Official population statistics and the Human Mortality Database estimates of populations aged 80+ in Germany and nine other European countries

A systematic comparison of the Human Mortality Database and official estimates of populations aged 80+ is presented. We consider statistical series for East and West Germany and also for Denmark, England and Wales, France, Finland, Hungary, the Netherlands, Russia, Sweden, and Switzerland. The Human Mortality Database (HMD, www.mortality.org) methodology relies on the methods of extinct and almost extinct generations. HMD estimates are precise if the quality of death data is high and the migration among the elderly is negligible. The comparisons between the HMD and the official populations are not fully appropriate for the 1990s since the HMD calculations are related to official population estimates. A significant overestimation of the male population aged 80+ and especially 90+ between the censuses of 1970 and 1987 was found in West Germany. The relative surplus of men aged 90+ increased from 5 to 20 percent, which expressed in absolute numbers indicates an increase from 2 to 10 thousand. In 1971-1987 the official death rates have fallen dramatically to implausibly low values. In 1987-88 death rates based on the official populations suddenly jumped to the HMD death rates due to the census re-estimation. In the 1990s an accelerated decrease in male death rates has resumed. Among other countries, the relative and absolute deviations from the HMD estimates were especially high in Russia, Hungary, and England and Wales. Regression analysis reveals common factors of the relative deviation from the HMD populations. The deviation tends to decrease with time, increase with age, be higher during inter-census periods than in census years, and to decrease after the introduction of population registers.age/aging, elderly, population estimates, quality of statistics, statistics

Estimates of mortality and population changes in England and Wales over the two World Wars

Almost one million soldiers from England and Wales died during the First and Second World War whilst serving in the British Armed Forces. Although many articles and books have been published that commemorate the military efforts of the British Armed Forces, data on the demographic aspects of British army losses remain fragmentary. Official population statistics on England and Wales have provided continuous series on the civilian population, including mortality and fertility over the two war periods. The combatant population and combatant mortality have not been incorporated in the official statistics, which shows large out-migration at the beginning and large in-migration towards the end of the war periods. In order to estimate the dynamics of the total population and its excess mortality, we introduce in this paper a model of population flows and mortality in times of war operations. The model can be applied to a detailed reconstruction of war losses, using various shapes of the input data. This enables us to arrive at detailed estimates of war-related losses in England and Wales during the two world wars. Our results agree with elements of data provided by prior studies.England, First World War, population estimates, Second World War, Wales

Verfahren zur Korrektur der Bevölkerungsbestände der amtlichen Statistik im hohen Alter

Mit den Daten der Rentenversicherung lassen sich die Bevölkerungsbestände der amtlichen Statistik im hohen Alter korrigieren. Die Korrektur wird notwendig, da die Mortalitätsschätzung im hohen Alter zu nicht plausiblen Ergebnissen führt. Es zeigt sich, dass die Bevölkerungsfortschreibung der amtlichen Statistik im Alter von 90 Lebensjahren und älter die Bestände überschätzt. Mit dem größer werdenden Abstand zur Volkszählung steigt der Fortschreibungsfehler. Die Ursache liegt mit großer Wahrscheinlichkeit in den nicht dokumentierten Abmeldungen insbesondere am Anfang der neunziger Jahre. Der relative Fehler wird für das Jahr 2004 bei Männern West mit 40% und bei Frauen West bis zu 20 % veranschlagt. Im Osten ist der Fehler auf Grund der geringen Abweichungen vernachlässigbar. Durch die Rekonstruktion mittels „Extinct Generation; Survival Ratio Method“ aus den Sterbefällen und dem Vergleich der Bestände der Rentenversicherung mit den Beständen der Amtlichen Statistik lassen sich Korrekturfaktoren ableiten. Mit Hilfe dieser Korrekturfaktoren ist es möglich, die Human Mortality Database (www.mortality.org) für Deutschland in der notwendigen Qualität nach Einzelalter bis in das höchste Lebensalter weiterzuführen.Germany, old age

Changes in educational differentials in old-age mortality in Finland and Sweden between 1971-1975 and 1996-2000

The majority of the studies on developed countries confirm that socioeconomic mortality inequalities have been persisting or even widening. It has also been suggested that inequalities have been becoming increasingly important for old ages. The vast majority of the findings on mortality differentials rely on life table or aggregated mortality measures. However, conventional mean lifespan (life expectancy) hides important characteristics of the distribution of lifespan. Modal age at death and measures of disparity provide additional important insights on longevity, especially when focusing on mortality and survival at old ages. In this paper, using high quality census-linked data and both conventional life expectancy and distribution of life span measures, we systematically assess the direction and magnitude of changes in mortality differences at old ages in Sweden and Finland over the period 1971 to 2000. We found that educational gap in life expectancy at age 65 increased in both countries. Although the results suggest that life expectancy gap was largely explained by differential mortality due to cardiovascular system diseases, the role of other causes of death (especially cancers) has also increased. The educational gap in the modal age at death for Swedish males and Finnish females decreased, whereas it remained at the same level or slightly increased for Finnish males and Swedish females. Life span disparity was initially lower in low education groups, but eventually became higher than in high education group

Beyond the Kannisto-Thatcher Database on Old Age Mortality: an assessment of data quality at advanced ages

The old age population in developed countries has been increasing remarkably, yet internationally comparable high quality data on oldest-old mortality remain relatively scarce. The Kannisto-Thatcher Old Age Mortality Database (KTD) is a unique source providing uniformly recalculated old-age mortality data for 35 countries. Our study addresses a number of data quality issues relevant to population and death statistics at the most advanced ages. Following previous studies by Väinö Kannisto, we apply the same set of measures. This allows us to identify dubious or irregular mortality patterns. Deviations such as this often suggest that the data quality has serious problems. We update previously published findings by extending the analyses made so far to thirty five countries and by adding data on longer historical periods. In addition, we propose a systematic classification of country- and period-specific data, thus simultaneously accounting for each indicator of data quality. We apply conventional procedures of hierarchical cluster analysis to distinguish four data quality clusters (best data quality, acceptable data quality, conditionally acceptable quality, and weak quality). We show that the reliability of old-age mortality estimates has been improving in time. However, the mortality indicators for the most advanced ages of a number of countries, such as Chile, Canada, and the USA should be treated with caution even for the most recent decade. Canada, Ireland, Finland, Lithuania, New Zealand (Non-Maori), Norway, Portugal, Spain, and the USA have particular problems in their historical data series. After having compared the KTD with official data, we conclude that the methods used for extinct and almost extinct generations produce more accurate population estimates than those published by national statistical offices. The most reliable official data come from the countries with fully functioning population registers.World, data evaluation, mortality, old age

Adjusting Inter-censal Population Estimates for Germany 1987-2011: Approaches and Impact on Demographic Indicators

To derive reliable demographic indicators, appropriate data on population exposures are needed. Access to such data is becoming increasingly challenging in many countries due to factors such as the growing diversity of international migration patterns and the trend towards replacing full censuses with register-based censuses. Germany represents a particularly challenging case in this respect. Before Germany implemented its first register-based census in 2011, the country had not conducted a census for more than two decades. This census revealed that the number of people living in Germany in 2011 was about 1.5 million lower than the previous official post-censal population estimates for that year indicated. It is likely that a large portion of this discrepancy had existed for quite some time prior to 2011. Due to the long inter-censal period, the Federal Statistical Office of Germany decided not to produce backward-adjusted population estimates by single-year ages and sex for the whole period. The main aim of this paper is thus to make such detailed adjusted inter-censal population estimates available. While we have to take the peculiarities of the German case into account, our evaluation of different strategies offers important insights for developing a generalised methodology to adjust inter-censal population estimates for globalised countries that face challenges in ensuring the proper registration of migration events. We discuss four alternative approaches for deriving adjusted inter-censal population estimates. The results suggest that even for a rather complicated case like Germany, a relatively simple approach seems to work reasonably well. Finally, we demonstrate to what extent the implemented adjustments affect mortality indicators. The adjusted inter-censal population estimates for Germany and its federal states are provided in the online data appendix

Adjusting Inter-censal Population Estimates for Germany 1987-2011: Approaches and Impact on Demographic Indicators

To derive reliable demographic indicators, appropriate data on population exposures are needed. Access to such data is becoming increasingly challenging in many countries due to factors such as the growing diversity of international migration patterns and the trend towards replacing full censuses with register-based censuses. Germany represents a particularly challenging case in this respect. Before Germany implemented its first register-based census in 2011, the country had not conducted a census for more than two decades. This census revealed that the number of people living in Germany in 2011 was about 1.5 million lower than the previous official post-censal population estimates for that year indicated. It is likely that a large portion of this discrepancy had existed for quite some time prior to 2011. Due to the long inter-censal period, the Federal Statistical Office of Germany decided not to produce backward-adjusted population estimates by single-year ages and sex for the whole period. The main aim of this paper is thus to make such detailed adjusted inter-censal population estimates available. While we have to take the peculiarities of the German case into account, our evaluation of different strategies offers important insights for developing a generalised methodology to adjust inter-censal population estimates for globalised countries that face challenges in ensuring the proper registration of migration events. We discuss four alternative approaches for deriving adjusted inter-censal population estimates. The results suggest that even for a rather complicated case like Germany, a relatively simple approach seems to work reasonably well. Finally, we demonstrate to what extent the implemented adjustments affect mortality indicators. The adjusted inter-censal population estimates for Germany and its federal states are provided in the online data appendix (http://dx.doi.org/10.12765/CPoS-2018-07en)

Adjusting Inter-censal Population Estimates for Germany 1987-2011: Approaches and Impact on Demographic Indicators - Online Appendix

This Online Appendix contains additional information regarding the article: DOI 10.12765/ CPoS-2018-05en

Assessing the quality of data on international migration flows in Europe: the case of undercounting

Undercounting is a critical issue in migration statistics, resulting in bias. It typically arises from insufficient reporting requirements and problems with enforcing such requirements. The main sources of information on undercounting are the metadata accompanying official statistics and expert opinions. However, metadata and arbitrary expert opinions may be limited by overlooking important details in migration data shared by various countries. This includes potential oversight of changes in methodologies, definitions, or retrospective updates to the data following censuses. This work presents a methodological solution with three objectives to address undercounting in international migration data. First, we provide an overview of available metadata and expert opinions on undercounting in European migration flows. Second, we propose a novel data-driven approach that incorporates year-specific and duration-of-stay-adjusted classifications. The proposed methodological solution relies on comparisons of flows in the same direction reported by a given country with high-quality data reported by another set of countries. We use bilateral migration data provided by Eurostat, UN and selected national statistical institutes. Duration-of-stay correction coefficients are derived through an optimization model or borrowed from the literature. Metadata and expert opinion scores can also be integrated to classify undercounting. Finally, we provide a dynamic classification of undercounting for 32 European countries (2002-2019), accessible through an online Shiny application, offering flexibility and adaptability. The findings highlight significant undercounting in new EU member states, particularly Bulgaria, Latvia, and Romania. Interestingly, other European countries, including those presumed to maintain reliable population statistics, also exhibit notable periods of undercounting