We investigate if, and under which conditions, the distinction between dictatorial and incentive-based policy interventions affects the capacity of Instrument Variable (IV) methods to estimate the relevant treatment effect parameter of an outcome equation. The analysis is set in a non-trivial framework, in which the right-hand side variable of interest is affected by selectivity, and the error term is driven by a sequence of unobserved life-cycle endogenous choices. We show that, for a wide class of outcome equations, incentive-based policies may be designed so to generate a sufficient degree of post-intervention randomization (a lesser degree of selection on individual endowments among the sub-population affected). This helps the instrument to fulfill the orthogonality condition. However, for a same class of outcome equation, dictatorial policies that enforce minimum consumption cannot meet this condition. We illustrate these concepts within a calibrated dynamic life cycle model of human capital accumulation, and focus on the estimation of the returns to schooling using instruments generated from mandatory schooling reforms and education subsidies. We show how the nature of the skill accumulation process (substitutability vs complementarity) may play a fundamental role in interpreting IV estimates of the returns to schooling.
Returns to schooling instrumental variable methods dynamic discrete choice dynamic programming local average treatment effects