IDEAS home Printed from https://ideas.repec.org/a/spr/astaws/v13y2019i2d10.1007_s11943-019-00243-x.html
   My bibliography  Save this article

Einsatzmöglichkeiten von Small Area-Verfahren bei Kohortenschätzungen im Zensus 2021
[Applicablity of small area estimation methods for demographic cohorts in the Census 2021]

Author

Listed:
  • Thomas Zimmermann

    (Statistisches Bundesamt)

Abstract

Zusammenfassung Wie schon 2011 wird auch 2021 in Deutschland wieder ein registergestützter Zensus durchgeführt. Dabei werden die benötigten Informationen soweit wie möglich aus Melderegistern und anderen Verwaltungsdaten zusammengetragen und um weitere Informationen aus Primärerhebungen ergänzt. Eine jener Erhebungen ist die Haushaltsstichprobe, deren wichtigster Zweck die Korrektur der Register um Karteileichen und Fehlbestände zur Schätzung der Einwohnerzahl ist. Darüber hinaus wird mit Hilfe der Haushaltsstichprobe eine Vielzahl von weiteren regional und inhaltlich tief gegliederten Zensusergebnissen ermittelt, wie zum Beispiel für regional und demographisch differenzierte Bevölkerungskohorten. Da es nicht möglich ist für alle Kohorten einen ausreichend großen Stichprobenumfang sicherzustellen, können design-basierte Schätzverfahren keine verlässlichen Schätzwerte für jene Kohorten garantieren. Im vorliegenden Beitrag untersuchen wir daher, inwiefern geeignete Small Area-Schätzverfahren verlässliche und plausible Ergebnisse für regional und demographisch differenzierte Bevölkerungskohorten im Zensus liefern können.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:astaws:v:13:y:2019:i:2:d:10.1007_s11943-019-00243-x
    DOI: 10.1007/s11943-019-00243-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11943-019-00243-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11943-019-00243-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    2. Nikos Tzavidis & Li‐Chun Zhang & Angela Luna & Timo Schmid & Natalia Rojas‐Perilla, 2018. "From start to finish: a framework for the production of small area official statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 927-979, October.
    3. Burgard, Jan Pablo & Münnich, Ralf T., 2012. "Modelling over and undercounts for design-based Monte Carlo studies in small area estimation: An application to the German register-assisted census," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2856-2863.
    4. Li‐Chun Zhang & Raymond L. Chambers, 2004. "Small area estimates for cross‐classifications," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(2), pages 479-496, May.
    5. Ralf Münnich & Jan Burgard & Martin Vogt, 2013. "Small Area-Statistik: Methoden und Anwendungen," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 6(3), pages 149-191, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Timo Schmid & Markus Zwick, 2019. "Vorwort der Herausgeber," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 13(2), pages 95-97, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Friedrich, Ulf & Münnich, Ralf & de Vries, Sven & Wagner, Matthias, 2015. "Fast integer-valued algorithms for optimal allocations under constraints in stratified sampling," Computational Statistics & Data Analysis, Elsevier, vol. 92(C), pages 1-12.
    3. 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.
    4. 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.
    5. 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.
    6. JANSSENS, Jochen & DE CORTE, Annelies & SÖRENSEN, Kenneth, 2016. "Water distribution network design optimisation with respect to reliability," Working Papers 2016007, University of Antwerp, Faculty of Business and Economics.
    7. Raymond Hernandez & Elizabeth A. Pyatak & Cheryl L. P. Vigen & Haomiao Jin & Stefan Schneider & Donna Spruijt-Metz & Shawn C. Roll, 2021. "Understanding Worker Well-Being Relative to High-Workload and Recovery Activities across a Whole Day: Pilot Testing an Ecological Momentary Assessment Technique," IJERPH, MDPI, vol. 18(19), pages 1-17, October.
    8. Christopher Hassall & Michael Nisbet & Evan Norcliffe & He Wang, 2024. "The Potential Health Benefits of Urban Tree Planting Suggested through Immersive Environments," Land, MDPI, vol. 13(3), pages 1-12, February.
    9. Jie Zhao & Ji Chen & Damien Beillouin & Hans Lambers & Yadong Yang & Pete Smith & Zhaohai Zeng & Jørgen E. Olesen & Huadong Zang, 2022. "Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    10. Elisabeth Beckmann & Lukas Olbrich & Joseph Sakshaug, 2024. "Multivariate assessment of interviewer-related errors in a cross-national economic survey (Lukas Olbrich, Elisabeth Beckmann, Joseph W. Sakshaug)," Working Papers 253, Oesterreichische Nationalbank (Austrian Central Bank).
    11. F J Heather & D Z Childs & A M Darnaude & J L Blanchard, 2018. "Using an integral projection model to assess the effect of temperature on the growth of gilthead seabream Sparus aurata," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-19, May.
    12. Valentina Krenz & Arjen Alink & Tobias Sommer & Benno Roozendaal & Lars Schwabe, 2023. "Time-dependent memory transformation in hippocampus and neocortex is semantic in nature," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    13. Morán-Ordóñez, Alejandra & Ameztegui, Aitor & De Cáceres, Miquel & de-Miguel, Sergio & Lefèvre, François & Brotons, Lluís & Coll, Lluís, 2020. "Future trade-offs and synergies among ecosystem services in Mediterranean forests under global change scenarios," Ecosystem Services, Elsevier, vol. 45(C).
    14. Jack McDonnell & Thomas McKenna & Kathryn A. Yurkonis & Deirdre Hennessy & Rafael Andrade Moral & Caroline Brophy, 2023. "A Mixed Model for Assessing the Effect of Numerous Plant Species Interactions on Grassland Biodiversity and Ecosystem Function Relationships," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(1), pages 1-19, March.
    15. Ana Pinto & Tong Yin & Marion Reichenbach & Raghavendra Bhatta & Pradeep Kumar Malik & Eva Schlecht & Sven König, 2020. "Enteric Methane Emissions of Dairy Cattle Considering Breed Composition, Pasture Management, Housing Conditions and Feeding Characteristics along a Rural-Urban Gradient in a Rising Megacity," Agriculture, MDPI, vol. 10(12), pages 1-18, December.
    16. Damian M. Herz & Manuel Bange & Gabriel Gonzalez-Escamilla & Miriam Auer & Keyoumars Ashkan & Petra Fischer & Huiling Tan & Rafal Bogacz & Muthuraman Muthuraman & Sergiu Groppa & Peter Brown, 2022. "Dynamic control of decision and movement speed in the human basal ganglia," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    17. Kathrin Stenchly & Marc Victor Hansen & Katharina Stein & Andreas Buerkert & Wilhelm Loewenstein, 2018. "Income Vulnerability of West African Farming Households to Losses in Pollination Services: A Case Study from Ouagadougou, Burkina Faso," Sustainability, MDPI, vol. 10(11), pages 1-12, November.
    18. Dongyan Liu & Chongran Zhou & John K. Keesing & Oscar Serrano & Axel Werner & Yin Fang & Yingjun Chen & Pere Masque & Janine Kinloch & Aleksey Sadekov & Yan Du, 2022. "Wildfires enhance phytoplankton production in tropical oceans," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    19. Zhaogeng Yang & Yanhui Li & Peijin Hu & Jun Ma & Yi Song, 2020. "Prevalence of Anemia and its Associated Factors among Chinese 9-, 12-, and 14-Year-Old Children: Results from 2014 Chinese National Survey on Students Constitution and Health," IJERPH, MDPI, vol. 17(5), pages 1-10, February.
    20. 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.

    More about this item

    Keywords

    Log-lineare Modelle; Multidimensionale Häufigkeitstabellen; Modellwahl; Geschlechterproportionen;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:astaws:v:13:y:2019:i:2:d:10.1007_s11943-019-00243-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.