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 zero price effect in transit shows why making public transport free generates demand shifts much larger than the equivalent fare reduction would predict, with implications for fare-free transit experiments now running in Tallinn, Luxembourg, and Kansas City. 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.