Economics on this site is empirical and quantitative: agent-based simulations, behavioral experiments, game theory applied to actual decisions. Less debate about what models should look like, more results from running them.
The flagship piece, agent-based modeling of wealth distribution, implements the Affine Wealth Model from Bruce Boghosian’s group at Tufts. Random transactions between equal agents produce Pareto-distributed outcomes, and the simulation reproduces 27 years of U.S. wealth data within 0.16% average error. About 10% of agents go negative, matching the share of U.S. households with negative net worth. The post then runs counterfactuals on what a wealth tax of 1% to 5% does to the distribution: the result is a steady-state equilibrium where the wealthiest agents hold at most 3 to 4 times their initial allocation.
Behavioral coverage starts from Kahneman, Thaler, and Ariely but lands in concrete policy. The economics of mobile money traces the M-Pesa playbook across African and Asian markets, looking at when network effects dominate regulatory friction.
Game-theoretic analysis appears where signaling and auction dynamics dominate outcomes. The Super Bowl ad piece breaks down the per-spot bidding equilibrium between brand-budget incumbents and growth-stage challengers, and asks why broadcast advertising’s ROI math still works for some categories and not others.
The thread across these posts is a preference for models that produce testable predictions over models that produce explanations.