Sequential Matching of Entrepreneurs to Accelerators and Venture Capitalists

Academic Paper
Title	Sequential Matching of Entrepreneurs to Accelerators and Venture Capitalists
Author	Ed Egan, Jeremy Fox
RAs	Amir Kazempour
Status	In development
© edegan.com, 2016

Summary

This paper describes a multi-stage matching model and estimates this model using data on entrepreneurs that match to accelerators and (lead) venture capitalists.

See Fox (2008) - An Empirical Repeated Matching Game Applied to Market for a brief write up on Jeremy's theory paper

Simple Outline of Model

As of now, the goal is to simulate a repeated matching model with dynamically optimizing agents. More specifically, there are two sides for a matching market with transferable utility (generically, call these men and women for now) with a continuum of agents, but a finite number of types. They participate in matches for T periods and receive utility that is a sum of a structural component (determined solely by their type and the type they are matched with) and a individual taste component (with some known distribution).

What distinguishes this model from a static matching model is that the agents have some probability of transitioning between types that is conditional on the match they make in the previous period (e.g., a man of low type might be more likely to change into a man of high type after being matched to a woman of high type). When making these matches, the agents take these transition probabilities into account when evaluating expected future utility. This adds a dynamic element to the model.

Work to do

• Code up three algorithms to simulate match(primal,IPFP,dual)
• Compare with R code from NYU

Work done so far

• Coded up primal and IPFP (may have errors)

Work to do in near term

• Compare with R code from NYU (using current solvers/optimizers, and with Gurobi)

Work Done in Late November by Dylan & Ed

SBIR Data taken from McNair\Projects\SBIR\Data\Aggregate SBIR\SBIR.txt. -Note! This file needed to be opened in excel to be readable, and took a very long time to open due to its large size. SBIR firm names converted to a pivot table to eliminate exact repeat entries, and then exported to a txt file, NSBIR. NSBIR then matched using The Matcher in mode 2 with the following code "-file1="NSBIR.txt" -file2="NSBIR.txt" -mode=2" Output then placed in McNair\Projects\MatchingEntrepsToVC\Matching\Output. The original pre-matched, cleaned NSBIR.txt file is moved to McNair\Projects\MatchingEntrepsToVC\Matching\Intput.