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

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.

KEYWORDS:

• Direct estimator
• Diagnostics
• Indebtedness
• Model-based estimation
• Mapping

MATHEMATICS SUBJECT CLASSIFICATION:

• 62D05

Acknowledgments

The authors would like to acknowledge the valuable comments and suggestions of the Editor and an anonymous referee. These led to a considerable improvement in the paper. The work of Hukum Chandra was done under ICAR-National Fellow Scheme at ICAR-IASRI, New Delhi, India.