In light of skilled-labor shortage, the effect of a change in the wage of nurses on their labor supply is intensely discussed in recent literature. Using extensive data of German 14- to 15-year-olds, I analyze the role of the beliefs about a nurse's wage in the decision to become one. To estimate a partial effect, I select controls and their functional form using post-double-selection, which is a data-driven selection method based on regression shrinkage. Highlighting the importance of wages at the extensive margin of labor supply, the wage beliefs play a positive and statistically significant role. Although information is publicly available, educational choices knowingly suffer from misinformation. I find that especially those who do not become a nurse understate the wage. The results lead to two important policy implications. First, increasing the wage may help to overcome the shortage observed in many countries. Second, providing more information on the (relative) wage may be a successful strategy to attract more individuals into this profession. To assess the sensitivity of the results regarding omitted variable bias, I apply a novel approach. It turns out that potential unobserved confounders would have to be strong to overrule the conclusions.
Keywords: health professional; machine learning; occupational choice; wage beliefs; wage information.
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