Zero Inflated Beta Model in Small Area Estimation to Estimate Poverty Rates on Village Level in Langsa Municipality

Abstract

Village level poverty rates are needed as a consideration for allocating village funds. The national socio economic survey samples are designed to estimate poverty rates in province and distric level. Direct estimate for calculating estimates of village level poverty rates does not have a good precision due to small sample sizes. Small Area Estimation (SAE) technique is used to produce a good precision with small sample sizes. The estimates of poverty rates should also be produced for non sampled area and when no poor are included in the sample. We propose zero inflated beta model because poverty rates takes value in the intervals [0,1). Clustering technique is used to acommodate random effect area for non sampled area. The purpose of this research is to estimate poverty rates on village level in Langsa Municipality. The result showed that estimates poverty rates on village level with zero inflated beta model is better than direct estimates.