Energy Economics • AI Infrastructure • Applied Econometrics
I'm Alan Lamb, an applied economist focused on energy markets and AI infrastructure. I'm completing an M.S. in Applied Economics at the University of Maryland. This site collects my research, writing, and technical work — papers, causal analyses, and software I've built. The reasoning is visible, the code is public, and the limitations are documented.
Between 2019 and 2025, electricity demand in ERCOT grew 27 percent while PJM and MISO were essentially flat. This paper estimates how much of that divergence data center investment can explain, using a four-layer identification strategy across three balancing authorities. The headline result is a 34.8 index-point divergence in ERCOT minimum hourly demand above a synthetic counterfactual. The paper documents the absence of public load-side queue data as a policy finding.
Read on SSRN • GitHub • Replication Data (Dataverse) • Interactive Dashboard
April 2026 • University of Maryland • Synthetic Control • DiD • Panel Regression • ARIMA • XGBoost
A policy brief arguing that FERC should require grid operators to publish large load interconnection queue data on the same terms currently applied to generation interconnection. Grounded in the empirical results of the companion paper, it traces thirty years of FERC precedent and proposes a specific regulatory mechanism that does not require new legislation.
April 2026 • University of Maryland • Energy Policy • FERC • Interconnection Queue
A mobile-first daily intelligence tool I designed and built solo. Bearing delivers a personalized morning brief connecting your work, reading, and projects to what's happening in the world. Built from zero to a fully deployed product with auth, AI, payments, and cross-device sync.
2026 • React • Vite • Supabase • Claude API • Stripe • Vercel