Descripción del plan de estudios

To summarize the business cycle facts discussed above, we present Tables 3.1 and 3.2. These two tables, particularly Table 3.2, prove very useful, particularly when we discuss the predictions of different theories of the business cycle in Chapters 13 and 14. A first test of the usefulness of macroeconomic theories is their ability to match what we see in macroeconomic data.

We have concluded our study of measurement issues, in that we now know the basics of national income accounting, basic macroeconomic accounting identities, price measurement, labor market facts, and business cycle facts. In the next chapters, we pro-ceed to build useful macroeconomic models, starting with some basic microeconomic principles concerning the behavior of consumers and firms.

Table 3.1 Correlation Coefficients and Variability of Percentage Deviations from Trend

Correlation Coefficient

Standard Deviation (% of S.D. of GDP)

Consumption 0.78 76.6

Investment 0.85 489.9

Price Level -0.19 56.3

Money Supply 0.20 81.0

Employment 0.80 63.0

Average Labor Productivity 0.80 62.4

Table 3.2 Summary of Business Cycle Facts

Variation Cyclicality Lead/Lag Relative to GDP

Consumption Procyclical Coincident Smaller

Investment Procyclical Coincident Larger

Price Level Countercyclical Coincident Smaller

Money Supply Procyclical Leading Smaller

Employment Procyclical Lagging Smaller

Real Wage Procyclical ? ?

Average Labor Productivity Procyclical Coincident Smaller

Chapter Summary

• The key business cycle facts relate to the deviations of important macroeconomic variables from their trends and the comovements in these deviations from trend.

• The most important business cycle fact is that real GDP fluctuates about trend in an irreg-ular fashion. Though deviations from trend in real GDP are persistent, there is no observed regularity in the amplitude or frequency of fluctuations in real GDP about trend.

• Business cycles are similar mainly in terms of the comovements among macroeconomic time series. Comovement can be discerned by plotting the percentage deviations from trend in two economic variables in a time series or in a scatter plot or by calculating the correlation coefficient between the percentage deviations from trend.

• We are interested principally in how a particular variable moves about trend relative to real GDP (whether it is procyclical, countercyclical, or acyclical), whether it is a leading, lagging, or coincident variable (relative to real GDP), and how variable it is relative to real GDP.

• Consumption is procyclical, coincident, and less variable than real GDP.

• Investment is procyclical, coincident, and more variable than real GDP.

• In the data set we examined here, the price level is a countercyclical variable (there is a reverse Phillips curve), it is coincident, and it is less variable than GDP.

• The money supply is procyclical, leading, and about as variable as real GDP. The fact that the money supply tends to lead real GDP was assigned much importance by Milton Friedman.

• In the labor market, employment is procyclical, lagging, and less variable than real GDP. The real wage, too, is procyclical. There is, however, no consensus among macroeconomists on whether the real wage is a leading or lagging variable. Average labor productivity is procyclical, coincident, and less variable than real GDP.

• Many macroeconomic time series used in economic analysis are seasonally adjusted. Seasonal adjustment takes out the predictable seasonal component, for example the effect of extra spending over the December holiday season on the money supply.

Key Terms

Business cycles Fluctuations about trend in real GDP. (p. 68)

Peak A relatively large positive deviation from trend in real GDP. (p. 68)

Trough A relatively large negative deviation from trend in real GDP. (p. 68)

Turning points Peaks and troughs in real GDP.

(p. 68)

Amplitude The maximum deviation from trend in an economic time series. (p. 69)

Frequency The number of peaks in an economic time series that occur per year. (p. 69)

Boom A series of positive deviations from trend in real GDP, culminating in a peak. (p. 69)

Recession A series of negative deviations from trend in real GDP, culminating in a trough. (p. 69)

Persistent Describes an economic time series that tends to stay above (below) trend when it has been above (below) trend during the recent past. (p. 69) Comovement How aggregate economic variables move together over the business cycle. (p. 72) Time series Sequential measurements of an eco-nomic variable over time. (p. 72)

Positive correlation Relationship between two eco-nomic time series when a straight line fit to a scatter plot of the two variables has a positive slope. (p. 73) Negative correlation Relationship between two eco-nomic time series when a straight line fit to a scatter plot of the two variables has a negative slope. (p. 73)

Scatter plot A plot of two variables, x and y, with x measured on the horizontal axis and y measured on the vertical axis. (p. 73)

Procyclical Describes an economic variable that tends to be above (below) trend when real GDP is above (below) trend. (p. 73)

Countercyclical Describes an economic variable that tends to be below (above) trend when real GDP is above (below) trend. (p. 73)

Acyclical Describes an economic variable that is nei-ther procyclical nor countercyclical. (p. 73)

Correlation coefficient A measure of the degree of correlation between two variables. (p. 74)

Perfectly positively correlated Describes two vari-ables that have a correlation coefficient of 1.

(p. 74)

Perfectly negatively correlated Describes two vari-ables that have a correlation coefficient of -1.

(p. 74)

Leading variable An economic variable that helps to predict future real GDP. (p. 75)

Lagging variable An economic variable that past real GDP helps to predict. (p. 75)

Coincident variable An economic variable that nei-ther leads nor lags real GDP. (p. 75)

Standard deviation A measure of variability. The cyclical variability in an economic time series can be measured by the standard deviation of the percentage deviations from trend. (p. 78)

Phillips curve A positive correlation between a money price or the rate of change in a money price and a measure of aggregate economic activity. (p. 81) Reverse Phillips curve A negative correlation bet-ween a money price or the rate of change in a money price and a measure of aggregate economic activity.

(p. 81)

Real wage The purchasing power of the wage earned per hour worked. (p. 85)

Average labor productivity Equal to Y/N where Y is aggregate output and N is total labor input. (p. 87) Seasonal adjustment The statistical process of re-moving the predictable seasonal component from an economic time series. (p. 88)

Questions for Review

1. What is the primary defining feature of business cycles?

2. Besides persistence, what are three important features of the deviations from trend in GDP?

3. Explain why forecasting GDP over the long term is difficult.

4. Why are the comovements in aggregate economic variables important?

5. What did Robert Lucas say about the comovements among economic variables?

6. How can we discern positive and negative correlation in a time series plot? In a scatter plot?

7. Give a noneconomic example of two variables that are positively correlated and an example of two variables that are negatively correlated.

8. Why is the index of leading economic indicators useful for forecasting GDP?

9. What are the three features of comovement that macroeconomists are interested in?

10. Describe the key business cycle regularities in consumption and investment expenditures.

11. What are the key business cycle regularities with respect to the price level and the money supply?

12. Does a Phillips curve relationship exist in the data set that was studied in this chapter?

13. What are the key business cycle regularities in the labor market?

Problems

1. In Figure 3.13, if we had only the data from 1980 to 2012 to go on, what would we conclude about the relationship between the nominal money sup-ply and real GDP? Explain the significance of this.

2. Average labor productivity tends to be a coin-cident variable. Examine Figure 3.16 carefully.

During the 1991–1992, 2001, and 2008–2009 recessions, how do you observe average labor productivity behaving relative to GDP? Comment on this, and explain what this has to do with the Macroeconomics in Action box on jobless recoveries.

3. Consumption of durables is more variable rela-tive to trend than is consumption of nondurables, and consumption of nondurables is more variable

relative to trend than is consumption of services.

Speculate on why we observe these phenomena, and relate this to the key business cycle facts in Tables 3.1 and 3.2.

4. In Figure 3.12, after the 1981–1982 recession, does the price level appear to be procyclical, countercylical, or acyclical? Why is this impor-tant?

5. The Great Moderation in part refers to the moder-ate variability in real GDP that occurred after the 1981–1982 recession and before the 2008–2009 recession. In Figure 3.12, what do you observe about the behavior of the deviations from tend in the price level over the period 1947–2007?

Relate this to the Great Moderation experience, and discuss.

Working with the Data

Answer these questions using the Federal Reserve Bank of St. Louis’s FRED database, accessible at http://research.stlouisfed.org/fred2/

1. Calculate the 12-month percentage increase in the consumer price index (CPI), and plot this, along with the unemployment rate. Do you observe a positive correlation, a negative correlation, or a correlation that is essentially zero? Can you find a Phillips curve relation or a reverse Phillips curve?

2. The index of industrial production is an output measure that is not as comprehensive as GDP, but it is available on a more timely basis (monthly rather than quarterly). Calculate the percentage 12-month growth rates in the index of industrial production and in the money supply, and graph these.

(a) Are growth in industrial production and in the money supply positively correlated or negatively correlated?

(b) Does one time series lead the other, or are they coincident?

(c) Are your answers to (a) and (b) consistent with what we observe in Figure 3.13?

Explain.

3. Calculate the percentage rates of increase in real GDP, consumption of durables, consump-tion of nondurables, and consumpconsump-tion of services, and plot these.

(a) What do you notice in these plots compared to the information in Figures 3.9 and 3.10?

(b) Provide an explanation for your observations in part (a).

4. Calculate and graph the ratio of: (i) real residential investment to real GDP; (ii) real nonresidential investment to real GDP; and (iii) real inventory investment to real GDP.

(a) Which of the components of investment shows the most (least) variability, in terms of its contribution to the variability in real GDP?

(b) Provide possible explanations for the patterns you detected in part (a).

PART II

A One-Period Model