Regression and neural network models of wage determination are constructed where the explanatory variables include detailed information about the impact of school curricula on future earnings. It is established that there are strong nonlinearities and interaction effects present in the relationship between curriculum and earnings. The results have important implications in the context of the human capital versus signalling and screening debate. They also throw light on contemporary policy issues concerning the desirability of breadth versus depth in the school curriculum
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