Optimal IV estimation of systems with stochastic regressors and var disturbances with applications to dynamic systems

This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.

The impact on the stationary state income of a pay-as-you-go system of social security

A model of overlapping generations in continuous time is composed. IndividuaIs pass through two distinct time periods during their life times. During the first period, they work, save and have a death probability equal to zero. During the second, from the periods T after birth, their probability of death changes to p and then they retire. Capital stock and the stationary state in come are calculated for two situations: in the first, people live from their accumulated capital after retirementj in the second, they live from a state transfer payment through income taxo To simplify matters, in this preliminary version, it is supposed that there is no population growth and that the instantaneous elasticity substitution of consumption is unitary.