Small Business Modeling
Computationally modeling small business to drive policy decisions (Economics)
Small businesses are a vital part of the economy, producing more than 50 percent of non-farm private U.S. GDP, employing half of all private sector employees, and generating 60 to 80 percent of net new jobs annually over the last decade.
With my colleagues Anne Villamil and M. Mobin Shorish, we are using computational modeling to study the factors that influence the startup and success of small businesses. In particular, we have focused on quantifying how policy decisions (e.g., bankruptcy law) and an institution's legal organization (e.g., incorporated versus unincorporated) affect an entrepreneur's willingness to start up or increase the scale of a business. For this project, we propose to extend this existing work by developing a model of the banking sector, a very timely subject given credit crunch and the likely reform of regulation. At the core of the model is a non-convex, constraint programming problem, and we are currently working on algorithms to solve this problem quickly and efficiently. The students will be involved in solving some of interesting computational challenges in the context of implementing numerical procedures for solving real world problems.