The Computational Social Science Workshop at the University of Chicago cordially invites you to attend this week's talk:

Abstract: In this talk, I will discuss the value of open source methods, workflow, and collaboration in the context of economic policy analysis, academic research, and teaching. The main paper that I hope students will read is the Quantitative Note analyzing the effects of the recent tax reform in the United States. I have also attached the expansive documentation for the open source model underlying that analysis, as well as a recent paper under review that details how we combine rich microsimulation tax data into our large-scale general equilibrium macroeconomic model.

• Economic Policy Analysis: U.S. fiscal policy influences how $3.8 trillion is spent every year and from whom $3.2 trillion in tax revenues are taken. Estimates of the effects of proposed fiscal reforms come from a variety of economic models, ranging partial equilibrium microsimulation models, to reduced-form econometric models, to large-scale general equilibrium macroeconomic models. All of the models used to analyze and predict the effects of new fiscal legislation have hundreds--sometimes thousands--of degrees of freedom. They are also all proprietary and closed source, except for some new models I have contributed to. I will present results from three papers recent papers describing uses of the OG-USA large-scale open source macroeconomic model for policy analysis, the Tax-Calculator microsimulation model of U.S. tax policy, and the TaxBrain web application through which noneconomists can run these models on AWS servers.

• Economic Research: With a renewed emphasis recently in the social sciences on replicability and transparency, open source methods provide an ideal way to help research meet those standards. Furthermore, open source platforms such as GitHub, BitBucket, SVN, and others provide a method of collaboration that should facilitate more efficient collaboration across coauthors regardless of whether the research is open source or closed source.

• Open Source Teaching and Curriculum: I am the director of the Open Source Macroeconomics Laboratory at the University of Chicago and am on the steering committee of QuantEcon. Both organizations provide open source training in computational and theoretical economics, applied mathematics, and data science methods. Open source in teaching and learning can be a powerful gateway to open source research and open source modeling.

A light lunch will be provided by Pizza Capri.

Dr. Evans came to UChicago in the fall of 2016 as a Senior Lecturer for the Masters of Computational Social Science Program, the Director of the Open Source Macroeconomics Laboratory, and a Fellow for the Becker Friedman Institute. Dr. Evans specializes in macroeconomics, public economics, computational economics, and international macroeconomics. Rick was the Co-Founder and Co-Director of the BYU Macroeconomics and Computational Laboratory and one of the original nine members of the Utah Economic Council. Rick is also a former member of the Board of Directors of the Economic Club of Utah, a chapter of the National Association of Business Economics. Aside from his educational experience, Rick began his economic career as a Research Economist at Thredgold Economic Associates in Salt Lake City, providing state and national economic analysis for Zions Bank and their operations in eight western states. He has also spent time as a researcher at the Joint Economic Committee of the US Congress, the Federal Reserve Bank of Dallas, and as an economic consultant. Rick has most recently partnered with the Open Source Policy Center at the American Enterprise Institute in building its large-scale macroeconomic model for dynamic scoring and integrating it with the microsimulation static scoring model. For more information, please visit his homepage.

The 2017-2018 Computational Social Science Workshop meets each Thursday from 11 a.m. to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.

Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the issues page of the workshop's public repository on GitHub. Further instructions are documented in the Computational Social Science Workshop's README on Github.