The Erasmus Data Service Centre (EDSC) offers one of the most comprehensive portfolios of financial and economic datasets across Dutch Universities and provides an internationally competitive reference point for finance, economics, and social science research.
The Datateam provides data retrieval support for students and researchers, with a focus on collection, processing, and structuring of financial and macroeconomic data for statistical analysis. The team is also responsible for the acquisition of complex datasets.
Access the EDSC full list of financial databases and topic-specific tutorials through the links below:
The Datateam provides individual support and will answer your financial data enquiries via edsc@eur.nl
The Erasmus Data Service Centre (EDSC) organises introduction workshops, which run bi-weekly between September and December, and topical weekly workshops (stock, M&A, Board data, etc.) to support MA thesis, from January to June.
For more information about the workshops, please visit the EDSC webpages.
Book a space for the next EDSC workshop using the interactive calendar below:
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EUR provides access to sophisticated applications for analysing large bodies of data, develop algorithms, and create models.
Below you will find the software which can be used on campus or downloaded to your personal computers.
SAS on WRDS provides a fast way of performing complex calculations and data management tasks like joining tables and can handle very large amounts of data (into the hundreds of Gigabytes). SAS comes with hundreds of common statistical procedures built-in that are highly accurate.
R at WRDS
WRDS provides a direct interface for R access, allowing native querying of WRDS data right within your R program. All WRDS data is stored in a PostgreSQL database and is available through R via a native R Postgres driver.
WRDS provides a direct interface for Python access, allowing native querying of WRDS data right within your Python program. All WRDS data is stored in a PostgreSQL database, and is available through Python, on PyPI via a pip install.
This topic guide provides a curated list of resources that acts as a filter to data, tools and information resources for all research that involves geo-referenced and spatial characteristics. Economic activity is closely linked to geographical characteristics, whether studied at a macro-, meso- or micro-level.
The “End of Geography” foreseen by Richard O’Brien (1992) seems nothing more than a shadow from the past. At the same time Paul Krugman’s writing that “The location of production in space is a key issue both within and between nations” is very much alive. Whether you approach geospatial characteristics, data and information from an economic, business, multi-national or data science perspective, GIS offer many opportunities for innovative research, business applications and fundamental insights in regional and multinational development.
EUR has a long-standing tradition for research in spatial economics and urban economics. Well-known EUR researchers are prof. Jan Tinbergen (publlcations), prof. Jean Paelinck and prof. Frank van Oort. Several EUR researchers are also involved in the Tinbergen Spatial Economics Research Group:
Matlab, R and Stata provide specific spatial packages, functions and scripts to read, process and analyze geospatial data.
