The Influence of the German Statutory Minimum Wage’s Introduction on Individuals’ Health
Abstract
This contribution scrutinises how introducing a statutory minimum wage of EUR 8.50 per hour, in January 2015, impacted Individuals’ Health. Based on representative data from the Labour Market and Social Security panel, the study applies linear and logistic difference-in-differences propensity score matching approaches on several different health outcomes.
Purpose: The introduction of the statutory minimum wage in Germany on January 1st. 2015 represents one of the sharpest interventions of labour market policy since world war II. Although influenced by many factors, employment and working conditions comprise important determinants for individual health like working hours, salary, workplace policies or company manners. Therefore, the question arises whether individual health is affected by introducing the minimum wage and if so through which channels this effect is mediated1.
Methods: The survey Panel “Labour Market and Social Security” (PASS) allows for the identification of persons who were affected by the new minimum wage (treatment-group) as well as non-treaded (control-group). Using this characteristic, the calculation of the causal effect of the minimum wage on different health indicators of the treated by applying a Difference-in-Differences Propensity Score Matching (DiD-PSM) model2. Methodologically the selection of the matching variables is based on the framework of the Rubin-Causal model for the identification of causal effects3.
Results: A positive causal effect of introducing the minimum wage is detected on the indicators “Health Satisfaction”, “Life satisfaction” and “Number of visits to the doctor”. Higher wage increases and extended observation periods have a larger impact on health.
Conclusions: The effects found empathize the relevance of the Health in All Policies (HiAP) concept.
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1 Hirsch Barry T, Kaufman Bruce E, Zelenska Tetyana. (2015): Minimum Wage Channels of Adjustment. In: Ind Relat 54 (02) , S. 199-239.
2 Lechner Michael. (2010): The Estimation of Causal Effects by Difference-in-Difference Methods. In: FNT in Econometrics 4 (03) ,S. 165-224.
3 Gangl Markus. (2010): Causal Inference in Sociological Research. In: Annu. Rev. Sociol. 36 (01) , S. 21-47.
Simon Ress
Data Science Consultant
I am a PhD candidate at the chairs of Comparative Politics & Social Science Data Analysis, Ruhr-Universität Bochum. My main research interests are labour market policies and their effects on individual health and interest groups and lobbyism. I have published articles on interest groups and prevention policies.