{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/85533"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/85533","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Smooth Test and Its Applications in Economics and Finance","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Ghosh, Aurobindo"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Bera, Anil K."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T22:47:16Z","date_published":"2015-09-25T22:47:16Z","updated_at":"2026-07-22T22:26:25Z","subjects":["Statistics"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3086066"],"render_values":[{"text":"(MiAaPQ)AAI3086066","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/85533","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bera, Anil K."]},{"key":"dc:creator","label":"Author","values":["Ghosh, Aurobindo"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T22:47:16Z","10000-01-01","2003"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Statistics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/85533","(MiAaPQ)AAI3086066"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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. 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