This article examines the exchange motive in intergenerational monetary transfers. The exchange motive is in operation if parents make transfers to their children in exchange for services. The analysis incorporates data on current inter vivos transfers and the self-assessed probability of making future transfers via bequests. The focus is on the correlation between child-provided help and transfers from parents to adult children. Cross-sectionally, small transfers (between EUR 250 and EUR 5,000) and child-provided help are positively related. Endogeneity arising from omitted variables and reverse causality are addressed by using a lagged value of child-provided help. Further, in an analysis of first-differenced data, the association is statistically significant at the 10% level of confidence. The correlation is not significant in the case of large (above EUR 5,000) transfers, or the self-assessed probability of making future transfers via bequests. These findings suggest that small inter vivos transfers may be driven by exchange motives, although the findings are also consistent with altruism.
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Laferrère and Wolff (2006) provide a detailed summary of the theoretical frameworks developed for examining transfer motives.
In the case of both altruism and exchange, the probability of a transfer (Tprob) is negatively related to the child’s income (Yk). In altruism, this relationship follows from the compensatory nature of transfers. In exchange, Yk determines the value of the child’s time (the implicit price of their services).
When the service is informal, the availability of substitutes is unlikely. Therefore, when modelling informal services, assuming inelastic demand is likely to be reasonable and the identification of transfer motives by examining the effect of child income on the value of transfer is potentially possible. An issue, however, with examining very informal services (such as visits and communication) is that the distinction between the service provider and recipient can be unclear. When it comes to more formal types of services, the roles of the two parties are somewhat easier to ascertain (Laferrère and Wolff 2006).
The direction of the effect of S on the value of the transfer (Tvalue), on the other hand, depends on whether the demand for services is own-price elastic or inelastic. If the demand is own-price elastic, Tvalue increases with S, whereas the opposite is the case when demand is own-price inelastic (see Cox and Rank 1992).
ADLs (Activities of Daily Life) include tasks required to take care of oneself and move around using one’s body, whereas IADLs (Instrumental Activities of Daily Life) are made up of activities that people commonly do outside of ADLs (i.e., cooking, household chores, grocery shopping, using the telephone, taking medications and managing finances).
An analysis was carried out checking whether the sample restriction leads to significant differences between the original (full) sample and the final analysis sample. The comparison of both spouses’ age, education level and the household’s number of children between the two samples shows no significant differences, suggesting that sample selection (based on these observable characteristics) is not an issue.
In Wave 1, the question was worded slightly differently: “In the last ten years, have you given the deeds of a house, business, property, or a large amount of money of EUR 5,000 or more to any of your children (or grandchildren)?”. One needs to take into consideration the time disconnect between large transfers (10 years prior) and child-provided help (2 years prior), when interpreting the analysis of the relationship between these two measures.
Alternative specifications presented in Table 11 use a continuous measure of the total daily hours of help that the children provide. Again, the estimated effect of help is statistically insignificant.
If a child and parent have a strong emotional bond, the child is more likely to provide help to the parent and the parent is more likely to make transfers to the child. TILDA contains a question about the number of their children that the respondents “feel very close to”. An emotional closeness measure is constructed by dividing the number of children the respondent reports feeling very close to by the total number of children they have. The mean value of this measure is 91% (see Table 5). The small inter vivos models were re-estimated using Wave 2 data with the inclusion of the emotional closeness variable. The estimates are presented in Models 1 and 2 in Table 12. The results reveal no significant impact of the emotional closeness measure on transfer behaviour, and the estimates of the effect of S are largely unchanged. Estimates obtained using Wave 1 data are virtually identical to the Wave 1 models of Tables 6 and 10. Wave 2 of TILDA measures the respondents’ personality type. A widely-used measure of personality, the “big five”, divides aspects of personality into five traits: extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience (Cobb-Clark and Schurer, 2012). The household head’s score in relation to these five traits is included in the models of small inter vivos transfers, presented in Models 3 and 4 of Table 12. The estimates are similar to those of the initial specifications, with no significant change to the estimated effects of S. As well as including the personality variables together, the models were also re-estimated with each personality measure included individually. The findings remain virtually identical.
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Nivakoski, S. Does the exchange motive influence intergenerational transfers? Evidence from Ireland. Rev Econ Household 17, 1049–1079 (2019). https://doi.org/10.1007/s11150-018-9422-4
- Exchange motive
- Intergenerational transfers
- Inter vivos
- Informal care