Modelling old-age retirement: An adaptive multi-outcome LAD-lasso regression approach.

Autor/inn/en	Lähderanta, Tero; Salonen, Janne; Möttönen, Jyrki; Sillanpää, Mikko J.
Titel	Modelling old-age retirement: An adaptive multi-outcome LAD-lasso regression approach. Gefälligkeitsübersetzung: Modellierung des Altersruhestands: Ein adaptiver Multi-Outcome LAD-lasso Regressionsansatz.
Quelle	In: International social security review, 75 (2022) 1, S. 3-29 PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
ISSN	1468-246X
DOI	10.1111/issr.12287
Schlagwörter	Älterer Arbeitnehmer; Altersversorgung; Finnland; Prognose; Qualifikation; Determinante; Rentenalter; Verfahren; Rentenanspruch; Lebensarbeitszeit; Determinante; Altersversorgung; Sozioökonomischer Faktor; Einkommenshöhe; Berufsausstieg; Erwerbsbeteiligung; Lebensarbeitszeit; Qualifikation; Rentenanspruch; Rentenalter; Geschlechtsspezifik; Modellentwicklung; Prognose; Statistische Methode; Verfahren; Institution; Älterer Arbeitnehmer; Finnland
Abstract	"Using unique administrative register data, we investigate old-age retirement under the statutory pension scheme in Finland. The analysis is based on multi-outcome modelling of pensions and working lives together with a range of explanatory variables. An adaptive multi-outcome LAD-lasso regression method is applied to obtain estimates of earnings and socioeconomic factors affecting old-age retirement and to decide which of these variables should be included in our model. The proposed statistical technique produces robust and less biased regression coefficient estimates in the context of skewed outcome distributions and an excess number of zeros in some of the explanatory variables. The results underline the importance of late life course earnings and employment to the final amount of pension and reveal differences in pension outcomes across socioeconomic groups. We conclude that adaptive LAD-lasso regression is a promising statistical technique that could be usefully employed in studying various topics in the pension industry." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons).
Erfasst von	Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg
Update	2022/3