| 13. Other Possible Experiments |
The suggested experiments in this manual by no means exhaust the possible experiments that can be performed. Indeed, the manual is really only meant to get you started on your way to your own analysis of macroeconomic questions and issues. This chapter presents a few more possible experiments for you to ponder. |
| 13.1 Combinations of Policies |
| It is best when first learning about the properties of a model to
change only
one exogenous variable at a time. Otherwise, one can get hopelessly lost
in trying to
figure out what is affecting what. In practice, however, one is usually
concerned with
more than one exogenous variable at a time. The government may want to
know the
consequences of changing both taxes and government expenditures at the
same time. A
business forecaster may want to know the outcome of an increase in import
prices and an
increase in exports. You would probably want to change state and local
government
expenditures or taxes at the same time that you change federal grants in
aid to state and
local governments. Now that you have gone through the workbook, you should not be shy about trying more complex sets of exogenous variable changes. If you know the consequences of changing one variable at a time, you should be able to explain the outcome when many variables are changed. A common type of experiment to perform is to pick a target path for some endogenous variable, say the federal government deficit, and keep changing policy variables until the target path is roughly met. You can answer questions like the following. What combinations of monetary and fiscal policy changes would lead to the target path being met, and are any of these combinations politically feasible? The variety of these types of experiments is quite large. Note also that you can phase in changes in policy variables. It is not necessary, for example, to have COG change by $20 billion from the first quarter on or to have RS change by one percentage point beginning immediately. The changes can differ by quarters and gradually work up to the final change that is desired. Don't forget that any experiment that you choose can be performed with different versions of the model. The types of changes in the model that were made in Chapters 9-11 can be made for any experiment. |
| 13.2 Effects of Changing State and Local Government Variables |
| The tax and spending variables of the state and local government sector are similar to those of the federal government sector. These variables are changed using option 3 of the main menu. The same types of experiments that were performed in Chapter 5 for the federal government can be performed for the state and local governments. |
| 13.3 Imposing Rational Expectations on the Model |
| In some cases it is possible to impose rational expectations on the
model.
Consider the bond market and the bond rate RB. RB is determined in the
model by the term
structure equation 23, where RB is a function of current and lagged
values of the short
term interest rate RS. If there are rational expectations in the bond
market, then RB
should instead be a function of current and expected future values of RS,
where the
expected future values of RS are what the model predicts them to be.
Say
we take an seven quarter horizon and we take RB to the be average of RS
and the next six
future values of RS:
If you work through and understand this example, you can probably think of other ways of adding rational expectations to the model. (See Section 11.7 in Fair (1984) for the case in which there are rational expectations in the stock market.) Iteration in the above manner is fairly straightforward and not too much extra work once you get practiced. |
| 13.4 Making Major Changes to the Model |
| The program is limited in how much you can change the model. You can drop equations, change coefficients, and add or subtract right hand side variables. You cannot, however, add new equations (except ones that have been dropped previously), change the left hand side variable in existing equations, or reestimate the equations. Fortunately, there is software that allows these types of changes to be made. If you use the US model in EViews or Fair-Parke, respecify the existing equations, add new equations, reestimate, and then solve the new version. In fact, if you don't like anything in the US model except the identities (which no one can complain about since they are always true), you can start from scratch and specify your own stochastic equations. Once you get your version of the model specified and estimated, you can use EViews or Fair-Parke to change policy variables and examine the model's properties. The range of possibilities here is essentially endless. |
| 13.5 Supply Side Experiments |
| Some "supply side" experiments are not sensible to perform
within the
model. The main example concerens
the variable LAM in equation 94. If, say,
you increase LAM, this makes labor more productive. If labor is suddenly
more productive,
there is more excess labor on hand, which has a negative effect on
employment demand and
hours paid for (JF and HF). These are not likely to be the effects one
has in mind when
considering exogenous productivity increases. There is simply no direct
way in which
productivity increases stimulate demand in the model, and if this is what
one has in mind,
the model is of really no use for this purpose. Supply experiments like
price shocks are
fine to run, but you should probably stay away from changing LAM.
Regarding supply side experiments, note that changing variables like tax rates that affect the labor force have supply side components. If personal tax rates are lowered, more people enter the labor force looking for work (the quantity of labor supplied increases). This in and of itself, however, does not create new jobs, only more people looking for jobs. Unless something is done to create new jobs, the main thing that happens when the labor force increases is that the unemployment rate increases. (A tax cut, of course, also stimulates demand, and so in this example new jobs will be created.) |
| 13.6 Counterfactual Experiments |
| It is easy with the model to ask questions like "what would the
economy
have been like had something that was done not been done or had something
that was not
done been done?" These "counterfactual" questions are
popular with economic
historians, among others. Experiment 7.2 is a counterfactual one, where
we are asking what
the economy would have been like had the price of imports not risen in
the 1970s. This workbook has not stressed counterfactual experiments because it is easier to learn about the properties of the model (and hopefully about the economy) by running simpler experiments. If you have worked through the experiments in this workbook, you are now ready to launch into counterfactual experiments if you wish. You should now have no trouble understanding the results from such experiments. How would the economy have been different had President A done x, y, and z instead of what he actually did? What if c, d, and e had not happened? What if f, g, and h had happened? There is room for many term papers here, so you can now get to work. |
| References |
|
Fair (1984): Specification, Estimation, and Analysis of Macroeconometric
Models, Harvard University Press, 1984.
Fair (1994): Testing Macroeconometric Models, Harvard University Press, 1994. Fair (2004): Estimating How the Macroeconomy Works, Harvard University Press, 2004. |