{"title":"住房过滤率的地理和时间变化","authors":"Liyi Liu, Douglas A. McManus, Elias Yannopoulos","doi":"10.2139/ssrn.3527800","DOIUrl":null,"url":null,"abstract":"In Housing Economics, filtering is the process by which properties, as they age, depreciate in quality and hence price and thus tend to be purchased by lower-income households. This is the primary mechanism by which competitive markets supply low-income housing. While at the national level filtering is an important long-term source of lower-income housing, this research shows that there is a wide range of filtering rates both across and within metropolitan statistical areas (MSAs) for owner-occupied properties. Notably, in some markets, properties “filter up” to higher-income households. This paper contributes to our understanding of filtering by demonstrating the heterogeneity of filtering rates. The analysis finds strong geographic and temporal variation in filtering rates.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Geographic and Temporal Variation in Housing Filtering Rates\",\"authors\":\"Liyi Liu, Douglas A. McManus, Elias Yannopoulos\",\"doi\":\"10.2139/ssrn.3527800\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Housing Economics, filtering is the process by which properties, as they age, depreciate in quality and hence price and thus tend to be purchased by lower-income households. This is the primary mechanism by which competitive markets supply low-income housing. While at the national level filtering is an important long-term source of lower-income housing, this research shows that there is a wide range of filtering rates both across and within metropolitan statistical areas (MSAs) for owner-occupied properties. Notably, in some markets, properties “filter up” to higher-income households. This paper contributes to our understanding of filtering by demonstrating the heterogeneity of filtering rates. The analysis finds strong geographic and temporal variation in filtering rates.\",\"PeriodicalId\":143058,\"journal\":{\"name\":\"Econometric Modeling: Microeconometric Studies of Health\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Modeling: Microeconometric Studies of Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3527800\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Modeling: Microeconometric Studies of Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3527800","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Geographic and Temporal Variation in Housing Filtering Rates
In Housing Economics, filtering is the process by which properties, as they age, depreciate in quality and hence price and thus tend to be purchased by lower-income households. This is the primary mechanism by which competitive markets supply low-income housing. While at the national level filtering is an important long-term source of lower-income housing, this research shows that there is a wide range of filtering rates both across and within metropolitan statistical areas (MSAs) for owner-occupied properties. Notably, in some markets, properties “filter up” to higher-income households. This paper contributes to our understanding of filtering by demonstrating the heterogeneity of filtering rates. The analysis finds strong geographic and temporal variation in filtering rates.