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Causality and interdependence analysis in linear econometric models with an application to fertility

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  • Laura Barbieri

Abstract

This paper is an applied analysis of the causal structure of linear multi-equational econometric models. Its aim is to identify the kind of relationships linking the endogenous variables of the model, distinguishing between causal links and feedback loops. The investigation is first carried out within a deterministic framework and then moves on to show how the results may change inside a more realistic stochastic context. The causal analysis is then specifically applied to a linear simultaneous equation model explaining fertility rates. The analysis is carried out by means of a specific RATS programming code designed to show the specific nature of the relationships within the model.

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  • Laura Barbieri, 2013. "Causality and interdependence analysis in linear econometric models with an application to fertility," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1701-1716, August.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:8:p:1701-1716
    DOI: 10.1080/02664763.2013.793660
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    References listed on IDEAS

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    1. José María Da Rocha & Luisa Fuster, 2003. "Why are Fertility and Female Participation Rates Positively Correlated across OECD countries?," Working Papers 72, Barcelona School of Economics.
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    Cited by:

    1. Cimpoeru Smaranda & Pisică Andrei, 2023. "Economic Determinants of Birth Rate in Romania. A Spatial Analysis," Journal of Social and Economic Statistics, Sciendo, vol. 12(1), pages 25-45, July.

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