Overview
John Geweke is a Bayesian econometrician who held positions at the University of Iowa and the University of Minnesota. He is a leading figure in the development and application of Markov Chain Monte Carlo methods in economics, particularly the Gibbs sampling algorithm for complex panel data models.
Key Contributions
- Geweke (1989): "Bayesian Inference in Econometric Models Using Monte Carlo Integration." Econometrica 57: 1317–1339. Foundational paper establishing Monte Carlo methods for Bayesian econometric inference; introduces the relative numerical efficiency diagnostic.
- Geweke (1996): "Posterior Simulators in Econometrics." In Advances in Economics and Econometrics, Vol. III. Cambridge University Press. Systematic treatment of posterior simulation and Gibbs sampling for economic models.
- Geweke and Keane (2000): "An Empirical Analysis of Earnings Dynamics Among Men in the PSID: 1968–1989." Journal of Econometrics 96: 293–356. Develops a nonstationary life-cycle earnings model with mixture-of-normals (non-Gaussian) shocks, estimated via Gibbs sampling with data augmentation; shows that the shock distribution assumption materially changes estimates of the education premium and racial earnings gap. See Earnings Dynamics.
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