On Bayesian Analysis and Computation for Functions with Monotonicity and Curvature Restrictions

Publisher:
Elsevier
Publication Type:
Journal Article
Citation:
Journal of Econometrics, 2008, 142 (1), pp. 484 - 507
Issue Date:
2008-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2010006474OK.pdf305.24 kB
Adobe PDF
Our goal is inference for shape-restricted functions. Our functional form consists of finite linear combinations of basis functions. Prior elicitation is difficult due to the irregular shape of the parameter space. We show how to elicit priors that are flexible, theoretically consistent, and proper. We demonstrate that uniform priors over coefficients imply priors over economically relevant quantities that are quite informative and give an example of a non-uniform prior that addresses this issue. We introduce simulation methods that meet challenges posed by the shape of the parameter space. We analyze data from a consumer demand experiment.
Please use this identifier to cite or link to this item: