|The key exogenous variable regarding the behavior of prices is the
imports (PIM). If PIM increases, this increases domestic prices through
the price equation
10. The effect of a change in PIM on domestic prices is in fact quite
7.1 examines this question.
Experiment 7.1: Increase in the Import Price Index PIM
- Increase PIM by 10 percent in each quarter of the forecast period.
- Note that stagflation resulted from this experiment. Why? In
particular, why did
aggregate expenditures fall in real terms?
- What did the Fed do in response to all of this? (Remember that
equation 30 is in
the model for this experiment since it is the default option and you
made no changes
regarding monetary policy.)
- What happened to the real wage and why? To the labor force? To the
saving rate? To corporate profits in nominal terms (PIEF)? To
corporate profits in real
The model attributes much of the stagflation of the 1970's to the huge
in PIM that occurred during this period. This can be seen in the
(This is the hardest experiment in the workbook so far.)
Experiment 7.2: What if PIM had not changed after 1973?
- Make no changes to dataset BASE and solve the model for the
Call this dataset BASEA. Take BASEA as your base dataset, and change
the values of PIM for
1974:1-1978:4 to be equal to the actual value in 1973:4. Solve the
model for the
1974:1-1978:4 period for these changes. Call this dataset NEWA.
- The differences between the values in BASEA and BASE are the errors
model makes in predicting the 1974:1-1978:4 period. How does the
model do for this hard to
- The differences between the values in NEWA and BASEA are the
amounts by which the
model estimates the variables would have been different had PIM not
changed from its value
in 1973:4, i.e., had there been no oil shocks. How much of the
stagflation during this
period does the model attribute to PIM?
- What does the model estimate the Fed would have done differently
had PIM not
risen? How would AG have been different?
- How would the labor force have been different, and what would the
rate have been?
- This is an important experiment in that it shows that according to
the model the
1970's would have been fine had it not been for the oil shock and the
other price shocks
that caused PIM to increase so rapidly.
|Almost everyone knows the stock market crashed in October of 1987.
crash, how was the economy affected? The model can be used to estimate
these effects. The
stock market variable in the model is CG, the capital gains (+) or losses
(-) on stocks
held by the household sector. The crash in October resulted in a fall in
CG of about $500 billion, which is $2000
billion at an annual rate. (The $2000 billion fall was put into the third
quarter value of
CG because the crash took place at the very beginning of the fourth
quarter. CG is the
change in stock prices from end of previous quarter to end of current
the October crash is history, we can ask how the economy would respond if
there were a
large fall in, say, 2011:3, the first quarter of the forecast period.
assume a fall of $2000 billion in 2011:3, which at an annual rate is $8000,
but no further fall after that.
Experiment 7.3: Stock Market Crash in 2011:3
- Drop equation 25, and change the value of CG in 2011:3 by -8000.
Solve the model
for the forecast period (beginning in 2011:3).
- How did the crash affect household net wealth, AA? How did
households respond to
this change in AA regarding consumption and
labor supply? (Note that
there is a lag of one quarter in the effects of AA on household
- What roughly was the fall in consumption per year as a
percent of the fall in AA? Does this percent seem reasonable?
- How did the Fed respond to the crash?
- What is roughly the loss of real GNP per year as a result of the
- This experiment is important in that it shows that a crash
of this size may result in a recession, but not a depression.