Forecast dated October 26, 2023

For the forecast on this site equations 25, 28, and 30 have been dropped, so the variables CGZ, LUB, and RS are exogenous. You can, however, solve the model with equation 30 back in---RS endogenous. The forecast in this case is different from the forecast on the site because the values of RS are different.

Solve the Model

SOLVE if you have read the following.
SOLVE--RS endogenous if you have read the following.

Getting Started

Before solving the model you should look over
Macroeconometric Modeling: 2018.
Also, read the Preface in
The US Model Workbook, October 26, 2023
and then decide what else you need to read. The following discussion gives details on the solution process.

Forecast Period versus Prediction Period

The phrase "forecast period" is used to refer to the actual forecast period in the base dataset. You may, however, deal with any period within the overall 1952.1-2027.4 period, and the phrase "prediction period" is used to refer to the period you have chosen. The only restriction is that if you are going to solve the model, the prediction period cannot begin earlier than 1954.1.

The US Model Datasets

Everything about the model is stored in a single dataset. The dataset for the October 31, 2022, update of the model is called ZATBASE with a password USBASE. (For the version with RS endogenous the dataset is ZBSBASE.) You will name and create your own dataset, using ZATBASE as a starting point. Say you call your dataset NEW and give it the password of NEW. When you first start, NEW and ZATBASE are exactly the same, and then NEW gets modified as you make changes (change exogenous variables, coefficients, etc.). Once you are done making changes, you tell the program to solve the model. The program solves the model, and after this solution, the values of the endogenous variables in NEW are the predicted values. You can examine (i.e., write to the screen, print to a printer, or download to a file) the values in ZATBASE and in any datasets you create.

In many cases one is interested in how the values of the endogenous variables in NEW compare to the original values in ZATBASE. Say that you changed federal government purchases of goods (COG) for the forecast period and are interested in how this change affected real GDP (GDPR). You can simply tell the program that you want to compare GDPR in NEW versus ZATBASE, and it will show you the two sets of values and the differences. (Once you do this a few times you will get the hang of it.)
WARNING: If you do this comparison for any period beginning earlier than the beginning of the forecast period, you must use the option to use the historical errors. See Section 2.6 in Chapter 2 of The US Model Workbook, October 26, 2023 for more discussion.

The program is flexible as to what you take as your base dataset. Although the first time you start the base dataset is ZATBASE, after you have created new ones, you can use any of these as your base. For example, if you created NEW and now want to makes further changes and create NEW1, you simply tell the program that you want NEW as your base dataset. Once you have created NEW1, you can either compare the values in NEW1 with those in NEW or the values in NEW1 with those in ZATBASE. You do this by simply telling the program which two datasets to use for the comparison.

If you make changes to your dataset and do not ask the program to solve it (which you are allowed to do), the values of the endogenous variables in the dataset are not consistent with your changes because they are not the solution values. Make sure you remember whether your dataset has been solved. As a general rule, you might always solve your datasets immediately after you have made your changes.

Units of the Variables

The flow variables in the US model are at quarterly rates, and unless otherwise noted these are the units on the site. Much of the data presented by the government are at annual rates, and if you want annual rates, just multiply the flow variables by four.

Changing the Prediction Period

The default prediction period for the July 28, 2022, version of the model is 2022.3-2025.4. If you want to change this period, you can use the option "Set prediction period." For this option, however, you can only enter years, where the beginning of the prediction period is the first quarter of the first year and the end is the fourth quarter of the last year. If you want a different starting quarter, you can do this by going to the option "Take equations to begin after the beginning of the prediction period" and entering the quarter you want for all of the equations. For example, if you want the beginning to be the second quarter of 2008, you would enter 20082 for all of the equations.

The option "Change exogenous variables" does not have the year restriction. You can enter any quarter, like 20082, for the changes.

Solution Errors

If you make wild changes to the exogenous variables or coefficients, the model may not solve. When the model does not solve, you will get a solution error message, and the existing values of the endogenous variables in your dataset will not be changed. (Your dataset will still be inconsistent in the sense discussed above.) You need to be less wild and try again. As a general rule, you should not try to push the economy into extreme areas. Macroeconometric models are not likely to be reliable when variable values are pushed far beyond their historical ranges.

Examining the Output

If you change the display period from the default in the output part of the site, you are also restricted to entering only years. This is not, however, much of a restriction, since all you get are a few more quarters displayed than you might optimally want. Remember the base dataset for comparison is ZATBASE with a password of USBASE.

Dataset Names and Storage

The dataset names cannot be longer than EIGHT (8) characters. A common mistake is to use more than eight characters. The datasets are stored on the site's hard drive for about three months. If you want to continue to use a dataset older than three months, simply copy it to a new named dataset, and the latter will be treated as a newly created dataset.

Note on some options:

For some options you may need to hit the back space arrow on your browser one or two times once you have made any changes to get back to the main page. Doing this will not erase your changes.

Solve the US Model


Solve the US Model---RS endogenous

SOLVE---RS endogenous

Note for the January 27, 2022, forecast

This forecast is used as a benchmark for the paper
A Note on the Fed's Power to Lower Inflation.
You can duplicate Table 3 in this paper by doing the following: 1) create a data set, 2) ask to change exogenous variable values and then choose RS, 3) add 1.0 to RS for all the quarters, 4) save changes and then solve. You can also duplicate Table 4 by typing in the new values for RS for each quarter, which are 1.5, 3.0, 4.5, 6.0, and then 7.0 for the rest. Then save changes and solve. The difference between the solution value and the base value for each variable and quarter is the effect of the change in RS.

For this forecast equations 25, 28, and 30 have been dropped, so the variables CGZ, LUB, and RS are exogenous,