Forecast Period versus Prediction Period
For the MC1 model we will use the phrase "forecast period" to refer to the 1997-2002 period. If you make no changes to the MC1 model and solve it for this period, the predicted values will be the values that are in the base dataset. You may, however, deal with other periods. Much of the data go back to 1960, and you can examine the data (list, graph, download, etc.) beginning with 1960. When solving the model, you should not begin before 1972, since data for a number of countries do not begin until about 1972. The period that you choose to work with will be called the "prediction period," which may, of course, differ from what we are calling the forecast period.

The MC1 Model Datasets
The treatment of the MC1 model datasets is similar to the treatment of the US model datasets. Everything about the MC1 model is stored in a single dataset:

1. values on all the endogenous and exogenous variables from 1960:1 through 2002:4,
2. specification information, and
3. coefficient estimates.

The dataset for the January 10, 1997, version of the model is called MCBASE with a password of MCBASE. You will name and create your own dataset, using MCBASE as a starting point. Say you call your dataset NEW and give it the password of NEW. When you first start, NEW and MCBASE 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 MCBASE 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 MCBASE. Say that you changed German government purchases of goods (GEG) for the forecast period and are interested in how this change affected real Japanese GDP (JAY). You can simply tell the program that you want to compare JAY in NEW versus MCBASE, 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: A comparison done this way only works if you take the beginning of your prediction period to be no earlier than the beginning of the forecast period in MCBASE. See Section 2.6 in Chapter 2 of The US Model Workbook for what needs to be done for comparisons within a period for which historical data exist. This is important: Do not take your prediction period to begin earlier than the forecast period until you have read Section 2.6.

The program is flexible as to what you take as your base dataset. Although the first time you start the base dataset is MCBASE, 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 MCBASE. 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
Although the flow variables in the MC1 Model are at quarterly rates, for most purposes it is useful to work with variables at annual rates. For the most part you will work with variables at annual rates: the program lists the variables at annual rates and your changes are taken to be at annual rates. The only time you need care about quarterly rates is if you are downloading the data to your computer for estimation purposes, since for estimation purposes the variables should be at quarterly rates. There is an option in the program to download the data at quarterly rates.

Years versus Quarters
Since some of the individual country models within the overall MC1 model are annual, the MC1 model must be solved in yearly (four-quarter) units. Thus, when choosing a period, you need only (and can only) choose years. The solution is, however, quarterly for the quarterly countries, and when you examine the output, you will be allowed to examine quarterly values for the quarterly countries.

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, as discussed in Chapter 2 of The US Model Workbook, 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.