Before revision:  This reformulation leads to new identification results and , most importantly, to practical , easy to implement, and computationally tractable estimators . We explore estimation algorithms based on the contraction mapping theorem and algorithms based on root-finding methods. We prove consistency and asymptotic normality of our estimators and establish the validity of a bootstrap procedure for estimating the limiting laws. Monte Carlo simulations support the estimator's enhanced computational tractability and demonstrate desirable finite sample properties .
After revision:  This reformulation leads to new identification results and , most importantly, to practical , easy to implement, and tuning-free estimators that do not require the availability of high-level black box optimization routines .