Scott-Clayton is an active participant in policy working groups at the state and federal level, and she has contributed to the New York Times' Economix and Upshot blogs, focusing on current topics in education.
Students, the syllabus for Fall 2014 EDPE 6023 (Causal Methods in Education Policy Research) is now posted.
Work-in-progress. "Should We Subsidize Student Employment? Conditional Counterfactuals and the Outcomes of Work-Study Participation," NBER Working Paper No. 20329 (with Veronica Minaya).
Forthcoming. "Improving the Targeting of Treatment: Evidence from College Remediation" (with Peter Crosta and Clive Belfield). Accepted in Educational Evaluation and Policy Analysis. Also available as NBER Working Paper No. 18457.
Forthcoming. "Development, Discouragement, or Diversion? New Evidence on the Effects of College Remediation" (with Olga Rodriguez). Accepted in Education Finance and Policy. Also available as NBER Working Paper No. 18328.
Forthcoming. "The Shapeless River: Does a Lack of Structure Inhibit Students' Progress at Community Colleges?" in Baum, S., Castleman, B., & Schwartz, S. (eds.). London: Routledge. Earlier version available as Community College Working Paper No. 25 (January 2011).
2013. "Financial Aid Policy: Lessons From Research" (with Susan M. Dynarski). The Future of Children, 23(1): 67-92.
"What Explains Trends in Labor Supply Among U.S. Undergraduates?"National Tax Journal, vol. 65, no. 1 (March 2012), pp. 181-210. Also available as NBER Working Paper No. 17744
"The Causal Effect of Federal Work-Study Participation: Quasi-Experimental Evidence From West Virginia." Educational Evaluation and Policy Analysis, vol. 33, no. 4 (December 2011), pp. 506-527
"On Money and Motivation: A Quasi-Experimental Analysis of Financial Incentives for College Achievement." Journal of Human Resources, vol. 46 (Summer 2011), no. 3: pp. 614-646.
"Assessing Developmental Assessment in Community Colleges: A Review of the Literature". (with Katherine Hughes). Community College Review, vol. 39, no. 4 (October, 2011), pp. 327-351.
"College Grants on a Postcard: A Proposal for Simple and Predictable Student Aid". (with Susan M. Dynarski).
"The Cost of Complexity in Federal Student Aid: Lessons from Optimal Tax Theory and Behavioral Economics". (with Susan M. Dynarski). National Tax Journal 59:2 (June 2006), pp. 319-356.
Federal Work Study:
This doctoral course covers the design, implementation and interpretation of econometric methods used for evaluating causal relationships in education research. We will read and discuss applied methodological texts as well as journal articles using advanced causal methods. We will cover randomized experiments, natural experiments, differences-in-differences, instrumental variables, regression discontinuity, and propensity score matching. Goals of the course are for students to understand the conceptual underpinnings of each type of study design; to be able to critically evaluate particular studies utilizing of each approach; to gain first-hand experience in formulating causal questions and implementing a causal method; and to develop skills in communicating research designs and findings (in both written and presentation form). Students will be expected to complete all readings and prepare answers to discussion questions in advance of each class. Students will work in teams to replicate and extend a paper using these causal methods and will present findings to the class. The course is designed for second-year PhD students in the Economics and Education program; other doctoral students and advanced masters candidates with appropriate preparation are also welcome, space permitting.
- Graduate-level statistics (at a minimum, multiple regression analysis, familiarity with concepts of statistical bias and precision)
- Microeconomics (e.g. exposure to concepts of consumer theory, producer theory, equilibrium analysis, market failure, welfare analysis, choice under uncertainty)
- Students with any questions about their preparation after the first day of class are encouraged to contact the professor for further guidance.
- To understand the conceptual underpinnings of current methods for causal inference
- To be able to read and critically evaluate papers that utilize these methods
- To gain first-hand experience formulating causal questions and implementing causal methods
- To develop skills in communicating research designs and findings in both written and oral form
- To encourage and facilitate collaborative learning and teaching between students
- Graduate-level microeconomics (e.g. concepts of consumer theory, partial equilibrium, choice under uncertainty, welfare analysis)
- Graduate-level statistics and/or econometrics (at a minimum, regression analysis, familiarity with concepts of statistical bias and precision)
- A course in causal inference is strongly recommended as a prerequisite, but not required
- To understand and be able to explain key theoretical concepts in labor economics
- To be able to read and critique papers that test these concepts empirically
- To understand the strengths and limitations of methodological tools commonly used in the field
- To apply concepts from the course to examine a research question of the student’s choosing
2005-2008 National Science Foundation Graduate Research Fellowship (awarded 2003)
Documents & Papers
Download: CV_JScottClayton_04-24-2012_long.pdf [PDF]
Download: Hamilton paper [PDF]
Download: CausalMethods Syllabus 2014 [PDF]
Download: August2014CV [PDF]
Centers and Projects