{"title":"社区、网络和交付方法","authors":"Emilia Barili, P. Bertoli, V. Grembi","doi":"10.2139/ssrn.3688559","DOIUrl":null,"url":null,"abstract":"We examine the contribution of information transmission among pregnant women to geographic variation in C-sections in Lombardy, Italy. Defining networks as pregnant women living in the same municipality, we observe that if the incidence of C-sections within the womans network is one standard deviation higher over the 12 months preceding delivery, then her probability of delivering by C-section is 0.007 percentage points (3%) higher. This result is mainly a network effect on Italian women, while it arises from both network and neighborhood effects on foreign women. Both groups respond to additional information, such as the incidence of C-section complications. The selection of pregnant women across hospitals does not uniquely explain our results, which are robust to alternative sample selections and specifications.","PeriodicalId":117634,"journal":{"name":"Social & Personality Psychology eJournal","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Neighborhoods, Networks, and Delivery Methods\",\"authors\":\"Emilia Barili, P. Bertoli, V. Grembi\",\"doi\":\"10.2139/ssrn.3688559\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We examine the contribution of information transmission among pregnant women to geographic variation in C-sections in Lombardy, Italy. Defining networks as pregnant women living in the same municipality, we observe that if the incidence of C-sections within the womans network is one standard deviation higher over the 12 months preceding delivery, then her probability of delivering by C-section is 0.007 percentage points (3%) higher. This result is mainly a network effect on Italian women, while it arises from both network and neighborhood effects on foreign women. Both groups respond to additional information, such as the incidence of C-section complications. The selection of pregnant women across hospitals does not uniquely explain our results, which are robust to alternative sample selections and specifications.\",\"PeriodicalId\":117634,\"journal\":{\"name\":\"Social & Personality Psychology eJournal\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Social & Personality Psychology eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3688559\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social & Personality Psychology eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3688559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We examine the contribution of information transmission among pregnant women to geographic variation in C-sections in Lombardy, Italy. Defining networks as pregnant women living in the same municipality, we observe that if the incidence of C-sections within the womans network is one standard deviation higher over the 12 months preceding delivery, then her probability of delivering by C-section is 0.007 percentage points (3%) higher. This result is mainly a network effect on Italian women, while it arises from both network and neighborhood effects on foreign women. Both groups respond to additional information, such as the incidence of C-section complications. The selection of pregnant women across hospitals does not uniquely explain our results, which are robust to alternative sample selections and specifications.