Overview
Daniel L. McFadden is an econometrician at the University of California, Berkeley (formerly MIT), awarded the 2000 Nobel Memorial Prize in Economic Sciences for developing the theory and methods of discrete choice analysis. He founded the random-utility approach to qualitative choice (conditional logit) and later pioneered simulation estimation for models whose likelihoods require high-dimensional integration.
Key Contributions / Features
- Conditional logit (1974): The random-utility foundation of discrete-choice econometrics; the workhorse model for qualitative choice behavior, with the independence-of-irrelevant-alternatives property later relaxed by probit and nested models.
- Method of Simulated Moments (1989): "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration" (Econometrica) — consistent estimation of MNP-type models using unbiased frequency simulators for a finite number of draws, foundational to simulation-based estimation.
- Method of Simulated Scores — Hajivassiliou–McFadden (1998): With Vassilis Hajivassiliou, simulates the likelihood score directly to attain ML efficiency with smooth (GHK / Gibbs) simulators; applied to LDC external-debt crises. See Method of Simulated Scores and Hajivassiliou-McFadden (1998).
- GHK simulator: The "H" in the Geweke–Hajivassiliou–Keane recursive-triangularization simulator for multivariate normal probabilities, central to modern probit estimation.
Related