES (20%)
There are 15 total problem sets (PS) and computer exercises (CE), named for the class in which
they’re due. We will drop the lowest two from your grade. Due to this flexibility we will not accept
late assignments; please contact me if you have extenuating circumstances. You must complete
PS 9 and CE 9; these cannot be dropped from your grade.
Problem sets/computer exercises are graded for completion, not correctness. Students should
take these assignments seriously as they’re good preparation for the exam and final project.
For the STATA code and output for computer exercises, submit the log file with the last “run” of
the analysis as a PDF. Please submit written answers to computer exercises and problems sets as
a Word file.
MIDTERM EXAM (35%)
An exam will be given during Class 11 on April 20th (see course schedule on the following page).
You may use a non-graphing calculator and two pages (single-sided) of notes.
GROUP PROJECT (45%)
In groups of 4-5 you will conduct a regression analysis, present your results, and write a paper.
Note all group members will complete peer evaluations that will factor into grades.
• Fill out Project Data Preference Form by EOD Thursday, February 2nd.
• Read Chapter 11, “Running Your Own Regression Project”, in the course text.
• Once groups have been assigned, meet with your group as soon as possible to plan the paper.
Teams must email me the question you propose to answer and at least one specification that
will be estimated by Thursday, March 2nd.
• Contact your instructor to meet with your group during the week of March 20th to discuss the
project. You should have descriptive statistics and initial results.
• Present your results during class April 27th or May 4th to get feedback.
• Write an 8–10-page paper, including two tables, organized as follows (tables do not count in
the page limit). DUE THURSDAY MAY 11. We also ask students to submit a group evaluation
form, to help ensure that all group members participate equally in the final project.

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FINAL PROJECT OUTLINE
1. Introduction: What is the goal of your regression study? Why is it interesting? Why do
we care? (This does not have to be momentous, but you should explain why the
results could be interesting or valuable.)
2. Data: Describe your sources and discuss the descriptive statistics in Table 1.
3. Model and Empirical Strategy: What is your model (equation) and how does it achieve
the goal of your analysis? Why are the specific variables used and measured as they
are? Do you have any prior expectations about the signs of coefficients? How will you
estimate the model? (Usually OLS with fixed effects.)
4. Results: Discuss the Results presented in Table 2.
5. Conclusions: What does your model say about your goal or issue? What is the next
step in this research?
6. Appendix:
i. Table 1 (with good, descriptive title): Descriptive statistics of all the variables
in your model(s).
ii. Table 2 (with good descriptive title): Results of your models, presented in 4-5
columns.
iii. Final annotated Stata log file of your results (note this should be “clean”, i.e.
contain no errors).
ACADEMIC INTEGRITY
Academic integrity is a vital component of Wagner and NYU. Each student is required to abide by
Wagner’s Academic Code. Plagiarism of any form will not be tolerated. Every student is expected
to maintain academic integrity and is expected to report violations to us. If you are unsure about
what is expected of you, please ask.
WRITING CENTER
NYU Wagner provides writing tutors free of charge to assist students—in person or online—with
their writing assignments. Beyond a general expertise in writing skills, NYU Wagner Writing
Tutors specialize in public policy-specific formats and can assist students at any point in their
writing process—from initial concept brainstorming and mid-paper writer’s block, to first draft
clarity and coherence checks and final draft line edits. Email appointments are a fantastic way to
get extensive feedback on a deep read of your paper. In-person and video chat appointments are
best used as a way to talk through a writing block, an organizational issue or something else. To
learn more about Wagner's writing tutors and to make an appointment, visit the Wagner Writing
Center site.
HENRY AND LUCY MOSES CENTER FOR STUDENTS WITH DISABILITIES AT NYU
Academic accommodations are available for students with disabilities. Please visit the Moses
Center for Students with Disabilities (CSD) website at www.nyu.edu/csd and click on the
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Reasonable Accommodations and How to Register tab or call or e-mail CSD at 212-998-4980 or
mosescsd@nyu.edu for information. Students requesting academic accommodations are
strongly advised to reach out to the Moses Center as early as possible in the semester.
NYU’S CALENDAR POLICY ON RELIGIOUS HOLIDAYS
NYU’s Calendar Policy on Religious Holidays states that members of any religious group may,
without penalty, absent themselves from classes when required in compliance with their
religious obligations. Please notify us in advance of religious holidays that might coincide with
exams to schedule mutually acceptable alternatives.
WELLNESS EXCHANGE
The Wellness Exchange is your greatest mental health resource at NYU. Call the 24-hour hotline
at (212) 443-9999, chat via the Wellness Exchange app anytime, make an appointment, or
arrange a same-day Urgent Counseling session to speak with a certified counselor about any day-
to-day challenges or health concerns, including medical issues, stress, depression, sexual assault,
anxiety, alcohol or drug dependence, and eating disorders. No concern is too big or too small.
Worried about a friend? Our counselors are here for that too — in person, over the phone, or
through chat. The Wellness Exchange is here for you, whatever the reason. Not sure which option
is right for you? Call or chat with our counselors to discuss your options and find the right fit. Not
interested in phone, chat or Urgent Counseling? Email wellness.exchange@nyu.edu.
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Class Date Lecture
Reading (Due Before
Class)
HW (Due Before
Blass)
Recitation
TC Office
Hrs.
1 Th 1/26
OLS Bivariate Regression Model with
Error Term
Ch.1
Ch. 2.1, 2.3-2.6
Student Info Form
M 1/23
Tu NONE
F 1/27
2 Th 2/2
OLS Multiple Regression and
Assumptions about Error Term
Ch. 2.2
Ch. 4
PS2
Project Form
M 1/30
Tu 1/31
Tu 1/31
3 Th 2/9
Hypothesis Testing in Multiple
Regression Context
Ch. 3.1, 3.2
Ch. 5
PS3
CE3
M 2/6
Tu 2/7
F 2/10
4 Th 2/16
Functional Form Part I: Polynomials
and Indicator Variables
Ch. 6; Ch. 3.3
Ch. 7.1, 7.2, 7.4
PS4
M 2/13
Tu 2/14
Tu 2/14
5 Th 2/23
Functional Form Part II: Interactions
and Logarithmic Transformations
Ch. 7.2, 7.3, 7.5, 7.6
PS5
CE5
M NONE
Tu 2/21
F 2/24
6 Th 3/2 Multicollinearity and Autocorrelation
Ch. 8
Ch. 9
PS6
CE6
Project Check-in
M 2/27
Tu 2/28
Tu 2/28
7 Th 3/9 Heteroskedasticity Ch. 10
PS7
CE7
M 3/6
Tu 3/7
F 3/10
Th 3/16 SPRING BREAK – NO CLASS NONE NONE
Th 3/23 Group Meetings with Instructors Ch. 11 Project Check-in NONE Tu 3/21
8 Th 3/30 Panel Data Estimation Part I Ch. 16
PS8
CE8
M 3/27
Tu 3/28
Fr 3/31
9 Th 4/6
Panel Data Estimation Part II; Linear
Probability Models
Ch. 13
PS9
CE9
M 4/3
Tu 4/4
Tu 4/4
10 Th 4/13
Intro. to Experimental & Quasi-
Experimental Methods / Exam Review
TBD CE 10
M 4/10
Tu 4/11
Fr 4/14
11 Th 4/20 EXAM
M 4/17
Tu 4/18
Tu 4/18
12 Th 4/27 Group Presentations Presentation F 4/28
13 Th 5/4 Group Presentations Presentation Tu 5/2
Th 5/11 Final Paper Due
Final Paper &
Group Eval. Form



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