The most commonly used method of small area estimation (SAE) is the empirical best linear unbiased prediction method based on a linear mixed model. However, it is not appropriate in the case of the zero-inflated target variable with a mixture of zeros and continuously distributed positive values. Therefore, various model-based SAE methods for zero-inflated data are developed, such as the Frequentist approach and the Bayesian approach. Both approaches are compared with the survey regression (SR) method which ignores the presence of zero-inflation in the data. The results show that the two SAE approaches for zero-inflated data are capable to yield more accurate area mean estimates than the SR method.
Sadik, K., Anisa, R., & Aqmaliyah, E. (2019). Small area estimation on zero-inflated data using frequentist and Bayesian approach. Journal of Modern Applied Statistical Methods, 18(1), eP2677. doi: 10.22237/jmasm/1582727606