Cover Image

A nonparametric approach to identify age, time, and cohort effects

Empirical studies in the social sciences and biometrics often rely on data and models where a number of individuals born at different dates are observed at several points in time, and the relationship of interest centers on the effects of age a, cohort c, and time t. Because of t=a+c, the design is...

Full description

Saved in:
Bibliographic Details
Main Authors: Antonczyk, Dirk (Author) , Mammen, Enno (Author)
Format: Article (Journal)
Language:English
Published: 2020
In: Journal of statistical planning and inference
Year: 2019, Volume: 204, Pages: 96-115
ISSN:0378-3758
DOI:10.1016/j.jspi.2019.04.009
Online Access:Verlag, Volltext: https://doi.org/10.1016/j.jspi.2019.04.009
Verlag: http://www.sciencedirect.com/science/article/pii/S037837581930045X
Get full text
Author Notes:Dirk Antonczyk, Bernd Fitzenberger, Enno Mammen, Kyusang Yu

MARC

LEADER 00000caa a2200000 c 4500
001 1680044737
003 DE-627
005 20240323101410.0
007 cr uuu---uuuuu
008 191028r20202019xx |||||o 00| ||eng c
024 7 |a 10.1016/j.jspi.2019.04.009  |2 doi 
035 |a (DE-627)1680044737 
035 |a (DE-599)KXP1680044737 
035 |a (OCoLC)1341249395 
040 |a DE-627  |b ger  |c DE-627  |e rda 
041 |a eng 
084 |a 27  |2 sdnb 
100 1 |a Antonczyk, Dirk  |d 1981-  |e VerfasserIn  |0 (DE-588)1016305257  |0 (DE-627)705510670  |0 (DE-576)351780238  |4 aut 
245 1 2 |a A nonparametric approach to identify age, time, and cohort effects  |c Dirk Antonczyk, Bernd Fitzenberger, Enno Mammen, Kyusang Yu 
264 1 |c 2020 
300 |a 20 
336 |a Text  |b txt  |2 rdacontent 
337 |a Computermedien  |b c  |2 rdamedia 
338 |a Online-Ressource  |b cr  |2 rdacarrier 
500 |a Gesehen am 28.10.2019 
500 |a Available online 11 May 2019 
520 |a Empirical studies in the social sciences and biometrics often rely on data and models where a number of individuals born at different dates are observed at several points in time, and the relationship of interest centers on the effects of age a, cohort c, and time t. Because of t=a+c, the design is degenerate and one is automatically confronted with the associated (linear) identification problem studied intensively for parametric models (Mason and Fienberg 1985; MaCurdy and Mroz 1995; Kuang, Nielsen and Nielsen 2008a,b). Nonlinear time, age, and cohort effects can be identified in an additive model. The present study seeks to solve the identification problem employing a nonparametric estimation approach: We develop an additive model which is solved using a backfitting algorithm, in the spirit of Mammen et al. (1999). Our approach has the advantage that we do not have to worry about the parametric specification and its impact on the identification problem. The results can easily be interpreted, as the smooth backfitting algorithm is a projection of the data onto the space of additive models. We develop a complete asymptotic distribution theory for nonparametric estimators based on kernel smoothing and apply the method to a study on wage inequality in Germany between 1975 and 2004. 
534 |c 2019 
650 4 |a Additive model 
650 4 |a Age-cohort models 
650 4 |a Kernel smoothing 
650 4 |a Nonparametric smoothing 
700 1 |a Mammen, Enno  |d 1955-  |e VerfasserIn  |0 (DE-588)170668606  |0 (DE-627)060788658  |0 (DE-576)13153159X  |4 aut 
773 0 8 |i Enthalten in  |t Journal of statistical planning and inference  |d Amsterdam : North-Holland Publ. Co., 1977  |g 204(2020), Seite 96-115  |h Online-Ressource  |w (DE-627)266882307  |w (DE-600)1468074-9  |w (DE-576)09405830X  |x 0378-3758  |7 nnas  |a A nonparametric approach to identify age, time, and cohort effects 
773 1 8 |g volume:204  |g year:2020  |g pages:96-115  |g extent:20  |a A nonparametric approach to identify age, time, and cohort effects 
856 4 0 |u https://doi.org/10.1016/j.jspi.2019.04.009  |x Verlag  |x Resolving-System  |3 Volltext 
856 4 0 |u http://www.sciencedirect.com/science/article/pii/S037837581930045X  |x Verlag 
951 |a AR 
992 |a 20191028 
993 |a Article 
994 |a 2020 
998 |g 170668606  |a Mammen, Enno  |m 170668606:Mammen, Enno  |d 110000  |d 110200  |d 110000  |d 110400  |e 110000PM170668606  |e 110200PM170668606  |e 110000PM170668606  |e 110400PM170668606  |k 0/110000/  |k 1/110000/110200/  |k 0/110000/  |k 1/110000/110400/  |p 3 
999 |a KXP-PPN1680044737  |e 3529213802 
BIB |a Y 
SER |a journal 
JSO |a {"origin":[{"dateIssuedKey":"2020","dateIssuedDisp":"2020"}],"language":["eng"],"note":["Gesehen am 28.10.2019","Available online 11 May 2019"],"recId":"1680044737","name":{"displayForm":["Dirk Antonczyk, Bernd Fitzenberger, Enno Mammen, Kyusang Yu"]},"relHost":[{"part":{"extent":"20","pages":"96-115","year":"2020","text":"204(2020), Seite 96-115","volume":"204"},"disp":"A nonparametric approach to identify age, time, and cohort effectsJournal of statistical planning and inference","titleAlt":[{"title":"JSPI"}],"physDesc":[{"extent":"Online-Ressource"}],"title":[{"title":"Journal of statistical planning and inference","title_sort":"Journal of statistical planning and inference","subtitle":"JSPI"}],"type":{"bibl":"periodical","media":"Online-Ressource"},"id":{"zdb":["1468074-9"],"eki":["266882307"],"issn":["0378-3758"]},"origin":[{"publisherPlace":"Amsterdam","dateIssuedKey":"1977","dateIssuedDisp":"1977-","publisher":"North-Holland Publ. Co."}],"language":["eng"],"recId":"266882307","note":["Gesehen am 01.06.2021"],"pubHistory":["1.1977 - 143.2013; Vol. 144.2014 -"]}],"title":[{"title":"A nonparametric approach to identify age, time, and cohort effects","title_sort":"nonparametric approach to identify age, time, and cohort effects"}],"physDesc":[{"extent":"20 S."}],"type":{"media":"Online-Ressource","bibl":"article-journal"},"id":{"doi":["10.1016/j.jspi.2019.04.009"],"eki":["1680044737"]},"person":[{"role":"aut","given":"Dirk","family":"Antonczyk","display":"Antonczyk, Dirk"},{"role":"aut","given":"Enno","family":"Mammen","display":"Mammen, Enno"}]} 
SRT |a ANTONCZYKDNONPARAMET2020 

Similar Items