COMPUTATIONAL SOCIAL SCIENCE SEMINAR-Introduction to The Economics ARK (Algorithmic Repository and toolKit)-Carroll
COMPUTATIONAL SOCIAL SCIENCE FRIDAY SEMINAR
Christopher Carroll, Professor
Department of Economics
Johns Hopkins University
Title: Introduction to The Economics ARK (Algorithmic Repository and toolKit)
The Econ-ARK/HARK toolkit is a modular and extensible open source toolkit for solving, simulating, and estimating heterogeneous-agent (HA) models in economics and the social sciences. Although the value of models of this kind has been clear both to academics and to policymakers for a long time, the code for implementing such models has so far been handcrafted and idiosyncratic. As a result, it may take years of human capital development for a new researcher to become proficient enough in these methods to contribute to the literature. The seminar will describe how the Heterogeneous Agents Resources and toolKit (HARK) eases this burden by providing a robust framework in which canonical examples of such models are solved. The toolkit provides object-oriented tools for representing heterogeneous agents, solution methods for solving or characterizing their dynamic choice problems, and a framework for representing the environment in which agents interact. The aim of the toolkit is to become the go-to resource for heterogeneous agent modelers, by providing a well-designed, well-documented, and powerful platform in which they can develop their own work in a robust and replicable manner.
I am a professor of economics at JHU and co-chair of the National Bureau of Economic Research’s working group on the Aggregate Implications of Microeconomic Consumption Behavior. Originally from Knoxville, Tennessee, I received my A.B. in Economics from Harvard University in 1986 and a Ph.D. from the Massachusetts Institute of Technology in 1990. After graduating from M.I.T., I worked at the Federal Reserve Board in Washington DC, where I prepared forecasts for consumer expenditure. I moved to Johns Hopkins University in 1995 and also spent 1997-98 working at the Council of Economic Advisors in Washington, where I analyzed Social Security reform proposals, tax and pension policy, and bankruptcy reform. Aside from my current work at Hopkins and the NBER, I am also an associate editor at the Review of Economics and Statistics,(ReStat) the Journal of Business and Economic Statistics, (JBES) and the Berkeley Electronic Journal of Macroeconomics (BEJM).
My research has primarily focused on consumption and saving behavior, with an emphasis on reconciling the empirical evidence from both microeconomic and macroeconomic sources with theoretical models. (In addition to articles in economic journals, I’ve authored Encyclopedia Britannica articles on consumption related topics.) My most recent research has focused on the dynamics of expectations formation, particularly on how expectations reflect households’ learning from each other and from experts. This focus flows from a career-long interest in consumer sentiment and its determinants.
CSS PhD Student
Title: Mesa, Agent-based modeling library in Python 3
Python has grown significantly in the scientific community, but there is no tool or reusable framework to do agent-based modeling (ABM) in Python. While there are well-established frameworks in other languages, the lack of one in the Python language is at odds with the growth of Python in the scientific community. As a result, we created an ABM framework called Mesa in Python 3 with sustained contributions. Mesa is built to be modular, so the backend server, the frontend visualization and tooling, the batch runner, and the data collector are each separate components that can be upgraded independently from each other. In addition to this, Mesa is extensible and meant to be decoupled from domain specific add-ons. This empowers the community to develop features and add-ons independent of the core Mesa library. In this talk, Jackie will set the stage for her Ph.D by providing an overview Mesa’s past, present, and proposed future, along with how that fits in the ABM ecosystem of other tooling.