Paper Title Number 1
Date:
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Posts by Collection
publications
Paper Title Number 2
Date:
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Date:
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
research
Contract Enforcement and Group Formation
Date:
PhD research at American University, building an agent based model in Python to simulate the contract enforcement problem of the Maghribi Traders, as modeled in the game theory work of Grief 2006.
Spark for Social Science
Date:
Research Programming at the Urban Institute: The platform, tools, and lessons to help bridge the gap between social science researchers and the big data methods used in data science.
National Center for Charitable Statistics IRS Core Files
Date:
Center on Nonprofits and Philanthropy at the Urban Institute: Converting an outdated process of mixed manual and SQL code into a seamless 4,000-line Python script, in order to build the NCCS IRS Core Files.
DC Courts Web Scraping
Date:
Justice Policy Center at the Urban Institute: Responsibly automating millions of connections to the DC Courts website in order to retrieve and parse public data.
Education Data
Date:
Income and Benefits Policy Center at the Urban Institute: Using Python to seamlessly maintain a network of datasets across Stata, SQL and S3 formats.
Parole Officer Text Messages
Date:
Metro Policy Center at the Urban Institute: A project studying a proprietary dataset of text messages between parole officers and parolees.
Essays on Uncertainty and Macroeconomic Dynamics
Published: American University, 2021
My Ph.D dissertation. See details within.
State-level Economic Policy Uncertainty
Published: Journal of Monetary Economics, 2022
We quantify and study state-level economic policy uncertainty. Tapping digital archives for nearly 3500 local newspapers, we construct three monthly indexes for each state: one that captures state and local sources of policy uncertainty (EPU-S), one that captures national and international sources (EPU-N), and a composite index that captures both. EPU-S rises around gubernatorial elections and own-state episodes like the California electricity crisis of 2000–01 and the Kansas tax experiment of 2012. EPU-N rises around presidential elections and in response to 9–11, Gulf Wars I and II, the 2011 debt-ceiling crisis, the 2012 fiscal cliff episode, and federal government shutdowns. Close elections elevate policy uncertainty much more than the average election. VAR models fit to pre-COVID data imply that upward shocks to own-state EPU foreshadow weaker economic performance in the state, as do upward EPU shocks in contiguous states. The COVID-19 pandemic drove huge increases in policy uncertainty and unemployment, more so in states with stricter government-mandated lockdowns.
Press: Vox EU
Recommended citation: Baker, Scott R., Steven J. Davis, and Jeffrey A. Levy. "State-level economic policy uncertainty." Journal of Monetary Economics 132 (2022): 81-99 https://doi.org/10.1016/j.jmoneco.2022.08.004
Causal Effects of Uncertainty: Evidence from Military Base Realignment and Closures
Date:
Working paper pending.
Presentations:
5th Biennial Conference, Padua, Italy (September 21st 2023): Uncertainty, Economic Activity, and Forecasting in a Changing Environment link
SITE 2023, Stanford University (September 8th 2023): The Macroeconomics of Uncertainty and Volatility link
Recommended citation: Levy, Jeffrey A., Gabriel P. Mathy, and Xuguang Simon Sheng. Causal Effects of Uncertainty: Evidence from Military Base Realignment and Closures (2023)
talks
Contract Enforcement and Group Formation: An Agent Based Model of the Maghribi Traders
Date:
Presentation of an agent based model I developed in Python of the game theory work of Avner Greif.
Python Brown Bag
Date:
Presentation to researchers at the Urban Institute on how and why to use Python in their research. More information here
Regional Variation in Economic Uncertainty
Date:
Presentation of early dissertation results, on the variation of news-based economic uncertainty at sub-national levels.
Spark for Social Science
Date:
Tutorial and discussion on using the Apache Spark distributed computing system with big data for social science researchers. More information here.
Spark for Social Science
Date:
Tutorial and discussion on using the Apache Spark distributed computing system with big data for social science researchers. More information here.
Introduction to Machine Learning for Economists
Date:
Guest lecture on the basics of machine learning given to finance students at the University of Science and Technology of China. Notebook available here
From New Graduate to Analyst: Making the Transition
Date:
This is a panel discussion I began in 2021, and hold again every fall quarter.
Code Sample Workshop: MATLAB
Date:
In this 2-hour lab, students with prior experience in Python or R will work with Professor Jeff Levy to learn what makes a good code sample, and the merits and usage of the MATLAB language. We will then go over some similarities and differences between MATLAB and R/Python, and conclude with group work developing our own simple data analysis program in MATLAB. Students will end this time with an understanding of how to leverage their Python/R experience to work in the MATLAB syntax, and with a working code sample suitable to include in job applications.
teaching
Teaching
Assistaint Instructional Professor, Harris School of Public Policy, 2023
I am passionate about teaching good data and programming skills to researchers. Many programs in the social sciences teach multiple semesters of statistcs or econometrics while paying scant attention to dealing with data in a rigorous way, despite the fact that successful research requires both. This has become my niche at the Harris School, where I designed and regularly teach three of the core courses in the Certificate in Data Analytics program for MPP students.