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 describes recent modifications to the mixed-frequency model vector autoregression (MF-VAR) constructed by Schorfheide and Song (2012). The changes to the model are restricted solely to the set of variables included in the model; all other aspects of the model remain unchanged. Forecast evaluations are conducted to gauge the accuracy of the revised model to standard benchmarks and the original model.

Doan, Litterman, and Sims have described a method for estimating Bayesian vector autoregressive (BVAR) forecasting models. The method has been successfully applied to the U.S. macroeconomic dataset, which is relatively long and stable. Despite the brevity and volatility of the post-1976 Chilean macroeconomic dataset, this paper shows that a straightforward application of the DLS method to this dataset, with simple modifications to allow for delays in the release of data, also appears to satisfy at least one criterion of relative forecasting accuracy suggested by Doan, Litterman, and Sims. However, the forecast errors of the Chilean BVARs are still large in absolute terms.Also, the model's coefficients change sharply in periods marked by policy shifts, such as the floating of the peso in 1982.

A model of a "real" business cycle is produced in which labor market participants possess private information. A class of economies is considered in which interesting cycles cannot arise without private information. A methodology adapted from Kydland and Prescott (1982) is then employed to show that models based on private information can empirically confront salient features of postwar U.S. business cycles. Moreover, this can be done in a way which is consistent with existing microeconomic evidence on wages and labor supply. Finally, it is shown that the important features of the model related to private information are fairly general.

A statistical definition of the natural unemployment rate hypothesis is advanced and tested. A particular illustrative structural macroeconomic model satisfying the definition is set forth and estimated. The model has "classical" policy implications, implying a number of neutrality propositions asserting the invariance of the conditional means of real variables with respect to the feedback rule for the money supply. The aim is to test how emphatically the data reject a model incorporating rather severe "classical" hypotheses.