A Collaborative Event of WIFO, IHS and CEU
The COVID-19-Pandemic has clearly shown that sound data and rigorous analyses are key for efficient and effective political decisions. This conference focuses on the use of data and statistics in evidence-based (public) policy making. It addresses current topics in data-driven, empirical research, with an emphasis on policy applications. National statistical systems are part of central governments, and the move to promote open statistical data is part of a broader development to make governments generally more transparent, efficient, and democratic. In a similar vein, open science pushes scientists to be more transparent in their approaches and to engage more with society.
What does openness mean in this context? How can data providers support research in a way to fully seize the chances inherent in the data revolution ("big data")? Can we harness big data to improve policy-decisions? Are we experiencing a backlash in evidence-based policy making and a return to ideology? How can we combine exploratory approaches and causal inference methods in making policy decisions? How can we ensure that empirical results in academic publications are scalable to the national and supra-national levels? How can we create a knowledge-generation environment that is sensitive to data protection issues, while still being able to connect different data sources?