MEĐUPOPISNE PROCENE U SRBIJI 2011-2022 Da li su neophodne?
INTERCENSAL POPULATION ESTIMATES IN SERBIA 2011-2022 Are they necessary?

Summary/Abstract: The paper aims to highlight the significance of understanding methodology and methodological changes in demographic research. A solid grasp of various methodological approaches to data collection and processing is crucial for any scientific analysis and interpretation of population trends. The paper examines certain methodological discrepancies in the data used for analyzing demographic trends in Serbia during the 21st century. However, its main focus is the creation and presentation of population intercensal estimates by age and sex for Serbia between 2011 and 2022. The findings suggest that if an appropriate method for postcensal estimates by age and gender is used (such as the cohort component method), without accounting for migration, there is a tendency to overestimate the young and working-age population, while underestimating the elderly population. Specifically, the significant overestimation of individuals aged 85 and older in official estimates is due to the application of an unsuitable estimation method. The adjustments of demographic indicators (such as the Total Fertility Rate and Aging Index), provided as examples in the paper, present a more realistic trajectory of changes and help avoid confusion caused by sharp value jumps just before the census. The analysis of intercensal estimates data can also offer insights into migration balances during the intercensal period and provide an estimation of the number of emigrants. The paper’s results show that Serbia experienced a emigration of 262,836 people between 2011 and 2022, averaging around 24,000 per year. According to the 2022 census, the number of immigrants was 155,867, representing the lowest possible figure (an average of about 14,000 annually). If we assume that administrative data expanded the census coverage in 2022, it can be inferred that the negative net migration, as estimated using vital statistics, is significantly underestimated.

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