{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/19013"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/19013","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Experience in the application of unit roots and fractional difference models and tests","abstract":"One of the most important aspects in analyzing economic time series is to specify whether the observed series is generated by a stationary or non-stationary process, since most macroeconomic variables could be generated by a unit autoregressive root process. This determination as to whether or not a series should be differenced is known as the unit root test. In other words, if a time series in non-stationary, then in the presence of a unit autoregressive root, it can be converted to a stationary and invertible process by first differencing.","abstract_html":"One of the most important aspects in analyzing economic time series is to specify whether the observed series is generated by a stationary or non-stationary process, since most macroeconomic variables could be generated by a unit autoregressive root process. This determination as to whether or not a series should be differenced is known as the unit root test. In other words, if a time series in non-stationary, then in the presence of a unit autoregressive root, it can be converted to a stationary and invertible process by first differencing.","abstract_has_math":false,"creators":["Agiakloglou, Christos N."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Newbold, Paul"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T11:54:20Z","date_published":"2011-05-07T11:54:20Z","updated_at":"2026-07-22T22:25:12Z","subjects":["Statistics","Economics","Economic Theory"],"languages":["eng"],"rights":["Copyright 1992 Agiakloglou, Christos N."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9305446","(UMI)AAI9305446"],"render_values":[{"text":"AAI9305446","href":null,"code":true},{"text":"(UMI)AAI9305446","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/19013","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Newbold, Paul"]},{"key":"dc:creator","label":"Author","values":["Agiakloglou, Christos N."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T11:54:20Z","10000-01-01","1992"]},{"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","Economics","Economic Theory"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1992 Agiakloglou, Christos N."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9305446","(UMI)AAI9305446","http://hdl.handle.net/2142/19013"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["One of the most important aspects in analyzing economic time series is to specify whether the observed series is generated by a stationary or non-stationary process, since most macroeconomic variables could be generated by a unit autoregressive root process. This determination as to whether or not a series should be differenced is known as the unit root test. In other words, if a time series in non-stationary, then in the presence of a unit autoregressive root, it can be converted to a stationary and invertible process by first differencing.","This thesis examines some techniques for testing the unit root hypothesis. It evaluates first the Dickey-Fuller-Type Tests for a unit autoregressive root in the presence of moving average components for any ARIMA (p, 1, q) process, proposed by Said and Dickey (1984, 1985). This type of test is conducted by either fitting a long autoregression to the data when the orders p and q are unknown, or by using the one-step Gauss-Newton least squares estimation when the orders p and q are known. Furthermore, to investigate the performance of the above tests, some applications of unit root models presented in the recent literature are also re-examined.","Moreover, this thesis employs the analysis of fractionally integrated models, which nests the unit root phenomenon, to distinguish in a more general way the value of the difference parameter. First, it evaluates and provides examples of the Geweke and Porter-Hudak (1983) estimation procedure which is frequently used to obtain an estimate of the fractional difference parameter, d. Next, it presents some new alternative testing techniques for fractionally integrated models. Finally, the behavior of the sample autocorrelations of fractional white noise is investigated.","Made available in DSpace on 2011-05-07T11:54:20Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9305446.pdf: 7314354 bytes, checksum: b88510abe958a8219cd33eb9e5b90ee8 (MD5) Previous issue date: 1992","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:34:04Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:12:50-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"]},{"key":"dc:title","label":"Title","values":["Experience in the application of unit roots and fractional difference models and tests"]}]}],"canonical_facts":{"dc:contributor":["Newbold, Paul"],"dc:creator":["Agiakloglou, Christos N."],"dc:date":["2011-05-07T11:54:20Z","10000-01-01","1992"],"dc:description":["One of the most important aspects in analyzing economic time series is to specify whether the observed series is generated by a stationary or non-stationary process, since most macroeconomic variables could be generated by a unit autoregressive root process. This determination as to whether or not a series should be differenced is known as the unit root test. In other words, if a time series in non-stationary, then in the presence of a unit autoregressive root, it can be converted to a stationary and invertible process by first differencing.","This thesis examines some techniques for testing the unit root hypothesis. It evaluates first the Dickey-Fuller-Type Tests for a unit autoregressive root in the presence of moving average components for any ARIMA (p, 1, q) process, proposed by Said and Dickey (1984, 1985). This type of test is conducted by either fitting a long autoregression to the data when the orders p and q are unknown, or by using the one-step Gauss-Newton least squares estimation when the orders p and q are known. Furthermore, to investigate the performance of the above tests, some applications of unit root models presented in the recent literature are also re-examined.","Moreover, this thesis employs the analysis of fractionally integrated models, which nests the unit root phenomenon, to distinguish in a more general way the value of the difference parameter. First, it evaluates and provides examples of the Geweke and Porter-Hudak (1983) estimation procedure which is frequently used to obtain an estimate of the fractional difference parameter, d. Next, it presents some new alternative testing techniques for fractionally integrated models. Finally, the behavior of the sample autocorrelations of fractional white noise is investigated.","Made available in DSpace on 2011-05-07T11:54:20Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9305446.pdf: 7314354 bytes, checksum: b88510abe958a8219cd33eb9e5b90ee8 (MD5) Previous issue date: 1992","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:34:04Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:12:50-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"],"dc:identifier":["AAI9305446","(UMI)AAI9305446","http://hdl.handle.net/2142/19013"],"dc:language":["eng"],"dc:rights":["Copyright 1992 Agiakloglou, Christos N."],"dc:subject":["Statistics","Economics","Economic Theory"],"dc:title":["Experience in the application of unit roots and fractional difference models and tests"],"dc:type":["text"],"thesis:degree_discipline":["Economics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:12Z"}