Long-run labour market and health effects of individual sports activities
Introduction
The positive effect of physical activities on individual health is widely acknowledged both in academics and in the general public. Nevertheless, a substantial part of the population is not involved in individual sports activities. For example, in Germany about 40% of the population older than 18 does not participate in sports activities at all, which is about the average for Europe (see Deutscher Bundestag, 2006, Gratton and Taylor, 2000). A similar pattern appears in the USA (see Ruhm, 2000, Wellman and Friedberg, 2002). These non-activity figures are surprisingly high considering that many Western countries subsidize the leisure sports sector substantially (Gratton and Taylor, 2000, provide some details). The large subsidies are justified by considerable positive externalities participation in sports may have, for example by increasing public health and fostering social integration of migrants or other social groups, who deal with integration difficulties (for Germany, see Deutscher Bundestag, 2006; for Austria, see Weiss and Hilscher, 2003; for Belgium, Krouwel et al., 2006, are less optimistic).
Here, the focus is on the effects of individual participation in leisure time sports on individual long-run labour market outcomes. Intuitively, one might expect that such labour market effects usually result through one or several of the following three channels. The first channel relates to direct productivity effects. Improved health and individual well-being might lead to direct gains in individual productivity that is rewarded in the labour market. The second channel concerns social networking effects that are particularly relevant for sport activities performed in groups. As for a third channel sport activities might signal potential employers that individuals enjoy good health, are motivated and thus will perform well.
To be more precise, this paper addresses two issues that are important to both the individual as well as the public: The first issue is whether the health gains appearing in medical studies are still observable when taking a long-run perspective. It is conceivable that the health gains disappear, because the additional ‘health capital’ may be ‘invested’ in less healthy activities such as working harder on the job. This would put into question one of the main justifications for the public subsidies. Second, even if the direct health effects are absent in the long run, participation in sports may increase individual productivity. Such an increase would be observable in standard labour market outcomes like earnings, wages, and labour supply. Quantifying such effects leads to valuable information that could be used in public information campaigns to increase participation in leisure sports.
The following four strands of the literature are relevant for this topic. The first strand appears in labour economics and analyzes the effects of participating in high school sports on future labour market outcomes. Based on various data sets mainly from the USA and various econometric methods to overcome the problem of self-selection into high school sports, this literature broadly agrees that participation improves future labour market outcomes.1
Next, the positive effect of sports activity on physical health is well documented in the medical and epidemiological literature.2 There is recent microeconometric evidence of a positive relationship as well: Rashad (2007) analyzes the effects of cycling on health outcomes. Lakdawalla and Philipson (2007) find that physical activity at work reduces body weight and thus the probability of obesity.3 Recent papers, for example Gomez-Pinilla (2008), also suggest that sports activities have a positive effect on mental health.
In addition, there exists a literature linking health and labour market outcomes: health is an important factor determining individual labour market productivity. If health declines, individual productivity is reduced and, as a consequence, individual wages and labour market participation declines. An important channel how this health effect materializes is the impact of body weight on labour market outcomes. In particular obesity is becoming wide spread (e.g., Andreyeva et al., 2005). It increases the risk of mortality, diabetes, high blood pressure, asthma, and other diseases, and thus drastically reduces labour productivity (e.g., Wellman and Friedberg, 2002, and the references given in Ruhm, 2007).
From a policy perspective, it is stressed (e.g., Deutscher Bundestag, 2006) that an important channel of how participation in sports, particularly team sports, may improve future labour market performance is by increasing social skills. These issues are analyzed in the sociological literature describing how social capital improves labour market performance (e.g., Aguilera and Bernabé, 2005) and how ‘positive’ extracurricular activities in youth lead to more successful labour market performance in later years (e.g., Eccles et al., 2003).4
Despite the large literature reviewed above, there appears to be no study on the effects of leisure sports on individual labour market outcomes. In that the effects of sports on labour market success take time to materialize, estimating long-run effects is particularly relevant in this case. Uncovering such long-run effects, however, comes with particular challenges: the first challenge is the data, which should record individual information over a sufficiently long time. This data should contain measurements of sports activities, labour market success and other outcome variables of interest, as well as the variables that jointly influence the outcomes of interest as well as the decision about participating in sports. It is argued below that the German Socio-Economic Panel Study (GSOEP) with annual measurements from 1984 to currently 2006 could be used for such an analysis.
The second challenge comes from individual self-selection into different levels of sports activity. For example, if individuals in well-paying jobs choose higher levels of sports activity, then a comparison of the labour market outcomes of individuals with low and high sports activity levels will not only contain the effects of different activity levels, but may also reflect differences of these groups with regard to other dimensions. This is called the problem of ‘selection bias’ in the econometric literature (see Heckman et al., 1999), and ‘confounding’ in the statistical literature (e.g., Rubin, 1974). The fact that selection into sports is not random is well documented.5 However, solving this problem by conditioning on the variables that pick up these confounding differences may not work as the values of these conditioning variables may in turn depend on participation in sports. Here, this endogeneity problem of the control variables is approached using a flexible semiparametric estimator together with performing the analysis in strata defined by the level of past sports activity.
The paper intends to contribute to the literature in three ways: The first goal is to learn more about the correlates of sports activities by using the GSOEP data with its wealth of information. The second and main contribution of this study is to uncover the long-run effects of participation in sports on labour market success and several other socio-demographic and health variables. Indeed, there are sizeable effects. For example, active participation in sports increased earnings on average by about 1200 EUR p.a. over a 16-year period compared to no or very low participation in sports. Finally, a methodological contribution is attempted by adapting existing robust semiparametric econometric estimation methods to the specific data situation for such a panel study.
The paper is organized in the following way: in Section 2 the basic study design is explained and motivated on an intuitive basis. Section 3 describes the data on which the empirical analysis is based and provides some descriptive statistics. In Section 4 the determinants into sport activities are analyzed. I find that individual activity levels are related to many socio-economic variables, roughly indicating a positive relation between socio-economic status and activity level. Section 5 describes the econometric approach to estimate the effects of sports on the various outcome variables. The key ingredients into the proposed econometric estimation strategy, based on semiparametric propensity score matching methods, are the results from the analysis of the determinants of sports participation, because they can be used to correct for ex ante differences in characteristics of individuals observed with different sport activity levels. Bringing all components together, Section 6 contains the main empirical results and checks of their robustness. Section 7 concludes. Appendix A documents some data related issues. Appendix B describes details of the procedures used for estimation and inference.6
Section snippets
The basic idea of the study design
As already mentioned in Section 1, there are two key econometric challenges for studies attempting to uncover causal effects of an event or action, like the participation in sport activities, on some outcome variables. The first challenge is commonly called selection bias. This term means that comparing the outcomes of people with high and low sport activities will not do, if those two groups differ with respect to other characteristics that also influence the outcome variables. To overcome
The German Socio-Economic Panel Study
The GSOEP is a representative German panel study with annual measurements starting in 1984. It contains individual data from 1984 to 2006. The GSOEP is interviewer based and recently switched to computer assisted personal interviews (CAPI). It started in West Germany. Since 1990 it includes East Germany as well. The GSOEP is one of the work-horses of socio-economic research in Germany, and beyond. More details on the survey can be found in Wagner et al. (2007) and on the GSOEP website (//www.diw.de/gsoep
Who participates in leisure sports activities?
This section attempts to better understand whether participants in sport activities differ a priori from non-participants. This is not only interesting for a better understanding of participation behaviour but also has consequences for the econometric estimation strategy, as the effects of such differences would have to be addressed econometrically.
Table 4.1 presents sample means of selected covariates for the eight different samples stratified according to sex, the sports status prior to the
Econometrics: identification, estimation, and inference
The previous section showed that participation in sports activities is not a random event. Based on this analysis, comparing earnings of sports participants and non-participants is expected to result in a positive earnings effect for the sports participants simply because better educated individuals are more likely to participate in sports (although Table 4.1 shows that this earnings–education relation shows up only in three of the four strata). Therefore, such crude comparisons lead to biases
Introductory remarks
Below, the effects of sports participation on various outcome measures are presented. The outcomes considered relate to success in the labour market, like earnings, wages, and employment status, as well as to various objective and subjective health measures, additional socio-demographic outcomes, and a direct measure of satisfaction with life in general. For each group of outcome variables, only a few specific variables are presented for the sake of brevity. Results for additional outcome
Conclusion
This microeconometric study described the correlates of sports participation and analyzed the effects of participation in sports on long-term labour market variables, on socio-demographic variables, as well as on health and subjective well-being outcomes for West Germany using individual data from the German Socio-Economic Panel Study (GSOEP) 1984–2006. The issue that people choose their level of sports activities and, thus, participants in sports may not be comparable to individuals not active
Acknowledgements
I am also affiliated with ZEW, Mannheim, CEPR and PSI, London, IZA, Bonn, and IAB, Nuremberg. This project received financial support from the St. Gallen Research Center in Aging, Welfare, and Labour Market Analysis (SCALA). A previous version of the paper was presented at the annual workshop of the social science section of the German Academy of Science Leopoldina in Mannheim, 2008, at the University of St. Gallen, at the annual meeting of the German Economic Association (VfS), Graz, 2008, at
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