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The trade-off between formal and informal care in Spain

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Abstract

Understanding the factors that determine the type and amount of formal care is important for predicting use in the future and developing long-term policy. In this context, we jointly analyze the provision of care at both the extensive (choice of care) and the intensive margin (number of hours of care received). In particular, we estimate and test, for the first time in this area of research, a sample selection model with the particularities that the first step is a multinomial logit model and the hours of care is an interval variable. Our results support the complementary and task-specific models which evidence has been found in other countries. Furthermore, we obtain evidence of substitution between formal and informal care for the male, young, married and unmarried subsamples. Regarding the hours of care, we find significant biases in predicted hours of care when sample selection is not taken into account. For the whole sample, the average bias is 2.77% for total hours and 3.23% for formal care hours. However, biases can be much larger (up to 10–15%), depending on the subsample and the type of care considered.

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Notes

  1. The fraction of the population aged between 65 and 80 has grown steadily since 1900, and in 2007 it represented 16.7% of the total population. Life expectancy at birth in 2005 was 83.5 (female) and 77.0 (male) in comparison with 35.7 (female) and 33.9 (male) in 1900. Fertility rate has decreased from 2.803 (1975) to 1.458 (2008).

  2. Eurostat. Population and Social Conditions.

  3. All these indicators have undergone dramatic changes in recent decades. For example, the birth rate (per 1,000 inhabitants) decreased from 18.8 in 1975 to 10 in 2006, with a minimum of 9.2 in 1998; the female participation rate increased from 28.8% in 1976 to 49.4% in the fourth quarter of 2007; finally, the divorce rate (per 100 marriages) increased from 4.7 in 1980 to 44.9 in 2006.

  4. For example, we do not know if the caregiver or the care-receiver has moved to other’s house to provide or to receive care. We also ignore if this is the first time the informal caregiver or the family have faced a similar situation in the past, which could condition the decision of who is going to be the principal informal caregiver and the decision of looking for formal care. And in the case where the dependent individual is receiving FIC we ignore if the onset of both types of care was sequential or simultaneous.

  5. There were 1,442 individuals (584 male, 838 female) aged between 40 and 64 years old who needed a caregiver to do daily living activities.

  6. Private organizations refer both to profit-making firms and non-governmental organizations. Both options are mentioned together in the questionnaire, so it is impossible for us to disentangle who is the provider of the formal help. Additionally, the reception of public formal care may imply the contribution by the user of a certain fraction of the cost of the service (co-payment). This circumstance depends on the nature of the service, the place of resident (because different Communities apply different requirements) and the amount of individual income. Given that the survey only reports the amount of household income, we can not attribute in which cases the individual had to face the co-payment and in which he did not. Other papers (Bolin et al. [3] using data from SHARE) analyzed also the relationship between formal and informal care without differentiating the nature of the formal provider, given the limitation of their data.

  7. The number of formal caregivers may suffer some deviations due to the existence of household employees (mainly female immigrants) who perform houseworking and additional caregiving tasks but do not have a legal contract with the family and are not quoting to Social Security.

  8. PADL’s include difficulties getting up and going to bed, standing up, moving indoors, washing oneself, controlling physical needs, dressing and undressing, eating and drinking. IADL’s include difficulties in carrying light objects, using utensils and tools, clutching small things with hands and fingers, moving without any mode of transport, driving one’s own vehicle, shopping, cooking, washing and ironing clothes, cleaning the house and looking after the well-being of the family.

  9. Mental illnesses refer to bipolar disorders, depression, anxiety and stress, whereas dementia relates to all possible kinds of dementia (senile, Alzheimer, AIDS-related, brain tumor, brain damage).

  10. The variable monthly household income refers to the sum of the regular income received at present by all the household members, irrespective of whether or not all or part of the income goes towards defraying household expenses. It includes self-employment income, employment earnings, contributory pensions (retirement, disability), non-contributory pensions, unemployment allowances and benefits, child benefits, other regular social allowances and benefits (social adjustment wage, family allowances), income from property (rents, dividends, interests) and other regular income. In the case of employment earnings, it refers to the total the amount per month (that is the percentage of regular income that is not paid on a monthly basis: bonus pay, regular social benefits and other extraordinary income that is received on a regular basis). Therefore, due to the certain degree of calculation complexity, this variable could suffer some misreporting errors.

  11. We acknowledge an anonymous referee for suggesting this observation.

  12. For example, the rate of household employees for the whole sample is 0.7%, whereas it increases to 20% for households with an income of more than €2,344/month (although we cannot be sure that these household employees behave as formal caregivers).

  13. Unfortunately, we do not know the distribution of hours between formal and informal care when the individual receives both types of care.

  14. With the exceptions of País Vasco, Cataluña and La Rioja, most of the time is devoted to home help rather than to personal care activities (IMSERSO [26]).

  15. Although it is not strictly necessary, we (over)identify the model by imposing some exclusion restrictions, that is, variables in Z that are not in X. For example: the variable “education” is included in Z but not in X because it may reflect the effect of learning externalities, that is, more education implies a higher degree of awareness about social services for dependent people (usage of internet). To check the appropriateness of this exclusion restriction in our two-stage selection model, we have included it in both stages and tested their significance in each stage. The F-test shows that this variable is significant at the 1% level in the first stage and not significant in the second stage, providing support for the exclusion restriction. We have included the coverage index of social services in X but not in Z, to consider the possibility of substitution between formal caregiving hours at home (home care) and outside (day centers) or between personal and technical aid (home care vs. telecare), and the alleviating effect of respite services for informal care. The coverage index is the ratio between the number of users and total population ≥ 65 years).

  16. The linear combination assumption is based on the fact that all \( u_{j}^{*} \) are independent of each other.

  17. The estimation of the model has been performed using a modified version of the program “selmlog.ado” because the original program was designed for a continuous variable. The original routine “selmlog.ado” is available at http://www.pse.ens.fr/gurgand/selmlog13.html.

  18. We have defined two binary variables (FC and IC). For those who do not receive any type of care, both variables take the value 0. For those who receive FIC, both variables take the value 1. We have included the same explanatory variables as in the multinomial logit model.

  19. We have defined three binary variables (FC, IC and FIC). For those who do not receive any type of care, all three of them take the value 0. We have included the same explanatory variables as in the multinomial logit model.

  20. “The variable ‘change of house’ means that as a consequence of a deficiency or disability the individual has moved from one municipality or region to another looking for more availability of health and/or social services (but not residential services) or because he is going to receive care from other family members. Therefore, depending of the application success’ for receiving social services and the availability of other relatives in the destination region, the individual with disabilities may receive IC and/or FC, but in any case we observe a significant increase in the probability of receiving FC, IC or both”.

  21. For men and women: individual aged 80–99, married, one PADL and one IADL, living in Cataluña. For young and old: man, married, one PADL and one IADL, living in Cataluña. For married and unmarried: man, aged 80–99, one PADL and one IADL, living in Cataluña.

  22. Regarding marital status, for the cohort of men (women) older than 40 years, 5.02% (21.79%) are widowed, and for the cohort of men (women) older than 65 years, 12.50% (24.53%) are widowed. With respect to age, 14.04% (17.90%) of men (women) are 65 years or more, and 2.08% (4.02%) are 80 years or more. (Source: DDHSS)

    .

  23. Home care and telecare services depend upon local administrations, which may result in large disparities in both eligibility and generosity.

  24. The cost of home care services differs greatly across regions (the most expensive being Navarra, at €19.1/h). Moreover, the co-payment rate varies from 0% in Ceuta and Melilla (5% in Andalucía and Murcia, 10% in País Vasco) to 20% in Rioja.

  25. IMSERSO [26].

  26. Censo de Población y Viviendas (INE [23]).

  27. However, we acknowledge that this result might be coincidental because the requirement of a third person for doing daily living activities and also for surveillance purposes could be a consequence of other pathologies.

  28. However, the identification of the model with relates FC and IC might suffer from lack of accuracy due to the limited information of the dataset (information of income, sequence of caregiving) which also restrain the type of model implemented (consideration of unobserved heterogeneity).

  29. Although the number of observations for some regressions is quite reduced, we have not found convergence problems. Other papers have found reliable estimates using sample sizes even smaller. For example, Litwin and Attias-Donfut [28] estimated the variables influencing the probability of receiving formal and informal care in France and Israel. In their regressions, for the probability of receiving both types of care at the same time, the number of observations was 115 for France and 54 for Israel.

  30. Although the DDHSS does not provide information of the kinship between caregiver and care-receiver, using another survey [24] for 1994 (the nearest available year to 1999) we have ascertained that for the cohort of women aged 65 and older who receive informal care from a co-resident caregiver: 65.28% of caregivers were daughters and 16.11% daughters-in-law.

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Acknowledgments

We are very grateful to Edward Norton for a helpful discussion and to David Casado, Pilar Garcia-Gómez, Juan Oliva, and workshop participants at the University of Barcelona, FEDEA, XXXII SAE congress, Coimbra HEEW, CEMFI and EEA-ESEM 2009 for helpful comments. Financial help from projects SEJ2005-08783-C04-01 and ECO2008-06395-C05-01 is gratefully acknowledged.

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Authors and Affiliations

  1. Universitat Pompeu Fabra, Barcelona GSE and FEDEA, Barcelona, Spain

    Sergi Jiménez-Martín

  2. Universidad de Murcia and FEDEA, Murcia, Spain

    Cristina Vilaplana Prieto

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  1. Sergi Jiménez-Martín
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Correspondence to Sergi Jiménez-Martín.

Appendix

Appendix

See Tables 6, 7, 8, 9, 10, 11, 12, 13, 14.

Table 6 Descriptive statistics by type of care received
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Table 7 BFG model (first-step multinomial model, all sample, marginal effects)
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Table 8 BFG model (first-step multinomial model by gender, marginal effects)
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Table 9 BFG model (first-step multinomial model by age group, marginal effects)
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Table 10 BFG model (first-step multinomial model by marital status, marginal effects)
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Table 11 BFG model and interval regression (second-step hours equations, all sample)
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Table 12 BFG model and interval regression by gender (second-step hours equations)
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Table 13 BFG model and Interval regression by age group (second-step hours equation)
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Table 14 BFG model and interval regression by marital status (second-step hours equation)
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Jiménez-Martín, S., Prieto, C.V. The trade-off between formal and informal care in Spain. Eur J Health Econ 13, 461–490 (2012). https://doi.org/10.1007/s10198-011-0317-z

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