This is a periodic newsletter of the interesting things we’ve seen and what we are thinking about in open source policy analysis.
Breaking down Joe Biden’s tax plan with OSPC-incubated models. In a new report, Jason DeBacker (University of South Carolina), Richard Evans (Rice University), and Kyle Pomerleau (AEI) used Tax-Calculator and OG-USA to analyze the revenue and macroeconomic effects of Joe Biden’s tax plan. The authors found that the Biden proposal would raise federal revenue by $3.8 trillion over the next decade, much of which would be a result of increased taxes on the top 1 percent of income earners. On the macroeconomic side, the authors estimate that the Biden plan would cause a slight decrease in GDP over the next decade and would not significantly affect the federal government’s short-run and long-run debt burden. Link
Contact tracing comes to Germany. In our last newsletter, we discussed Italy’s progress on developing an open-source contact tracing app for COVID-19. Now, Germany has developed and open sourced its own contact tracing app. To alleviate privacy concerns, the app does not collect user data in a centralized repository. Instead, the app stores relevant information locally, and cell phones use bluetooth to communicate with other nearby devices. The app is available for public use as of June 16. Link
An algorithmic approach to legislative redistricting. Concerns regarding partisan gerrymandering grow stronger as state legislatures gear up to redraw legislative district lines following the 2020 Census. As a tool to understand gerrymandering, the open-source project Antimander features interactive maps and optimizing software that generates hypothetical congressional districts based on user inputs. The algorithm takes factors such as geographical compactness, statewide political affiliation, and election competitiveness when finding the “optimal” districting. Link
A meta-analysis of open research. An OECD working paper reports the results from its survey of scientific authors on their digital practices. The results offer insights regarding researchers’ tendencies to open source their code, broken down by country of origin and academic discipline. Overall, approximately 40 percent of authors report using repositories to share data or code, but only 30 percent of authors in economics and related disciples report sharing their data or code. Link
Upcoming webinars on reproducibility. Next week’s annual Western Economic Association International meeting will feature two presentations about replicability in computational social science research. Fernando Hoces de la Guardia (UC Berkeley) will give a presentation titled “How to Teach Reproducibility in Classwork,” followed by a presentation from Lars Vilhuber (American Economics Association) titled “Reproducibility: Lessons Learned.” The presentations will begin at 12:15 p.m. ET on June 27 and will be free to stream. Link
Edited by Matt Jensen and Peter Metz