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Abstract Modeling-based estimation, namely small area estimation (SAE), is increasingly developing to provide reliable statistics on small areas. SAE’s critical role is to overcome the resource limitations required in presenting statistics at the small area level through direct estimation methods, namely census and survey. SAE is an alternative in fulfilling the need for basic data in small areas to support the accuracy of various policies both by the government and multiple stakeholders to encourage the successful implementation of Agromaritime 4.0 to contribute to sustainable development goals. This research applies SAE to present mean years of schooling (MYS) to provide reliable statistics in small areas. MYS is one of the benchmark indicators and the basis for efforts to improve human resource quality to optimize the implementation of Agromaritime 4.0 and successfully achieve the 2030 agenda of sustainable development goals. The application of the SAE model in this study uses a nested error regression model and a multivariate exchangeable copula model. The use of two models is expected to provide information regarding the performance of the two models and determine the best model in presenting indicators of the youth mean years of schooling by sub-district in West Java Province.
Agustina et al. (Sat,) studied this question.