The Survey of Plant Capacity (SPC) is the primary source of data used to construct the Federal Reserve's manufacturing utilization rates. A major restructuring of the SPC in 1989 presents a potential obstacle to constructing measures of utilization that are consistent over time. The object of this study is to take advantage of plant-level data that is available at the Census Bureau's O'ce of the Chief Economist to thoroughly reexamine the link between the historical and current measures of capacity. The preponderance of evidence in this study suggests that preferred utilization is consistent with \full" utilization and, therefore, supports the underlying Federal Reserve methodology for estimating capacity utilization.
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Outsourcing Business Service and the Scope of Local Markets
December 2001
Working Paper Number:
CES-01-15
This paper examines outsourcing to test whether productivity-enhancing specialization is facilitated in bigger cities. First, the paper provides a theoretical model which shows that greater local demand for a given input promotes the entry of suppliers into a city; the increased number of suppliers then results in lower outsourcing prices and a higher use of outsourcing by final producers, therefore reducing the final producers' production costs. I then test the predictions of the model by examining manufacturing plants' practices of outsourcing business services, by using plant-level data from the 1992 Annual Survey of Manufactures. The empirical results show that an exogenous increase in local demand promotes the entry of service suppliers and increases a firm's probability of outsourcing for white-collar services. In particular, I found that doubling the intensity of the use of a service in a U.S. county, which can be attributed to the industrial composition of the county, results in a 7% to 25% increase in the probability of outsourcing.
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Outsourcing Business Service and the Scope of Local Markets
August 2000
Working Paper Number:
CES-00-14
This paper examines outsourcing to test whether productivity-enhancing specialization is facilitated in bigger cities. First, the paper provides a theoretical model which shows that greater local demand for a given input promotes the entry of suppliers into a city; the increased number of suppliers then results in lower outsourcing prices and a higher use of outsourcing by final producers, therefore reducing the final producers' production costs. I then test the predictions of the model by examining manufacturing plants' practices of outsourcing business services, by using plant-level data from the 1992 Annual Survey of Manufactures. The empirical results show that an exogenous increase in local demand promotes the entry of service suppliers and increases a firm's probability of outsourcing for white-collar services. In particular, I found that doubling the intensity of the use of a service in a U.S. county, which can be attributed to the industrial composition of the county, results in a 7% to 25% increase in the probability of outsourcing.
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Public Disclosure of Private Information as a Tool for Regulating Environmental Emissions: Firm-Level Responses by Petroleum Refineries to the Toxics Release Inventory
October 2005
Working Paper Number:
CES-05-13
I investigate whether, as is commonly believed -- and if so how -- firm disclosure of so-called "toxic" releases, required since 1987 by the federal "Toxics Release Inventory ("TRI"), has brought about the reductions in toxic releases that have occurred since that time. Existing literature, consisting principally of event studies of stock market returns, suggest that dirty firms experience abnormal negative returns. Using a micro-level data set that links TRI releases to plant level Census data for petroleum refineries, I study plant-level behavior, exploiting state variation in toxics regulations, and exploring the relationship between TRI releases and concomitant regulation of non-toxic pollutants. I find that, although TRI induced public disclosure may have contributed to the decline in reported toxic releases, that alone has not been the cause of those reductions: the evidence is strong that changes in toxic emission intensity are a byproduct of more traditional command and control regulation of emissions of non-toxic pollutants. I find that (1) since 1987, refineries have become substantially cleaner in terms of over-all toxic releases; (2) the clean-up has not occurred through substitution away from TRI listed substances as inputs or alteration in the mix of outputs; and (3) refineries in states with more stringent supplemental regulation of toxics (e.g. with specific state-wide goals for toxic reductions) have significantly lower toxic emission intensity levels than refineries in other states. I find also that (4) TRI air releases are highly correlated with levels of criteria air pollution; (5) both toxic pollution levels and intensity fall with increases in pollution abatement (operating and maintenance) expenditures for non-toxic air pollution; and (6) TRI air releases are affected by being in more stringent regulatory regions for the criteria air pollutants. Finally, I link my data-set with CRSP data to re-evaluate the effect of TRI reporting on company stock market valuation, correcting for a methodological shortcoming (stemming from the fact that all reporting firms face a common event window) of prior event studies of the impact of the TRI. Correcting for that shortcoming, I find that (7) the evidence of negative abnormal returns around TRI reporting dates for petroleum companies is not significant. My findings suggest that the most probable mechanism through which TRI reporting may induce firms to clean up is local and state governmental use of TRI disclosures. They suggest also not only that the perceived effectiveness of TRI regulation has been overstated, but perhaps more importantly that the benefits of command and control regulation of non-toxic pollutants have been underestimated.
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Using the Survey of Plant Capacity to Measure Capital Utilization
July 2011
Working Paper Number:
CES-11-19
Most capital in the United States is idle much of the time. By some measures, the average workweek of capital in U.S. manufacturing is as low as 55 hours per 168 hour week. The level and variability of capital utilization has important implications for understanding both the level of production and its cyclical fluctuations. This paper investigates a number of issues relating to aggregation of capital utilization measures from the Survey of Plant Capacity and makes recommendations on expanding and improving the published statistics deriving from the Survey of Plant Capacity. The paper documents a number of facts about properties of capital utilization. First, after growing for decades, capital utilization started to fall in mid 1990s. Second, capital utilization is a useful predictor of changes in capacity utilization and other factors of production. Third, adjustment of productivity measures for variable capital utilization improves statistical and economic properties of these measures. Fourth, the paper constructs weights to aggregate firm level capital utilization rates to industry and economy level, which is the major enhancement to available data.
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Long-Run Expectations And Capacity
April 1988
Working Paper Number:
CES-88-01
In this paper, we argue at a general level, that recent economic models of capacity and of its utilization are deficient because they do not adequately take into account firms' long-run expectations about conditions which are pertinent to their investment decisions, i.e., their decisions about altering productive capacity. We argue that the problem with these models is that they rely on the two conventional definitions of capacity which ignore these long-run expectations. Accordingly, we propose a third definition of capacity which incorporates these expectations and, thereby, corrects the problem. Furthermore, we argue that a correct, empirical analysis with the proposed definition -- indeed, any credible analysis of capacity or its utilization -- must take into account the demand for the output produced by the firms being studied. Finally, we apply the definition to clarify the meaning of surveys of capacity and, thus, show how it can be used to improve future surveys of capacity.
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Why Are Plant Deaths Countercyclical: Reallocation Timing or Fragility?
November 2006
Working Paper Number:
CES-06-24
Because plant deaths destroy specific capital with large local economic impacts and potentially important macroeconmic effects, understanding the causes of deaths and, in particular, why they are concentrated in cyclical downturns, is important. The reallocationtiming hypothesis posits that plants suffering adverse permanent demand/productivity shocks delay shutdowns until cyclical downturns when plant capacity is less valuable, while the fragility hypothesis posits that shutdowns occur in downturns because the option value of maintaining the plant through low profitability periods is too small. I show that the effect that a plant's specific capital has on the timing of plant deaths differs across these two hypotheses and then use this insight to test the hypotheses' relative importance. I find that fragility is the dominant cause of the countercyclical behavior of plant deaths. This suggests that the endogenous destruction of capital is likely an important amplification and propagation mechanism for cyclical shocks and that stabilization policies have the benefit of reduced capital destruction.
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The Dynamics of Plant-Level Productivity in U.S. Manufacturing
July 2006
Working Paper Number:
CES-06-20
Using a unique database that covers the entire U.S. manufacturing sector from 1976 until 1999, we estimate plant-level total factor productivity for a large number of plants. We characterize time series properties of plant-level idiosyncratic shocks to productivity, taking into account aggregate manufacturing-sector shocks and industry-level shocks. Plant-level heterogeneity and shocks are a key determinant of the cross-sectional variations in output. We compare the persistence and volatility of the idiosyncratic plant-level shocks to those of aggregate productivity shocks estimated from aggregate data. We find that the persistence of plant level shocks is surprisingly low-we estimate an average autocorrelation of the plantspecific productivity shock of only 0.37 to 0.41 on an annual basis. Finally, we find that estimates of the persistence of productivity shocks from aggregate data have a large upward bias. Estimates of the persistence of productivity shocks in the same data aggregated to the industry level produce autocorrelation estimates ranging from 0.80 to 0.91 on an annual basis. The results are robust to the inclusion of various measures of lumpiness in investment and job flows, different weighting methods, and different measures of the plants' capital stocks.
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What Do Establishments Do When Wages Increase?
Evidence from Minimum Wages in the United States
November 2019
Working Paper Number:
CES-19-31
I investigate how establishments adjust their production plans on various margins when wage rates increase. Exploiting state-by-year variation in minimum wage, I analyze U.S. manufacturing plants' responses over a 23-year period. Using instrumental variable method and Census Microdata, I find that when the hourly wage of production workers increases by one percent, manufacturing plants reduce the total hours worked by production workers by 0.7 percent and increase capital expenditures on machinery and equipment by 2.7 percent. The reduction in total hours worked by production workers is driven by intensive-margin changes. The estimated elasticity of substitution between capital and labor is 0.85. Following the wage increases, no statistically significant changes emerge in revenue, materials or total factor productivity. Additionally, I nd that when wage rates increase, establishments are more likely to exit the market. Finally, I provide evidence that when the minimum wage increases the wages of some of the establishments in a firm, the firm also increases the wages for its other establishments.
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Automation, Labor Share, and Productivity:
Plant-Level Evidence from U.S. Manufacturing
September 2018
Working Paper Number:
CES-18-39
This paper provides new evidence on the plant-level relationship between automation, labor and capital usage, and productivity. The evidence, based on the U.S. Census Bureau's Survey of Manufacturing Technology, indicates that more automated establishments have lower production labor share and higher capital share, and a smaller fraction of workers in production who receive higher wages. These establishments also have higher labor productivity and experience larger long-term labor share declines. The relationship between automation and relative factor usage is modelled using a CES production function with endogenous technology choice. This deviation from the standard Cobb-Douglas assumption is necessary if the within-industry differences in the capital-labor ratio are determined by relative input price differences. The CES-based total factor productivity estimates are significantly different from the ones derived under Cobb-Douglas production and positively related to automation. The results, taken together with earlier findings of the productivity literature, suggest that the adoption of automation may be one mechanism associated with the rise of superstar firms.
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The Importance of Reallocations in Cyclical Productivity and Returns to Scale: Evidence from Plant-Level Data
March 2007
Working Paper Number:
CES-07-05
This paper provides new evidence that estimates based on aggregate data will understate the true procyclicality of total factor productivity. I examine plant-level data and show that some industries experience countercyclical reallocations of output shares among firms at different points in the business cycle, so that during recessions, less productive firms produce less of the total output, but during expansions they produce more. These reallocations cause overall productivity to rise during recessions, and do not reflect the actual path of productivity of a representative firm over the course of the business cycle. Such an effect (sometimes called the cleansing effect of recessions) may also bias aggregate estimates of returns to scale and help explain why decreasing returns to scale are found at the industry-level data.
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