About the Database
Ready to immerse yourself in data?
The database will aim to serve researchers with data for projects that can help shed light on the structural causes and effects of Nordic corporate governance characteristics, in order to protect the Nordic model’s competitive advantage.
The Nordic Database in Corporate Governance is a collaborative effort of leading universities in the Nordics to establish, build and maintain the most extensive Nordic database in the area of quantitative corporate governance research. The project is supported by the Nordic network (NCGN) in corporate governance and sponsored by Nasdaq Nordic Foundation.
Mission & vision
The NCGN community, including more than 110 scholars, strongly believe that data quality is the fundamental corner stone of any research infrastructure. Despite any innovative method, bad data leads to bad analytics and ultimately misguided decisions. IBM recently estimated that yearly costs associated with bad data amount to $3.1 trillion for US only.
Currently, the coverage of Nordic firms in international databases is fragmented and often unreliable. Local Nordic data providers cover fragments of the relevant variables and most often only for a single country. Researchers who wish to pursue large scale Nordic cross-country studies over longer time horizons face severe difficulties to obtain data about delisted firms.
– Our main mission and vision is shown down below –
The mission of the Nordic Database in Corporate Governance is to provide access to high quality, clean, complete, and reliable time series data covering all relevant aspects of corporate governance to a large pool of leading Nordic scholar, as well as to national and international regulator.
We do not only aim at cleanness, reliability and completeness in a unique dataset, but we have an ambition to extend such characteristics to a Nordic cross-country database that also offer academics with the following:
Flexibility
To produce an heterogeneous range of datasets that can serve a broad spectrum of research questions.
Compatibility
To easily combine data with external sources by means of prevalent company and individual identifiers, e.g. company registration number ISIN, Ticker, Compustat Gvkey.
Consistency
To ensure that each represented entity (firms or individuals) is uniquely identified and can be tracked across time.