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Informal caring-time and caregiver satisfaction

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Abstract

This paper examines the role of care decision processes on informal caring-time choices. We focus on three care decisions: the caregiver’s own decision, a family decision and a recipient request. Results show that informal caregivers, engaged in care activities as a result of a family decision, are more likely to devote more than 5 h to care activities, even after allowing for endogeneity. Our findings are robust to controlling for a large number of socio-demographic characteristics, including care recipient and caregiver characteristics. Supplemental analysis, developed to explore whether care arrangements are related to informal caregiver’s satisfaction, indicates that the family decision heavily penalizes informal caregivers. Given the importance of informal care activities in reducing health care costs, our findings imply that care decision processes should be taken into consideration when formulating health care policies.

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Notes

  1. In the year 2000, dependents comprised 4–5% of the global population, or 7–8% of the working-age population [19].

  2. Other surveys, such as the Health and Retirement Study (HRS), do not include questions related to this issue. The Survey of Health, Ageing and Retirement in Europe (SHARE) does include some questions about the reasons, if any, why caregivers engage in such activities, but only accounts for the difference between the caregiver’s own decision (to meet other people, to contribute something useful, for personal achievement,…) and the caregiver’s sense of obligation.

  3. The Spanish Survey of Infomal Assistance, in 2004, asked informal caregivers the hours they spent caring for the dependent person, in five categories: less than 1 h, from 1 to 2 h, from 3 to 5 h, from 5 to 8 h and a continuous variable for those cases with more than 8 caregiving hours. In our work, we combine categories less than 1 h and from 1 to 2 h in a new category less than 2 h since we have observed that those categories are indistinguishable by testing whether none of the independent variables significantly affect the odds of alternative m versus alternative n [2]. Formally, we test:

    $$ H_{0}:\,\beta_{1,m|n}=\cdots=\beta_{i,m|n}=\cdots=\beta_{I,m|n}=0 $$

    with β i being the coefficient associated with the explanatory variable x i . Results show that we cannot reject the hypothesis those categories are indistinguishable when using Wald tests and LR tests. We also group the outcome categories from 5 to 8 h and more than 8 h in a new category more than 5 h of caring time, as those two categories are also statistically indistinguishable. This also allows us to compare our results with those obtained by repeating the analysis with the Spanish Survey of Informal Assistance of 1994, since it only uses the categories considered in our work.

  4. Note that we checked for the validity of the MNL model in this setting by testing the property of the independence of irrelevant alternatives (IIA). This property is convenient as regards estimation in MNL models, since if alternatives are not truly independent, then the parameter estimates will be inconsistent [20]. Results suggest that the MNL model is appropriate since we find evidence that the odds are independent of other alternatives by using two of the most common tests: Hausman’s specification test [20] and the Small-Hsiao test [39].

  5. To provide additional evidence that our results are not driven by the dropping of those individuals, we repeated the analysis without eliminating them from the sample and considered another care decision process called ‘No Choice’. Results are quite consistent. Note that informal caregivers also report other reasons. However, those are difficult to classify and the sample is quite small so we have excluded those individuals from the analysis.

  6. We have also repeated the analysis using a less recent wave of the Spanish Survey of Informal Assistance for the Elderly (1994). Results are quite consistent and are available upon request.

  7. For instance, in the case of housework, only the additional part of housework due to the illness or disability of the care recipient should be seen as informal care.

  8. There is no available information about the compensation that informal caregivers may receive from other family members.

  9. Results are presented for the joint sample of men and women. Tests reject separate specifications by gender. For consistency, we have also estimated with different sub-samples to correct for other selection biases. We consider that the selection bias may be generated by either age or frequency of the help. To that end, we change the age range and we estimate only using those caregivers who devote time to care activities every day. Results are consistent and are available upon request.

  10. To select among the specifications presented in Table 2 , we first use as a measure of fit the Pseudo-R 2. This test favours the use of the specification in Column 4, since the test is greater in this case. We also utilize the McFadden’s Adj R 2 since the Pseudo-R 2 always increases as new variables are added. Now, the model selected is that in Column 3, where the value of the test is greater. Additionally, we have also computed the Bayesian information criterion, an information measure, to compare the estimated models. As in the previous case, since the more negative value is the better-fitting model, the best is the model in Column 3. Thus, it seems that the better-fitting model is that in Column 3, which includes caregiver and recipient’s characteristics and the help and decision variables.

  11. The per cent changes are obtained as follows: 100(exp(β i,m|n  × δ) − 1),  δ = 1 except when we note the contrary.

  12. The Spanish Survey also provides information on the nature of the illness of the dependent person. Certainly, the type of illness may well affect the informal care the disabled person needs and it can also influence on how the decision of care is taken. We have repeated the analysis including dummies to control for the type of illness and results do not change. Then, this suggests that our estimations are not capturing the effect of the type of illness instead of the care decision process. Since we have few observations when we include the type of illness and the type of illness is highly correlated with the care needs (those are included as controls), we prefer to present our results without those controls.

  13. All these results are available upon request.

  14. Women are today more likely to participate in the labour market and to contribute to the family finances in Spain (OECD Labour Market Statistics), but there remain some differences between men and women. Since our sample consists of informal carers who are around 52, an age where these differences are more pronounced, it is not unrealistic to suppose that women are less likely to be in paid work or to earn more than men, so that potential female caregivers could have lower opportunity costs when the care decision was taken.

  15. Note that we have also repeated the analysis without the variable that controls for the employment status of the caregiver, and our results are robust.

  16. Wilde [47] explains that, given the assumption of joint normality, the model is identified by functional form, which requires no exclusion restrictions.

  17. For purposes of consistency, we also run the analysis using several different sub-samples, dropping each variable in turn. Our results do not vary significantly.

  18. The BIC was obtained using the Schwarz formula as (− 2logL + log(N)p) where p is the number of parameters and N is the number of observations. The AIC is defined as (− 2logL + 2p). Information criteria suggest that the better-fitting model is that showed in Panel C which includes exclusion restrictions.

  19. Of course, we also checked whether this model is appropriate by testing the parallel regression assumption, which is a property implicit in the OLM. To do that, we compute the approximate likelihood-ratio test of proportionality of odds across response categories. This test provides evidence that the parallel regression assumption cannot be rejected at the 5% level. Thus, we favour the use of the OLM.

  20. We do not include the labour, leisure and health costs in the previous analysis, since they are not exogenous factors in the estimation of the informal caring-time choice. In the Spanish survey, respondents are asked whether they have labour, leisure and health costs through their participation in informal care activities.

  21. The informal caring-time choices are included as dummy variables; one takes the value one if the informal caregiver reports devoting time from 3 to 5 h per day, and the other dummy variable takes the value one if the informal caregiver devotes more than 5 h per day. The informal caring-time choice for less than 2 h per day is the variable of reference.

  22. We repeated the analysis considering informal caregivers of working age and results are quite consistent.

  23. We also repeat the analysis by allowing for endogeneity as we do in the previous analysis. Results do not change.

  24. For consistency, we have also estimated with different sub-samples to correct for other selection biases. We consider that the selection bias may be generated by either age, frequency of care and living arrangements. To that end, we change the age range and we estimate only with those caregivers who devote time to care activities every day or who cohabit with the care recipient. Results are consistent with those previously obtained and are available upon request. The analysis cannot be repeated by using the Spanish Survey of Informal Assistance for the Elderly (Encuesta de Apoyo Informal a los Mayores) 1994, since the informal caregiver satisfaction question is not available.

  25. The better-fitting model is the one estimated in column 5, since it is the model with the smaller AIC, Akaike’s information criterion, and the greater Pseudo-R 2 and McFadden’s Adj R 2. If we only compare the Bayesian information criterion (BIC), we conclude that the better-fitting model is that shown in column 4, which includes the same variables as in column 5, but does not include the controls for the caregiver and recipient demographic characteristics.

  26. If it does not decrease the caregiver’s satisfaction, then the informal caregiver would always accept the recipient request.

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Acknowledgments

We are grateful to Olivier Donni, Adriaan Kalwij, Víctor Montuenga, Almudena Sevilla-Sanz, and Arantza Ugidos for comments that improved earlier versions of the paper. Support from the Spanish Ministry of Science and Innovation is gratefully acknowledged (grant reference number ECO2008-01297/ECO).

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Authors and Affiliations

  1. Departamento de Análisis Económico, Universidad de Zaragoza, Gran Vía 2, 50005, Zaragoza, Spain

    Miriam Marcén & José Alberto Molina

  2. Departamento de Análisis Económico, Universidad de Zaragoza and Institute for the Study of Labour-IZA, Bonn, Germany

    José Alberto Molina

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  1. Miriam Marcén
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Correspondence to Miriam Marcén.

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Marcén, M., Molina, J.A. Informal caring-time and caregiver satisfaction. Eur J Health Econ 13, 683–705 (2012). https://doi.org/10.1007/s10198-011-0322-2

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