Lassoing the Determinants of Retirement

Publikation: Working paperForskning

Standard

Lassoing the Determinants of Retirement. / Kallestrup-Lamb, Malene; Kock, Anders Bredahl; Kristensen, Johannes Tang.

Aarhus : Institut for Økonomi, Aarhus Universitet, 2013.

Publikation: Working paperForskning

Harvard

Kallestrup-Lamb, M, Kock, AB & Kristensen, JT 2013 'Lassoing the Determinants of Retirement' Institut for Økonomi, Aarhus Universitet, Aarhus.

APA

Kallestrup-Lamb, M., Kock, A. B., & Kristensen, J. T. (2013). Lassoing the Determinants of Retirement. Institut for Økonomi, Aarhus Universitet. CREATES Research Papers Nr. 2013-21

CBE

Kallestrup-Lamb M, Kock AB, Kristensen JT. 2013. Lassoing the Determinants of Retirement. Aarhus: Institut for Økonomi, Aarhus Universitet.

MLA

Kallestrup-Lamb, Malene, Anders Bredahl Kock, og Johannes Tang Kristensen Lassoing the Determinants of Retirement. Aarhus: Institut for Økonomi, Aarhus Universitet. (CREATES Research Papers; Journal nr. 2013-21). 2013., 39 s.

Vancouver

Kallestrup-Lamb M, Kock AB, Kristensen JT. Lassoing the Determinants of Retirement. Aarhus: Institut for Økonomi, Aarhus Universitet. 2013 jul 1.

Author

Kallestrup-Lamb, Malene ; Kock, Anders Bredahl ; Kristensen, Johannes Tang. / Lassoing the Determinants of Retirement. Aarhus : Institut for Økonomi, Aarhus Universitet, 2013. (CREATES Research Papers; Nr. 2013-21).

Bibtex

@techreport{0803377f93b0441b9eb44afc049d9dd8,
title = "Lassoing the Determinants of Retirement",
abstract = "This paper uses Danish register data to explain the retirement decision of workers in 1990 and 1998.Many variables might be conjectured to influence this decision such as demographic, socio-economic, financially and health related variables as well as all the same factors for the spouse in case the individual is married. In total we have access to 399 individual specific variables that all could potentially impact the retirement decision.We use variants of the Lasso and the adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our knowledge this is the first application of these estimators in microeconometrics to a problem of this type and scale. Furthermore, we investigate whether the factors influencing the retirement decision are stable over time, gender and marital status. It is found that this is the case for core variables such as age, income, wealth and general health. We also point out themost important differences between these groups and explain why these might be present.",
keywords = "Retirement, Register data, High-dimensional data, Lasso, Adaptive Lasso, Oracle property, Logistic regression",
author = "Malene Kallestrup-Lamb and Kock, {Anders Bredahl} and Kristensen, {Johannes Tang}",
year = "2013",
month = jul,
day = "1",
language = "English",
series = "CREATES Research Papers",
publisher = "Institut for {\O}konomi, Aarhus Universitet",
number = "2013-21",
type = "WorkingPaper",
institution = "Institut for {\O}konomi, Aarhus Universitet",

}

RIS

TY - UNPB

T1 - Lassoing the Determinants of Retirement

AU - Kallestrup-Lamb, Malene

AU - Kock, Anders Bredahl

AU - Kristensen, Johannes Tang

PY - 2013/7/1

Y1 - 2013/7/1

N2 - This paper uses Danish register data to explain the retirement decision of workers in 1990 and 1998.Many variables might be conjectured to influence this decision such as demographic, socio-economic, financially and health related variables as well as all the same factors for the spouse in case the individual is married. In total we have access to 399 individual specific variables that all could potentially impact the retirement decision.We use variants of the Lasso and the adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our knowledge this is the first application of these estimators in microeconometrics to a problem of this type and scale. Furthermore, we investigate whether the factors influencing the retirement decision are stable over time, gender and marital status. It is found that this is the case for core variables such as age, income, wealth and general health. We also point out themost important differences between these groups and explain why these might be present.

AB - This paper uses Danish register data to explain the retirement decision of workers in 1990 and 1998.Many variables might be conjectured to influence this decision such as demographic, socio-economic, financially and health related variables as well as all the same factors for the spouse in case the individual is married. In total we have access to 399 individual specific variables that all could potentially impact the retirement decision.We use variants of the Lasso and the adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our knowledge this is the first application of these estimators in microeconometrics to a problem of this type and scale. Furthermore, we investigate whether the factors influencing the retirement decision are stable over time, gender and marital status. It is found that this is the case for core variables such as age, income, wealth and general health. We also point out themost important differences between these groups and explain why these might be present.

KW - Retirement, Register data, High-dimensional data, Lasso, Adaptive Lasso, Oracle property, Logistic regression

M3 - Working paper

T3 - CREATES Research Papers

BT - Lassoing the Determinants of Retirement

PB - Institut for Økonomi, Aarhus Universitet

CY - Aarhus

ER -