Effects Of Exogenous Variables Research Articles

The prediction variance and related statistics for stationary time series

SUMMARY A spectral estimate of the generalized prediction variance of a stationary time series is considered and a modification which uses a frequency domain regression to allow for the effect of exogenous variables is introduced. Strong consistency and a central limit theorem are proved for this estimate and for several statistics derived from it. The results of some simulations are presented, together with the results of application to two published sets of data.

A Stochastic Equilibrium Model of an Open Economy Under Flexible Exchange Rates*

I. Setup of the model, 149. — II. Determination of the exchange rate and the expected future exchange rate, 154. — III. Effects of exogenous variables, 156. — IV. Incomplete current information, 159. — V. Concluding remarks, 161.

Causal Models in Educational Research: Nonrecursive Models

This paper extends the causal modelling technique described in an earlier article (Anderson and Evans, 1974) to nonrecursive causal models that involve feedback and/or reciprocal causation. The problem of identification is discussed and a rule provided that can be used to determine whether or not a unique set of parameter estimates can be found for each equation that makes up the model. Three different procedures are described for estimating the parameters of these equations, namely, ordinary least squares, indirect least squares, and two-stage least squares. A formula is provided for the derivation of the reduced form of the model. The reduced form provides information concerning the total effect of exogenous variables on endogenous variables in the model. Data from an empirical study have been used to illustrate the causal modelling technique that is described.