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EXPERIMENT DESIGN THEORY for regression analysis is becoming important in econometric work, most notably in the context of negative income tax 1 and other subsidy experiments (such as housing and health subsidy experiments being planned). The usual regression design model requires the experimenter to specify the functional form of the behavioral equation under investigation. An apparent difficulty is that the experimenter does not know the true functional form. This paper suggests new procedures for handling the difficulty. The procedures were stimulated by work in planning the New Jersey negative tax experiment. To the planners of the New Jersey experiment, the relevant statistical design literature was not applicable, cookbook fashion, because the practical design guidelines were constructed for simpler situations. However, by combining ingredients from the statistical literature, the New Jersey experimenters were able to define a well-behaved mathematical programming model whose solution would tailor a design to their situation 3. (The references 2 and 4 provide a useful entry to the relevant statistical literature.) The new procedures suggested here build on the New Jersey design model, which is reviewed in Section 2. Though the exposition runs in terms of subsidy experiments, the material is more generally applicable.
John Conlisk (Sun,) studied this question.
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