A Framework for Producing Small Area Estimates Based on Area-Level Models in R

The R package emdi facilitates the estimation of regionally disaggregated indicators using small area estimation methods and provides tools for model building, diagnostics, presenting, and exporting the results. The package version 1.1.7 includes unit-level small area models that rely on access to micro data. The area-level model by Fay and Herriot (1979) and various extensions have been added to the package since the release of version 2.0.0. These extensions include (a) area-level models with back-transformations, (b) spatial and robust extensions, (c) adjusted variance estimation methods, and (d) area-level models that account for measurement errors. Corresponding mean squared error estimators are implemented for assessing the uncertainty. User-friendly tools like a stepwise variable selection, model diagnostics, benchmarking options, high quality maps and results exportation options enable a complete analysis procedure. The functionality of the package is illustrated by examples based on synthetic data for Austrian districts.

Sylvia Harmening (Institute for Statistics and Econometrics, School of Business & Economics, Freie Universität Berlin) , Ann-Kristin Kreutzmann (Institute for Statistics and Econometrics, School of Business & Economics, Freie Universität Berlin) , Sören Schmidt (Institute for Statistics and Econometrics, School of Business & Economics, Freie Universität Berlin) , Nicola Salvati (Department of Economics and Management, University of Pisa) , Timo Schmid (Institute of Statistics, Otto-Friedrich-Universität Bamberg)
2023-09-24

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2023-039.zip

R. E. Fay and R. A. Herriot. Estimates of income for small places: An application of James-Stein procedures to census data. Journal of the American Statistical Association, 74(366): 269–277, 1979. URL https://doi.org/10.1080/01621459.1979.10482505.

References

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Citation

For attribution, please cite this work as

Harmening, et al., "A Framework for Producing Small Area Estimates Based on Area-Level Models in R", The R Journal, 2023

BibTeX citation

@article{RJ-2023-039,
  author = {Harmening, Sylvia and Kreutzmann, Ann-Kristin and Schmidt, Sören and Salvati, Nicola and Schmid, Timo},
  title = {A Framework for Producing Small Area Estimates Based on Area-Level Models in R},
  journal = {The R Journal},
  year = {2023},
  note = {https://doi.org/10.32614/RJ-2023-039},
  doi = {10.32614/RJ-2023-039},
  volume = {15},
  issue = {1},
  issn = {2073-4859},
  pages = {316-341}
}