Federal Reserve Bank of San Francisco
Publications

FRBSF Economic Letter

1996-34 | November 15, 1996

More Economic Letters

Capacity Utilization and Structural Change

Joe Mattey

The Federal Reserve Board’s measures of capacity utilization for the U.S. manufacturing sector have been a useful indicator of inflationary pressures. However, some observers have claimed that the relationship between capacity utilization and inflation has broken down recently, owing to increased international trade, a shift in the share of the nation’s workforce in service-producing industries, and rapid technological change. This Economic Letter, which draws on Corrado and Mattey (1997), reviews the evidence for this claim and finds it largely unsupported by the facts. Although there have been some structural changes in the U.S. economy, the basic indicator value of capacity utilization for inflation has endured.

What is capacity utilization?

Capacity utilization for an individual manufacturing plant is the ratio of the plant’s actual output level to its potential or capacity output level. Capacity output is a measure of the extent to which the manufacturing plant can produce goods, given its current technology and fixed factors of production (such as the capital stock).

The Federal Reserve publishes monthly indices of capacity utilization for a wide range of manufacturing industries. Each industry utilization rate is the ratio of an industrial production index to a related index of capacity output. Short-run movements in industrial production are the primary source of changes in utilization rates, but the Fed utilization measures also reflect the year-to-year evolution of capacity.

The primary source of information on capacity changes is the Census Bureau’s Survey of Plant Capacity. The survey method has the advantage of allowing respondents to incorporate in their estimates a broad range of capacity determinants, such as technological changes.

Capacity utilization and inflation

There are some microeconomic underpinnings to the aggregate relation between overall capacity utilization and inflation. With a perfectly competitive market structure, an increase in capacity utilization at a manufacturing plant will tend to be associated with an increase in its output price, assuming that output is increasing because the demand curve has shifted outward along an upward-sloping supply (marginal cost) curve. However, evidence from micro-data has neither been able to confirm nor refute such a structural interpretation of the relationship between capacity utilization and price changes.

On the other hand, evidence from macro-data does provide support to the idea that increases in aggregate demand increase inflationary pressures. In macroeconomic models, the relationship between resource utilization and inflation generally is embodied in multiple equations. For example, in a two-equation wage-price subsystem, a (Phillips-curve) wage equation may relate the excess of wage inflation over expected price inflation to the unemployment rate, and a (markup) price equation may relate the excess of price inflation over wage inflation to capacity utilization or another measure of product market slack, such as the gap between actual and potential GDP. If capacity utilization is made to do the double-duty of reflecting both product and labor market slack, the two equations can be combined into a single reduced-form price equation with a single measure of resource utilization as an explanatory variable. Note, however, that well-specified models of inflation also will include many other explanatory factors.

In other words, even the most basic macroeconomic model does not suggest that overall inflation should be highly correlated with capacity utilization without controlling for other factors. Indeed, the correlation between the level of inflation and utilization is weak, reflecting the important role of long-term monetary policy influences, short-run food and energy price shocks, and other inflation determinants which belong in fully specified models of inflation in addition to measures of resource utilization.

Lagged inflation rates can be used to proxy some of the longer-run determinants of the underlying inflation rate, such as long-term monetary policy effects. In fact, statistical analysis reveals that last year’s inflation rate is a decent approximation to these longer-term inflation influences. Accordingly, capacity utilization is related more strongly to the acceleration of inflation than to the level of inflation. Also, to keep matters simple, most of the effects of food and energy price shocks can be controlled for by focusing on the acceleration in the core measure of the CPI, which excludes the prices of food and energy items. As illustrated in Figure 1, capacity utilization has a relatively strong correlation with the acceleration of core consumer price inflation.

Relation to (un)employment

Though only directly measuring the relative level of activity in the industrial sector, capacity utilization also tends to reflect the state of the broader economy. This shows up in a high correlation between capacity utilization and the jobless rate. Figure 2 shows standardized (mean zero, unit variance) measures of the percent of the labor force employed (that is, 100 minus the unemployment rate) and manufacturing capacity utilization. Much of the time, both measures convey the same qualitative signal about the extent of resource utilization.

However, capacity utilization has the advantage of being somewhat more stable than other commonly used cyclical indicators of inflationary pressures. Note that the (un)employment rate has experienced more persistent deviations from its mean than has capacity utilization. For example, in each of the thirteen years from 1975 to 1987, the unemployment rate remained above its 5-3/4 percent post-war mean. Yet, inflation did not decelerate throughout this period; rather, it accelerated sharply in the late 1970s when capacity utilization rose well above its 82 percent post-war mean. Unless the estimates of the non-accelerating inflation rate of unemployment (NAIRU) are allowed to vary over time, capacity utilization retains a slight advantage over the unemployment rate as a simple predictor of the acceleration of inflation. This slight advantage of capacity utilization reflects the long-run stationarity of capacity utilization. That is, capacity utilization tends to return to the same mean level over time, while the trend unemployment rate and the estimates of the rate of unemployment consistent with stable inflation tend to change.

Based essentially on the simple relationship shown in Figure 1, many researchers have found that for each percentage point capacity utilization exceeds 82 percent, inflation tends to accelerate by about 0.15 percentage points. Although the 82 percent figure for the non-accelerating inflation rate of capacity utilization is estimated imprecisely, with a 95 percent confidence interval that ranges from about 78-1/2 to 83-1/2 percent of capacity, similarly wide confidence intervals must be attached to estimates of the non-accelerating inflation rate of unemployment.

Recent evidence

The relative stability, but somewhat imprecise nature, of the relationship between capacity utilization and inflation acceleration can be seen in the most recent historical experience. Capacity utilization peaked at about 84-1/2 percent at the end of 1994, in the range typically associated with a slight acceleration of core inflation. Although core inflation slowed a bit that year, the prediction error was not large, relative to the historical fit of the simple relationship between capacity utilization and inflation acceleration. In 1995, capacity utilization edged down to an operating rate more clearly consistent with neutrality of inflation pressures, and core inflation was little changed. In the first eight months of 1996, manufacturing capacity utilization averaged 82 percent, which is neutral with respect to inflationary pressures. Although core inflation did slow about 1/2 percentage point at an annual rate in the first eight months of 1996, a prediction error of this size or larger is relatively common in a stripped down model which relates core inflation acceleration only to the level of manufacturing capacity utilization. As indicated above, the simple relationship between capacity utilization and the acceleration of core inflation is relatively imprecise, so the events of 1996 are not necessarily evidence of recent instability.

Structural change and capacity utilization as an indicator of inflation

The relative stability of capacity utilization as an inflation indicator spans an era of large structural changes in the U.S. economy. This finding runs counter to some observers who suggest that “globalization,” the shift of employment to the services sector, and rapid technological change should have altered the relationship substantially. For example, with the significant expansion of international trade over the past 35 years, some commentators have opined that goods prices are now set in international markets—thus a measure of the domestic capacity to produce is no longer useful as an inflation indicator. That logic leads them to the conclusion that, in monitoring inflation, global resource utilization measures be substituted for domestic capacity utilization.

However, the increased openness of the U.S. economy has not diminished the usefulness of domestic capacity utilization for predicting inflation. For one, although foreign penetration of domestic markets has grown substantially, the proportions are still fairly small for most industries. Second, although slack capacity abroad will lower local currency prices of foreign goods and help slow foreign inflation, other factors—changes in the exchange rate and the extent to which changes in foreign prices are passed through to prices of goods supplied to the U.S. market–also influence the dollar price of U.S. imports.

Furthermore, despite the relatively increased importance of the domestic service sector in recent decades, the predictive power of factory operating rates for inflation has endured for a couple of reasons. First, capacity utilization in manufacturing is indicative of the cyclical state of overall aggregate demand. Fluctuations in the goods and structures component of GDP account for most of the variation in total output. Moreover, changes in factory output are highly correlated with changes in this segment of final demand. Second, capacity utilization is a correlate of cyclical activity in labor markets. This correlation exists largely because most of the economy’s cyclical employment adjustments occur in the sectors facing variable aggregate demand, the sectors producing goods and structures, not services.

Finally, recent technological changes have not diminished the usefulness of capacity utilization for predicting inflation. In this regard, the critical question concerning the reliability of the FRB capacity indexes is whether the productivity gains from the adoption of advanced technologies, such as flexible manufacturing techniques, are adequately captured in the survey-based estimates of capacity. Studies of the individual survey responses on why capacity has changed suggest that investments in flexible technologies and the like are recorded by respondents as increases in capacity (Mattey and Strongin 1995). The productivity gains that result from their use appear in both the numerator and denominator of utilization measures.

In sum, recent changes in the structure of the U.S. economy do not appear to have altered the basic relationship between capacity utilization and inflation.

Joe Mattey
Senior Economist

References

Corrado, C., and J. Mattey. 1997. “Capacity Utilization.” Journal of Economic Perspectives. Forthcoming, Winter.

Mattey, J., and S. Strongin. 1995. “Factor Utilization and Margins of Output Adjustment.” Federal Reserve Board FEDS Discussion Paper 95-12, March.

Opinions expressed in FRBSF Economic Letter do not necessarily reflect the views of the management of the Federal Reserve Bank of San Francisco or of the Board of Governors of the Federal Reserve System. This publication is edited by Sam Zuckerman and Anita Todd. Permission to reprint must be obtained in writing.

Please send editorial comments and requests for reprint permission to
Research Library
Attn: Research publications, MS 1140
Federal Reserve Bank of San Francisco
P.O. Box 7702
San Francisco, CA 94120