3 papers
econ.EM2026
Quasi-Bayesian Hierarchical Models
Desmond Fairall, Thomas Glinnan
We develop the Quasi-Bayesian Hierarchical Model (QBHM) for grouped GMM settings. The framework combines Bayesian hierarchical modelling with Laplace-type estimation: it preserves…
econ.EM2026
Design-Based Inference for Time-Series GMM
Thomas Glinnan
This paper studies inference for time-series GMM when uncertainty comes from shock assignment within a realized historical episode. Rather than treating the data as one random draw…
econ.EM2026
Bounds on inequality with incomplete data
James Banks, Thomas Glinnan, Tatiana Komarova
We study inequality measures when outcomes are observed only in intervals, as in historical tabulations, privacy-protected grouped data, and modern surveys. We develop a nonparamet…