Parameter estimation underpins the construction and validation of statistical and mathematical models across the natural sciences, engineering and economics. Accurate inference of model parameters ...

Bayesian inference offers a principled mechanism for updating beliefs by combining prior distributions with observed data via Bayes’s theorem. Central to this approach is the specification of a ...

We investigate the question of whether or not estimates of relative risk from matched case-control studies well represent the population from which they were drawn. We derive the formula for the ...

We consider how fear of model misspecification on the part of the planner and/or the households affects welfare gains from optimal macroprudential taxes in an economy with occasionally binding ...

Andrews, Isaiah, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan, and Jesse M. Shapiro. "Structural Estimation Under Misspecification: Theory and Implications for Practice." Quarterly Journal of ...

Being able to understand and quantify the model risk inherent in loss-projection models used in macroeconomic stress testing and impairment estimation is a significant concern for both banks and ...