This paper studies an economy in which producers incur resource costs to replace depreciated machines. The process of costly replacement and depreciation creates endogenous fluctuations in productivity, employment and output of a single producer. We also explore the spillover effects of machine replacement on other sectors of the economy and provide conditions for synchronized machine replacement by multiple, independent producers. The implications of our model are generally consistent with observed monthly output, employment and productivity fluctuations in automobile plants. Synchronization of retooling across plants within the auto industry is widespread so that the fluctuations observed at the plant level have aggregate implications.
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Manufacturing Plants' Use of Temporary Workers: An Analysis Using Census Micro Data
December 2008
Working Paper Number:
CES-08-40
Using plant-level data from the Plant Capacity Utilization (PCU) Survey, we examine how manufacturing plants' use of temporary workers is associated with the nature of their output fluctuations and other plant characteristics. We find that plants tend to hire temporary workers when their output can be expected to fall, a result consistent with the notion that firms use temporary workers to reduce costs associated with dismissing permanent employees. In addition, we find that plants whose future output levels are subject to greater uncertainty tend to use more temporary workers. We also examine the effects of wage and benefit levels for permanent workers, unionization rates, turnover rates, seasonal factors, and plant size and age on the use of temporary workers; based on our results, we discuss various views of why firms use temporary workers.
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Aggregate Productivity Growth: Lessons From Microeconomic Evidence
September 1998
Working Paper Number:
CES-98-12
In this study we focus on the role of the reallocation of activity across individual producers for aggregate productivity growth. A growing body of empirical analysis yields striking patterns in the behavior of establishment-level reallocation and productivity. Nevertheless, a review of existing studies yields a wide range of findings regarding the contribution of reallocation to aggregate productivity growth. Through our review of existing studies and our own sensitivity analysis, we find that reallocation plays a significant role in the changes in productivity growth at the industry level and that the impact of net entry is disproportionate since entering plants tend to displace less productive exiting plants, even after controlling for overall average growth in productivity. However, an important conclusion of our sensitivity analysis is that the quantitative contribution of reallocation to the aggregate change in productivity is sensitive to the decomposition methodology employed. Our findings also confirm and extend others in the literature that indicate that both learning and selection effects are important in this context. A novel aspect of our analysis is that we have examined the role of reallocation for aggregate productivity growth to a selected set of service sector industries. Our analysis considers the 4-digit industries that form the 3-digit industry automobile repair shops. We found tremendous churning in this industry with extremely large rates of entry and exit. Moreover, we found that productivity growth in the industry is dominated establishment data at Census, the results are quite striking and clearly call for further analysis.
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Business Volatility, Job Destruction, and Unemployment
August 2008
Working Paper Number:
CES-08-26
Unemployment inflows fell from 4 percent of employment per month in the early 1980s to 2 percent or less by the mid 1990s and thereafter. U.S. data also show a secular decline in the job destruction rate and the volatility of firm-level employment growth rates. We interpret this decline as a decrease in the intensity of idiosyncratic labor demand shocks, a key parameter in search and matching models of unemployment. According to these models, a lower intensity of idiosyncratic shocks produces less job destruction, fewer workers flowing through the unemployment pool and less frictional unemployment. To evaluate the importance of this theoretical mechanism, we relate industry-level unemployment flows from 1977 to 2005 to industry-level indicators for the intensity of idiosyncratic shocks. Unlike previous research, we focus on the lower frequency relationship of job destruction and business volatility to unemployment flows. We find strong evidence that declines in the intensity of idiosyncratic labor demand shocks drove big declines in the incidence and rate of unemployment. This evidence implies that the unemployment rate has become much less sensitive to cyclical movements in the job-finding rate.
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Technology Locks, Creative Destruction And Non-Convergence In Productivity Levels
April 1995
Working Paper Number:
CES-95-06
This paper presents a simple solution to a new model that seeks to explain the distribution of plants across productivity levels within an industry, and empirically confirms some key predictions using the U.S. textile industry. In the model, plants are locked into a given productivity level, until they exit or retool. Convex costs of adjustment captures the fact that more productive plants expand faster. Provided there is technical change, productivity levels do not converge; the model achieves persistent dispersion in productivity levels within the context of a distortion free competitive equilibrium. The equilibrium, however, is rather turbulent; plants continually come on line with the cutting edge technology, gradually expand and finally exit or retool when they cease to recover their variable costs. The more productive plants create jobs, while the less productive destroy them. The model establishes a close link between productivity growth and dispersion in productivity levels; more rapid productivity growth leads to more widespread dispersion. This prediction is empirically confirmed. Additionally, the model provides an explanation for S-shaped diffusion.
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Technology and Jobs: Secular Changes and Cyclical Dynamics
September 1996
Working Paper Number:
CES-96-07
In this paper, we exploit plant-level data for U.S. manufacturing for the 1970s and 1980s to explore the connections between changes in technology and the structure of employment and wages. We focus on the nonproduction labor share (measured alternatively by employment and wages) as the variable of interest. Our main findings are summarized as follows: (i) aggregate changes in the nonproduction labor share at annual and longer frequencies are dominated by within plant changes; (ii) the distribution of annual within plant changes exhibits a spike at zero, tremendous heterogeneity and fat left and right tails; (iii) within plant secular changes are concentrated in recessions; and (iv) while observable indicators of changes in technology account for a significant fraction of the secular increase in the average nonproduction labor share, unobservable factors account for most of the secular increase, most of the cyclical variation and most of the cross sectional heterogeneity.
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The Life Cycles of Industrial Plants
October 2001
Working Paper Number:
CES-01-10
The paper presents a dynamic programming model with multiple classes of capital goods to explain capital expenditures on existing plants over their lives. The empirical specification shows that the path of capital expenditures is explained by (a) complementarities between old and new capital goods, (b) the age of plants, (c) an index that captures the rate of technical change and (d) the labor intensiveness of a plant when it is newly born. The model is tested with Census data for roughly 6,000 manufacturing plants that were born after 1972.
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REALLY UNCERTAIN BUSINESS CYCLES
March 2014
Working Paper Number:
CES-14-18
We propose uncertainty shocks as a new shock that drives business cycles. First, we demonstrate that microeconomic uncertainty is robustly countercyclical, rising sharply during recessions, particularly during the Great Recession of 2007-2009. Second, we quantify the impact of time-varying uncertainty on the economy in a dynamic stochastic general equilibrium model with heterogeneous firms. We find that reasonably calibrated uncertainty shocks can explain drops and rebounds in GDP of around 3%. Moreover, we show that increased uncertainty alters the relative impact of government policies, making them initially less effective and then subsequently more effective.
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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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Explaining Cyclical Movements in Employment: Creative-Destruction or Changes in Utilization?
November 2006
Working Paper Number:
CES-06-25
An important step in understanding why employment fluctuates cyclically is determining the relative importance of cyclical movements in permanent and temporary plant-level employment changes. If movements in permanent employment changes are important, then recessions are times when the destruction of job specific capital picks up and/or investment in new job capital slows. If movements in temporary employment changes are important, then employment fluctuations are related to the temporary movement of workers across activities (e.g. from work to home production or search and back again) as the relative costs/benefits of these activities change. I estimate that in the manufacturing sector temporary employment changes account for approximately 60 percent of the change in employment growth over the cycle. However, if permanent employment changes create and destroy more capital than temporary employment changes, then their economic consequences would be relatively greater. The correlation between gross permanent employment changes and capital intensity across industries supports the hypothesis that permanent employment changes do create and destroy more capital than temporary employment changes.
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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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