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02-2018
Krueger, Dirk; Ludwig, Alexander: "Optimal Taxes on Capital in the OLG Model with Uninsurable Idiosyncratic Income Risk".
01-2018
Grevenbrock, Nils; Groneck, Max; Ludwig, Alexander; Zimper, Alexander: "Cognition, Optimism and the Formation of Age-Dependent Survival Beliefs".
Börsch-Supan, Axel (2018): "Kann die Rente generationengerecht sein?", In: Hank, Karsten; Erlinghagen, Marcel; Kreyenfeld, Michaela (eds.), Innovation und Wissenstransfer in der empirischen Sozial-und Verhaltensforschung, Campus, Frankfurt, New York, pp. 235-246.
Börsch-Supan, Axel (2018): "Dynamik in die Rentenversicherung", In: Kosturkova, Nadya; Rieger, Jörg (eds.), Ordnungspolitisch stets auf Kurs: Festschrift zum 65. Geburtstag von Prof. Dr. Norbert Berthold, Franz Vahlen, München, pp. 217-220.
Börsch-Supan, Axel; Goll, Nicolas; Ferrari, Irene; Rausch, Johannes (2018): Trend reversal of old-age labour force participation in Germany, VoxEU, 01-26-2018.
Villar, Ana; Sommer, Elena; Finnøy, Didrik; Gaia, Alessandra; Berzelak, Nejc; Bottoni, Gianmaria (2018): "CROss-National Online Survey (CRONOS) panel data and documentation user guide.". In: ESS ERIC.
(2018): "Die Flüchtlingskrise in den Medien". In: Die Highlights aus dem Jahrbuch der Max-Planck-Gesellschaft 2018.
Pflüger, Senta-Melissa; Bergmann, Michael; Bristle, Johanna (2018): "Scoping study of the auxiliary data sources and its potential to reduce nonresponse bias". In: Deliverable 2.7 of the SERISS project funded under the European Union’s Horizon 2020 research and innovation programme GA No: 654221.
Bristle, Johanna; Bergmann, Michael; Scherpenzeel, Annette; Butt, Sarah; Emery, Tom (2018): "Joint workshop with country representatives of SHARE and ESS to discuss available data sources and potential for subsequent use". In: Deliverable 2.6 of the SERISS project funded under the European Union’s Horizon 2020 research and innovation programme GA No: 654221.
Bergmann, Michael; de Luca, Giuseppe (2018): "Guidelines for computing longitudinal weights and sampling documentation". In: Deliverable 2.11 of the SERISS project funded under the European Union’s Horizon 2020 research and innovation programme GA No: 654221.