Becker Friedman Institute
for Research in Economics
The University of Chicago

Research. Insights. Impact. Advancing the Legacy of Chicago Economics.

modeling

Automated Economic Reasoning with Quantifier Elimination

Casey Mulligan

Many theorems in economics can be proven (and hypotheses shown to be false) with "quantifier elimination." Results from real algebraic geometry such as Tarski's quantifier elimination theorem and Collins' cylindrical algebraic decomposition algorithm are applicable because the economic hypotheses, especially those that leave functional forms unspecified, can be represented as systems of multivariate polynomial (sic) equalities and inequalities.

Modeling Financial Sector Linkages to the Macroeconomy

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The second meeting of the Macro Financial Modeling (MFM) Working Group gathered 55 scholars in New York for close review and discussion of research that examines financial sector shocks to the economy.

The goal, according to project co-director Lars Peter Hansen, was “to think hard and critically about incorporating financial frictions into macroeconomic models and identify productive avenues for future exploration.”

 

Aloysius Siow Lecture Series

In late October of 2012, the institute proudly sponsored two lectures by Aloysius Siow for graduate students and faculty in the Department of Economics and the Booth School of Business.

Who marries whom, and why? How do individual's employment prospects and choices affect their matrimonial matches? Visiting Scholar Aloysius Siow offered an economic analysis of that question in two lectures during his residency.

Extended Mathematical Programming: Competition and Stochasticity

Michael Ferris, Steven P. Dirkse, Jan-H. Jagla, Alexander Meeraus

Extended mathematical programs are collections of functions and variables joined together using specific optimization and complementarity primitives. This paper outlines a mechanism to describe such an extended mathematical program by means of annotating the existing relationships within a model to facilitate higher level structure identification. The structures, which often involve constraints on the solution sets of other models or complementarity relationships, can be exploited by modern large scale mathematical programming algorithms for efficient solution.