Advance Quantitative Methods
Tues 9:50 to 12:30pm
Instructor:
Spring 2014
CSB112
Professor William M. Rodgers III
wrodgers@ejb.rutgers.edu
Office Hours:
Instructor:
M and T, 1:00pm to 2:00pm
W, 1:00pm to 2:30pm
By Appointment
Overview
The purpose of the course is to understand a variety of advanced econometric theories and apply
them to estimate the impact of policies and laws. The course’s capstone experience will be the
completion of a “peer review” style research paper on a question of interest to the student.
After completing the course, students will have answers to the following questions:

What tools do social scientists use to distinguish between correlation and causality?

How are law and policy changes used to estimate causal empirical relations?

What are the benefits of using panel (pooled cross section and time series) data versus
cross section?

How does measurement error impact the quality of one’s estimates? How do we
minimize its adverse impact?

How do researchers estimate models where the dependent variables are discrete
outcomes, such as employment or duration of unemployment?
These and other questions are the focus of this course which introduces students to advanced
quantitative methods used to perform policy analysis. Events such as natural disasters, law
changes, regional, state and municipal variation have become popular ways to assess whether a
policy has a causal impact on an outcome.
Textbooks
*Peter Kennedy, Guide to Econometrics, 6th Edition, The MIT Press, Cambridge, MA, 2003.
*William H. Greene, Econometric Analysis, 6th Edition, Prentice Hall, Upper Saddle River, NJ,
2007
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Grading, Communication and Academic Integrity Policies
Four Problem Sets (30%)
Throughout the semester, we will have problem sets. The exercises will consist of answering
theory, empirical, and computer-based questions, which you are encouraged to complete with
your classmates (still submit your own original copy). The purpose of the exercises is to make
sure that students are learning the underlying theory presented in the lectures and are able to
utilize STATA to apply the knowledge.
Two Midterm Exams (30%)
In class exam that covers the theoretical and empirical work covered in the first half of the
semester.
Empirical Paper (40%)
Students will construct a journal style 20-25 page (this does not include tables and charts)
empirical paper that performs a descriptive analysis of a planning, policy or public health
question, or evaluates a public policy or program.
These manuscripts can serve as dissertation chapters or writing samples that can be used during
job searches. I will work with students that want to revise them for conference presentation and
publication in a peer-reviewed journal.
Due Dates:
1/28
1-Page Proposal Due
(Scholarly Motivation, 2-3 questions/hypotheses)
By 2/11
Meet 1 to 2 times with Rodgers to discuss proposal
(Refine question(s), identify data, and method of analysis)
2/18
Problems Set #1 Due
2/25
In class midterm #1
3/4
Literature Review Table
Revised hypotheses/method/data
3/11
Problem Set #2 Due
3/18
Rutgers Spring Break
4/1
Problem Set #3 Due
4/8
In class midterm #2
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4/15
No Class
4/29
Problem Set #4 Due
Last 2 weeks in April
Writing the manuscript
5/7
20-25 Page Empirical Paper
Communication:
All readings, course updates and other announcements will be posted on the course website. You
should have received an e-mail with a password and instructions on how to login to the course
website. If you've not, this is most likely due to the fact that you are either not using your
Rutgers assigned e-mail or registered for the course.
Integrity Policies:
Academic and intellectual integrity is not only at the center of the policymaking process, but are
also values of the Bloustein and Rutgers communities. Because of this, we will hold all students
to the following standards:
o Prompt arrival at all course sessions and meetings (random attendance will be taken)
o Attendance, participation, and respectful behavior in all sessions
o No use of cell phones and instant messaging during lectures, discussion groups, quizzes
and exams
Statement on Academic Honesty:
All members of our community must be confident that each person’s work has been responsibly
and honorably acquired, developed, and presented. Any effort to gain an advantage not given to
all students is dishonest whether or not the effort is successful. We view a violation of academic
honesty as a breech of trust, and will result in a “Fail” in this class, as well as possible
suspension or expulsion from the institution. When in doubt about plagiarism, paraphrasing,
quoting, or collaboration, consult the course instructors.
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Course Topics
Review of Classical Regression Model (Single Variable Case)
Application: Expenditure-Income Relationship
Matrix Algebra-The Basics
Review of Classical Regression Model (Multiple Variable Case)
Application: The Earnings Equation
Establishing Causality: Instrumental Variables and Two Stage Least Squares
Application: Impact of Vietnam Service on civilian earnings
Establishing Causality: Natural Experiments
Application: Mariel Boat Lift
Establishing Causality: Matched Pair Analysis
Application: Job Training
Errors-in-variables
Application: Economic Returns to Schooling
Sample Selection: Endogenous Right-hand Side Variables
Application:
Sample Selection: Truncation and Censored Data
Application: TBD
Pooled Cross Section and Time Series Models
Application: Economic Growth Models
Pooled Cross Section and Time Series Models cont.
Application: National Longitudinal Survey of Youth
Duration Models
Application: Unemployment Duration
Macro Variables in a Micro Equation
Application: Wage Curve Analysis
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I.
Introduction
Review of Classical Regression Model (Single Variable Case)
Text: Consult your previous methods books
Application: Expenditure-Income Relationship
Computer Note #1: Analysis of Consumer Expenditure Data
“The Pitfalls of Using a Child Support Schedule Based on Outdated Data,” Family Economics
and Nutrition Review, 16:2, 2004 (with Yana V. Rodgers) (Published in 2005).
2.
Matrix Algebra-The Basics
Text: Greene 7th Edition, Appendix A
Computer Note #2: Solving for the Least Squares Estimator
3.
Review of Classical Regression Model (Multiple Variable Case)
Text: Greene, Chapters 2-5
Application: The Earnings Equation and Decompositions
Computer Note #3: Estimating the returns to schooling and experience, and decomposing racial
and gender earnings gaps
Maxwell, Nan L. 1994. "The Effect on Black-White Wage Differences of Differences in the
Quantity and Quality of Education." Industrial and Labor Relations Review, Vol. 47, No. 2
(January), pp. 249-64.
Neal, Derek A., and William R. Johnson. 1996. "The Role of Premarket Factors in Black-White
Wage Differences." Journal of Political Economy, Vol. 104, No. 5 (October), pp. 869-95.
Rodgers, Yana van der Meulen, “A Primer on Wage Gap Decompositions in the Analysis of
Labor Market Discrimination,” in Handbook on the Economics of Discrimination, Edited by
William M. Rodgers III, Edgar Elgar Publishers: Northampton, MA, 2006.
4.
Establishing Causality: Instrumental Variables and Two Stage Least Squares
Text: Greene, Chapter 8
Application: Impact of Schooling on Earnings
Computer Note #4: Analysis of Census Data
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Angrist, Joshua D. and Krueger, Alan B. “Does Compulsory School Attendance Affect
Schooling and Earnings,” Quarterly Journal of Economics, November 2001, v. 106:4, pp. 9791014.
Angrist, Joshua D. and Krueger, Alan B. “Instrumental Variables and the Search for
Identification: From Supply and Demand to Natural Experiments,” Journal of Economic
Perspectives, Fall 2001, v. 15, pp. 69-85.
5.
Establishing Causality: Natural Experiments
Text: Class Notes, Greene, pp. 251-254
Application: Impact of the Mariel Boatlift on the Miami Labor market.
Computer Note #5: Replication of Card (1990).
Card, David. “The Impact of the Mariel Boatlift on the Miami Labor Market,” Industrial and
Labor Relations Review, January 1990, v. 43, iss. 2, pp. 245-57.
Zimmerman, David J., “Peer Effects in Academic Outcomes: Evidence from a Natural
Experiment,” February 2003, Vol. 85, No. 1, Pages 9-23.
Card, David and Alan B. Krueger. Minimum Wages and Employment: A Case Study of the FastFood Industry in New Jersey and Pennsylvania. American Economic Review. Vol. 84 (4). p 77293. September 1994.
Council of Economic Advisors, “The Economic Impact of the American Recovery and
Reinvestment Act of 2009 Eighth Quarterly Report” December 9, 2011.
6.
Establishing Causality: Matched Pair Analysis
Text: TBD
Application: Job Training
Computer Note #6: Analysis of NLSY job training data
Heckman, James and Jeff Smith. “Assessing the Case for Social Experiments,” Journal of
Economic Perspectives, 9 (Spring 1995): 85-110.
7.
Errors-in-variables and Proxy Variables
Text: Greene, Chapter 8, pp. 239-250
Application: Economic Returns to Schooling
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Computer Note #7: TBD
Ashenfelter, Orley and Cecilia Rouse, “Income, Schooling and Ability: Evidence from a New
Sample of Identical Twins,” Quarterly Journal of Economics 113 (February 1998): 253-284.
8.
Sample Selection: Endogenous Right-hand Side Variables
Text: Greene, Chapters 8 and 10
Application: Geographic Mobility and Returns to Immigration
Computer Note #8: Analysis of the 1970 to 2000 NJ US Census
*Borjas, George J. “Self-Selection and the Earnings of Immigrants,” American Economic Review
77 (September 1987): 531-553.
Chiswick, Barry R. “The Effect of Americanization on the Earnings of Foreign-Born Men,”
Journal of Political Economy 86 (October 1978): 897-921.
9.
Sample Selection: Truncation and Censored Data
Text: Greene, Chapter 19
Application: Labor Supply (wage and hours equations)
Computer Note #8: Analysis of Current Population Survey
Kaplan, E. (2012). Estimating the Duration of Jihadi Terror Plots in the United States. Studies In
Conflict & Terrorism, 35(12), 880-894.
10.
Pooled Cross Section and Time Series Models
Text: Greene: Chapter 11
Application: Marital Wage Differential and the Family Gap
Computer Note #9: Analysis of the NLSY
“The Male Marital Wage Differential: Race, Ability, and Training,” Economic Inquiry, 48:3,
July 2010, (with Leslie S. Stratton).
*Waldfogel, Jane. “Understanding the “Family Gap” in Pay for Women with Children,” The
Journal of Economc Perspectives, Volume 12, Issue 1 (Winter, 1998): 137-156.
11.
Duration Models
Text: Greene, Chapter 19
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Application: Unemployment Duration
Computer Note #10: Analysis of the CPS Dislocated Worker Survey
Pedace, R., & Rohn, S. (2011). The Impact of Minimum Wages on Unemployment Duration:
Estimating the Effects Using the Displaced Worker Survey. Industrial Relations, 50(1), 57-75.
12.
Macro Variables in a Micro Equation
Text: Class Notes
Application: Wage Curve Analysis
Computer Note #10: Merging BLS local area unemployment rate to micro wage data
Aaronson, D., & Sullivan, D. (2000). Unemployment and wage growth: Recent cross-state
evidence. Economic Perspectives, 24(2), 54.
Hines, James R. Jr., Hilary W. Hoynes and Alan B. Krueger, “Another Look at Whether a Rising
Tide Lifts All Boats” in Roaring Nineties: Can Full Employment Be Sustained?, edited by Alan
B. Krueger and Robert Solow, The Russell Sage Foundation and The Century Foundation Press:
New York, 2001: 493-537.
Freeman, Richard B. and William M. Rodgers III, “Area Economic Conditions and the Labor
Market Outcomes of Young Men in the 1990s Expansion,” in Prosperity for All: The Economic
Boom and African Americans, edited by William M. Rodgers and Robert Cherry, The Russell
Sage Foundation and The Century Foundation Press: New York, 2001: 50-87.
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Advanced Quantitative Methods
W. Rodgers
Spring Semester 2014
Name____________________________________
Background Information
1.
In what degree program are you enrolled? ______________
2.
How far along are you in the program?_________________
3.
Why did you enroll in this course?
4.
What are your goals for the semester?
5.
Describe the type of math courses that you have taken?
6.
In what areas of policy or planning are you most interested? Why?
7.
Describe the type of statistics and econometrics courses that you have taken?
8.
Is there anything about you that I should know? (e.g., potential conflicts)
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Advanced Quantitative Methods
W. Rodgers
Spring Semester 2014
Developing Your Research Prospectus
What is our goal for this research paper assignment?
1. Develop an original piece of research that utilizes existing data (e.g., CPS) or creates a data
set and does one of the following:
a. Provides the empirical analysis to help inform a policy discussion
Trends and causes in recent wage inequality growth
Impact of recession and/or slow recovery on different demographic groups
What’s broken with the U.S. jobs machine?
b. Estimates the impact of a law or program
Impact of $787 billion ARRA funds on employment
Effect of minimum wage increase on food security
Impact of ACA on employment
Impact of Super Storm Sandy funds
How do you find a topic?
1. Class lectures and syllabi
a.
Professor alludes to unresolved issue
b.
Outdated study- need to update
c.
Replication of past study
2. Newspaper articles
a.
Chapter of my dissertation came from seeing an article in the Boston Globe
3. Journal articles
a.
Update or replicate past study on syllabus
b.
Read Literature Reviews (JEL and Journal of Economic Perspectives)
Building literature review (finding related studies):
1.
2.
3.
4.
JSTOR and EconLit (Internet)
Google Scholar
References in papers on syllabus
References in studies that you read
What should your 250 word proposal contain?
The prospectus should contain a question (actually narrower the better), a motivation for the question, and
brief summary of literature to date (what we know and don’t know about the question).
**I am happy for students to link their projects in other courses to this course. However, there needs to be
a feature that distinguishes the projects from one another.**
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