Smooth Test and Its Applications in Economics and Finance
Ghosh, Aurobindo
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/85533
Description
Title
Smooth Test and Its Applications in Economics and Finance
Author(s)
Ghosh, Aurobindo
Issue Date
2003
Doctoral Committee Chair(s)
Bera, Anil K.
Department of Study
Economics
Discipline
Economics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Statistics
Language
eng
Abstract
One of the drawbacks of the original smooth test is that it was designed for a one-sample problem with fully specified null distribution, which is not always possible to have in practice. I propose both parametric (for density forecast evaluation) and non-parametric (for comparing two unknown densities) techniques in formulating tests based on the probability integral transforms. In case of parametric applications of density forecast evaluation we have to account for the effect of parameter estimation and dependent data in the implementation of the smooth test. In the non-parametric case of comparing two densities I used the orders of the relative sizes of the two samples to get a consistent test. Monte Carlo simulation of these tests shows good power of size characteristics. I applied the proposed smooth tests to evaluate S&P 500 density forecasts and compare age distribution of insured population in New York.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.