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The European Journal of Health Economics

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22.03.2018 | Original Research

The impact of health on wages: evidence for Europe

verfasst von: Ana Rodriguez-Alvarez, César Rodriguez-Gutierrez

Erschienen in: The European Journal of Health Economics | Ausgabe 8/2018

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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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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.

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.

The presence of an individual in a particular year is controlled by means of yearly dummy variables: D_2008-D₂₀₁₁.

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.

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.

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

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

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.

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].

The same occurs in Austria, Belgium and Poland.

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).

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.

Luft, H.S.: The impact of poor health on earnings. Rev. Econ. Stat. 57(1), 43–57 (1975). https://doi.org/10.2307/1937862 CrossRef

Mushkin, S.J.: Health as an investment. J Polit Econ 70(Supplement), 129–157 (1962). https://doi.org/10.1086/258730 CrossRef

Grossman, M.: On the concept of health capital and the demand for health. J Polit Econ 80(2), 223–255 (1972). https://doi.org/10.1086/259880 CrossRef

Grossman, M., Benham, L.: Health, hours and wages. In: Perlman, Mark (ed.) The economics of health and medical care, pp. 205–233. Macmillan, London (1974)CrossRef

Berkowitz, M., Fenn, P., Lambrinos, J.: The optimal stock of health with endogenous wages: application to partial disability compensation. J Health Econ 2(2), 139–147 (1983). https://doi.org/10.1016/0167-6296(83)90003-6 CrossRefPubMed

Hsieh, W., Hsiao, P., Lee, J.: The impact of health status on wages: evidence from the quantile regression. J Int Global Econ Stud 5(1), 35–56 (2012)CrossRef

Connolly, M.P., Tashjian, C., Kotsopoulos, N., Bhatt, A., Postma, M.J.: A comparison of average wages sith age-specific wages for assessing indirect productivity losses: analytic simplicity versus analytic precision. Eur J Health Econ 18, 697–701 (2017). https://doi.org/10.1007/s10198-016-0819-9 CrossRefPubMed

Barnay, T.: Health, work and working conditions: a review of the euroepan economic literature. Eur J Health Econ 17(6), 693–709 (2016). https://doi.org/10.1007/s10198-015-0715-8 CrossRefPubMed

Mincer, J.: The distribution of labor incomes: a survey with special reference to the human capital approach. J Econ Lit 8(1), 1–26 (1970)

10.

Mincer, J.: Schooling, experience and earnings. National Bureau of Economic Research, New York (1974)

11.

Blaug, M.: The empirical status of human capital theory: a slightly jaundiced survey. J Econ Lit 14(3), 827–855 (1976)

12.

Becker, G.S.: Human capital: A theoretical and empirical analysis with special reference to education, 3rd edn. National Bureau of Economic Research, New York (1993)CrossRef

13.

Jimeno, J.F., Toharia, L.: The effects of fixed-term employment on wages: theory and evidence from Spain. Invest Econ XVII 3, 475–494 (1993)

14.

Davia, M.A., Hernanz, V.: Temporary employment and segmentation in the Spanish labour market: an empirical analysis through the study of wage differentials. Span Econ Rev 6(4), 291–318 (2004). https://doi.org/10.1007/s10108-004-0086-2 CrossRef

15.

Booth, A.L., Francesconi, M., Frank, J.: A sticky floors model of promotion, pay, and dender. Eur Econ Rev 47, 295–322 (2003). https://doi.org/10.1016/S0014-2921(01)00197-0 CrossRef

16.

De la Rica, S., Ugidos, A.: Son las diferencias de capital humano determinantes de las diferencias salariales observadas entre hombres y mujeres. Invest Econ XIX 3, 395–414 (1995)

17.

Díaz, M.A., Sánchez, R.: Gender and potential wages in Europe: a stochastic frontier approach. Int J Manpower 32(4), 410–425 (2011). https://doi.org/10.1108/01437721111148531 CrossRef

18.

Pérez-Villadóniga, M.J., Rodríguez-Álvarez, A.: Analysing wage differentials when workers maximize the return to human capital investment. Appl. Econ. 49(42), 4196–4208 (2017). https://doi.org/10.1080/00036846.2017.1279267 CrossRef

19.

Perez-Villadóniga, M.J., Rodríguez-Álvarez, A.: Comparing the gender gap in gross and base wages. Int J Manpower 38(5), 646–660 (2017). https://doi.org/10.1108/IJM-10-2015-0162 CrossRef

20.

Drydakis, N.: Health impairments and labour market outcomes. Eur J Health Econ 41, 457–469 (2010). https://doi.org/10.1007/s10198-009-0182-1 CrossRef

21.

Contoyannis, P., Rice, N.: The impact of health on wages: evidence from the British Household Panel Survey. Empir Econ 26(4), 599–622 (2001)CrossRef

22.

Gambin, L. M. (2005): The impact of health on wages in Europe—does gender matter? HEDG Working Paper, 05/03, The University of York

23.

Kumbhakar, S.C., Lovell, C.A.K.: Stochastic frontier analysis. Cambridge University Press, UK (2000)CrossRef

24.

Caudill, S.B., Ford, J.M.: Biases in frontier estimation due to heteroscedasticity. Econ. Lett. 41, 17–20 (1993). https://doi.org/10.1016/0165-1765(93)90104-K CrossRef

25.

Wang, H.J., Schmidt, P.: One-step and two-step estimation of the effects of exogenous variables on technical efficiency eevels. J. Prod. Anal. 18, 129–144 (2002). https://doi.org/10.1023/A:1016565719882 CrossRef

26.

Caudill, S.B., Ford, J.M., Gropper, D.M.: Frontier estimation and firm specific inefficiency measures in the presence of heteroscedasticity. J Bus Econ Stat 13, 105–111 (1995). https://doi.org/10.2307/1392525 CrossRef

27.

Battese, G.E., Coelli, T.J.: A model for technical inefficiency effects in a stochastic frontier production function for panel aata. Empir Econ 20, 325–332 (1995). https://doi.org/10.1007/BF01205442 CrossRef

28.

Wang, H.J.: Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model. J. Prod. Anal. 18(3), 241–253 (2002). https://doi.org/10.1023/A:1020638827640 CrossRef

29.

Greene, W.: Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. J Econometrics 126, 269–303 (2005). https://doi.org/10.1016/j.jeconom.2004.05.003 CrossRef

30.

Hadri, K.: Estimation of a doubly heteroscedastic stochastic frontier cost function. J Bus Econ Stat 17(3), 359–363 (1999). https://doi.org/10.2307/1392293 CrossRef

31.

Díaz, M. A. and Sánchez, R. (2007): Gender and potential wage in Europe: a stochastic frontier approach. Paper presented at VII JEL, Las Palmas de Gran Canaria, España

32.

Flores, M., Fernandez, M. and Pena-Boquete, Y. (2015): The impact of health on wages: evidence from Europe before and during the great recession. Netspar Discussion Paper. 10/2014-097. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2649973

33.

Hsieh, W., Hsiao, P., Lee, J.: The impact of health status on wages—evidence from the quantile regression. J. Int. Global Econ. Studies 5(1), 35–56 (2012)CrossRef

34.

Jäckle, R., Himmler, O.: Health and wages. Panel data estimates considering selection and endogeneity. J Human Resour 45(2), 364–406 (2010)CrossRef

Titel: The impact of health on wages: evidence for Europe
verfasst von: Ana Rodriguez-Alvarez
César Rodriguez-Gutierrez
Publikationsdatum: 22.03.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: The European Journal of Health Economics / Ausgabe 8/2018
Print ISSN: 1618-7598
Elektronische ISSN: 1618-7601
DOI: https://doi.org/10.1007/s10198-018-0966-2

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