{"title":"A Study on Long-Term Housing Demand by Region using the Demographic and Household based Mankiw-Weil Method","authors":"Hyun-jun Park, Changha Jin","doi":"10.24957/hsr.2023.31.2.5","DOIUrl":null,"url":null,"abstract":"We attempt to analyze longitudinal housing demand with the number of population and number of household size from the Korea Housing Survey from 2016 to 2020 using the Mankiw-Weil Method. We also include singles and couples in the young and the old age group to identify the relative housing demand. Furthermore, we extend our analysis to 17 regional housing markets and examine the regional housing demand to confirm whether heterogeneity of regional housing demand exists. Using the machine learning method, we also provide the relative importance of variables influencing housing demand. Thus, we expect to provide an efficient housing policy by monitoring critical changes in the influential variables affecting housing demand.","PeriodicalId":255849,"journal":{"name":"Korean Association for Housing Policy Studies","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korean Association for Housing Policy Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24957/hsr.2023.31.2.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We attempt to analyze longitudinal housing demand with the number of population and number of household size from the Korea Housing Survey from 2016 to 2020 using the Mankiw-Weil Method. We also include singles and couples in the young and the old age group to identify the relative housing demand. Furthermore, we extend our analysis to 17 regional housing markets and examine the regional housing demand to confirm whether heterogeneity of regional housing demand exists. Using the machine learning method, we also provide the relative importance of variables influencing housing demand. Thus, we expect to provide an efficient housing policy by monitoring critical changes in the influential variables affecting housing demand.