The US Model in EViews 7: January 30, 2016 |

If you have EViews
on your computer and want to work with the US model in EViews, you can do
this by
downloading the relevant datasets. The datasets are zipped in the file:
fmev.zip.
You should download this file by clicking it, and then unzip it. The
datasets in it are: - FM.WF1---the complete workfile. Variables that end in _0 are solution values
- FMGENR.PRG---contains commands to generate variables (not needed; for reference purposes only)
- FMEQ.PRG---contains commands to estimate all the equations (not needed)
- FMA---contains the listing of the model for solution purposes (not needed)
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 2016:1--2022:4 period in the workfile, and the solution values end with _0. These solution values are the forecast values of the January 30, 2016, 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 slightly 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. For the current version (January 30, 2016) there were problems with equations 4 and 26. The coefficient estimates of these two equations were not close to the model's estimates. Again, the autoregressive errors were handled differently. To make the estimates closer, in EViews equation 4 was estimated by ordinary least squares and equation 26 was estimated with no autoregressive error. Using these estimates, which are closer to the model's estimates, the forecasts using EViews are slightly different from the model's forecasts, but not too bad. 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. |