Wilfred Mertz

Wilfred Mertz


The Potential Partnership Between Economics and Computational Science

The Potential Partnership Between Economics and Computational Science by Dr, Kenneth Judd

Economists use very few modern computational tools, most confining their research to what they can do on their laptop with Matlab. I will describe some examples where economists and computational scientists have worked to push economics into the third millennium. First, I will describe DSICE, an Integrated Asset Model of the social cost of capital that incorporates both economic and climate uncertainties. Second, an advance in degenerate programming which now allows us to solve complex optimal tax problems. Third, applications of polynomial system solution methods to greatly increase the range of economic models that can be solved. Fourth, asynchronously parallelizable methods that could exploit exascale computing to solve complex dynamic games. Funny story: I met with Barry Smith about the potential application of PETSc to economics problems. I interrupted him when he started to point to complex applications, and said “Economics problems are more like this” pointing to a simple example. I said “There is a lot of low-hanging fruit in economics” to which he responded “That’s not low-hanging fruit, that fruit rotting on the ground.” My purpose will be to inform you of potential applications of computational science in economics, and perhaps recruit some help in going after higher-hanging fruit.

Kenneth L. Judd, the Paul H. Bauer Senior Fellow at the Hoover Institution, is an expert in the economics of taxation, imperfect competition, and mathematical economics.

His current research focuses on developing computational methods for economic modeling and applying them to tax policy, antitrust issues, macroeconomics, and policies related to climate change. He was a co–principal investigator at the Center for Robust Decision Making on Climate and Energy Policy, the director of the Initiative for Computational Economics at the University of Chicago, and a member of the National Academies Board on Mathematical Sciences and Applications. He developed new PhD courses on Computational Economics at Stanford University and the University of Chicago, and teaches at Penn State University and the University of Zurich.

He was coeditor of the RAND Journal of Economics (1988–95) and the Journal of Economic Dynamics and Control (2002–6). He was an associate editor of the Journal of Public Economics (1988–97).

His work has also been published in the Journal of Economic Dynamics and Control, Journal of Public Economics, Journal of Political Economy, RAND Journal, Journal of Finance, Journal of Economic Theory, Brookings Papers of Economic Activity,American Economic Review, and Econometrica.

His book Numerical Methods in Economics was published by MIT Press in 1998.

He is a fellow of the Econometric Society and served as a member of the Economics Panel of the National Science Foundation (1986–88).


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The Potential Partnership Between Economics and Computational Science