Digital population and housing census – the experience of Serbia

Miladin Kovačević; Mira Nikić; Branko Josipović; Snežana Lakčević; Vesna Pantelić; Nevena Mitrović; Adil Kolaković; Petar Korović

doi:https://doi.org/10.59139/ws.2023.10.3

Miladin Kovačević Statistical Office of the Republic of Serbia, Serbia. ORCID: https://orcid.org/0009-0002-2398-7955 , Mira Nikić Statistical Office of the Republic of Serbia, Serbia. ORCID: https://orcid.org/0009-0003-2340-8789 , Branko Josipović Statistical Office of the Republic of Serbia, Serbia. ORCID: https://orcid.org/0009-0009-3191-5784 , Snežana Lakčević Statistical Office of the Republic of Serbia, Serbia. ORCID: https://orcid.org/0009-0002-8106-8412 , Vesna Pantelić Statistical Office of the Republic of Serbia, Serbia. ORCID: https://orcid.org/0009-0002-6430-9288 , Nevena Mitrović Statistical Office of the Republic of Serbia, Serbia. ORCID: https://orcid.org/0009-0000-2730-8011 , Adil Kolaković Statistical Office of the Republic of Serbia, Serbia. ORCID: https://orcid.org/0009-0008-2553-3707 , Petar Korović Statistical Office of the Republic of Serbia, Serbia. ORCID: https://orcid.org/0009-0004-5761-8554 Wiadomości Statystyczne. The Polish Statistician, vol. 68, 2023, 10, s. 49-70 Opublikowano online: 31 października 2023 DOI https://doi.org/10.59139/ws.2023.10.3 Sposób cytowania: Kovačević, M., Nikić, M., Josipović, B., Lakčević, S., Pantelić, V., Mitrović, N., Kolaković, A., Korović, P. (2023). Digital population and housing census – the experience of Serbia. Wiadomości Statystyczne. The Polish Statistician, 68(10), 49–70. https://doi.org/10.59139/ws.2023.10.3.

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ARTYKUŁ

(Angielski) PDF

STRESZCZENIE

The aim of the paper is to present the experience of the Republic of Serbia in conducting the 2022 Census of Population, Households and Dwellings, focusing on the employment, legal framework and financing of the census as well as on its successful implementation. It discusses strategic decisions on data collection and the integration of information technology – including geospatial data, data collection techniques, machine learning, record linkage and monitoring system – to overcome the challenges posed by the census. The paper addresses the census undercoverage, explores the use of administrative data for item imputation, and examines the development of a statistical population register. The study demonstrates the benefits of adopting a digital-census approach: significant improvement of accuracy, cost reduction and acquired expeditiousness.
The Statistical Office of the Republic of Serbia conducted a digital census combined with traditional methods, excluding self-enumeration, along with the use of administrative data for item imputation, and recommends this approach as the most effective way to obtain precise and comprehensive information about a population, including its demographic characteristics, geographic distribution and overall size.

SŁOWA KLUCZOWE

2022 Census of Population, Households and Dwellings, digital census, geospatial data, monitoring system, machine learning, administrative data, record linkage, imputation, statistical population register, Serbia

JEL

J18, M15, N34

BIBLIOGRAFIA

Law on 2021 Census of Population, Households and Dwellings (Official Gazette of RS No. 9/20 of 4 February 2020). https://popis2022.stat.gov.rs/media/1596/law-on-the-2021-census.pdf.

United Nations. (2015). Conference of European Statisticians Recommendations for the 2020 Censuses of Population and Housing. http://www.unece.org/publications/2020recomm.html.

United Nations. (2017). Principles and Recommendations for Population and Housing Censuses, Revision 3. https://unstats.un.org/unsd/demographic-social/Standards-and-Methods/files/Principles_and_Recommendations/Population-and-Housing-Censuses/Series_M67rev3-E.pdf.

United Nations. (2019). Guidelines on the use of electronic data collection technologies in population and housing censuses. https://unstats.un.org/unsd/demographic/standmeth/handbooks/data-collection-census-201901.pdf.

United Nations Economic Commission for Europe Statistic Wikis. (n.d.). Machine Learning for Official Statistics. https://statswiki.unece.org/display/ML/Machine+Learning+for+Official+Statistics+Home.

Zakon o izmienama zakona o popisu stanownisztwa, domaćinstawa i stanowa 2022. Godine (Official Gazette of RS No. 35/21 of 16 April 2021). https://popis2022.stat.gov.rs/media/1595/zakon-o-popisu-2021.pdf.

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