I'm Matthew Wildrick Thomas, an Economics PhD candidate at Northwestern University. I am currently interested in applied microeconomic theory including information in financial markets, contests, and lobbying. 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?

PDFWhen 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 SlidesA 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 spillovers

SourceNotes 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 contests

PDFSimple derivation of equilibria in a general two player war of attrition

PDFNotes 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