Estimating the value of safety with labour market data: are the results trustworthy?


Hintermann, B., Alberini, A. and Markandya, A., 2010. Estimating the value of safety with labour market data: are the results trustworthy? Applied Economics, 42 (9), pp. 1085-1100.

Related documents:

This repository does not currently have the full-text of this item.
You may be able to access a copy if URLs are provided below. (Contact Author)

Official URL:

Related URLs:


We use a panel dataset of UK workers, combined with risk data at the four-digit industry level, to look for evidence of compensating wage differentials for workplace risk. We discuss various econometric problems associated with the hedonic wage approach, namely the instability of the estimates to specification changes, unobserved heterogeneity and endogeneity. We find evidence of significant compensating wage differentials and Values of a Statistical Life (VSL) figures only under the most restrictive assumptions, i.e. when we assume that there is no unobserved heterogeneity and that all regressors are exogenous. However, the VSL values are large and vary dramatically with the inclusion or exclusion of industry and/or occupation dummies, as well as with the addition of nonfatal risk. When we specify models that allow for heterogeneity and endogeneity of risk and of other regressors, we find no evidence of compensating wage differentials. We conclude that if compensating differentials for risk exists, econometric problems and the changing nature of labour markets prevent us from observing them. We also conclude that models and techniques for panel data that account for unobserved heterogeneity and endogeneity present a completely different picture about compensating wage differentials than that inferred by most wage-risk studies, which have generally used single cross-sections of data.


Item Type Articles
CreatorsHintermann, B., Alberini, A. and Markandya, A.
Related URLs
DepartmentsFaculty of Humanities & Social Sciences > Economics
ID Code18943


Actions (login required)

View Item