7. Price Shocks and Stock Market Shocks 7.1 Price Shocks The key exogenous variable regarding the behavior of prices is the price of 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 large. Experiment 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. Solve the model. 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 household saving rate? To corporate profits in nominal terms (PIEF)? To corporate profits in real terms (PIEF/PF)? The model attributes much of the stagflation of the 1970's to the huge increase in PIM that occurred during this period. This can be seen in the following experiment. (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 1974:1-1978:4 period. 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 that the model makes in predicting the 1974:1-1978:4 period. How does the model do for this hard to forecast period? 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 unemployment 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. 7.2 Stock Market Shocks Almost everyone knows the stock market crashed in October of 1987. After the 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 quarter.) Although 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. We will 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 behavior.) 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 crash? This experiment is important in that it shows that a crash of this size may result in a recession, but not a depression.