Beyond the Black Box: A Data Science Reading List for Economists
Data science is reshaping how we understand markets, organizations, and economic behavior. As analytical methods evolve—from causal inference to generative modeling and explainable machine learning—so does the need for readings that bridge theory, empirical evidence, and cutting‑edge computational techniques. This curated list brings together six thought‑provoking pieces that span foundational concepts, global risk perspectives, long‑horizon financial insights, and advanced applications of machine learning in economics and corporate strategy. 1. On Causality : A History of How Economics Learned to Think About Cause and Effect ( Carlos Chavez substack ). 2. The future of risk: How global trends are reshaping risk management . A rapidly shifting and interconnected risk landscape, technology, and AI transform what good risk management looks like. Financial institutions must embrace new operating models and best practices ( McKinsey ). 3. What Earnings Explain, and What They Don’t :...
