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The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators
[journal article]
Abstract The R package emdi enables the estimation of regionally disaggregated indicators using small area estimation methods and includes tools for processing, assessing, and presenting the results. The mean of the target variable, the quantiles of its distribution, the headcount ratio, the poverty gap, the... view more
The R package emdi enables the estimation of regionally disaggregated indicators using small area estimation methods and includes tools for processing, assessing, and presenting the results. The mean of the target variable, the quantiles of its distribution, the headcount ratio, the poverty gap, the Gini coefficient, the quintile share ratio, and customized indicators are estimated using direct and model-based estimation with the empirical best predictor (Molina and Rao 2010). The user is assisted by automatic estimation of datadriven transformation parameters. Parametric and semi-parametric, wild bootstrap for mean squared error estimation are implemented with the latter offering protection against possible misspecification of the error distribution. Tools for (a) customized parallel computing, (b) model diagnostic analyses, (c) creating high quality maps and (d) exporting the results to Excel and OpenDocument Spreadsheets are included. The functionality of the package is illustrated with example data sets for estimating the Gini coefficient and median income for districts in Austria.... view less
Keywords
official statistics; statistics; survey; estimation; visualization; software; Austria
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
survey statistics; parallel computing; small area estimation; European Union Statistics on Income and Living Conditions (EU-SILC) in Austria from 2006
Document language
English
Publication Year
2019
Page/Pages
p. 1-33
Journal
Journal of Statistical Software, 91 (2019) 7
DOI
https://doi.org/10.18637/jss.v091.i07
ISSN
1548-7660
Status
Published Version; peer reviewed