挪威住房财富，1993-20151

Q3 Social Sciences Journal of Economic and Social Measurement Pub Date : 2021-01-13 DOI:10.3233/jem-200471

Å. Fagereng, Martin B. Holm, Kjersti Næss Torstensen

{"title":"挪威住房财富，1993-20151","authors":"Å. Fagereng, Martin B. Holm, Kjersti Næss Torstensen","doi":"10.3233/jem-200471","DOIUrl":null,"url":null,"abstract":"We provide a new estimate of household-level housing wealth in Norway between 1993 and 2015 using an ensemble machine learning method on housing transaction data. The new housing wealth measure is an improvement over existing data sources for two reasons. First, the model outperforms previously applied regression models in out-of-sample prediction precision. Second, we extend the sample of estimated housing wealth by including cooperative units, non-id apartments, and cabins.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/jem-200471","citationCount":"1","resultStr":"{\"title\":\"Housing wealth in Norway, 1993–20151\",\"authors\":\"Å. Fagereng, Martin B. Holm, Kjersti Næss Torstensen\",\"doi\":\"10.3233/jem-200471\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We provide a new estimate of household-level housing wealth in Norway between 1993 and 2015 using an ensemble machine learning method on housing transaction data. The new housing wealth measure is an improvement over existing data sources for two reasons. First, the model outperforms previously applied regression models in out-of-sample prediction precision. Second, we extend the sample of estimated housing wealth by including cooperative units, non-id apartments, and cabins.\",\"PeriodicalId\":53705,\"journal\":{\"name\":\"Journal of Economic and Social Measurement\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.3233/jem-200471\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Economic and Social Measurement\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/jem-200471\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic and Social Measurement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/jem-200471","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

摘要

我们使用房屋交易数据的集成机器学习方法，对挪威1993年至2015年间的家庭住房财富进行了新的估计。新的住房财富衡量标准是对现有数据来源的改进，原因有二。首先，该模型在样本外预测精度上优于先前应用的回归模型。其次，我们扩大了估计住房财富的样本，包括合作单位，非id公寓和小木屋。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Housing wealth in Norway, 1993–20151

We provide a new estimate of household-level housing wealth in Norway between 1993 and 2015 using an ensemble machine learning method on housing transaction data. The new housing wealth measure is an improvement over existing data sources for two reasons. First, the model outperforms previously applied regression models in out-of-sample prediction precision. Second, we extend the sample of estimated housing wealth by including cooperative units, non-id apartments, and cabins.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Economic and Social Measurement Social Sciences-Social Sciences (all)

CiteScore

1.60

自引率

0.00%

发文量

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.