{"title":"南非家庭对气候变化的脆弱性:一个多层次回归模型","authors":"Sandile Mthethwa, Edilegnaw Wale Zegeye","doi":"10.1080/0376835X.2022.2085667","DOIUrl":null,"url":null,"abstract":"ABSTRACT This study measures the vulnerability of households to food insecurity by measuring the risk or threat posed by climate change. This is conducted using multilevel or hierarchal regression, an extension of the “Three Stage Least Squares” model. Unlike the standard ordinary least squares regression model, this model can produce estimates of different hierarchal levels and produce unbiased reliable standard errors. With a sample size of 18,444 households nested within nine provinces, the findings show that climate change is a reality in South Africa, and it poses serious threats that expose households to future food consumption inadequacies. This study also offers a deeper understanding of the different sources of vulnerability among these households. Poverty or structural-induced vulnerability emerged as the main source of vulnerability for South African households. Climate change-induced vulnerabilities were also found to be prevalent and detrimental in rural areas with Limpopo and Eastern Cape being the most vulnerable provinces.","PeriodicalId":51523,"journal":{"name":"Development Southern Africa","volume":"40 1","pages":"466 - 481"},"PeriodicalIF":1.3000,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Household vulnerability to climate change in South Africa: A multilevel regression model\",\"authors\":\"Sandile Mthethwa, Edilegnaw Wale Zegeye\",\"doi\":\"10.1080/0376835X.2022.2085667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT This study measures the vulnerability of households to food insecurity by measuring the risk or threat posed by climate change. This is conducted using multilevel or hierarchal regression, an extension of the “Three Stage Least Squares” model. Unlike the standard ordinary least squares regression model, this model can produce estimates of different hierarchal levels and produce unbiased reliable standard errors. With a sample size of 18,444 households nested within nine provinces, the findings show that climate change is a reality in South Africa, and it poses serious threats that expose households to future food consumption inadequacies. This study also offers a deeper understanding of the different sources of vulnerability among these households. Poverty or structural-induced vulnerability emerged as the main source of vulnerability for South African households. Climate change-induced vulnerabilities were also found to be prevalent and detrimental in rural areas with Limpopo and Eastern Cape being the most vulnerable provinces.\",\"PeriodicalId\":51523,\"journal\":{\"name\":\"Development Southern Africa\",\"volume\":\"40 1\",\"pages\":\"466 - 481\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2022-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Development Southern Africa\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1080/0376835X.2022.2085667\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"DEVELOPMENT STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Development Southern Africa","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/0376835X.2022.2085667","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DEVELOPMENT STUDIES","Score":null,"Total":0}
Household vulnerability to climate change in South Africa: A multilevel regression model
ABSTRACT This study measures the vulnerability of households to food insecurity by measuring the risk or threat posed by climate change. This is conducted using multilevel or hierarchal regression, an extension of the “Three Stage Least Squares” model. Unlike the standard ordinary least squares regression model, this model can produce estimates of different hierarchal levels and produce unbiased reliable standard errors. With a sample size of 18,444 households nested within nine provinces, the findings show that climate change is a reality in South Africa, and it poses serious threats that expose households to future food consumption inadequacies. This study also offers a deeper understanding of the different sources of vulnerability among these households. Poverty or structural-induced vulnerability emerged as the main source of vulnerability for South African households. Climate change-induced vulnerabilities were also found to be prevalent and detrimental in rural areas with Limpopo and Eastern Cape being the most vulnerable provinces.
期刊介绍:
The Development Southern Africa editorial team are pleased to announce that the journal has been accepted into the Thomson Reuters (formerly ISI) Social Science Citation Index. The journal will receive its first Impact Factor in 2010. Development Southern Africa offers a platform for expressing views and encouraging debate among development specialists, policy decision makers, scholars and students in the wider professional fraternity and especially in southern Africa. The journal publishes articles that reflect innovative thinking on key development challenges and policy issues facing South Africa and other countries in the southern African region.