Nusrat Jafrin, M. M. Masud, A. Saif, M. Mahi, Moriam Khanam
{"title":"对选定南盟国家预期寿命决定因素的面板数据估计","authors":"Nusrat Jafrin, M. M. Masud, A. Saif, M. Mahi, Moriam Khanam","doi":"10.37190/ord210404","DOIUrl":null,"url":null,"abstract":"The precarious and decisive dynamics concerning the health of the population of South Asian Association for Regional Cooperation (SAARC) countries has called for further inquiry into the determinants of Life Expectancy (LE) in this region. Hence, the current paper employs panel data estimation methods to analyse the economic, social, demographic, environmental, and technological factors influencing LE in five SAARC countries. These countries (Bangladesh, India, Pakistan, Nepal, and Sri Lanka) are selected as they are favoured by the country similarity theory and other identical contexts, and because their data are obtained from the World Bank and UNDP databases from 2000 to 2016. The results reveal that the mean year of schooling and sanitation services are significant positive predictors of Life Expectancy at Birth (LEAB). However, the total fertility rate, urban population, and CO2 emissions negatively influence life expectancy. Furthermore, the impact of health expenditure on life expectancy is significant but negative, which is unconventional. On the other hand, other independent variables, such as GDP, gross capital formation, internet usage, and mobile cellular subscription turn out to be insignificant predictors of LEAB. Our aggregate findings reveal some common factors on which the governments of SAARC countries can collaborate to improve the LEAB of the region while identifying some idiosyncratic factors that require tailored attention of the governments and policymakers of the respective nations","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A panel data estimation of the determinants of life expectancy in selected SAARC countries\",\"authors\":\"Nusrat Jafrin, M. M. Masud, A. Saif, M. Mahi, Moriam Khanam\",\"doi\":\"10.37190/ord210404\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The precarious and decisive dynamics concerning the health of the population of South Asian Association for Regional Cooperation (SAARC) countries has called for further inquiry into the determinants of Life Expectancy (LE) in this region. Hence, the current paper employs panel data estimation methods to analyse the economic, social, demographic, environmental, and technological factors influencing LE in five SAARC countries. These countries (Bangladesh, India, Pakistan, Nepal, and Sri Lanka) are selected as they are favoured by the country similarity theory and other identical contexts, and because their data are obtained from the World Bank and UNDP databases from 2000 to 2016. The results reveal that the mean year of schooling and sanitation services are significant positive predictors of Life Expectancy at Birth (LEAB). However, the total fertility rate, urban population, and CO2 emissions negatively influence life expectancy. Furthermore, the impact of health expenditure on life expectancy is significant but negative, which is unconventional. On the other hand, other independent variables, such as GDP, gross capital formation, internet usage, and mobile cellular subscription turn out to be insignificant predictors of LEAB. Our aggregate findings reveal some common factors on which the governments of SAARC countries can collaborate to improve the LEAB of the region while identifying some idiosyncratic factors that require tailored attention of the governments and policymakers of the respective nations\",\"PeriodicalId\":43244,\"journal\":{\"name\":\"Operations Research and Decisions\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research and Decisions\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37190/ord210404\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research and Decisions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37190/ord210404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
A panel data estimation of the determinants of life expectancy in selected SAARC countries
The precarious and decisive dynamics concerning the health of the population of South Asian Association for Regional Cooperation (SAARC) countries has called for further inquiry into the determinants of Life Expectancy (LE) in this region. Hence, the current paper employs panel data estimation methods to analyse the economic, social, demographic, environmental, and technological factors influencing LE in five SAARC countries. These countries (Bangladesh, India, Pakistan, Nepal, and Sri Lanka) are selected as they are favoured by the country similarity theory and other identical contexts, and because their data are obtained from the World Bank and UNDP databases from 2000 to 2016. The results reveal that the mean year of schooling and sanitation services are significant positive predictors of Life Expectancy at Birth (LEAB). However, the total fertility rate, urban population, and CO2 emissions negatively influence life expectancy. Furthermore, the impact of health expenditure on life expectancy is significant but negative, which is unconventional. On the other hand, other independent variables, such as GDP, gross capital formation, internet usage, and mobile cellular subscription turn out to be insignificant predictors of LEAB. Our aggregate findings reveal some common factors on which the governments of SAARC countries can collaborate to improve the LEAB of the region while identifying some idiosyncratic factors that require tailored attention of the governments and policymakers of the respective nations