Several models aim to measure how demographic, professional, and labour market factors influence unemployment duration, which has a compelling social and economic interest. Nevertheless, this quest still appear challenging in both interpretations and solutions, due to various difficulties. Among others, a relevant issue is the accurate measurement of unemployment, which is often biased by the presence of unknown errors. In this paper, we consider the measurement error as a latent variable and derive an Expectation-Maximization (EM) algorithm in the context of aWeibull regression model. The proposed methodology allows to estimate at the same time: (i) the effect of the covariates of interest on unemployment duration and (ii) the measurement error.
Weibull regression of unemployment duration measured with error via the EM algorithm / Ferrari, Davide; Frederic, Patrizio; Lalla, Michele. - ELETTRONICO. - (2008), pp. su CD-su CD. (Intervento presentato al convegno XLIV Riunione Scientifica della SIS tenutosi a Università della Calabria, nel 25 -27 giugno 2008).
Weibull regression of unemployment duration measured with error via the EM algorithm
FERRARI, Davide;FREDERIC, Patrizio;LALLA, Michele
2008
Abstract
Several models aim to measure how demographic, professional, and labour market factors influence unemployment duration, which has a compelling social and economic interest. Nevertheless, this quest still appear challenging in both interpretations and solutions, due to various difficulties. Among others, a relevant issue is the accurate measurement of unemployment, which is often biased by the presence of unknown errors. In this paper, we consider the measurement error as a latent variable and derive an Expectation-Maximization (EM) algorithm in the context of aWeibull regression model. The proposed methodology allows to estimate at the same time: (i) the effect of the covariates of interest on unemployment duration and (ii) the measurement error.Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris