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Estimating the causal effect of fertility on economic wellbeing: data requirements, identifying assumptions and estimation methods

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Abstract

This article aims to answer to what extent fertility has a causal effect on households’ economic wellbeing—an issue that has received considerable interest in development studies and policy analysis. However, only recently has this literature begun to give importance to adequate modelling for estimation of causal effects. We discuss several strategies for causal inference, stressing that their validity must be judged on the assumptions we can plausibly formulate in a given application, which in turn depends on the richness of available data. We contrast methods relying on the unconfoundedness assumption, which include regressions and propensity score matching, with instrumental variable methods. This discussion has a general importance, representing a set of guidelines that are useful for choosing an appropriate strategy of analysis. The discussion is valid for both cross-sectional or panel data.

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Authors and Affiliations

  1. Department of Decision Sciences, DONDENA Centre for Research on Social Dynamics, Bocconi University, Via Roentgen, 20136, Milan, Italy

    Bruno Arpino & Arnstein Aassve

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  1. Bruno Arpino
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  2. Arnstein Aassve
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Correspondence to Bruno Arpino.

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Arpino, B., Aassve, A. Estimating the causal effect of fertility on economic wellbeing: data requirements, identifying assumptions and estimation methods. Empir Econ 44, 355–385 (2013). https://doi.org/10.1007/s00181-010-0356-9

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  • DOI: https://doi.org/10.1007/s00181-010-0356-9

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