We introduce a model for categorical panel data which is tailored to the dynamic evaluation of the impact of job training programs. The model may be seen as an extension of the dynamic logit model in which unobserved heterogeneity between subjects is taken into account by the introduction of a discrete latent variable. For the estimation of the model parameters we use an EM algorithm and we compute standard errors on the basis of the numerical derivative of the score vector of the complete data log-likelihood. The approach is illustrated through the analysis of a dataset containing the work histories of the employees of the private firms of the province of Milan between 2003 and 2005, some of whom attended job training programs supported by the European Social Fund

Bartolucci, F., Pennoni, F. (2011). Impact evaluation of job training programs by a latent variable model. In S. Ingrassia, R. Rocci, M. Vichi (a cura di), New Perspectives in Statistical Modelling and Data Analysis (pp. 65-73). Milano : Springer [10.1007/978-3-642-11363-5_8].

Impact evaluation of job training programs by a latent variable model

Pennoni, F
2011

Abstract

We introduce a model for categorical panel data which is tailored to the dynamic evaluation of the impact of job training programs. The model may be seen as an extension of the dynamic logit model in which unobserved heterogeneity between subjects is taken into account by the introduction of a discrete latent variable. For the estimation of the model parameters we use an EM algorithm and we compute standard errors on the basis of the numerical derivative of the score vector of the complete data log-likelihood. The approach is illustrated through the analysis of a dataset containing the work histories of the employees of the private firms of the province of Milan between 2003 and 2005, some of whom attended job training programs supported by the European Social Fund
Capitolo o saggio
Causal inference; Latent class model; Panel data; State dependence; Unobserved heterogeneity
English
New Perspectives in Statistical Modelling and Data Analysis
Ingrassia, S; Rocci, R; Vichi, M
2011
978-3-642-11362-8
Springer
65
73
Bartolucci, F., Pennoni, F. (2011). Impact evaluation of job training programs by a latent variable model. In S. Ingrassia, R. Rocci, M. Vichi (a cura di), New Perspectives in Statistical Modelling and Data Analysis (pp. 65-73). Milano : Springer [10.1007/978-3-642-11363-5_8].
none
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/26511
Citazioni
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
Social impact