This paper deals with the evaluation of some public employment policies set up in France during the 1980's to improve the labour market prospects of unskilled young workers. The evaluation implemented in this paper is restricted to the impact of such public measures on durations and outcomes of subsequent spells of unemployment and employment. The econometric study is conducted with non-experimental longitudinal microdata recording individual labour market histories. A particular attention is paid to the differential effects of various types of measures, according to the educational level of recipients. Programmes involving a higher level of on-the-job training, such as alternating work/training programmes in private firms, are principally beneficial to the less educated young workers. In contrast, for more educated young workers, “work fare” programmes in the public sector decrease the intensity of transition from the subsequent unemployment spell to regular jobs; for that subgroup, “work fare” programmes may act as a signal of low employment performance.

In Imbens and Ingrist (1994), Angrist, Imbens and Rubin (1996) and Imbens and Rubin (1997), assumptions have been outlined under which instrumental variables estimands can be given a causal interpretation as a local average treatment effect without requiring functional form or constant treatment effect assumptions. We extend these results by showing that under these assumptions one can estimate more from the data than the average causal effect for the subpopulation of compliers; one can, in principle, estimate the entire marginal distribution of the outcome under different treatments for this subpopulation. These distributions might be useful for a policy maker who wishes to take into account not only differences in average of earnings when contemplating the merits of one job training programme vs. another. We also show that the standard instrumental variables estimator implicitly estimates these underlying outcome distributions without imposing the required nonnegativity on these implicit density estimates, and that imposing non-negativity can substantially alter the estimates of the local average treatment effect. We illustrate these points by presenting an analysis of the returns to a high school education using quarter of birth as an instrument. We show that the standard instrumental variables estimates implicitly estimate the outcome distributions to be negative over a substantial range, and that the estimates of the local average treatment effect change considerably when we impose nonnegativity in any of a variety of ways.