Précis
Productivity
Boom?
Young
workers and unemployment rates
Inequality
In the "golden age of productivity"—between 1948 and 1973—labor productivity in the U.S. nonfarm business sector grew by nearly 3 percent per year. In the following two decades, labor productivity growth plodded along at an average annual rate of about 1 percent.
However, there were signs of improvement in the 1990s; labor productivity—measured by output per hour—rose by 2.5 percent in 1996 and 2.3 percent in 1998. In a recent issue of Economic Commentary from the Federal Reserve Bank of Cleveland, Paul W. Bauer, an economic advisor at the bank, wonders if a boom in productivity is occurring.
In "Are We in a Productivity Boom? Evidence from Multifactor Productivity Growth," Bauer looks at two types of productivity measures published by BLS: labor productivity, a well-known measure, and multifactor productivity (MFP), which is less widely known. One reason that MFP is not better known is that MFP series are only available annually, unlike the labor productivity measures, which come out quarterly. Another reason is that MFP is a more complex concept than labor productivity—whereas labor productivity relates output to just one input, labor, MFP relates output to combined inputs, such as capital and labor. MFP is considered to be a better measure of technical change than labor productivity, because it takes more inputs into account.
Using BLS productivity series, Bauer notes that while both labor and multifactor productivity growth in nonfarm business rebounded in recent years, the growth rates were still below those of the golden age. Manufacturing, on the other hand, attained rates of labor and multifactor productivity growth in the 1990s that exceeded their golden-age counterparts.
Young workers and unemployment rates
What happens to a labor market when the proportion of young workers in the market rises? Considering that the entrance of baby-boomers into labor markets in the 1970s coincided with higher unemployment rates, it might seem that an influx of young workers drives up unemployment. But a time series analysis of this type can be problematic, in part because simultaneous macroeconomic fluctuations can affect unemployment rates.
To get around such problems, Robert Shimer of Princeton University turned to State data. In "The Impact of Young Workers on the Aggregate Labor Market" (NBER Working Paper 7306), he analyzed data on unemployment rates and the age structure of the workforce for all 50 States and the District of Columbia, from 1978 to 1996. For the study, young workers were defined as those who were 16 to 24 years old.
Perhaps surprisingly, Shimer found that a 1-percent increase in the youth share of the labor market in a State reduced the unemployment rate of young workers by more than 1 percent (holding constant conditions in other States). In addition, a 1-percent rise in the youth share led to a reduction in the unemployment rate of older workers of more than 2 percent.
Shimer attributed these results to increasing returns to scale in the labor market. This could occur because young workers often are mismatched in their employment and firms may create jobs in order to take advantage of this, which could lower the unemployment rate.
The past few months yielded a bumper crop of research on inequality. In the December 1999 American Economic Review, Daron Acemoglu in "Changes in Unemployment and Wage Inequality: An Alternative Theory and Some Evidence," proposes a supply-driven theoretical approach to understanding inequality. In his model, when there are relatively few skilled workers available and the difference in productivity between skilled and unskilled labor is relatively low, firms will create one kind of "middling" job and staff it with either kind of worker.
If, however the supply of skilled labor increases or the productivity gap widens, there can be a qualitative change in the composition of jobs. Specifically, the nature of the equilibrium changes from the "pooling" solution to an equilibrium in which employers separate their jobs into higher and lower quality positions. This qualitative shift theoretically reduces the unskilled wages, increases the earnings of the skilled, and increases unemployment rates for both.
In a December 1999 Journal of Economic Literature survey article, "Inequality and Economic Growth: The Perspective of the New Growth Theories," Philippe Aghion, Eve Caroli, and Cecilia Garcia-Penalosa use a variant of this position. They write, "Once skill-biased technical change is taken into account, ex-post inequality may actually be increased by rising educational levels. In the case of disembodied technical change, education does narrow the differential between skilled and unskilled workers and has therefore the direct effect of reducing wage inequality. However, increasing the supply of skills has a counteracting impact on wage inequality because it is itself a cause of skill-biased technical change."
A third contribution was a conference on "The Macrodynamics of Inequality in the Industrialized and Developing Countries" sponsored by the Jerome Levy Economics Institute. In the keynote address, as summarized in The Levy Institute’s Report for November 1999, James K. Galbraith observed that because most economists look at distribution as a microeconomic question, it is especially important to broaden the approach to include important macroeconomic questions as well. The conference sessions attempt, as does the survey by Aghion, Caroli, and Garcia-Penalosa, to examine the macroeconomic implications of inequality and vice versa.
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