Performance of copula and nested error regression models in estimating per capita expenditure of sub-district in Pidie Regency

In unit-level small area estimation (SAE), the commonly used nested error regression (NER) model assumes normality which is not always case. To handle non-normal data, researchers in statistics have developed a novel approach using exchangeable and extendible copula called multivariate (MEC) model. This study compares performance of parametric MEC NER models estimating sub-district average per capita expenditure (PCE) Pidie Regency, Aceh Province. presents PCE, has skewed distribution three-parameter skew-normal. The uses Gaussian from Elliptical family an empirical best unbiased prediction (EBUP) estimator. Meanwhile, linear (EBLUP) results reveal that at 95% confidence level, outperforms with smaller root mean squared (RMSE) provides more precise estimate PCE. highlights importance considering as alternative method for data SAE. this potential to support achievement Goal 1 (to end poverty) 10 reduce inequality) sustainable development goals (SDGs) by providing PCE estimates level.