Many reasons for the Great Moderation - the substantial decline in economic volatility and inflation in the mid 1980s - have been given, including better technology (e.g. information processing allowing better inventory control and management), better policy (e.g. inflation targeting), a run of good luck where no big shocks hit the economy, and financial innovation and deregulation.
The paper discussed in this article from the Minneapolis Fed proposes another reason for the Great Moderation, demographic changes, and finds changes in the demographic composition of the labor force can account for around one fifth to one third of the decline in output variability:
Demographics and Economic Volatility, by Douglas Clement, Editor, The Region, Minneapolis Fed: In 2004, then Fed Governor Ben Bernanke addressed the “Great Moderation”—the remarkable decline in economic volatility observed in the United States and other advanced economies over the past two or three decades. He reviewed evidence for three explanations: structural change, good luck and improved policy, and then he focused on the last: the role that better monetary policy has played, particularly in the United States...
In a recent paper, ... Henry Siu of the University of British Columbia and Nir Jaimovich of Stanford University develop a new theory to help explain the Great Moderation in not only the United States but other industrialized economies. “Specifically,” write Jaimovich and Siu, “we find that changes in the age composition of the workforce account for a significant fraction of the variation in business cycle volatility.”
In “The Young, the Old and the Restless: Demographics and Business Cycle Volatility” (Federal Reserve Bank of Minneapolis Staff Report 387), the economists begin by documenting age variations in labor market volatility. The task is easiest in the United States and Japan, which compile data on average hours worked by different demographic groups. Both nations, they find, display profound differences across age groups.
In the United States, the young exhibit far greater fluctuation in hours worked per capita than the middle-aged; those at or close to retirement fall somewhere between. By one statistical measure, employment fluctuation for workers 15 to 19 years old is over five times that for those 40 to 49 years old. So while teenagers account for just 3 percent of total employment, they account for 11 percent of employment volatility. And the volatility of workers 65 years and older is about twice that of those 40 to 49 years old—not as volatile as teens but still quite high.
The relationship is similar in Japan. “As in the U.S.,” they write, “there is a distinct U-shaped pattern to ... volatility of hours worked as a function of age.”
For the other G7 members—Canada, France, Germany, Italy and the United Kingdom—the economists look at employment rates since age-specific data on hours worked aren't available. While the nations vary, each strongly displays the same relationship: Younger and older workers have far more labor market volatility than the middle-aged. Averaged across the seven countries, employment volatility “for 15-19 year olds is nearly six times greater than that of 40-49 year olds,” conclude Jaimovich and Siu. “Similarly, the average employment volatility of 60-64 year olds is about three times greater than that of 40-49 year olds.”
This pattern is remarkable, they note, given the significant dissimilarities among these nations. “That these economies differ greatly in terms of industry composition and the degree of labor market regulation makes this finding all the more striking [which suggests] that the age composition of the labor force is potentially a key determinant of the responsiveness of an economy to business cycle shocks.”
Having established a similarity among G7 countries—in all seven, the young and old have higher employment fluctuations than the middle-aged—the economists take the next step: examining cross-country differences in the extent and timing of demographic change. These differences are crucial to their strategy for discerning the relationship between demographics and business cycles.
In the United States and Canada, post-World War II baby booms led to a large cohort of “20-something” workers in the 1970s and a subsequent boom in “prime-aged” workers beginning in 1990 or so. But France, Italy and Germany had far smaller baby booms, and the labor force has gradually aged. The United Kingdom fell between those extremes, while Japan experienced a strong decline in fertility after World War II, resulting in an increasing share of workers over 60 years, especially since 1980.
The economists exploit these differences in demographic trends to determine the impact of labor force age composition on economic volatility. After all, a simple correlation in a specific country between trends in economic volatility and shares of the labor force made up by young workers could be mere coincidence, they note. ... But finding the demography/volatility correlation in several countries—which face the same oil prices, but very different demographic patterns—“strongly suggests that the correlation is not spurious.”
Their graphs provide a striking picture. (See charts below.) In six of the seven G7 countries, the economists observe, “business cycle volatility and the volatile labor force share clearly co-vary.” The relationship is weaker in France, they admit, “but relative to the other countries, there is little change in volatility to explain.”
To measure the degree to which age distribution impacts volatility, the economists use regression analysis, a statistical technique that gauges how much different factors influence a specific outcome. (Regression equations might be used, for instance, to estimate the impact of higher teacher salaries on student test scores, holding other factors constant.) In this case, the economists input data from the seven countries over a span of several decades and, in a “first cut” estimate, find that a 10 percent increase in the volatile share of the labor force (15-19 year olds plus 60-64 year olds) would increase economic volatility by 0.402.*
After experimenting with various age-group definitions and statistical refinements, and expanding the analysis to the entire age distribution rather than simply the “volatile” share, they estimate a slightly stronger impact: A 10 percent labor force shift into the most stable age group (40-49 years) will decrease volatility by 0.406.
So, if this estimate were applied to the United States and the Great Moderation that Bernanke discussed, how much of this moderation might demographic change explain? ..
During [the 1978 to 1999]... time span, Jaimovich and Siu point out, the volatile share of the labor force dropped from 38.5 percent to 27.1 percent, an 11.4 point reduction. According to their regression estimates, "such a shift in workforce composition ... predicts a volatility reduction [of] ... roughly 32 percent ... of total macroeconomic moderation between 1978 and 1999.
Using a different statistical method for measuring the impact of age shifts, the economists generate a more modest estimate, about 21 percent. Still, it's in the same ballpark. “That the results ... are similar in magnitude ... we take as evidence for an important role for demographics in explaining the Great Moderation.”
Business cycle models
The final step in this ambitious paper is to build a mathematical model that can analyze the relationship between differences in labor force age volatility and trends in general economic volatility. The economists take a standard “real business cycle” model and modify it accordingly. ...
The economists refine the model and run it, generating simulated figures for labor and output for the United States between 1968 and 2004. The simulations do a good job of matching real data over that time span...
In other words, their model, their regression analysis and their other estimation techniques all arrive at the same robust conclusion: “Variation in the age composition of aggregate hours accounts for a significant fraction of the moderation in U.S. business cycle volatility.”