Newsletter 1–2018



Fit for management? How good health helps your career

By Martin Ljunge

There is a well-known positive association between job status and health. The relationship has been taken as evidence of how the work environment shapes health. But newly published research from the Research Institute of Industrial Economics (IFN) and the London School of Economics (LSE) establishes an effect in the opposite direction. It finds that better health increases the likelihood of being a supervisor, as well as having more autonomy and more influence at the workplace.

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It is a common observation that individuals with higher status occupations live longer and have better health, see for example Marmot et al. (1978) and Marmot (2003). This correlation is sometimes taken to prove that high status occupations lead to good health. A recent study by IFN researcher Martin Ljunge and co-author Joan Costa-Font at the LSE presents evidence to suggest that it is the other way around – that healthy individuals tend to land good jobs.

It is obvious that many low status occupations lead to poor health, for instance due to physically hazardous working environments or onerous tasks. But it is also clear that good health is a requisite, or is at least helpful, to work intensively and for long hours. Employers therefore have incentives to ensure that healthy individuals are selected when hiring new personnel, or when promoting staff internally. It seems plausible that employers generally manage to screen out unhealthy individuals in these decisions regarding well paid, high status occupations. In what follows we denote this, that healthier employees may attain higher job status, the “healthy worker effect”.

Migrants as a natural laboratory

Health and occupational status are positively correlated. But how are they related? Intuitively, there could be health benefits from occupations that have high status, for instance since these occupations often involve fewer workplace hazards. But it also seems plausible that individuals with poor health are less frequently promoted to high status occupations. Presumably, the two effects are at play at the same time, making it hard to disentangle the effect of health on occupational status. Since individual health may depend on occupational status, an individual’s health cannot be used on its own when trying to establish a causal relationship. Instead, we need a measure of health that is not a function of the individual’s occupational status.

Migrants offer a laboratory to study these effects. The cultural transmission literature has found that trust and other social traits stay with migrants after they move to foreign countries. If this also holds for health, the health status of the birth country would predict migrants’ health in a foreign country. By comparing individuals who are born in different countries it should be possible to isolate the causal direction between better health and occupational status. A critical factor for this approach to work is that an individual migrant’s occupational status cannot determine health in another country; this is ensured when birth country health is measured as the country average. Consequently, using variation in birth country health to predict individual health, one can interpret the subsequent relationship to occupational status causally.

The empirical analysis is done in two steps. The first examines the health transmission – how well a migrant’s current health is predicted by average birth country health. The individual’s health is measured by self-reported health status recorded on a five point scale from very bad to very good. Individual characteristics are accounted for, including age (and its square), gender, education, income, religion, as well as labor force and marital status. Individual data are taken from the European Social Survey.

Institutional characteristics in 30 European countries are accounted for by comparing individuals within each country through the use of residence country fixed effects. Comparisons are made within a country, for example comparing migrants in the UK who originate from different countries across the world. Time trends are accounted for through time fixed effects. Birth country health is measured by average self-reported health. The first stage of the analysis shows that migrants’ reported health strongly correlates with birth country average health. The persistent health effect is similar when only accounting for age and gender, factors that do not change with health, as well as the full set of individual factors above. It also holds when accounting for occupational category fixed effects, hence enabling individuals to be compared within occupational categories.


Based on data from European Social Survey (ESS)

Health promotes occupational status 

Given the finding that health has a persistent component, the second step is to examine the effect of health on occupational status. We study three separate dimensions of occupational status.

The first outcome is if the individual has a supervising role at work. This is a binary variable taking the value 1 if the individual is a supervisor and 0 otherwise. A second measure asks to what extent the individual can organize daily work tasks: the answers range from having no control, coded as 0, to having complete control, coded as 10. The third outcome asks what influence over policy the individual has at work. Responses range from having no influence, coded as 0, to having complete control, coded as 10. A fourth summary measure is created as the principal component of the three different outcomes. Higher values capture higher occupational status in all the measures, which again are recorded in the European Social Survey.

Positive and strongly significant estimates of health are found on all occupational status dimensions. This is evidence that better health has positive effects on occupational status. The approach rules out reverse causality, since health in the migrants’ birth countries cannot plausibly be affected by their occupational status in another country. Birth country health is used to shift, or predict, the individual’s self-reported health.

The results hold when accounting for a wide range of birth country characteristics, indicating that it is indeed health that promotes occupational status and not other characteristics of the migrants’ birth countries. The study uses GDP per capita to account for differences in economic development; average birth country IQ to capture differences in human capital; differences in life expectancy to account for differences in social development; Gini coefficients to account for inequality in the birth country; and measures of regulatory quality to capture the functioning of institutions.

Two measures capture cultural differences across countries, and are from Hofstede et al. (2010). The first is called masculinity (versus femininity), capturing a focus on achievement and material rewards versus getting along and understanding each other. The second measure is named power distance, capturing to what extent individuals accept that power and resources are distributed unequally. As it turns out, even when accounting for these eight birth country characteristics, health still has a strong positive effect on occupational status.

The study also considers the extent to which the healthy worker effect is driven by occupational sorting, that is, that health determines occupation, and/or that healthier workers in an occupation are more likely to get promoted. By including occupational category fixed effects, we obtain an estimate of the effect of health within occupations. The estimate on health in this model is about two-thirds of the baseline model without occupational fixed effects. This indicates that the bulk of health effects operate within occupations. Examples of such effects would be promotion of workers with better health, or allowing them to work more autonomously.

The results imply that about one-third of the total healthy worker effect operates through occupational sorting. That is, individuals with better health tend to work in occupations with more autonomy and policy influence. The baseline results remain when employing a range of additional robustness checks. Excluding immigrants from Africa and Asia, or only including European migrants, yields similar results, as does accounting for birth continent fixed effects. The effect is present for recent migrants and when restricting the analysis to the most highly skilled occupations. Accounting for parental education, a measure of parental investment, does not change the results. An overidentification test provides additional support for the two stage model.



Health is good for your career. That is our basic finding, and the effect is quantitatively large. People with better health are more likely to work in a supervisory role, have more work autonomy and policy influence at work. The results are obtained in a “laboratory” consisting of migrants in Europe. This population allows us to use variation in birth country health – variation that does not depend on the individuals’ occupational status – to establish the causal direction from health to occupational status.

The results add another facet to our understanding of the positive association between health and occupational status. The association has often been seen as the effect of the work environment on health, but we show that there is an effect in the opposite direction, from health to occupational status.

Future research could extend the analysis to the U.S. and other countries, to examine if the effects go beyond Europe, as well as to look at heterogeneity along gender and age dimensions, which could shed light on gender wage gaps and ageism. Our results do not rule out that work conditions affect health, but they point to the need for such studies to use variation in occupational status that does not depend on the individual’s health.



Costa-Font, J., and M. Ljunge (2018). The ‘healthy worker effect’: Do healthy people climb the occupational ladder? Economics & Human Biology, Vol. 28, pp. 119–131.

Hofstede, G., G.J. Hofstede, M. Minkov (2010). Cultures and Organizations: Software of the Mind. 3rd Edition, McGraw-Hill USA, New York.

Marmot, M. (2003). Understanding social inequalities in health. Perspectives in Biology and Medicine, Vol. 46, No.3, pp. S9–S23.

Marmot, M., G. Rose, M. Shipley, and P. Hamilton (1978). Employment grade and coronary heart disease in British civil servants. Journal of Epidemiology and Community Health, Vol. 32, No.4, pp. 244–249.


Labour Markets in Finland and Sweden

IFN Policy Paper No. 75 by Per Skedinger | Labour market institutions in Finland and Sweden have many features in common. This has inspired a joint Finnish-Swedish research project on the effects of these institutions (jointly with Petri Böckerman, Roope Uusitalo).

The research shows diverging paths of employment growth after 2012 in the two countries – lower employment rates in Finland for those aged 55–64.

One of the research questions in the project deals with employment protection legislation. The overall stringency of the regulation is rather similar. The key difference is that seniority rules are laid down by law in Sweden, but absent in Finnish legislation. The seniority rules stipulate that workers be dismissed in inverse order of seniority when firms lay off workers for economic reasons, unless unions and employers agree otherwise in firm-level bargaining.

The results indicate that more senior workers are less likely to exit from employment in the firm in both Sweden and Finland. But the effect is stronger in Sweden than in Finland and the researchers interpret this difference as the effect of seniority rules. They argue: “We also find that the difference between the countries is striking in shrinking firms, but negligible in stable or expanding firms. This is exactly what we should expect if our results are driven by seniority rules, since they only come into play when firms downsize.”

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In each issue of News from IFN a researcher at IFN writes an article on policy-relevant research. Previous topics include market power and underinvestment in nuclear power, as well as effects of privatization on competition and efficiency.

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