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Body Size, Skills, and Income: Evidence From 150,000 Teenage Siblings

Demography

Abstract

We provide new evidence on the long-run labor market penalty of teenage overweight and obesity using unique and large-scale data on 150,000 male siblings from the Swedish military enlistment. Our empirical analysis provides four important results. First, we provide the first evidence of a large adult male labor market penalty for being overweight or obese as a teenager. Second, we replicate this result using data from the United States and the United Kingdom. Third, we note a strikingly strong within-family relationship between body size and cognitive skills/noncognitive skills. Fourth, a large part of the estimated body-size penalty reflects lower skill acquisition among overweight and obese teenagers. Taken together, these results reinforce the importance of policy combating early-life obesity in order to reduce healthcare expenditures as well as poverty and inequalities later in life.

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Fig. 1

Notes

  1. The WHO has estimated that the health consequences of obesity represent between 2 % and 7 % of total healthcare costs for several developed countries (WHO 2000).

  2. We interchangeably use “family” and “sibling fixed effects” throughout the text.

  3. An alternative mechanism would be that children who lack social skills to begin with have fewer friends and therefore play less, which increases the risk of obesity. This scenario implies that the causal arrow goes in the opposite direction. Nevertheless, it would hardly explain why the link between obesity and noncognitive skills occurs as early as age 2 or 3.

  4. Case and Paxson (2008), however, challenged this argument. They showed, using the same data as Persico et al. (2004), that the relation between height and earnings mainly reflected the positive relationship between height and cognitive skill that exists during childhood and adolescence. Lundborg et al. (2014) used Swedish data and showed that both cognitive and noncognitive skills are of importance for the height premium.

  5. The individuals had to live in Sweden during 1999 because many important variables—for example, the enlistment information and the family information—were collected for the 1999 population data.

  6. For a detailed description of the measure of noncognitive skills, see Lindqvist and Vestman (2011), who used the same measure of noncognitive skills and found it to be a somewhat stronger predictor of adult earnings than cognitive skills.

  7. The NCDS is a longitudinal study of approximately 17,000 individuals born in Great Britain in the week of March 3–9, 1958, who have been followed up several times, with the last being 2004, when they were 46 years old. For details, see Lundborg et al. (2010).

  8. Averett and Korenman (1996) and Cawley (2004) also used the NLSY79 and related the respondent’s weight, classified into discrete intervals, seven years back in time to the respondent’s contemporary wage. Averett and Korenman used weight in 1981 and wages in 1988, whereas Cawley pooled data for the period 1981–2000, with weight being measured at t – 7. The reason for using lagged measures of obesity in these studies was to address reverse causality between wages and obesity. Averett and Korenman (1996), controlling for a number of background variables (e.g., years of schooling), showed that obese workers have a statistically significant 8 % wage penalty compared with normal-weight workers. This penalty is lowered to 3 % if contemporary weight is used instead. A similar result was obtained in Cawley’s study.

  9. The reason for bringing in height is that being overweight or obese might be associated with shorter stature. In this case, the omission of height could downwardly bias the coefficient on overweight or obesity because it is well established that height is positively associated with earnings (Case and Paxson 2008; Lundborg et al. 2014; Persico et al. 2004).

  10. These are 17 indicators of rank within the military, ranging from different officer ranks to squad leaders, soldiers, and seamen. In addition, we include a dummy variable for those with missing rank.

  11. The choice of setting the threshold at 120,000 SEK (approximately US$18,500 or 13,300 euros) is somewhat arbitrary, but it has been shown that by analyzing earnings above this threshold using Swedish tax record data, one receives a return to schooling similar to the one obtained from analyzing hourly wages; see Antelius and Björklund (2000). Additional sensitivity analyses of earning specifications and thresholds are presented in Online Resource 1.

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Acknowledgments

We thank John Cawley, Andrew Clark, Gordon Dahl, Fabrice Etile, Pierre-Yves Geoffard, John Komlos, Fabian Lange, Inas Rashad, and participants at the 9th IZA-SOLE conference, the workshop on the Economics of Obesity at the Paris School of Economics, the 3rd ASHE conference, the Seminar at the Centre for Economic Demography, Lund University, and anonymous referees for useful comments. Research grants from the Centre for Economic Demography at Lund University and the Swedish Council for Working Life and Social Research are gratefully acknowledged.

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Lundborg, P., Nystedt, P. & Rooth, DO. Body Size, Skills, and Income: Evidence From 150,000 Teenage Siblings. Demography 51, 1573–1596 (2014). https://doi.org/10.1007/s13524-014-0325-6

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