Implementing night light data as auxiliary variable of small area estimation

Abstract

Along with the growing popularity of the small area estimation method, the need to utilize good auxiliary variables also increases. Remote sensing data, such as night light imagery, offers advantages such as time-cost efficiency and global coverage but is easily accessible. This research aims to implement night light intensity as an auxiliary variable for the EBLUP model to estimate per capita consumption expenditure at West Java in 2018. This research employs three scenarios of auxiliary variables usage in EBLUP model construction: official data, night light intensity, and the combination between both data. The results show that night light intensity is an efficient auxiliary variable for estimating per capita consumption expenditure. Furthermore, the EBLUP model with a combination of official data and night light as auxiliary variables gives the best accuracy with coefficient of variation (CV) as evaluation.

Keywords:

• EBLUP
• Black Marble
• remote sensing
• household expenditure
• PODES