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The impact of health on wages: evidence for Europe

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Abstract

This paper analyses the effects of health on wages in sixteen European countries using production frontier methodology. It is assumed that workers have a potential income/productivity which basically depends on their human capital, but due to several health problems, situations could exist where workers fail to reach their potential income frontier. The estimation of a true-random-effects model allows us to conclude that the potential hourly wage of workers is significantly influenced by their level of education and their job experience. However, health problems, especially those strongly influencing work activities, contribute towards an individual not attaining the potential income which would otherwise be guaranteed by their human capital endowment. Suffering a strong limitation reduces gross wage per hour by 6.1%. This wage reduction is also observed in the case of a weak limitation, but here the wage difference with respect to workers without any limitation is 2.6%. Additionally, other factors, such as being a woman, the economic cycle or having a temporary contract, appear to distance an individual from their wage frontier.

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Notes

  1. It is worth noting that the sample is composed solely by wage-earner workers, with self-employed being excluded. Besides, wages are computed at constant prices (real wages) taking 2015 as the base year.

  2. Since we are estimating a Mincer wage equation our analysis focuses only on workers who are in the labour market. Therefore, these results cannot be extrapolated to individuals who, because of their strong health limitations, are outside the labour market.

  3. The presence of an individual in a particular year is controlled by means of yearly dummy variables: D2008-D2011.

  4. It is possible to distinguish between deterministic and stochastic frontiers. The deterministic frontier assumes that any deviation from the frontier is due to inefficiency, while the stochastic frontier incorporates the statistical noise. Hence, in deterministic frontiers any measurement error and any other source of stochastic variation in the dependent variable are attributed to inefficiency. Moreover, given that the number of individuals is very large, it is not possible to perform the Housman test to contrast whether the model is of a fixed or random effects nature.

  5. For example, the maximum wage is reached after 38.4 years of experience in the case of Spain. For the case of Norway the experience squared is not statistically significant. On the other hand, in the case of the United Kingdom we have used worker age instead of work experience as a specific proxy of human capital, given that the variable for work experience is not available in the majority of cases in the database.

  6. The same is true, for example, in the case of France for workers in the service sector and operators.

  7. For example, in the Spanish case the internal devaluation process occurred mainly from 2012 onwards, coinciding with the application of the labour reform.

  8. The case of Romania must be highlighted where the estimate only incorporates the information corresponding to the years 2008 and 2009, given that the database did not offer information on this variable in the years 2010 and 2011.

  9. Nevertheless, in countries like Denmark and Portugal the gender effect is not statistically significant. The exception for Denmark was also found in the study by [31].

  10. The same occurs in Austria, Belgium and Poland.

  11. For the case of Greece, strong limitation is not statistically significant. This may be due to the small number of Greek workers who have a strong limitation in the sample used (see Table A2).

  12. Others studies present a different approach analyzing the effect of health on the probability of participating in the labour market [32–34]. In this case, and as [32] points out: "this creates a selection problem as the decision to participate in the labour market is likely to be non-randomly determined and this is unlikely to be fully covered by observable factors". Because of this, they tackle this selection problem by applying a Heckman procedure.

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Acknowledgements

The authors acknowledge financial support from the project ECO2017-86402-C2-1-R (Ministry of Economy and Competitiveness) and the project “Oviedo Efficiency Group” FC-15-GRUPIN14-048 (FEDER and Principality of Asturias). This article is based on data from Eurostat, EU Statistics on Income and Living Conditions (2008–2011). The responsibility for all conclusions drawn from the data lies entirely with the authors.

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  1. Economics Department, University of Oviedo, Avda. del Cristo S/N, 33006, Oviedo, Spain

    Ana Rodriguez-Alvarez & César Rodriguez-Gutierrez

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  1. Ana Rodriguez-Alvarez
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Correspondence to Ana Rodriguez-Alvarez.

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Appendix

Appendix

Definitions of the variables and descriptive statistics see Tables (3 and 4)

Table 3 Variable definitions
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Table 4 Descriptive statistics
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Rodriguez-Alvarez, A., Rodriguez-Gutierrez, C. The impact of health on wages: evidence for Europe. Eur J Health Econ 19, 1173–1187 (2018). https://doi.org/10.1007/s10198-018-0966-2

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