FRB/US in EViews
The main FRB/US model EViews package contains model equations, programs and documentation that enables various types of simulations and provides information about the model's structure using the EViews software. The package contains the following files and subdirectories:
- A readme file with basic information about the organization of the package and how to get started;
- The subdirectory addins with EViews add-in commands that must be installed, following the instructions provided in the readme file;
- The subdirectory mods containing model equations and parameter values;
- The subdirectory subs containing two libraries of subroutines, including the library mce_solve used for solving FRB/US under model-consistent (rational) expectations in EViews; the RE Solver Package is available for those wishing to download the mce_solve software and documentation by itself;
- The subdirectory programs containing some basic applications of the model including those described in the article "The FRB/US Model: A Tool for Macroeconomic Policy Analysis"
- The subdirectory documentation among whose documents are one with basic instructions for simulating FRB/US and another with a description of all of the model's equations.
FRB/US EViews package (ZIP) (Updated: April 21, 2022)
Data-Only Package and Disclaimer
Note: Because the FRB/US database is updated more frequently than the model and other material, the database is stored separately in the FRB/US data package. To run the model with the latest data, please download the FRB/US data package, create a directory in frbus_package named data and copy the files from eviews_database to the new directory. When updates are available only for the dataset, it is not necessary to re-download the FRB/US EViews package.
The following zip file contains the historical dataset (csv format) and FRB/US dataset (csv format and EViews edb format). The FRB/US dataset merges historical values with a mechanical extrapolation whose initial part follows the median path in the FOMC's Summary of Economic Projections (SEP). Beyond the horizon of the SEP, variables for real GDP, PCE inflation, unemployment, and the federal funds rate automatically converge to the median long-run SEP targets. This dataset is provided as a convenience, so that users have data on which to run the FRB/US model, and is for illustrative purposes only. The trajectories in this dataset are not FRB/US model forecasts, nor should they be interpreted as forecasts of the FOMC, the Federal Reserve Board or its staff.
FRB/US data package (ZIP) (Updated: January 4, 2024)
The program frbus_supply.prg estimates a multivariate state-space model that forms the basis of the FRB/US specification of potential output and its components. The zip file below contains the code and the data set used in estimation. The zip file also includes a note (latent_note.pdf) that provides documentation of the state-space model. The model is closely related to one presented in Charles Fleischman and John Roberts, "From Many Series, One Cycle: Improved Estimates of the Business Cycle from a Multivariate Unobserved Components Model," FEDS Working Paper 2011-46.
FRB/US supply-side package (ZIP) (Updated: December 30, 2015)
RE Solver Package
The software library mce_solve provides code for the solution of linear and non-linear models under model-consistent (MC) or "rational" (RE) expectations in EViews. This code is more reliable and efficient than the RE algorithm built into EViews (Fair-Taylor) at solving FRB/US when any of its expectations are MC. The mce_solve library includes two RE algorithms: E-Newton and E-QNewton. These algorithms iterate to find a model's RE solution with a sequence of updates to either exogenous estimates of the model's future-dated endogenous variables or exogenous components of such estimates. For single simulations of linear RE models, E-Newton is likely to be faster for models of small-to-medium size and E-QNewton is likely to be faster for larger models. For nonlinear models, E-Newton tends to be penalized relative to E-QNewton. The E-Newton algorithm has a substantial advantage over E-QNewton on experiments that involve a large number of RE solutions, as long as the same expectations Jacobian can be used for each E-Newton solution.
The solution algorithms are described in detail in Flint Brayton,"Two Practical Algorithms for Solving Rational Expectations Models," FEDS Working Paper 2011-44, and in the documentation included in the zip file. The zip file also contains some sample programs that illustrate how to use the algorithms.
NOTE: The programs for simulating the FRB/US model are written for use with the software EViews, available at www.EViews.com. The current version of FRB/US is compatible with the full-featured version of EViews but is not compatible with the student version.