Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We use a unique data set about the wage distribution that Swiss students expect for themselves ex ante, deriving parametric and non-parametric measures to capture expected wage risk. These wage risk measures are unfettered by heterogeneity which handicapped the use of actual market wage dispersion as risk measure in earlier studies. Students in our sample anticipate that the market provides compensation for risk, as has been established with risk augmented Mincer earnings equations estimated on market data: higher wage risk for educational groups is associated with higher mean wages. With observations on risk as expected by students we find compensation at similar elasticities as observed in market data. The results are robust to different specifications and estimation models.