{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/85575"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/85575","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Modeling Conditional Heteroskedasticity in Time Series and Spatial Analysis","abstract":"My fourth chapter investigates heterogeneity in the assessment of spatial dependence by exploring (jointly) two main mechanisms: distributional misspecification and conditional heteroskedasticity. I first derive a simple specification test for spatial autoregressive model using the information matrix (IM) test principle. As a byproduct of my test development, I obtain a general model that has similar features like autoregressive conditional heteroskedasticity (ARCH) in time series context. My suggested spatial ARCH (SARCH) model can take account of some of the stylized facts observed in spatial data. To illustrate the usefulness of our test and SARCH model, I apply our theoretical result to Boston housing price data and show the importance of modeling the conditional second moment in spatial context.","abstract_html":"My fourth chapter investigates heterogeneity in the assessment of spatial dependence by exploring (jointly) two main mechanisms: distributional misspecification and conditional heteroskedasticity. I first derive a simple specification test for spatial autoregressive model using the information matrix (IM) test principle. As a byproduct of my test development, I obtain a general model that has similar features like autoregressive conditional heteroskedasticity (ARCH) in time series context. My suggested spatial ARCH (SARCH) model can take account of some of the stylized facts observed in spatial data. To illustrate the usefulness of our test and SARCH model, I apply our theoretical result to Boston housing price data and show the importance of modeling the conditional second moment in spatial context.","abstract_has_math":false,"creators":["Simlai, Pradosh Kumar"],"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":"2015-09-25T22:47:27Z","date_published":"2015-09-25T22:47:27Z","updated_at":"2026-07-22T22:26:25Z","subjects":["Economics, Theory"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3242994"],"render_values":[{"text":"(MiAaPQ)AAI3242994","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/85575","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":["Simlai, Pradosh Kumar"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T22:47:27Z","10000-01-01","2006"]},{"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":["Economics, Theory"]}]},{"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/2142/85575","(MiAaPQ)AAI3242994"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["My fourth chapter investigates heterogeneity in the assessment of spatial dependence by exploring (jointly) two main mechanisms: distributional misspecification and conditional heteroskedasticity. 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I first derive a simple specification test for spatial autoregressive model using the information matrix (IM) test principle. As a byproduct of my test development, I obtain a general model that has similar features like autoregressive conditional heteroskedasticity (ARCH) in time series context. My suggested spatial ARCH (SARCH) model can take account of some of the stylized facts observed in spatial data. To illustrate the usefulness of our test and SARCH model, I apply our theoretical result to Boston housing price data and show the importance of modeling the conditional second moment in spatial context.","Made available in DSpace on 2015-09-25T22:47:27Z (GMT). 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