Estimating the Impact of Recent Interventions on Transportation Indicators
Whenever an unusual even disrupts the structural patterns of a time series, one of the aims of a forecaster is to model the effects of that event, with a view to establishing a new basis for forecasting. Intervention analysis has long been the method of choice for such adjustments, but it is often r...
Gespeichert in:
Veröffentlicht in: | Journal of transportation and statistics 2004-01, Vol.7 (1), p.69 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 1 |
container_start_page | 69 |
container_title | Journal of transportation and statistics |
container_volume | 7 |
creator | Ord, Keith Young, Peg |
description | Whenever an unusual even disrupts the structural patterns of a time series, one of the aims of a forecaster is to model the effects of that event, with a view to establishing a new basis for forecasting. Intervention analysis has long been the method of choice for such adjustments, but it is often represented as a procedure for dealing with events in the middle of the time series rather than for the most recent observations. In this paper, we develop a method, termed the three-intervention approach, to provide a flexible solution to this problem. We examine its application for a number of transportation series that were disrupted by the tragic events of September 2001. Analyses of the series using up to six months of post-event data show good agreement with results based on longer post-event series, and suggest that the proposed method will often provide adequate modifications to a series in a timely manner. The method is applicable to most economic time series, but has been tested only for transportation series. [PUBLICATION ABSTRACT] |
format | Article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_210678365</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>790735581</sourcerecordid><originalsourceid>FETCH-LOGICAL-g159t-8d4b9b9bc73e0f40acd546fffe353659bdd932cdf0478b070f8d2e7441f2a3e33</originalsourceid><addsrcrecordid>eNotjUFLAzEUhHNQaK3-h-B94WWT3SRHKVVXCgWp55JNXtotNlmT1N9vRJnDDDPwzQ1ZMtCiUUqoBbnL-QwAPePtkrxtcpkupkzhSMsJ6XCZjS00evqOFkOhQyiYvmuaYsg0BrpPJuQ5pmJ-q7q7yZoSU74nt958Znz49xX5eN7s16_NdvcyrJ-2zZF1ujTKiVFXWckRvABjXSd67z3yjvedHp3TvLXOg5BqBAleuRalEMy3hiPnK_L4x51T_LpiLodzvKZQLw8tg16qSuE_sRtI-g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>210678365</pqid></control><display><type>article</type><title>Estimating the Impact of Recent Interventions on Transportation Indicators</title><source>Free E-Journal (出版社公開部分のみ)</source><creator>Ord, Keith ; Young, Peg</creator><creatorcontrib>Ord, Keith ; Young, Peg</creatorcontrib><description>Whenever an unusual even disrupts the structural patterns of a time series, one of the aims of a forecaster is to model the effects of that event, with a view to establishing a new basis for forecasting. Intervention analysis has long been the method of choice for such adjustments, but it is often represented as a procedure for dealing with events in the middle of the time series rather than for the most recent observations. In this paper, we develop a method, termed the three-intervention approach, to provide a flexible solution to this problem. We examine its application for a number of transportation series that were disrupted by the tragic events of September 2001. Analyses of the series using up to six months of post-event data show good agreement with results based on longer post-event series, and suggest that the proposed method will often provide adequate modifications to a series in a timely manner. The method is applicable to most economic time series, but has been tested only for transportation series. [PUBLICATION ABSTRACT]</description><identifier>ISSN: 1094-8848</identifier><language>eng</language><publisher>Washington: Bureau of Transportation Statistics</publisher><subject>Airlines ; Forecasting techniques ; Studies ; Time series ; Traffic flow</subject><ispartof>Journal of transportation and statistics, 2004-01, Vol.7 (1), p.69</ispartof><rights>Copyright Bureau of Transportation Statistics 2004</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids></links><search><creatorcontrib>Ord, Keith</creatorcontrib><creatorcontrib>Young, Peg</creatorcontrib><title>Estimating the Impact of Recent Interventions on Transportation Indicators</title><title>Journal of transportation and statistics</title><description>Whenever an unusual even disrupts the structural patterns of a time series, one of the aims of a forecaster is to model the effects of that event, with a view to establishing a new basis for forecasting. Intervention analysis has long been the method of choice for such adjustments, but it is often represented as a procedure for dealing with events in the middle of the time series rather than for the most recent observations. In this paper, we develop a method, termed the three-intervention approach, to provide a flexible solution to this problem. We examine its application for a number of transportation series that were disrupted by the tragic events of September 2001. Analyses of the series using up to six months of post-event data show good agreement with results based on longer post-event series, and suggest that the proposed method will often provide adequate modifications to a series in a timely manner. The method is applicable to most economic time series, but has been tested only for transportation series. [PUBLICATION ABSTRACT]</description><subject>Airlines</subject><subject>Forecasting techniques</subject><subject>Studies</subject><subject>Time series</subject><subject>Traffic flow</subject><issn>1094-8848</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid/><recordid>eNotjUFLAzEUhHNQaK3-h-B94WWT3SRHKVVXCgWp55JNXtotNlmT1N9vRJnDDDPwzQ1ZMtCiUUqoBbnL-QwAPePtkrxtcpkupkzhSMsJ6XCZjS00evqOFkOhQyiYvmuaYsg0BrpPJuQ5pmJ-q7q7yZoSU74nt958Znz49xX5eN7s16_NdvcyrJ-2zZF1ujTKiVFXWckRvABjXSd67z3yjvedHp3TvLXOg5BqBAleuRalEMy3hiPnK_L4x51T_LpiLodzvKZQLw8tg16qSuE_sRtI-g</recordid><startdate>20040101</startdate><enddate>20040101</enddate><creator>Ord, Keith</creator><creator>Young, Peg</creator><general>Bureau of Transportation Statistics</general><scope/></search><sort><creationdate>20040101</creationdate><title>Estimating the Impact of Recent Interventions on Transportation Indicators</title><author>Ord, Keith ; Young, Peg</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-g159t-8d4b9b9bc73e0f40acd546fffe353659bdd932cdf0478b070f8d2e7441f2a3e33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Airlines</topic><topic>Forecasting techniques</topic><topic>Studies</topic><topic>Time series</topic><topic>Traffic flow</topic><toplevel>online_resources</toplevel><creatorcontrib>Ord, Keith</creatorcontrib><creatorcontrib>Young, Peg</creatorcontrib><jtitle>Journal of transportation and statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ord, Keith</au><au>Young, Peg</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating the Impact of Recent Interventions on Transportation Indicators</atitle><jtitle>Journal of transportation and statistics</jtitle><date>2004-01-01</date><risdate>2004</risdate><volume>7</volume><issue>1</issue><spage>69</spage><pages>69-</pages><issn>1094-8848</issn><abstract>Whenever an unusual even disrupts the structural patterns of a time series, one of the aims of a forecaster is to model the effects of that event, with a view to establishing a new basis for forecasting. Intervention analysis has long been the method of choice for such adjustments, but it is often represented as a procedure for dealing with events in the middle of the time series rather than for the most recent observations. In this paper, we develop a method, termed the three-intervention approach, to provide a flexible solution to this problem. We examine its application for a number of transportation series that were disrupted by the tragic events of September 2001. Analyses of the series using up to six months of post-event data show good agreement with results based on longer post-event series, and suggest that the proposed method will often provide adequate modifications to a series in a timely manner. The method is applicable to most economic time series, but has been tested only for transportation series. [PUBLICATION ABSTRACT]</abstract><cop>Washington</cop><pub>Bureau of Transportation Statistics</pub></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1094-8848 |
ispartof | Journal of transportation and statistics, 2004-01, Vol.7 (1), p.69 |
issn | 1094-8848 |
language | eng |
recordid | cdi_proquest_journals_210678365 |
source | Free E-Journal (出版社公開部分のみ) |
subjects | Airlines Forecasting techniques Studies Time series Traffic flow |
title | Estimating the Impact of Recent Interventions on Transportation Indicators |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T06%3A34%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Estimating%20the%20Impact%20of%20Recent%20Interventions%20on%20Transportation%20Indicators&rft.jtitle=Journal%20of%20transportation%20and%20statistics&rft.au=Ord,%20Keith&rft.date=2004-01-01&rft.volume=7&rft.issue=1&rft.spage=69&rft.pages=69-&rft.issn=1094-8848&rft_id=info:doi/&rft_dat=%3Cproquest%3E790735581%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=210678365&rft_id=info:pmid/&rfr_iscdi=true |