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Titolo:
Discrete-time hazard regression models with hidden heterogeneity - The semiparametric mixed Poisson regression approach
Autore:
Land, KC; Nagin, DS; McCall, PL;
Indirizzi:
Duke Univ, Durham, NC 27706 USA Duke Univ Durham NC USA 27706Duke Univ, Durham, NC 27706 USA Carnegie Mellon Univ, H John Heinz III Sch Publ Policy & Management, Pittsburgh, PA 15213 USA Carnegie Mellon Univ Pittsburgh PA USA 15213 nt, Pittsburgh, PA 15213 USA N Carolina State Univ, Dept Anthropol & Sociol, Raleigh, NC 27695 USA N Carolina State Univ Raleigh NC USA 27695 Sociol, Raleigh, NC 27695 USA
Titolo Testata:
SOCIOLOGICAL METHODS & RESEARCH
fascicolo: 3, volume: 29, anno: 2001,
pagine: 342 - 373
SICI:
0049-1241(200102)29:3<342:DHRMWH>2.0.ZU;2-Q
Fonte:
ISI
Lingua:
ENG
Soggetto:
MAXIMUM-LIKELIHOOD METHODS; CRIMINAL CAREERS; EMPIRICAL APPLICATIONS; MIXTURE MODEL; LIFE-TABLES; COUNT DATA; DURATION; SPECIFICATION;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Social & Behavioral Sciences
Citazioni:
50
Recensione:
Indirizzi per estratti:
Indirizzo: Land, KC Duke Univ, Durham, NC 27706 USA Duke Univ Durham NC USA 27706Duke Univ, Durham, NC 27706 USA
Citazione:
K.C. Land et al., "Discrete-time hazard regression models with hidden heterogeneity - The semiparametric mixed Poisson regression approach", SOCIOL METH, 29(3), 2001, pp. 342-373

Abstract

Previous methodological research has shown that hidden heterogeneity in hazard rate regression models-in the form of systematic differences between sample members in the risk or hazard of making a transition due to unobserved variables not accounted for by the measured covariates-can produce biasedparameter estimates and erroneous inferences. However, few empirical applications of hazard regression do more than pay lip service to the complications of hidden heterogeneity. In part, this is due to the relative inaccessibility of the mathematical apparatus of continuous-time hazard regression methodology with flexible nonparametric specifications on the hidden heterogeneity This article presents new methods for incorporating nonparametric specifications of hidden heterogeneity into hazard regressions by developing discrete-time Poisson rate/complementary log-log hazard regression models with nonparametric hidden heterogeneity that are analogous to the continuous-rime models of Heckman and Singer: Maximum-likelihood estimators and associated hypothesis tests are described. An empirical application to data on criminal careers, which illustrates the utility of models that explicitly incorporate hidden heterogeneity, is presented.

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Documento generato il 12/07/20 alle ore 06:55:52