Many regional econometric models are estimated under the maintained assumption that certain national variables are exogenous with respect to the regional variables in the models. This exogeneity assumption is testable using time series methods of inference, yet, to my knowledge, no regional model has been so tested. In this paper, I test the national exogeneity assumption included in the specification of a particular regional forecasting model. Such a test is, I believe, a necessary and important step in the construction of any econometric model.

This paper puts forward a method of policy simulation with an existing macroeconometric model under the maintained assumption that individuals form their expectations rationally. This new simulation technique grows out of Lucas' criticism that standard econometric policy evaluation permits policy rules to change but doesn't allow expectations mechanisms to respond as economic theory predicts they will. This technique is applied to versions of the St. Louis Federal Reserve model and the FRB-MIT-Penn model to simulate the effects of different constant money growth policies. I shall briefly summarize the current practice of policy evaluation and the Lucas critique in the first section. The second section includes an explanation of the method I propose. The third section includes the two illustrative applications. In the conclusion, I cannot resist the temptation to offer some opinions about the use and usefulness of econometric models.

This paper puts forward a method of policy simulation with an existing macroeconometric model under the maintained assumption that individuals form their expectations rationally. This new simulation technique grows out of Lucas' criticism that standard econometric policy evaluation permits policy rules to change but doesn't allow expectations mechanisms to respond as economic theory predicts they will. This technique is applied to versions of the St. Louis Federal Reserve model and the FRB-MIT-Penn model to simulate the effects of different constant money growth policies. I shall briefly summarize the current practice of policy evaluation and the Lucas critique in the first section. The second section includes an explanation of the method I propose. The third section includes the two illustrative applications. In the conclusion, I cannot resist the temptation to offer some opinions about the use and usefulness of econometric models.

This paper puts forward a method for simulating an existing macroeconometric model while maintaining the additional assumption that individuals form their expectations rationally. This simulation technique is a first response to Lucas' criticism that standard econometric policy evaluation allows policy rules to change but doesn't allow expectations rules to change as economic theory predicts they will. The technique is applied to a version of the St. Louis Federal Reserve Model with interesting results. The rational expectations version of the St. Louis Model exhibits the same neutrality with respect to certain policy rules as small, analytic rational expectations models considered by Lucas, Sargent, and Wallace.

This paper puts forward a method for improving the forecasting accuracy of an existing macroeconometric model without changing its policy response characteristics. The procedure is an extension and formalization of the practice of additive adjustments currently used by most forecasters. The method should be of special interest to forecasters who use models built by other investigators because it does not involve reestimation of the original model and uses only information routinely included in the documentation available to model users. The paper ends with a demonstration of the prediction improvement realized by application of this method to a version of the MIT-Penn-SSRC (MPS) model.