Finance professor at Oklahoma State University. Network economist. Songwriter. Carpenter. I study how firms' decisions ripple through production and geographic networks, and I write rap songs about Ben Bernanke.
Songs I've written from my trailer to explain economic concepts, make fun of finance and research topics, or just entertain myself. They're all on Spotify and YouTube — click below to listen!
I'm a finance professor who studies how firms' decisions ripple through production networks and geographic clusters. Most empirical work in corporate finance treats firms as independent observations, as though they are Robinson Crusoe firms operating on an island. But firms are connected to each other in complex webs of supply chains, industry relationships, and geographic proximity. My research shows what you likely miss when you ignore the connections. Network effects alter the economic magnitudes of well-studied relationships dramatically, as one would expect from decades of game theory and industrial organization research. The econometrics required to identify these effects properly is not as hard as one might think, and they offer far more than better parameter estimates. Rather, they offer an entirely new class of measurable phenomena.
I specialize in network analysis, spatial econometrics, financial constraints, and corporate investment. I focus on methods that glean new insights into old questions, empirical approaches that capture indirect links, spillover channels, and propagation effects that standard models miss entirely.
I teach Financial Markets & Institutions and empirical research methods. My classroom runs on games, simulations, and experiential learning — not slides. I've written rap songs to teach econometrics, explain tariffs, and welcome students back from Covid. They work better than you'd think.
Before Oklahoma State, I was at Tulane, TCU, and USC. Outside of research, I write music spanning several genres from my trailer in Stillwater, I'm working on a book that formalizes love as an integral of emotional energy dedicated over time, and I spend more time than is probably healthy arguing with AI about identification strategies in working papers.
Built around classroom games and experiential learning. Students trade, build portfolios, and learn market mechanics by doing, not watching.
Identification strategies, spatial econometrics, causal inference. Heavy emphasis on what can go wrong and usually does.
A comprehensive guide for finance PhD students — from reading papers to writing them, with everything I wish someone had told me.
Materials for interactive finance teaching. Trading simulations, market design exercises, and coordination games.