Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Topics
Data & Maps
Surveys & Programs
Resource Library
Hierarchical Bayes Estimation of Poverty Rates
Hierarchical Bayes Estimation of Poverty Rates
Abstract
In practice many applications of small area models use a `Normal-Normal-Linear' assumption, i.e., a normality assumption for the design-based survey estimates and for the area-level random effects and a linear regression function relating the true parameters to available co-variates. We compare the performance of rate models by slightly changing the assumptions and using internal and external checks, when area sample sizes are in the hundreds, empirical analyses using a 'Normal-t-Linear' to protect against outliers, or a seemingly reasonable `Beta-logistic' assumption for rates, show no gain over the `Normal-Normal-Linear' type model. However, the same type of analyses show additional benefit from including historical data through a cross-sectional and time series model. We use Monte Carlo Markov Chain (MCMC) to implement the proposed models, posterior predictive checks, as well as external checks for model comparisons.
Related Information
Page Last Revised - October 8, 2021
✕
Is this page helpful?
Yes
No
Yes
No✕
NO THANKS
255 characters maximum
255 characters maximum reached
255 characters maximum reached
✕
Thank you for your feedback.
Comments or suggestions?
Comments or suggestions?
