Seasonal adjustment of hybrid time series: An application to U.S. regional jobs data

Q3 Social Sciences Journal of Economic and Social Measurement Pub Date : 2016-01-01 DOI:10.3233/JEM-160428
K. Phillips, Jianguo Wang
{"title":"Seasonal adjustment of hybrid time series: An application to U.S. regional jobs data","authors":"K. Phillips, Jianguo Wang","doi":"10.3233/JEM-160428","DOIUrl":null,"url":null,"abstract":"Hybrid time series data often require special care in estimating seasonal factors. Series such as the state and metro area Current Employment Statistics produced by the U.S. Bureau of Labor Statistics (BLS) are composed of two different source series that often have two different seasonal patterns. In this paper we address the process to test for differing seasonal patterns within the hybrid series. We also discuss how to apply differing seasonal factors to the separate parts of the hybrid series. Currently, for state employment data, the BLS simply juxtaposes the two different sets of seasonal factors at the transition point between the benchmark part of the data and the survey part. We argue that the seasonal factors should be extrapolated at the transition point or that an adjustment should be made to the level of the unadjusted data to correct for a bias in the survey part of the data caused by differing seasonal factors at the transition month.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"41 1","pages":"191-202"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-160428","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic and Social Measurement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JEM-160428","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 1

Abstract

Hybrid time series data often require special care in estimating seasonal factors. Series such as the state and metro area Current Employment Statistics produced by the U.S. Bureau of Labor Statistics (BLS) are composed of two different source series that often have two different seasonal patterns. In this paper we address the process to test for differing seasonal patterns within the hybrid series. We also discuss how to apply differing seasonal factors to the separate parts of the hybrid series. Currently, for state employment data, the BLS simply juxtaposes the two different sets of seasonal factors at the transition point between the benchmark part of the data and the survey part. We argue that the seasonal factors should be extrapolated at the transition point or that an adjustment should be made to the level of the unadjusted data to correct for a bias in the survey part of the data caused by differing seasonal factors at the transition month.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
混合时间序列的季节调整:在美国地区就业数据中的应用
混合时间序列数据在估计季节因素时往往需要特别注意。诸如美国劳工统计局(BLS)发布的州和都市区当前就业统计数据系列由两个不同的来源系列组成,通常有两种不同的季节模式。在本文中,我们讨论了在混合系列中测试不同季节模式的过程。我们还讨论了如何将不同的季节因素应用于混合系列的各个部分。目前,对于州就业数据,劳工统计局只是在数据的基准部分和调查部分之间的过渡点并置两组不同的季节性因素。我们认为,季节因素应该在过渡点外推,或者应该对未调整数据的水平进行调整,以纠正由过渡月份不同季节因素引起的调查部分数据的偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Economic and Social Measurement
Journal of Economic and Social Measurement Social Sciences-Social Sciences (all)
CiteScore
1.60
自引率
0.00%
发文量
4
期刊介绍: The Journal of Economic and Social Measurement (JESM) is a quarterly journal that is concerned with the investigation of all aspects of production, distribution and use of economic and other societal statistical data, and with the use of computers in that context. JESM publishes articles that consider the statistical methodology of economic and social science measurements. It is concerned with the methods and problems of data distribution, including the design and implementation of data base systems and, more generally, computer software and hardware for distributing and accessing statistical data files. Its focus on computer software also includes the valuation of algorithms and their implementation, assessing the degree to which particular algorithms may yield more or less accurate computed results. It addresses the technical and even legal problems of the collection and use of data, legislation and administrative actions affecting government produced or distributed data files, and similar topics. The journal serves as a forum for the exchange of information and views between data producers and users. In addition, it considers the various uses to which statistical data may be put, particularly to the degree that these uses illustrate or affect the properties of the data. The data considered in JESM are usually economic or social, as mentioned, but this is not a requirement; the editorial policies of JESM do not place a priori restrictions upon the data that might be considered within individual articles. Furthermore, there are no limitations concerning the source of the data.
期刊最新文献
Measuring the US employment situation using online panels: The Yale Labor Survey Revisiting taste change in cost-of-living measurement Assessing the potential for nonresponse bias and measurement concordance in the clinical preventive services self-administered questionnaire survey1 An improved definition of official excess winter mortality statistics as the basis for detailed analysis and monitoring Extending Current Population Survey Linkages: Obstacles and Solutions for Linking Monthly Data from 1976 to 1988.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1