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Found 10 result(s)
Country
The German Socio-Economic Panel Study (SOEP) is a wide-ranging representative longitudinal study of private households, located at the German Institute for Economic Research, DIW Berlin. Every year, there were nearly 11,000 households, and more than 20,000 persons sampled by the fieldwork organization TNS Infratest Sozialforschung. The data provide information on all household members, consisting of Germans living in the Old and New German States, Foreigners, and recent Immigrants to Germany. The Panel was started in 1984. Some of the many topics include household composition, occupational biographies, employment, earnings, health and satisfaction indicators.
Country
The Research Data Center Wissenschaftsstatistik provides the scientific community with data on economics and innovation in Germany. Data on research and development (R&D) in Germany (collected on behalf of the Federal Ministry of Education and Research) and on the development and startup culture of universities are made available via scientific use files and campus use files. Most studies and data are in German.
Country
Statistics Greenland collects, processes, and publicizes statistical material concerning social issues in Greenland. Information is published in English, Greenlandic, and Danish, although not all information has been translated.
TIW’s Warehouse is a centralized, electronic database holding the most current details on the official, or “gold,” record for virtually all cleared and bilateral credit default swap (CDS) contracts outstanding in the global marketplace. The Warehouse contains more than 50,000 accounts representing derivatives counterparties across 95 countries.
Country
WHIP is a database of individual work histories, based on Inps administrative archives. The reference population is made up by all the people – Italian and foreign – who have worked in Italy even only for only a part of their working career. A large representative sample has been extracted from this population: in the standard file the sampling coefficient is about 1: 180, for a dynamic population of about 370,000 people (figures will be doubled in the full edition). For each of these people the main episodes of their working careers are observed. The complete list of observations includes: private employee working contracts, atypical contracts, self-employment activities as artisan, trader and some activities as freelancer, retirement spells, as well as non-working spells in which the individual received social benefits, like unemployment subsidies or mobility benefits. The workers for whom activity is not observed in WHIP are those who worked in the public sector or as freelancers (lawyers or notaries) – who have an autonomous security fund. The WHIP section concerning employee contracts is a Linked Employer Employee Database: in addition to the data about the contract, thanks to a linkage with the Inps Firm Observatory, data concerning the firm in which the worker is employed is also available.
A consolidated feed from 35 million instruments provides sophisticated normalized data, streamlining analysis and decisions from front office to operations. And with flexible delivery options including cloud and API, timely accurate data enables the enterprise to capture opportunities, evaluate risk and ensure compliance in fast-moving markets.
Country
The GML contributes to the continual improvement of access to and information about official microdata; provides a service and research infrastructure for these data; adopts the function of an intermediary between the Federal Statistical Office and empirical research; conducts exemplary research based upon official data. The GML is an integral part of the German data infrastructure and features as one of six institutions funded by the German Council of Social and Economic Data.
Knoema is a knowledge platform. The basic idea is to connect data with analytical and presentation tools. As a result, we end with one uniformed platform for users to access, present and share data-driven content. Within Knoema, we capture most aspects of a typical data use cycle: accessing data from multiple sources, bringing relevant indicators into a common space, visualizing figures, applying analytical functions, creating a set of dashboards, and presenting the outcome.