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Demographic aging puts social insurance systems under immense pressure as frailty risks increase with age. The statutory long-term care insurance in Germany (GPV), whose society has been aging for decades due to low fertility and decreasing mortality, faces massive future pressure. The present study presents a stochastic outlook on long-term care insurance in Germany until 2045 by forecasting the future number of frail persons who could claim insurance services by severity level with theory-based Monte Carlo simulations. The simulations result in credible intervals for age-, sex- and severity-specifc care rates as well as the numbers of persons for all combinations of age, sex and severity by defnition of the GPV on an annual basis. The model accounts for demographic trends through time series analysis and considers all realistic epidemiological developments by simulation. The study shows that increases in the general prevalence of disabilities, especially for severe disabilities, caused by the demographic development in Germany are unavoidable, whereas the infuence of changes in agespecifc care risks does not afect the outcome signifcantly. The results may serve as a basis for estimating the future demand for care nurses and the fnancial expenses of the GPV.

This paper presents the implementation of a language model–based strategy for the automatic codification of crime narratives for the production of official statistics. To address the high workload and inconsistencies associated with manual coding, we developed and evaluated three models: an XGBoost classifier with bag-of-words features and word embeddings features, an LSTM network using pretrained Spanish word embeddings as a language model, and a fine-tuned BERT language model (BETO). Deep learning models outperformed the traditional baseline, with BETO achieving the highest accuracy. The new ENUSC (Encuesta Nacional Urbana de Seguridad Ciudadana) workflow integrates the selected model into an API for automated classification, incorporating a certainty threshold to distinguish between cases suitable for automation and those requiring expert review. This hybrid strategy led to a 68.4% reduction in manual review workload while preserving high-quality standards. This study represents the first documented application of deep learning for the automated classification of victimization narratives in official statistics, demonstrating its feasibility and impact in a real-world production environment. Our results demonstrate that deep learning can significantly improve the efficiency and consistency of crime statistics coding, offering a scalable solution for other national statistical offices.

This article uses a “mystery client” approach and visits the websites of National Statistical Offices and international microdata libraries to assess whether foundational microdata sets for countries in the Middle East and North Africa region are collected, up to date, and made available to researchers. The focus is on population and economic censuses, price data and consumption, labor, health, and establishment surveys. The results show that about half of the expected core data sets are being collected and that only a fraction is made available publicly. As a consequence, many summary statistics, including national accounts and welfare estimates, are outdated and of limited relevance to decision-makers. Additional investments in microdata collection and publication of the data once collected are strongly advised.

Citizen science data are an example of a non-traditional data source that is starting to be used in the monitoring of the United Nations (UN) Sustainable Development Goals (SDGs) and for national monitoring by National Statistical Systems (NSSs). However, little is known about how the official statistics community views citizen science data, including the opportunities and the challenges, apart from some selected examples in the literature. To fill this gap, this paper presents the results from a survey of NSS representatives globally to understand the key factors in the readiness of national data ecosystems to leverage citizen science data for official monitoring and reporting, and assesses the current awareness and perceptions of NSSs regarding the potential use of these data. The results showed that less than 20% of respondents had direct experience with citizen science data, but almost 50% felt that citizen science data could provide data for SDG and national indicators where there are significant data gaps, listing SDGs 1, 5, and 6 as key areas where citizen science could contribute. The main perceived impediments to the use of citizen science data were lack of awareness, lack of human capacity, and lack of methodological guidance, and several different kinds of quality issues were raised by the respondents, including accuracy, reliability, and the need for appropriate statistical procedures, among many others. The survey was then used as a starting point to identify case studies of successful examples of the use of citizen science data, with follow-up interviews used to collect detailed information from different countries. Finally, the paper provides concrete recommendations targeted at NSSs on how they can use citizen science data for official monitoring.

The goal of the article is to explore the potential of explicatory Structural Equation Modelling (SEM) and its specifications for measuring the shadow economy (SE). This is done from the perspective of various approaches in selected countries. The article is a review and conceptual paper. The study is divided into three stages: a comprehensive description of the nature of the SE and the difficulties associated with measuring it; a comparative analysis of the approaches applied in selected EU countries (with particular emphasis on Italy and Poland), and finally, the concept of SE estimation based on SEM model is proposed.One of the most important limitations regarding the SE is that it is not possible to measure the extent of this phenomenon directly. This leads to the use of non‑standard estimation techniques based on latent variable models. The innovation of this approach is that it considers three factors that are not directly observable, i.e., tax morality, concealing salaries, and regulation of the economy.The proposed model allows us to capture and explain empirical SE phenomena more precisely and effectively than with classical statistical and econometric methods. However, we are aware that it is highly probable that many SEMs will need to be tested and modified to achieve the final result.

Good data, Michael Ward argues, serve to enhance a perception about life as well as to deepen an understanding of reality. This history of the UN's role in fostering international statistics in the postwar period demonstrates how statistics have shaped our understanding of the world. Drawing on well over 40 years of experience working as a statistician and economist in more than two dozen countries around the world, Ward traces the evolution of statistical ideas and how they have responded to the needs of policy while unraveling the question of why certain data were considered important and why other data and concerns were not. The book explores the economic, social, and environmental dimensions of the UN's statistical work and how each dimension has provided opportunities for describing the well-being of the world community. Quantifying the World also reveals some of the missed opportunities for pursuing alternative models.

Zusammenfassung Hintergrund In den letzten Jahren verringerte sich die frühgeburtliche Morbidität und Mortalität über Ländergrenzen hinweg deutlich. Allen Untersuchungen gemeinsam ist aber eine höhere Betroffenheit und Sterblichkeit von Jungen gegenüber Mädchen, insbesondere bei der nekrotisierenden Enterokolitis. Fragestellung Besteht in Deutschland auf Basis der amtlichen Krankenhausstatistik eine höhere Inzidenz oder Sterblichkeit von Jungen an nekrotisierender Enterokolitis? Material und Methoden Die Autoren werteten die Diagnosedaten der amtlichen Krankenhausstatistik für die Jahre 2000–2017 für die Hauptdiagnose P77 – nekrotisierende Enterokolitis –, getrennt nach Geschlechtern und Überleben, aus. Der Zusammenhang zwischen Geschlecht und Versterben resp. Erkrankungshäufigkeit wurde mittels einseitigem χ 2 -Test auf ein höheres Risiko für Jungen untersucht. Ergebnisse Zwischen 2000 und 2017 hatten 3119 Frühgeborene die Hauptdiagnose nekrotisierende Enterokolitis, davon 1769 Jungen (0,27 ‰ der männlichen Lebendgeburten) und 1350 Mädchen (0,22 ‰ der weiblichen Lebendgeburten). Jungen haben ein höheres Risiko, an nekrotisierender Enterokolitis zu erkranken (relatives Risiko 1,24, 95 %-Konfidenzintervall: 1,17–∞, p  < 0,001) und zu versterben (relatives Risiko 1,25, 95 %-Konfidenzintervall: 1,02–∞, p  = 0,036). Diskussion Jungen erkranken und sterben häufiger an nekrotisierender Enterokolitis als Mädchen. Allerdings erfasst die amtliche Statistik nicht die leichteren Fälle einer nekrotisierenden Enterokolitis, da nur die Hauptdiagnose erfasst wird. Überdies ermöglicht die amtliche Statistik keine Adjustierung für verzerrende Faktoren. Die sekundäre Datennutzung der Qualitätssicherungsdaten der Neonatalerhebung könnte eine detailliertere Untersuchung dieser Fragestellung ermöglichen.

Certain discrepancies in datasources for estimating the household consumption expenditure to derive Gross Domestic Product (GDP) of India are discussed in this paper. Simple implementable strategies are suggested toimprove the estimation of GDP.

The need for subnational demographic, social, economic, and fiscal data in designing effective intergovernmental fiscal systems is becoming increasingly evident. In Central and Eastern European countries, the legacy of the region’s communist past are information systems rooted in the centralized economy. Such an approach becomes less acceptable as economic issues become more complex and subnational governments in these transition economies become responsible for the delivery of local services. As political imperatives support increasingly democratic forms of governance in which people’s needs must be taken into account in the design of policy options, there is a need for information systems that provide data to allow policymakers and citizens to assess the outcomes of policy choices. Subnational Data Requirements for Fiscal Decentralization summarizes the findings of needs assessment activities in five demonstration countries that are at different stages of fiscal decentralization: Bulgaria, Romania, the Slovak Republic, Slovenia, and Ukraine. These assessments are part of a program on subnational statistical capacity building, launched by the World Bank Institute, the Organisation for Economic Co-operation and Development, and the Economic Development Center of the Soros Foundation.

Zusammenfassung Hintergrund Die operative Versorgung proximaler Femurfrakturen (PF) geht bei geriatrischen Patienten mit einer hohen Sterblichkeitsrate im 1. postoperativen Jahr einher. Nachuntersuchungen mindestens 10 Jahre postoperativ stehen hierzu aus. Material und Methoden Basierend auf unserer Datenbank wurden alle Patienten mit PF und operativer Versorgung mindestens 10 Jahre postoperativ reevaluiert. Einschlusskriterium war ein Lebensalter von 65 bis 99 Jahren. Primäres Zielkriterium war die Überlebenszeit mit einer vergleichenden Auswertung zur mittleren Lebenserwartung der Allgemeinbevölkerung des Statistischen Bundesamtes. Sekundäres Kriterium waren Revisionen später als ein Jahr postoperativ. Mindestens 10 Jahre postoperativ erfolgte eine telefonische Kontaktierung der Patienten oder deren Angehörigen. Ergebnisse Von initial 1203 konsekutiven Patienten konnten 1000 Patienten mit 1000 PF eingeschlossen und im Mittel 12,2 Jahre (10,0–14,0) postoperativ evaluiert werden. Die mittlere Überlebenszeit betrug 4,5 ± 1,6 Jahre, die 10-Jahres-Überlebensrate betrug 13,1 %. Es wurden 7 Altersgruppen mit jeweils 5 Lebensjahren analysiert, beginnend von 65–69 Jahre bis 95–99 Jahre. Im Vergleich zur Lebenserwartung der Allgemeinbevölkerung des Statistischen Bundesamtes war die Überlebenszeit von Patienten mit PF in allen Altersgruppen um bis zu maximal 9 Lebensjahre reduziert. Mit zunehmendem Lebensalter war die Verkürzung der Lebenszeit geringer ausgeprägt, blieb aber durchgehend bestehen. Eine Subgruppenanalyse mit Patienten, welche mindestens > 1 Jahr überlebten, zeigte keinen wesentlichen Anstieg der mittleren Überlebenszeit. Revisionen später als ein Jahr postoperativ bildeten eine Rarität; lediglich n  = 27 (2,7 %) wurden dokumentiert. Schlussfolgerung Im Vergleich zu den Daten des Statistischen Bundesamtes weisen geriatrische Patienten mit PF deutlich geringere Überlebensraten auf als erwartet. Die Ergebnisse reflektieren die hohe Morbidität und Fragilität von Patienten mit PF.