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The European Journal of Health Economics
Published in: The European Journal of Health Economics 6/2015

Open Access 01-07-2015 | Original Paper

Productivity or discrimination? An economic analysis of excess-weight penalty in the Swedish labor market

Published in: The European Journal of Health Economics | Issue 6/2015

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Abstract

This article investigates the excess-weight penalty in income for men and women in the Swedish labor market, using longitudinal data. It compares two identification strategies, OLS and individual fixed effects, and distinguishes between two main sources of excess-weight penalties, lower productivity because of bad health and discrimination. For men, the analysis finds a significant obesity penalty related to discrimination when applying individual fixed effects. We do not find any significant excess-weight penalty for women.
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Footnotes
1
There are other underlying factors, e.g., self-confidence and time preferences [e.g., 10, 15] that may influence the relationship between weight and income directly and indirectly through the channels of discrimination and health-related productivity. This study considers the indirect effect when analyzing the excess weight penalty in the Swedish labor market.
 
2
We exclude super obesity based on a concern for misreported values. Our results are insensitive to the exclusion of these observations.
 
3
Research on weight and health often finds that underweight is associated with increased health risks, which, however, may differ from those of excess weight [42, 43]. By excluding underweight, our analysis focuses on factors influencing the labor market situation for excess weight individuals. We run regressions including underweight in our model specifications and then observe insignificant underweight estimates and virtually unaltered overweight and obesity estimates.
 
4
Lundborg et al. [40] find no effect on obesity estimates of excluding social benefits from their income measure, also based on tax records. However, in their case annual income includes earnings from self-employment, which makes it difficult to draw any conclusions pertaining to employed individuals only, considering that there may be a selection problem related to self-employment and excess weight. In addition, their analysis considers men but not women.
 
5
We also controll for self-reported unemployment and sickness absence, an exercise that does not affect the excess weight estimates in any considerable way.
 
6
The “health scores” are distributed as follows: about 2.5 % of the observations belong to category “bad health,” about 13 % to “between good and bad health” and about 84.5 % to “good health.” We observe some variation in the distribution over time, e.g., there appears to be a larger share of observations in categories “bad health” and “between good and bad health” (by 1–1.5 % points) in wave 2004–2005 compared to wave 1988–1989. However, whether the variation is attributable to actual changes in health status, to the finer scale introduced in the last wave or to our recoding is difficult to identify.
 
7
In addition, we also perform an attrition analysis comparing the variable means in a panel sample and a separate cross-section sample for every survey wave (using current values of all variables). Thereby we investigate how representative the panel sample is relative to the cross-sectional one. For the first three waves, there are virtually no significant differences in variable means between the samples. In the fourth wave, we observe several significant differences in variable means (p < 0.01). However, there are no significant differences between the two samples with regard to our variables of special interest, income, obesity and health, in any survey wave.
 
8
There is also a potential concern for reversed causality regarding health and income. However, we have run regressions with lagged weight and lagged health variables without observing any material changes to the excess weight estimates.
 
9
It is of course possible that time-varying unobservable factors drive the relationship between weight and income. Unfortunately, we do not have any clearly appropriate instrument to perform such an analysis.
 
10
Investigating the variation of a continuous weight variable (when applying individual fixed effects), we have run regressions of income from employment on BMI and BMI squared in the same model specification. In essence, the analysis of a continuous BMI indicates the same relationship as the analysis of weight categories: We find a positive but decreasing relationship between income and continuous BMI for both men and women, larger estimates for men and significant estimates only for men.
 
11
We also investigate the effect on the excess weight penalty of applying different income thresholds (annual income >0, >20,000 SEK, >50,000 SEK, >100,000 SEK, >150,000 SEK, >200,000 SEK). Overall, we observe that the obesity penalty decreases in size, in particular the OLS estimates, which also lose considerably in statistical significance when we increase the threshold. We also try applying an income ceiling (maximum 500,000 SEK) and find that the results are quite similar to the ones presented in Table 3. Thus, the relationship between weight and income appears to be robust to the exclusion of very high income (cf., [40]).
 
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Metadata
Title
Productivity or discrimination? An economic analysis of excess-weight penalty in the Swedish labor market
Publication date
01-07-2015
Published in
The European Journal of Health Economics / Issue 6/2015
Print ISSN: 1618-7598
Electronic ISSN: 1618-7601
DOI
https://doi.org/10.1007/s10198-014-0611-7

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