{"title":"Estimation of Total Fertility Rate (TFR) Using Small Area Estimation (SAE) in Nusa Tenggara Timur (NTT) Province","authors":"Mellinda Mellinda, C. Sumarni","doi":"10.34123/icdsos.v2021i1.107","DOIUrl":null,"url":null,"abstract":"The large population in Indonesia has an impact on providing basic services for population which is not optimal so the condition and distribution of the population in a country must be addressed through fertility control methods. Total Fertility Rate (TFR) is one of fertility measures used in Indonesia. The estimation of TFR at the district level is very important, especially for the Nusa Tenggara Timur (NTT) Province as the province with the highest TFR in Indonesia. The availability of TFR data up to the district level is difficult to obtain every year due to data limitations. This study uses the National Socio-Economic Survey to address these problems. TFR estimation through survey data (direct estimation) generally results in a large Relative Standard Error (RSE) value, so it is necessary to estimate using an indirect estimate in the form of Small Area Estimation (SAE). By using SAERestricted Maximum Likelihood (REML) procedure, TFR with an RSE that is lower than the direct estimate is obtained. There are 5 district that have a medium-high TFR, namely: Sumba Barat Daya, Sumba Tengah, Sabu Raijua, Sumba Barat, and Manggarai Barat. The government is recommended to focus more on that 5 districts to suppress the high TFR in NTT.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of The International Conference on Data Science and Official Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34123/icdsos.v2021i1.107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The large population in Indonesia has an impact on providing basic services for population which is not optimal so the condition and distribution of the population in a country must be addressed through fertility control methods. Total Fertility Rate (TFR) is one of fertility measures used in Indonesia. The estimation of TFR at the district level is very important, especially for the Nusa Tenggara Timur (NTT) Province as the province with the highest TFR in Indonesia. The availability of TFR data up to the district level is difficult to obtain every year due to data limitations. This study uses the National Socio-Economic Survey to address these problems. TFR estimation through survey data (direct estimation) generally results in a large Relative Standard Error (RSE) value, so it is necessary to estimate using an indirect estimate in the form of Small Area Estimation (SAE). By using SAERestricted Maximum Likelihood (REML) procedure, TFR with an RSE that is lower than the direct estimate is obtained. There are 5 district that have a medium-high TFR, namely: Sumba Barat Daya, Sumba Tengah, Sabu Raijua, Sumba Barat, and Manggarai Barat. The government is recommended to focus more on that 5 districts to suppress the high TFR in NTT.
印度尼西亚人口众多,对向人口提供基本服务产生了影响,这种服务不是最佳的,因此必须通过生育控制方法来解决一个国家人口的状况和分布问题。总生育率(TFR)是印度尼西亚使用的生育指标之一。地区一级的总生育率估算非常重要,特别是对于努沙登加拉帖木儿省(NTT),因为它是印度尼西亚总生育率最高的省份。由于数据的限制,每年都难以获得地区一级的总生育率数据。本研究使用国家社会经济调查来解决这些问题。通过调查数据估算TFR(直接估算)通常会导致较大的相对标准误差(Relative Standard Error, RSE)值,因此有必要采用小面积估算(Small Area estimation, SAE)的形式进行间接估算。通过使用saererestricted Maximum Likelihood (REML)方法,获得了RSE低于直接估计的TFR。有5个地区的总生育率为中高水平,分别是:Sumba Barat Daya、Sumba Tengah、Sabu Raijua、Sumba Barat和Manggarai Barat。建议政府将重点放在这5个地区,以抑制NTT地区的高TFR。