Commission Decision of 25 February 2016 setting up a Scientific, Technical and Economic Committee for Fisheries, C(2016) 1084, OJ C 74, 26.2.2016, p. 4-10. The Commission may consult the group on any matter relating to marine and fisheries biology, fishing gear technology, fisheries economics,...

We use a rigorous three-stage many-analysts design to assess how different researcher decisions-specifically data cleaning, research design, and the interpretation of a policy question-affect the variation in estimated treatment effects. A total of 146 research teams each completed the same...

We propose an observation-driven dynamic common factor model for missing value imputation in high-dimensional panel data. The model exploits both serial and cross-sectional information in the data and can easily cope with time-variation in conditional means and variances, as well as with either...

Background: Accurate, real-time data about response technologies, capabilities, and availabilities are key to effective emergency response logistics; this is particularly important in remote settings, such as in the Arctic, where limited infrastructure, logistics, and technologies occasion the...

Policy evaluation is an essential tool of government as it ensures that the objectives of policies and programmes are being met and that tax revenues are being well spent. In many instances, policy evaluation involves using standard counterfactual analysis to measure the impact of a programme on...

Der Bedarf an schnell verfügbaren Daten zur kurzfristigen Entwicklung des Arbeitsmarktes steigt. Das Statistische Bundesamt analysiert diesbezüglich bereits seit Jahren das Potenzial von Online-Stellenanzeigen. Insbesondere in Projekten des "ESSnet Big Data" wurden verschiedene...

Supervisory data are typically not conceived for statistical purposes or considered "official statistics", but they are disclosed to the public, either directly by the supervised institutions or indirectly by the competent authorities. This disclosure is required under Pillar 3 of the Basel...

In September 2024, an assessment was undertaken of the data quality of the public sector debt statistics (PSDS) of the United Republic of Tanzania against the IMF's Data Quality Assessment Framework (DQAF) for PSDS. The mission was undertaken as part of a project to strengthen the quality of...

In October 2024, an assessment was undertaken of the data quality of the public sector debt statistics (PSDS) of the Republic of Zambia against the IMF's Data Quality Assessment Framework (DQAF) for PSDS. The assessment was undertaken as part of a project to strengthen the quality of public...

Der Bedarf an schnell verfügbaren Daten zur kurzfristigen Entwicklung des Arbeitsmarktes steigt. Das Statistische Bundesamt analysiert diesbezüglich bereits seit Jahren das Potenzial von Online-Stellenanzeigen. Insbesondere in Projekten des "ESSnet Big Data" wurden verschiedene...

In today's rapidly evolving digital landscape, the substantial advance and rapid growth of data presents companies and their operations with a set of opportunities from different sources that can profoundly impact their competitiveness and success. The literature suggests that data can be...

Monitoring soil quality provides indispensable inputs for effective policy advice, but very few poorer countries can implement high-quality surveys on soil. We offer an alternative, low-cost imputation-based approach to generating various soil quality indicators. The estimation results validate...

Policy evaluation is an essential tool of government as it ensures that the objectives of policies and programmes are being met and that tax revenues are being well spent. In many instances, policy evaluation involves using standard counterfactual analysis to measure the impact of a programme on...

The IABSE-ADIAB dataset provides the linkage between the most recent case of a hire from the IAB Job Vacancy Survey and the administrative data of the hired person. The data comprise the entire working history of persons who were identified as IAB Job Vacancy Survey hires from 2010 to 2020. The...

Data cooperatives are a type of data intermediary using long established cooperative models and global regulatory affordances to manage data with or on behalf of members (data producers) for the benefit of members or for trade with external queriers (data users).

Monitoring soil quality provides indispensable inputs for effective policy advice, but very few poorer countries can implement high-quality surveys on soil. We offer an alternative, low-cost imputation-based approach to generating various soil quality indicators. The estimation results validate...

Virtualization is indispensable for a service-oriented IT infrastructure, and hybrid models are also obvious in research and teaching in order to use cloud environments and on-premises solutions equally. In addition to multi-cloud solutions, internal integration concepts are also important if an...

Background: The importance of up-to-date product master data in the digital age should not be underestimated. However, companies still struggle to ensure high-quality product data, especially in the field of logistics. Hence, the focus of our research lies in the disregard of the importance of...

Interviewers have long been identified as a source of error in face-to-face surveys. However, previous studies have typically focused on a single source of interviewer-related error and single-country cross-sectional surveys. We extend this literature by investigating the influence of...

Der Austausch von Daten über die eigenen Organisationsgrenzen hinweg ist ein wesentlicher Bestandteil der Digitalisierung und im Zuge von Logistik 4.0 unabdingbar. Wenngleich dieser kooperative Datenaustausch noch in den Kinderschuhen steckt, wird ihm großes Potenzial für Kooperationen von...

Data-driven approaches to root cause analysis (RCA) have received attention recently due to their ability to exploit increasing data availability for more effective root cause identification in complex processes. Advancements in the field of causal inference enable unbiased causal investigations...

Considering calls for more collective approaches to governing data about people, this paper explores how such interventions have been envisioned and enacted by their proponents. I focus on four types of data intermediary: data trusts, decentralised autonomous organisations, data cooperatives and...

Missing data can significantly impact dataset integrity and suitability, leading to unreliable statistical results, distortions, and poor decisions. The presence of missing values in data introduces inaccuracies in clustering and classification and compromises the reliability and validity of...

The JRC Terrorism and Extremism Database is a tool created by the Joint Research Centre to gather data on terrorism and extremism-related events in the European Union, as well as on the global level. By automatically categorising and grouping events using machine-learning approaches, the...

Micro-data on robots have been very sparse in Germany so far. Consequently, a dedicated section has been introduced in the IAB Establishment Panel 2019 that includes questions on the number and type of robots used. This article describes the background and development of the survey questions,...

Henry, Zhuravskaya, and Guriev (2022) examine whether people are willing to share "alternative facts" espoused by right-wing populist parties before the 2019 European elections in France and how this interacted with the availability of fact-checking information. They find that both imposed and...

Supervised machine learning methods, in which no error labels are present, are increasingly popular methods for identifying potential data errors. Such algorithms rely on the tenet of a 'ground truth' in the data, which in other words assumes correctness in the majority of the cases. Points...