|The US Model in EViews 7: April 28, 2018|
US Model Optimized for EViews: January 28, 2018, version of the US model
If you have EViews on your computer and want to work with the US model in EViews, there are now two ways to do this. First, you can do this by downloading the zipped file usev174.zip. You should download this file by clicking it, and then unzip it. One of the files in the zipped file is readme.txt, which is repeated below. This version is due to Matthew Cushing at the University of Nebraska-Lincoln. It takes advantage of many more of the features of EViews than does the other way (below) of downloading EViews. It is recommended that you use this version rather than the version below.
The included workfile is optimized to take advantage of a number of features of Eviews. 1. It uses the native EVIEWS NA rather than the FP 999999 to represent a missing observation. This way, Eviews does not mistake 999999 has an actual observation in graphs and estimation. Future values of the endogenous variables are represented by NAs. This automatically avoids the mistake of estimating equations over forecasted rather than actual data. 2. It exploits EVIEWS's ability to recognize simple functions in regression commands. The variable LOG(CS/POP) is entered directly into equation 1, so there is no need to define LCSZ and then recover CS from the forecasts of LCSZ. This greatly reduces the number of variables on the workfile and the number equations in the model. Further, the equations are much easier to interpret, as they look very much like the equations reported in the FAIRMODEL appendix. 3. Coefficient restriction are made explicit in equations 16, 23 and 24, rather than imposed by redefining variables. 4. Variables have labels and equations have more understandable names. Clicking on the Details tab brings up the description of each variable. 5. Identities are labelled as such. This is useful in making add factors and doing stochastic simulations. 6. The included SETUP.PRG file automatically converts the Eviews workfile provided on the website, FM.WK1 to FMEZ.WK1 The included workfile is optimized to take advantage of a number of features of Eviews.
end of readme.txt
US Model in EViews: No Optimization: April 28, 2018, version of the US Model
For this version the zipped file to download is: fmev.zip. You should download this file by clicking it, and then unzip it. The datasets in it are:
The following discussion assumes that you know EViews 7. If not, you should learn EViews first before trying to get the model working in it.
Enter EViews and type LOAD FM. The entire model is now loaded. In the main workfile the model is called FMA. If you double click FMA, you are ready to go. The model has been solved for the 2018:1--2022:4 period in the workfile, and the solution values end with _0. These solution values are the forecast values of the January 28, 2018, forecast within rounding error. You do not need the datasets FMGENR.PRG, FMEQ.PRG, and FMA, which are included in FMEV.ZIP, but they may be useful for reference purposes. FMGENR.PRG generates various variables, and FMEQ.PRG estimates the model.
EViews handles the use of 2SLS with autoregressive errors somewhat differently than does the FP program, and so some of the estimates using EViews differ from those using the FP program. EViews sometimes adds instruments from the ones specified, which FP does not. If the ALT2SLS option is used in the FP program (see page 61 of the User's Guide), which is used for the estimation of the US model, then extra instruments do not have to be added to insure consistency.
IMPORTANT NOTE: For the current version (April 28, 2018) the EViews TSLS estimates of equations 1, 4, and 11 were quite different from the Fair-Parke estimates and were not sensible. These three equations were instead estimated by OLS in EViews. (The TSLS commands for these three equations are in FMEQSTO.PRG. The OLS commands are in FMEQ.PRG.) The EViews predictions thus do not exactly duplicate the predictions on the site (which use the Fair-Parke TSLS estimates). For some variables the differences in the predictions are fairly large near the end of the horizon.
Two variables are renamed when using EViews. COS is renamed COSS, and AR is renamed ARR.
This should be enough to get you started. If you want to modify the model in bigger ways than are allowed on this site and/or want to estimate the model, EViews allows you to do this.
NOTE: This site receives no money from EViews; we are simply making the US model datasets available for those who are interested.