During the COVID-19 crisis, the French National Institute of Statistics and Economic Studies (INSEE) used aggregated and anonymous counting indicators based on network signaling data of three of the four mobile network operators (MNOs) in France to measure the distribution of population over the territory during and after the lockdown and to enrich the toolbox of high-frequency economic indicators used to follow the economic situation. INSEE’s strategy was to combine information coming from different MNOs together with the national population estimates it usually produces in order to get more reliable statistics and to measure uncertainty. This paper relates and situates this initiative within the long-term methodological collaborations between INSEE and different MNOs, and INSEE, Eurostat, and some other European national statistical institutes (NSIs). These collaborations aim at constructing experimental official statistics on the population present in a given place and at a given time, from mobile phone data (MPD). The COVID-19 initiative has confirmed that more methodological investments are needed to increase relevance of and trust in these data. We suggest this methodological work should be done in close collaboration between NSIs, MNOs, and research, to construct the most reliable statistical processes. This work requires exploiting raw data, so the research and statistical exemptions present in the general data protection regulation (GDPR) should be introduced as well in the new e-privacy regulation. We also raise the challenges of articulating commercial and public interest rationales and articulating transparency and commercial secrets requirements. Finally, it elaborates on the role NSIs can play in the MPD valorization ecosystem.

In this discussion paper, we outline the motivations and the main principles of the Trusted Smart Statistics (TSS) concept that is under development in the European Statistical System. TSS represents the evolution of official statistics in response to the challenges posed by the new datafied society. Taking stock from the availability of new digital data sources, new technologies, and new behaviors, statistical offices are called nowadays to rethink the way they operate in order to reassert their role in modern democratic society. The issue at stake is considerably broader and deeper than merely adapting existing processes to embrace so-called Big Data. In several aspects, such evolution entails a fundamental paradigm shift with respect to the legacy model of official statistics production based on traditional data sources, for example, in the relation between data and computation, between data collection and analysis, between methodological development and statistical production, and of course in the roles of the various stakeholders and their mutual relationships. Such complex evolution must be guided by a comprehensive system-level view based on clearly spelled design principles. In this paper, we aim at providing a general account of the TSS concept reflecting the current state of the discussion within the European Statistical System.

Since 1876, statistical data on twin and multiple (TAM) births and deliveries have been registered in Hungary. Although there were some years during this 138-year period when twin births and deliveries were left out of the statistics, the trends can be followed, except for the period of World War II. The trends of twinning over the past four decades are summarized in this article, relying on official statistical data since 1970. Notably, the TAM birth rate rose following the Act CLIV of 1997 on Health. The Act provided state support for assisted reproductive treatments (ART), which spectacularly increased the ratio of twins — and especially of triplets — among live births. The trend has turned around since 2009–2010, and a decreasing era of TAM births seems to have begun. This article discusses some of the main and most interesting findings connected with TAM births, including twinning rates associated with different age groups, educational level, and actual place of residence by mothers, and the number of previous pregnancies of the mother. Ratios of live born males compared with live born females, lengths and weights at birth both among twins and singletons, and infant mortality rates have been calculated from the data. Twinning rates are higher in the western counties, the capital and its suburbs, and lower in the eastern counties.