G. De Giorgi, Anders Frederiksen, Luigi Pistaferri
{"title":"消费网络效应","authors":"G. De Giorgi, Anders Frederiksen, Luigi Pistaferri","doi":"10.1093/RESTUD/RDZ026","DOIUrl":null,"url":null,"abstract":"\n In this article we study consumption network effects. Does the consumption of our peers affect our own consumption? How large is such effect? What are the economic mechanisms behind it? We use administrative panel data on Danish households to construct a measure of consumption based on tax records on income and assets. We combine tax record data with matched employer–employee data to identify peer groups based on workplace, which gives us a much tighter and credible definition of networks than used in previous literature. We use the non-overlapping network structure of one’s peers group, as well as firm-level shocks, to build valid instruments for peer consumption. We estimate non-negligible and statistically significant network effects, capable of generating sizable multiplier effect at the macro-level. We also investigate what mechanisms generate such effects, distinguishing between intertemporal and intratemporal consumption effects as well as a more traditional risk sharing view.","PeriodicalId":331900,"journal":{"name":"IZA Institute of Labor Economics Discussion Paper Series","volume":"131 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"91","resultStr":"{\"title\":\"Consumption Network Effects\",\"authors\":\"G. De Giorgi, Anders Frederiksen, Luigi Pistaferri\",\"doi\":\"10.1093/RESTUD/RDZ026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n In this article we study consumption network effects. Does the consumption of our peers affect our own consumption? How large is such effect? What are the economic mechanisms behind it? We use administrative panel data on Danish households to construct a measure of consumption based on tax records on income and assets. We combine tax record data with matched employer–employee data to identify peer groups based on workplace, which gives us a much tighter and credible definition of networks than used in previous literature. We use the non-overlapping network structure of one’s peers group, as well as firm-level shocks, to build valid instruments for peer consumption. We estimate non-negligible and statistically significant network effects, capable of generating sizable multiplier effect at the macro-level. We also investigate what mechanisms generate such effects, distinguishing between intertemporal and intratemporal consumption effects as well as a more traditional risk sharing view.\",\"PeriodicalId\":331900,\"journal\":{\"name\":\"IZA Institute of Labor Economics Discussion Paper Series\",\"volume\":\"131 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"91\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IZA Institute of Labor Economics Discussion Paper Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/RESTUD/RDZ026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IZA Institute of Labor Economics Discussion Paper Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/RESTUD/RDZ026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this article we study consumption network effects. Does the consumption of our peers affect our own consumption? How large is such effect? What are the economic mechanisms behind it? We use administrative panel data on Danish households to construct a measure of consumption based on tax records on income and assets. We combine tax record data with matched employer–employee data to identify peer groups based on workplace, which gives us a much tighter and credible definition of networks than used in previous literature. We use the non-overlapping network structure of one’s peers group, as well as firm-level shocks, to build valid instruments for peer consumption. We estimate non-negligible and statistically significant network effects, capable of generating sizable multiplier effect at the macro-level. We also investigate what mechanisms generate such effects, distinguishing between intertemporal and intratemporal consumption effects as well as a more traditional risk sharing view.