We address long-standing concerns in the literature on compensating wage differentials: the econometric properties of the estimated value of statistical life (VSL) and the wide range of such estimates. We confront prominent econometric issues using panel data, a more accurate fatality risk measure, and systematic application of panel data estimators. Controlling for measurement error, endogeneity, latent individual heterogeneity possibly correlated with regressors, state dependence, and sample composition yields VSL estimates of $4 million to $10 million. The comparatively narrow range clarifies the cost-effectiveness of regulatory decisions. Most important econometrically is controlling for latent heterogeneity; less important is how one does it.

We examine an econometric model of counts of worker absences due to illness in a sluggishly adjusting hedonic labor market. We compare three estimators that parameterize the conditional variance—least squares, Poisson, and negative binomial pseudo maximum likelihood—to generalized least squares (GLS) using nonparametric estimates of the conditional variance. Our data support the hedonic absenteeism model. Semiparametric GLS coefficients are similar in sign, magnitude, and statistical significance to coefficients where the mean and variance of the errors are specified ex ante. In our data, coefficient estimates are sensitive to a regressor list but not to the econometric technique, including correcting for possible heteroskedasticity of unknown form.