Andrea Albanese is a Research Scientist at Luxembourg Institute of Socio-Economic Research (LISER), Adjunct Teacher at the University of Luxembourg and affiliated at Ghent University (Belgium), IZA (Germany) and Université catholique de Louvain (Belgium). His research interests are Labour Economics, Causal Analysis & Policy Evaluation and his papers have been published in journals such as Journal of the Royal Statistical Society (Series A), Labour Economics, Oxford Economic Papers, Empirical Economics, Economics Letters, amongst others.
He completed a joint PhD programme at DEFAP Graduate School of Milan (Italy) and Ghent University (Belgium) in December 2015 under the supervisor of Prof. L. Cappellari and Prof. B. Cockx. Prof. M. Lechner (University of St. Gallen) and Prof. M. Leonardi (University of Milan) were part of his doctoral examination committee. The PhD thesis won the PhD thesis prize for the academic years 2014-2015 and 2015-2016 from AISSEC (Italian Association for the Analysis of Comparative Economic Systems). In 2016 he moved to Luxembourg Institute of Socio-Economic Research (LISER) where he won a large research grant as principal investigator funded by the Luxembourg National Research Fund (FNR - CORE Junior scheme).
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.