Abstract
This paper provides a structural approach to testing investment equations based on the log-likelihood function of a nonlinear investment rule. The analysis integrates the predictions of theq-theory for the commonly studied active region of investment and provides new inferences on how real and financing frictions affect the probability that a firm invests. The empirical findings are consistent with the macro-finance literature suggesting thatq-theory models with nonconvex investment frictions better explain the data. I also find that both real and financing costs of investment are related to the capital intensity of the industry in which firms operate.
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