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Journal of Happiness Studies

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08-05-2023 | Research Paper

Informal Caregivers and Life Satisfaction: Empirical Evidence from the Netherlands

Authors: Marie Blaise, Laetitia Dillenseger

Published in: Journal of Happiness Studies | Issue 6/2023

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Abstract

The evidence base on the causal relation between informal care and susbjective well-being is scarce and often methodologically limited. Most research to date, using simple cross-sectional estimations or fixed-effect models, fails to consider reverse causality and unobserved heterogeneity and, thus provides biased estimates. Using panel data from the Longitudinal Internet Studies for the Social Sciences for the Netherlands over the period 2009–2018, this paper investigates the causal relationship between the informal care provision and caregivers’ life satisfaction and compares Ordinary Least Square (OLS) with Arellano-Bond system Generalized-Method-of-Moments estimates. When controlling for endogeneity biases, namely unobserved heterogeneity, reverse causality and dynamic endogeneity, the caregiving effect increases by almost 300%, highlighting that OLS with fixed-effects produces a downward biased estimation. Overall, providing care has a negative effect on life satisfaction with female caregivers being the most impacted, especially when providing housekeeping and personal support to their partners.

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Kristoffersen (2017, p. 846) referred to Ferrer-i Carbonell & Frijters (2004) and mentioned that « the assumption of cardinal comparability is often justified largely on the basis of statistical requirements, (…), rather than on reason». Thus, he followed the principle of simultaneous conjoint measurement to observe the response function's shape for subjective well-being indirectly. Using 11 waves from the HILDA survey, the author evaluated the association between life satisfaction and mental health (MH5). The results provide reasonable arguments in favour of ordinal and cardinal comparability.

Due to data limitations, we do not observe the health of the care recipient.

There are two GMM estimators. Firstly, the difference GMM, implemented by Arellano & Bond (1991), estimated one single difference equation where variables were first differentiated and instrumented by lagged variables. Secondly Arellano & Bover (1995) and Blundell & Bond (1998) developed a system GMM model in order to improve the efficiency of Arellano & Bond (1991)’s model, as lagged values were sometimes poor instruments for first differences. In this model the level equation was added to the difference equation, thus leading to additional instruments. Blundell et al. (2001) suggested a second rule-of-thumb to compare difference GMM with system GMM model efficiency. Following these authors, the autoregressive model should be initially estimated using pooled OLS and OLS with fixed-effect estimators. The pooled OLS estimate of the lagged outcome parameter should be considered as an upper-bound estimate while the one of the OLS with fixed-effects is the lower-bound estimate. A difference GMM estimate close or below the fixed-effect estimate suggests a downward bias and points to the use of the system GMM estimator (see Table B1, in Appendix for detailed results). According to Arellano & Bover (1995), the two-step GMM model provides more efficient and consistent estimates in the case of panel data than the one-step GMM model.

See Tables 17, 18, 19, 20, 21 and 22 for detailed results.

Standardized differences between raw and matched data are presented in Annexe D.

Full estimates are given in Appendix, see Table 23.

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Title: Informal Caregivers and Life Satisfaction: Empirical Evidence from the Netherlands
Authors: Marie Blaise
Laetitia Dillenseger
Publication date: 08-05-2023
Publisher: Springer Netherlands
Published in: Journal of Happiness Studies / Issue 6/2023
Print ISSN: 1389-4978
Electronic ISSN: 1573-7780
DOI: https://doi.org/10.1007/s10902-023-00663-1

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