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From start to finish: a framework for the production of small area official statistics

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Cited by:

  1. Batterham, Deb & Nygaard, Christian & reynolds, margaret & De Vries, Jacqueline, 2021. "Estimating the population at-risk of homelessness in small areas," SocArXiv hkc7y, Center for Open Science.
  2. Till Koebe & Alejandra Arias‐Salazar & Natalia Rojas‐Perilla & Timo Schmid, 2022. "Intercensal updating using structure‐preserving methods and satellite imagery," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 170-196, December.
  3. Corral Rodas,Paul Andres & Kastelic,Kristen Himelein & Mcgee,Kevin Robert & Molina,Isabel, 2021. "A Map of the Poor or a Poor Map ?," Policy Research Working Paper Series 9620, The World Bank.
  4. Noah Cheruiyot Mutai, 2022. "Small area estimation of health insurance coverage for Kenyan counties," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 16(3), pages 231-254, December.
  5. Rebecca C. Steorts & Timo Schmid & Nikos Tzavidis, 2020. "Smoothing and Benchmarking for Small Area Estimation," International Statistical Review, International Statistical Institute, vol. 88(3), pages 580-598, December.
  6. Jan Pablo Burgard & Ralf Münnich & Martin Rupp, 2020. "Qualitätszielfunktionen für stark variierende Gemeindegrößen im Zensus 2021 [Quality measures respecting highly varying community sizes within the 2021 German Census]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 14(1), pages 5-65, March.
  7. Chwila Adam & Żądło Tomasz, 2020. "On the choice of the number of Monte Carlo iterations and bootstrap replicates in Empirical Best Prediction," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 35-60, June.
  8. Dawber James & Smith Paul A. & Tzavidis Nikos & Würz Nora & Flower Tanya & Thomas Heledd & Schmid Timo, 2022. "Experimental UK Regional Consumer Price Inflation with Model-Based Expenditure Weights," Journal of Official Statistics, Sciendo, vol. 38(1), pages 213-237, March.
  9. Natalia Rojas‐Perilla & Sören Pannier & Timo Schmid & Nikos Tzavidis, 2020. "Data‐driven transformations in small area estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 121-148, January.
  10. Masaki,Takaaki & Newhouse,David Locke & Silwal,Ani Rudra & Bedada,Adane & Engstrom,Ryan, 2020. "Small Area Estimation of Non-Monetary Poverty with Geospatial Data," Policy Research Working Paper Series 9383, The World Bank.
  11. Dehnel Grażyna & Wawrowski Łukasz, 2020. "Robust estimation of wages in small enterprises: the application to Poland’s districts," Statistics in Transition New Series, Polish Statistical Association, vol. 21(1), pages 137-157, March.
  12. Jan Pablo Burgard & Ralf Münnich & Martin Rupp, 2019. "A Generalized Calibration Approach Ensuring Coherent Estimates with Small Area Constraints," Research Papers in Economics 2019-10, University of Trier, Department of Economics.
  13. Patrick Krennmair & Timo Schmid, 2022. "Flexible domain prediction using mixed effects random forests," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1865-1894, November.
  14. Andreea L. Erciulescu & Jean D. Opsomer, 2022. "A model‐based approach to predict employee compensation components," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1503-1520, November.
  15. Adam Chwila & Tomasz Żądło, 2020. "On the choice of the number of Monte Carlo iterations and bootstrap replicates in Empirical Best Prediction," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 35-60, June.
  16. Paul A. Smith & Chiara Bocci & Nikos Tzavidis & Sabine Krieg & Marc J. E. Smeets, 2021. "Robust estimation for small domains in business surveys," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(2), pages 312-334, March.
  17. Marchetti Stefano & Tzavidis Nikos, 2021. "Robust Estimation of the Theil Index and the Gini Coeffient for Small Areas," Journal of Official Statistics, Sciendo, vol. 37(4), pages 955-979, December.
  18. Paul Corral & Kristen Himelein & Kevin McGee & Isabel Molina, 2021. "A Map of the Poor or a Poor Map?," Mathematics, MDPI, vol. 9(21), pages 1-40, November.
  19. Nora Würz & Timo Schmid & Nikos Tzavidis, 2022. "Estimating regional income indicators under transformations and access to limited population auxiliary information," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1679-1706, October.
  20. Natascha Hainbach & Christoph Halbmeier & Timo Schmid & Carsten Schröder, 2019. "A Practical Guide for the Computation of Domain-Level Estimates with the Socio-Economic Panel (and Other Household Surveys)," SOEPpapers on Multidisciplinary Panel Data Research 1055, DIW Berlin, The German Socio-Economic Panel (SOEP).
  21. Tomasz .Zk{a}d{l}o & Adam Chwila, 2024. "A step towards the integration of machine learning and small area estimation," Papers 2402.07521, arXiv.org.
  22. Christophe Quentin Valvason & Stefan Sperlich, 2024. "A Note on Simultaneous Confidence Intervals for Direct, Indirect and Synthetic Estimators," Stats, MDPI, vol. 7(1), pages 1-17, March.
  23. Benedetti, Ilaria & Crescenzi, Federico, 2023. "The role of income poverty and inequality indicators at regional level: An evaluation for Italy and Germany," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
  24. Jan Breitkreuz & Gabriela Brückner & Jan Pablo Burgard & Joscha Krause & Ralf Münnich & Helmut Schröder & Katrin Schüssel, 2019. "Schätzung kleinräumiger Krankheitshäufigkeiten für die deutsche Bevölkerung anhand von Routinedaten am Beispiel von Typ-2-Diabetes [Estimation of regional diabetes type 2 prevalence in the German p," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 13(1), pages 35-72, April.
  25. Paul Walter & Marcus Groß & Timo Schmid & Nikos Tzavidis, 2021. "Domain prediction with grouped income data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1501-1523, October.
  26. Ann-Kristin Kreutzmann, 2018. "Estimation of sample quantiles: challenges and issues in the context of income and wealth distributions [Die Schätzung von Quantilen: Herausforderungen und Probleme im Kontext von Einkommens- und V," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 245-270, December.
  27. Tonutti, Giovanni & Bertarelli, Gaia & Giusti, Caterina & Pratesi, Monica, 2022. "Disaggregation of poverty indicators by small area methods for assessing the targeting of the “Reddito di Cittadinanza” national policy in Italy," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
  28. Enrico Fabrizi & Maria Rosaria Ferrante & Carlo Trivisano, 2020. "A functional approach to small area estimation of the relative median poverty gap," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1273-1291, June.
  29. Thomas Zimmermann, 2019. "Einsatzmöglichkeiten von Small Area-Verfahren bei Kohortenschätzungen im Zensus 2021 [Applicablity of small area estimation methods for demographic cohorts in the Census 2021]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 13(2), pages 157-177, September.
  30. Katarzyna Reluga & María‐José Lombardía & Stefan Sperlich, 2023. "Simultaneous inference for linear mixed model parameters with an application to small area estimation," International Statistical Review, International Statistical Institute, vol. 91(2), pages 193-217, August.
  31. J. N. K. Rao, 2020. "Discussion of "Small Area Estimation: Its Evolution in Five Decades", by Malay Ghosh," Statistics in Transition New Series, Polish Statistical Association, vol. 21(4), pages 53-58, August.
  32. Kreutzmann, Ann-Kristin & Marek, Philipp & Salvati, Nicola & Schmid, Timo, 2019. "Estimating regional wealth in Germany: How different are East and West really?," Discussion Papers 35/2019, Deutsche Bundesbank.
  33. Grażyna Dehnel & Łukasz Wawrowski, 2020. "Robust estimation of wages in small enterprises: the application to Poland’s districts," Statistics in Transition New Series, Polish Statistical Association, vol. 21(1), pages 137-157, March.
  34. Paolo Frumento & Nicola Salvati, 2020. "Parametric modelling of M‐quantile regression coefficient functions with application to small area estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 229-250, January.
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