Measures Of Capacity Utilization Research Articles

Capacity utilization rates and unemployment rates: are they complements or substitutes in warning about future inflation?

This research examines capacity utilization as a measure of economic slack in the US economy. Many macroeconomists have questioned the use of capacity utilization as a measure of economics slack on several fronts. The first issue revolves around the definition and accuracy of measurement of the capacity utilization rate in the US economy. Since this research uses existing Federal Reserve measures of capacity utilization, no insights into the definition and measurement issues are offered other than the fact that a consistent role was found for two different Fed measures of capacity utilization in explaining inflation. The second issue effectively involves the concern as to robustness of the link between the capacity utilization rate and inflation. There is indeed reason for the Federal Reserve to take note of changes in capacity utilization when trying to determine its policy position with regard to inflation. Clearly, the high capacity measure developed in this research offers distinct information about the inflation process. The third issue raises the question as to whether the capacity utilization and unemployment rates are complements or substitutes in the inflation equation. Both rates tend to provide similar information regarding price changes at low levels of aggregate resource usage. However, as resource usage in the economy becomes increasingly close to its maximum potential, the labour market impact on inflation, as capture by unemployment rate measures, is distinctly different from that of capacity constraints. Finally, if the capacity utilization rate is indeed a useful measure of inflationary pressure, is there a threshold level of the capacity utilization rate above which policymakers should become particularly concerned about the potential of accelerating inflation? Across two measures of inflation, the widely discussed capacity threshold level is in the 84-85% range.

Multi‐Output Capacity Measures and Their Relevance for Productivity

In this paper, measures of capacity are developed following those suggested in 1968 by Leif Johansen. By taking advantage of Shephard’s duality, both primal and dual multi‐output measures of capacity can be derived. Having generalized the capacity utilization measures, the authors show how these may be entered into measures of productivity. In particular, it is shown how the Malmquist direct and indirect productivity measures are related to various measures of capacity utilization.

Industrial Production and Capacity Utilization: Recent Developments and the 1999 Revision

In late 1999, the Federal Reserve published revised measures of industrial production, capacity, and capacity utilization for the period January 1992 through October 1 999. The updated measures reflect both the incorporation of newly available, more comprehensive source data typical of annual revisions and the introduction of improved methods for compiling a few series, including computer and office equipment and motor vehicles. The new source data are for recent years, primarily from 1997 on, and the modified methods affect data beginning in 1992. The production index for the third quarter of 1999 is at 137.7 percent of output in 1992, compared with 135.2 percent reported before the annual revision, and the capacity index is 170.7 percent of output in 1992, compared with 167.9 percent reported previously. As a result, the rate of industrial capacity utilization was revised up 0.1 percentage point, to 80.7 percent for the third quarter of 1999.

Industrial Production and Capacity Utilization: 1998 Annual Revision

In late 1998, the Federal Reserve published the results of an annual revision of its measures of industrial production, capacity, and capacity utilization, which cover the nation's manufacturing, mining, and electric and gas utilities industries. The revision involved both the incorporation of newly available and more comprehensive source data and, for some series, the introduction of modified methods for compiling the series. The revised figures show stronger growth of both production and capacity since 1996; however, the overall capacity utilization rate was little changed from the previous data.

Economic Capacity Utilization and its Determinants: Theory and Evidence

This paper develops and estimates a model of economic capacity utilization and its determinants by allowing for the firm's full optimization behavior that considers endogenous output choice. The model consists of deriving the short-run output supply function and the capital demand function which generate optimal and capacity output. Optimal capacity utilization is determined as the ratio of optimal to capacity output and its determinants are identified. Evidence from U.S. manufacturing shows that capital expansion not accompanied by market growth and higher materials and capital prices has contributed to lower capacity utilization. Energy price increases have exerted a stimulating impact on capacity utilization. Conventional capacity utilization measures are found to be biased and fail to capture the influences of changes in economic conditions facing firms.

Excess capacity: a permanent characteristic of US airlines?

This paper examines the permanence of excess capacity in the US airline industry. To avoid the problems with the standard engineering measure of capacity utilization, load factor, we define and measure capacity as an economic concept. Two measures of economic capacity utilization are then computed—one, a demand-based measure and the other an output-based measure of capacity utilization. Both measures share little in common with the standard engineering measure (load factor) and reveal some interesting attributes of airline travel demand. This paper also provides interesting new insights into the role of deregulation and the costs of excess capacity during regulation. Specifically, it is found that deregulation with the concomitant rationalization of route structures enabled airlines to move closer to their optimal levels of capacity and facilitated substantial improvements in capacity utilization and cost reductions over the period considered. © 1998 John Wiley & Sons, Ltd.

Excess capacity: a permanent characteristic of US airlines?

This paper examines the permanence of excess capacity in the US airline industry. To avoid the problems with the standard engineering measure of capacity utilization, load factor, we define and measure capacity as an economic concept. Two measures of economic capacity utilization are then computed—one, a demand-based measure and the other an output-based measure of capacity utilization. Both measures share little in common with the standard engineering measure (load factor) and reveal some interesting attributes of airline travel demand. This paper also provides interesting new insights into the role of deregulation and the costs of excess capacity during regulation. Specifically, it is found that deregulation with the concomitant rationalization of route structures enabled airlines to move closer to their optimal levels of capacity and facilitated substantial improvements in capacity utilization and cost reductions over the period considered. © 1998 John Wiley & Sons, Ltd.

Industrial Production and Capacity Utilization: Annual Revision and 1997 Developments

In December 1997, the Board of Governors published the results of an annual revision of its measures of industrial production and capacity utilization, which cover the nation's manufacturing, mining, and electric and gas utilities industries. The revision entailed primarily the incorporation of new and more comprehensive source data, the most important of which were annual figures on industry real output in 1995 and survey information on industry utilization rates for the fourth quarters of 1995 and 1996. The revised measures show stronger growth of production and capacity and lower rates of capacity utilization since 1992 than did earlier estimates. The revised production indexes and the new source data on utilization rates implied that manufacturing capacity growth was stronger than previously estimated.

Regional Measures of Capacity Utilization in the 1980s

This paper presents a model to estimate the rate of capacity utilization (CU) in the manufacturing sector by state. Consistent measures of state-level CU rates have been unavailable since 1982. The lack of a capacity measure has hindered regional studies of capital formation, long-run output growth, and productivity growth. Our model employs a neoclassical approach to estimate CU. We estimate a model to determine the optimal level of production and compare it with the actual level in order to define our CU index. Our results show that states in the West North Central, South Atlantic, and Pacific census divisions tend to have a CU index consistently above the nation's average. On the other hand, states in the East North Central and West South Central census divisions tend to have a CU index below the nation's average.

Industrial Production and Capacity Utilization: Historical Revision and Recent Developments

The Board of Governors of the Federal Reserve System has completed a revision of its measures of output, capacity, and capacity utilization for the industrial sector. The primary feature of the revision is a new formulation for aggregating the indexes and utilization rates based on weights that are updated annually rather than every five years. The new formulation has been used to revise the output, capacity, and utilization rates back to 1977. It provides more accurate current estimates of developments in industrial production and capacity utilization and eliminates an earlier, small overstatement of the growth trends of production and capacity. The revised indexes of industrial production and capacity show slower growth, on average, than the earlier estimates while the cyclical patterns of the revised measures are practically the same as before. Both from 1977 to 1987 and from 1987 to 1996, total industrial output grew at an average pace of about 2.3 percent a year--about 1/4 percentage point less than previously estimated. The growth of industrial capacity was revised down nearly as much; consequently, the rate of total industrial capacity utilization was revised down only a fraction of a percentage point at the end of 1996. (Statistical Release G.17, "Industrial Production and Capacity Utilization.")

Capacity utilization under dynamic profit maximization

Empirically implementable measures of optimal capacity utilization are developed from the dynamic profit maximization perspective. The primal measure is based on behavior of the firm's supply along an optimal path to the steady state. The dual measure is based on the behavior of the dynamic value function in the stock of the quasi-fixed input. Rates of optimal capacity utilization are estimated for the U.S. food processing and distribution sector over the period 1948–1991.

Endogenous capital utilization and productivity measurement in dynamic factor demand models Theory and an application to the U.S. electrical machinery industry

The literature on dynamic factor demand models has, until recently, largely overlooked the issue of capital utilization. In this paper we allow for variations in the rate of capital utilization within the context of a dynamic factor demand model by adopting a modeling framework within which the firm combines its beginning-of-period stocks with other inputs to produce its outputs as well as its end-of-period stocks. We also define measures of productivity and capacity utilization for the adopted framework. As a by-product, the framework also provides for a consistent decomposition of gross investment into replacement and expansion investment. As an illustration, the model is applied to U.S. electrical machinery data.

Comparative performance of short-run capacity utilization measures

We present parametric estimates for primal and dual capacity utilization and then evaluate their comparative performance. Empirical findings indicate that alternative capacity utilization ratios, depending upon the reference variables, are procyclically consistent with each other.

MEASUREMENT OF CAPACITY UTILIZATION FOR REVENUE‐MAXIMIZING FIRMS*

ABSTRACTA dual measure of capacity utilization is developed for multiproduct, revenue‐maximizing firms. Under the assumption of revenue maximization, the sensitivity of CU to a change in an individual product price is shown to be directly related to the product‐specific scale elasticity. The results are given a simple graphical interpretation.

Capacity Utilization and Prices Within Industries

tt%tjtthe strength of the economic expansion ~II during the past two years has renewed I fears of accelerating inflation. As these fears have grown, people have turned to various statistics to substantiate any signs of rising inflation. Commodity prices, wages, sales-to-inventory ratios, civilian unemployment rates and capacity utilization rates are some of the statistics commonly used to predict the future path of inflation, These measures embody the basic idea of supply and demand: As the demand for scarce goods increases, their prices must also increase. The staff of the Board of Governors of the Federal Reserve System measures capacity utilization as the ratio of industrial production to industrial capacity’ Since the denominator in this ratio normalizes industrial production by a measure of the potential industrial output of the economy the ratio provides a cyclical measure of industrial output. The Boards measure of capacity assumes that a firm’s or an industry’s production capacity is fixed over some moderate time horizon, usually due to the quantity of the available plant and equipment stock. When firms attempt to produce beyond their “normal” levels, the cost of producing the additional output becomes increasingly expensive if the firm’s production process exhibits diminishing returns-to-scale. The higher cost then translates into higher prices. Most of the empirical researchers on this subject use total industrial capacity utilization and the consumer price index (CPI) or producer price index (PPI) finished goodsbased measures of inflation. Since inflation is an aggregate phenomenon, their focus is undoubtedly justified. Yet, the economic analysis that links inflation to capacity utilization should apply to any product market, regardless of its size. Therefore, the relationship between price and capacity use should also be evident in industry level data—perhaps more so. In this paper, I use two-digit standard industrial classification (SIC) industry measures of capacity utilization to explore the robustness of the relationship between capacity utilization and prices. The results suggest that such measures do not have a consistently strong and simple relationship with each industry’s price data.

Optimal capacity with stochastic demand

A model focusing on the choice of capacity in an environment with stochastic demand is presented. The paper establishes the conditions under which bias in traditional econometric measures of capacity utilization may occur. As illustration, the model is applied to the Norwegian vessel-building industry. The results from traditional econometric studies in this industry are adjusted using the results from the model presented. The analysis indicates an upward bias in the traditional capacity utilization index; the excess capacity in the analyzed industry, as determined by deviation from the optimal, stochastically-adjusted level of capacity, is higher than that determined by traditional econometric measures. However, the author is reluctant to draw definitive conclusions from the empirical part of the paper due to uncertainty regarding data and assumptions made. The empirical implementation is primarily illustrative and should be interpreted as such.

Interpretation and measurement of capacity utilization: the case of Korean manufacturing

This paper focuses attention on the conceptual difference between optimal (ex ante) and actual (ex post) capacity untilization (CU). The dynamic version of the efficient output approach to capacity untilization which this paper presents is theoretically superior to other alternative approaches. Our concept of optimal CU has been applied to estimate CU measures for Korean manufacturing. We fing that our measure of CU explains the trends and cycles in Korean economy rather convincingly, and that Korean manufacturing has adjusted much more flexibly to market-demand shocks than it has to exogenous changes in factor prices. From the examination of the determinants of CU we find that, while wages and material prices have positive effects on CU, energy prices and capital stock have nagative effects. The study also implies that overambitious government incentive policies to stimulate investment may have an adverse effect on capacity utilization.

Morrison's measure of capacity utilization: A critique

Morrison (1986) has developed and used new capacity utilization measures based on an optimization framework to adjust productivity growth for changes in capacity utilization. She argues that we can adjust productivity growth for variations in capacity utilization by dividing a conventional productivity growth rate by a capacity utilization measure. However, Morrison's analysis is based on a conceptual error, which she recognizes in later research. This error can have considerable empirical significance.

Un modello di analisi fattoriale dinamica per la stima della capacità produttiva utilizzata:prime specificazioni

In this work a dynamic factor model for capacity utilization in industry is estimated. Several measures of capacity utilization, based on the different concepts and procedures (Wharton method, surveys, electricity estimates) are considered and interpreted as indicators of a common latent factor, the capacity utilization. Identification and estimation problems are worked out within the state-space framework. Some attention is given to the computation of the likelihood estimates. Some preliminary results are presented relative to the Italian manufacturing industry for the period 1978-1988.

Measuring Fleet Capacity and Capacity Utilization

Fishing capacity measures the capability to catch fish. Capacity utilization is the actual effectiveness in catching fish; the ratio of catch to capacity. The factors comprising a fleet's capacity are the number and size of vessels, the technical efficiency of those vessels, and the time commitment of fishermen. Knowing the capacity utilization of a fleet is critical for evaluating management alternatives. This is true regardless of whether fisheries are managed with fleet controls or with individual controls. We illustrate the measurement of capacity utilization with the Oregon bottom trawl fishery, in which fleet capacity quadrupled between 1976 and 1982. From 1982 to 1985 capacity declined 30% due to economic problems in the industry and vessels finding better opportunities elsewhere. Capacity measurement is necessary to assess management-induced changes in controlled fisheries. Controlling capacity requires addressing all the elements associated with capacity growth. Examination of the components of fleet capacity reveals an array of management options.