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How Do Leisure Activities Impact on Life Satisfaction? Evidence for German People with Disabilities

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Abstract

This study analyses the effect of participating in leisure activities on the levels of life satisfaction reported by people with and without disabilities. Particular attention is paid to exploring how different types of leisure activities (e.g. social gatherings, cultural events, active sports, volunteer work, etc.) affect individuals’ life satisfaction and which of them contribute most to improving it. Using longitudinal data at an individual level from the German Socio-Economic Panel, we estimate a “Probit Adapted OLS (POLS)” model which allows us to identity the determinants of life satisfaction by disability status and to control for the unobserved heterogeneity and thus determine cause and effect between the key variables. Although participation in leisure activities increases the life satisfaction scores reported by people with disabilities (except for the participation in public initiatives), this effect is quite different by leisure activity. The participation in leisure activities such as holidays, going out, or attending cultural events and church has a significant positive effect on the life satisfaction of people with disabilities. Event organizers, destination managers, business owners, professionals, governments, and the leisure industry in general must promote and facilitate full access and participation of people with disabilities in all leisure activities, especially in those that contribute more intensely to increasing their life satisfaction scores. The elimination of all disabling barriers, the understanding of their differential needs and the existence of inclusive leisure environments are key elements for improving the life satisfaction of people with disabilities.

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Notes

  1. For some leisure activities (e.g. participation in public initiatives, doing volunteer work, taking part in active sports, going to the cinema and cultural events) we can find more information for other years included in the GSOEP. In addition, the wording of the questions used in this study on free time and possible answers has changed slightly over the years. Additional information on methodology aspects of the GSOEP (e.g. target populations, sampling, survey design, questionnaires, generated variables, weights, etc.) is available at: http://www.diw.de/en/diw_02.c.222847.en/desktop _companion_overview.html.

  2. In line with Becchetti et al. (2012), it is likely that the distance from “at least once a month” and “daily/weekly” corresponds to a more than proportional increase in life satisfaction than the distance between “seldom” and “at least once a month”. If this is the case, our leisure measure flattens the high intensity response and may be conceived as a sort of log transform of the true unobserved variable. A similar strategy is followed by Lancee and Radl (2012). In any case, we have re-estimated all our life satisfaction equations by introducing different options. First, we have used different coding schemes for the distances between the possible answers and the results were extremely similar to those shown in Table 1. Second and following Winkelmann (2009), we have also created a dummy variable for each leisure activity that equals 1 if the individual is engaged in that activity with a “daily/weekly” frequency, and zero otherwise. Once again, the results obtained did not alter the main conclusions of our study.

  3. For example, see Sirgy (2012) for a full review of the concept of life satisfaction (chapter 1).

  4. The reason for using this measure is that if we look at the GSOEP questionnaire, we find that the work limitation question has been changed over time and it was not asked in all its waves (from 1988 to 1991 and in 1993 and 1994, or at all from 2002 onwards).

  5. This test is based on the inclusion of three additional variables in our model: (1) the number of waves in which the ith individual participates in the panel; (2) a binary variable taking the value 1 if and only if the ith individual is observed over the entire sample and 0 otherwise; and (3) a binary variable indicating whether the individual was observed in the previous period.

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  1. Applied Economics Department, University of Malaga, Plaza de El Ejido s/n, 29.071, Malaga, Spain

    Ricardo Pagán

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Table 2 Correlation matrix between life satisfaction (LS) and leisure activities by disability status
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Pagán, R. How Do Leisure Activities Impact on Life Satisfaction? Evidence for German People with Disabilities. Applied Research Quality Life 10, 557–572 (2015). https://doi.org/10.1007/s11482-014-9333-3

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