We examine the effect of streaming based on ability levels on individuals’ civic participation throughout their adult life. The hypothesis we test is that ability grouping influences individuals’ general self-concept and, consequently, their civic participation choices across the life course. We employ data from the British National Child Development Study, which follows all UK citizens born during a certain week in 1958. Six binary variables observed at 33, 42, and 51 years of age are considered to measure civic participation. Our approach defines causal estimands with multiple treatments referring to the evolution of civic engagement over time in terms of potential versions of a sequence of latent variables assumed to follow a Markov chain with initial and transition probabilities depending on posttreatment time-varying covariates. The model also addresses partially or entirely missing data on one or more indicators at a given time occasion and missing posttreatment covariate values using dummy indicators. The model is estimated by maximizing a weighted log-likelihood function with weights corresponding to the inverse probability of the received treatment obtained from a multinomial logit model based on pretreatment covariates. Our results show that ability grouping afects the civic participation of high-ability individuals when they are 33 years old with respect to participation in general elections.

Bartolucci, P., Favaro, D., Pennoni, F., Sciulli, D. (2024). An analysis of the effect of streaming on civic participation through a causal hidden Markov model. SOCIAL INDICATORS RESEARCH, 1-28 [10.1007/s11205-023-03261-z].

An analysis of the effect of streaming on civic participation through a causal hidden Markov model

Pennoni, F.
;
2024

Abstract

We examine the effect of streaming based on ability levels on individuals’ civic participation throughout their adult life. The hypothesis we test is that ability grouping influences individuals’ general self-concept and, consequently, their civic participation choices across the life course. We employ data from the British National Child Development Study, which follows all UK citizens born during a certain week in 1958. Six binary variables observed at 33, 42, and 51 years of age are considered to measure civic participation. Our approach defines causal estimands with multiple treatments referring to the evolution of civic engagement over time in terms of potential versions of a sequence of latent variables assumed to follow a Markov chain with initial and transition probabilities depending on posttreatment time-varying covariates. The model also addresses partially or entirely missing data on one or more indicators at a given time occasion and missing posttreatment covariate values using dummy indicators. The model is estimated by maximizing a weighted log-likelihood function with weights corresponding to the inverse probability of the received treatment obtained from a multinomial logit model based on pretreatment covariates. Our results show that ability grouping afects the civic participation of high-ability individuals when they are 33 years old with respect to participation in general elections.
Articolo in rivista - Articolo scientifico
Causal inference - Civic participation; Expectation-maximization algorithm; 
Generalized propensity score; Voting behavior; Streaming 

English
1-feb-2024
2024
1
28
none
Bartolucci, P., Favaro, D., Pennoni, F., Sciulli, D. (2024). An analysis of the effect of streaming on civic participation through a causal hidden Markov model. SOCIAL INDICATORS RESEARCH, 1-28 [10.1007/s11205-023-03261-z].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/458422
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