I'm Matthew W. Thomas, an Economics PhD candidate at Northwestern University. I am currently interested in microeconomic theory including contests, lobbying, and labor. This page is here to share my academic and non-academic projects.
What happens when the prize in an all-pay auction depends on players’ bids?PDF
When opposing parties compete for a prize, the sunk effort players exert during the conflict can affect the value of the winner’s reward. These spillovers can have substantial influence on the equilibrium behavior of participants in applications such as lobbying, warfare, labor tournaments, marketing, and R&D races. To understand this influence, we study a general class of asymmetric, two-player all-pay contests where we allow for spillovers in each player’s reward. The link between participants’ efforts and rewards yields novel effects – in particular, players with higher costs and lower values than their opponent sometimes extract larger payoffs.
Can you design a symmetric contest such that one player is favored?PDF Slides
A contest designer may wish to disadvantage a stronger player to improve competitiveness. We show this can be done in all-pay auctions such that the game is fair (i.e. symmetric) ex-ante. Yet, the stronger player is endogenously offered a lower prize in expectation. Thus, discrimination is covert.
Python package to estimate the equilibria of all-pay contests with spilloversSource
Notes about how to optimize over a space of functions instead of numbers
Thoughts on efficient revenue maximizing symmetric contests
Summary of existing results on the design of asymmetric Tullock contestsPDF
Simple derivation of equilibria in a general two player war of attritionPDF
Notes on VCG and issues with current applications of quadratic voting
Mirrors for open source software
Allows you to use GitHub issues for blog comments in Jekyll
Python function for GPU accelerated regression of censored data
Wolfram function that identifies and animates images with ML
Wolfram function that converts ISO 3166-1 codes to country data