Small area estimation of proportions under a spatial dependent aggregated level random effects model

Hukum Chandra and Nicola Salvati

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 5, 1234-1255

Abstract: This paper describes small area estimation (SAE) of proportions under a spatial dependent generalized linear mixed model using aggregated level data. The SAE is also applied to produce reliable district level estimates and mapping of incidence of indebtedness in the State of Uttar Pradesh in India using debt and investment survey data collected by National Sample Survey Office (NSSO) and the secondary data from the Census. The results show a significant improvement in precision of model-based estimates generated by SAE as compared to direct estimates. The estimates generated by incorporating spatial information are more efficient than the one generated by ignoring this information.

Date: 2018
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DOI: 10.1080/03610926.2017.1317806

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