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.

Common cycles in macroeconomic aggregates (revised version)

Although there has been substantial research on long-run co-movement (common trends) in the empirical macroeconomics literature. little or no work has been done on short run co-movement (common cycles). Investigating common cycles is important on two grounds: first. their existence is an implication of most dynamic macroeconomic models. Second. they impose important restrictions on dynamic systems. Which can be used for efficient estimation and forecasting. In this paper. using a methodology that takes into account short- and long-run co-movement restrictions. we investigate their existence in a multivariate data set containing U.S. per-capita output. consumption. and investment. As predicted by theory. the data have common trends and common cycles. Based on the results of a post-sample forecasting comparison between restricted and unrestricted systems. we show that a non-trivial loss of efficiency results when common cycles are ignored. If permanent shocks are associated with changes in productivity. the latter fails to be an important source of variation for output and investment contradicting simple aggregate dynamic models. Nevertheless. these shocks play a very important role in explaining the variation of consumption. Showing evidence of smoothing. Furthermore. it seems that permanent shocks to output play a much more important role in explaining unemployment fluctuations than previously thought.