Estimation of Dynamic Discrete Choice Models with and without Value Function Measurement

Abstract

We show that direct measurement of value functions allows for identification of dynamic discrete choice models without restrictive "normalization" assumptions in traditional settings as well as settings with incomplete data on state variables. Using data on US cropland use, empirical results reveal that a priori restrictions on the profit function have an impact on only certain types of long-run land use elasticities.