This article explores the application of the Structural Causal Models (SCM) approach in the field of demography, discussing the PC algorithm to identify the causal chain, and the backdoor criterion, to identify the variables that need to be controlled for. Using a subset of the Panel Study of Income Dynamics (PSID) dataset, we applied the SCM approach to investigate the causal effects of women’s age at first child on completed family size and household income, with the aim of simulating potential interventions designed at promoting an earlier onset of fertility. We found contrasting effects: inducing women to have their first child one year earlier could result in a 5% increase in their completed fertility, but it would also lead to a 4% reduction in their household income.

US fertility through the lens of graphical causal models / Gustavo De Santis. - In: RIVISTA ITALIANA DI ECONOMIA, DEMOGRAFIA E STATISTICA. - ISSN 0035-6832. - STAMPA. - 77:(2023), pp. 103-114.

US fertility through the lens of graphical causal models

Gustavo De Santis
2023

Abstract

This article explores the application of the Structural Causal Models (SCM) approach in the field of demography, discussing the PC algorithm to identify the causal chain, and the backdoor criterion, to identify the variables that need to be controlled for. Using a subset of the Panel Study of Income Dynamics (PSID) dataset, we applied the SCM approach to investigate the causal effects of women’s age at first child on completed family size and household income, with the aim of simulating potential interventions designed at promoting an earlier onset of fertility. We found contrasting effects: inducing women to have their first child one year earlier could result in a 5% increase in their completed fertility, but it would also lead to a 4% reduction in their household income.
2023
77
103
114
Gustavo De Santis
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1357435
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