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SICENTER (Socio-economic Indicators Center)
is a private non-profit research institution focusing on research and consultancy in the field of analysis of indicators in numerous fields and at various levels of aggregation, with application in economics, politics, business and statistics. It is registered with the Ministry of Higher Education, Science and Technology in Slovenia.
The principal researcher is Professor
Pavle Sicherl, Director of SICENTER and Professor of Economics
at the Faculty of Law, University of Ljubljana. He was also
consultant to the World Bank, OECD, UN, ILO, UNIDO, INSTRAW,
UNRISD, EUROCHAMBRES and Harvard University Development Advisory Service.
Pavle Sicherl on the Second OECD World Forum on "Statistics, Knowledge and Policy", Istanbul, Turkey, 27-30 June, 2007
EU is performing better but not yet good enough: TRACKING THE TIMETABLE TO LISBON…
EUROCHAMBRES MESSAGE TO THE 2007 SPRING SUMMIT
Monitoring Implementation of the Millennium Development Goals in the Time Dimension presents an additional methodology for measuring implementation of the UN goals… MORE.
The Inter-temporal Aspect of Well-being and Societal Progress is published in Social Indicators Research journal on SpringerLink in an electronic Online First article MORE.
Measuring Progress of Societies: Keynote speaker at the international conference 16th Statistical Days, Radenci, Slovenia, November 2006 MORE.
R&D and Lisbon strategy: The urgent need for
more R&D resources for Lisbon strategy .... MORE.
EU15 compared with USA: P. Sicherl prepared for EUROCHAMBRES 2005 Spring Business Forum in Brussels on March 11, 2005 ‘Time for a fresh start - A Comparison of European and US Economies based on Time Distances’ Some results of the study were presented also in Financial Times (Europe), March 11, 2005, page 2.... MORE.
Time Distance: Novel
statistical measure S-time-distance is generalized to complement
conventional measures in time series comparisons... MORE.
News: Nobel prize winner for economics
Professor C. Granger extended the application of the time
distance measure to evaluation of forecasting models.