FRB/US model packages
The main FRB/US model package is a self-contained set of equations, data, programs and documentation that enables various types of simulations and provides information about the model's structure. 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.
Note: The November 2018 release of the FRB/US model package contains a new version of the model, one that is significantly different than the previous version. Many of the modifications reduce the complexity and scope of the model via the consolidation, aggregation or elimination of various model variables and equations whose contribution to the major properties and uses of FRB/US is relatively minor.
For more information, see (a) the FEDS Note "Overview of the Changes to the FRB/US Model (2018)" by Jean-Phillipe Laforte; and (b) the HTML documentation located in the FRB/US model package under documentation/documentation_model_nov2018/documentation.html.
As of November 2017, the FRB/US model package no longer contains a data folder with Eviews database files. These files have been moved to the “eviews_database” folder of the FRB/US dataset. To run the model with the latest data please download the data only package, create a directory in frbus_package named “data” and copy the files from “eviews_database” to the new directory.
FRB/US model package (ZIP) (Updated: August 12, 2019)
The following zip file contains the historical FRB/US database (csv format) and FRB/US EViews databases (edb format).
FRB/US dataset (ZIP) (Updated: October 16, 2019)
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 latest data set used in estimation.
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 latest 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)
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 EViews versions 7, 8, 9, and 10, but not the student version.