We use the control function approach to identify the average treatment effect and the effect of treatment on the treated in models with a continuous endogenous regressor whose impact is heterogeneous.
We consider the identification of the average treatment effect in models with continuous endogenous variables whose impact is heterogeneous and derive a testable restriction that allows us to assess the degree of unobserved heterogeneity.
We propose inference procedures for partially identified population features for which the population identification region can be written as a transformation of the Aumann expectation of a properly defined set valued random variable (SVRV).
We study identification in static, simultaneous move finite games of complete information, where the presence of multiple Nash equilibria may lead to partial identification of the model parameters.
We consider the identification of a Markov process {W<sub>t</sub>, X<sub>t</sub>*} for t=1,2,...,T when only {W<sub>t</sub>} for t=1, 2,..,T is observed.
For semi/nonparametric conditional moment models containing unknown parametric components θ and unknown functions of endogenous variables (h), Newey and Powell (2003) and Ai and Chen (2003) propose sieve minimum distance (SMD) estimation of (θ, h) and derive the large sample properties.
This paper describes the conceptual development of a self-enumerated scale of quality of life (CASP-19) and presents an empirical evaluation of its structure using a combination of exploratory and confirmatory factor analytic approaches across three different survey settings for older people living in England and Wales in the new millennium.
