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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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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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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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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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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Modelling Technical Progress And Total Factor Productivity: A Plant Level Example
October 1988
Working Paper Number:
CES-88-04
Shifts in the production frontier occur because of changes in technology. A model of how a firm learns to use the new technology, or how it adapts from the first production frontier to the second, is suggested. Two different adaptation paths are embodied in a translog cost function and its attendant cost share equations. The paths are the traditional linear time trend and a learning curve. The model is estimated using establishment level data from a non-regulated industry that underwent a technological shift in the time period covered by the data. The learning curve resulted in more plausible estimates of technical progress and total factor productivity growth patterns. A significant finding is that, at the establishment level, all inputs appear to be substitutes.
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REALLOCATION IN THE GREAT RECESSION: CLEANSING OR NOT?
August 2013
Working Paper Number:
CES-13-42
The high pace of output and input reallocation across producers is pervasive in the U.S. economy. Evidence shows this high pace of reallocation is closely linked to productivity. Resources are shifted away from low productivity producers towards high productivity producers. While these patterns hold on average, the extent to which the reallocation dynamics in recessions are 'cleansing' is an open question. That is, are recessions periods of increased reallocation that move resources away from lower productivity activities towards higher productivity uses? It could be recessions are times when the opportunity cost of time and resources are low implying recessions will be times of accelerated productivity enhancing reallocation. Prior research suggests the recession in the early 1980s is consistent with an accelerated pace of productivity enhancing reallocation. Alternative hypotheses highlight the potential distortions to reallocation dynamics in recessions. Such distortions might arise from many factors including, for example, distortions to credit markets. We find that in post-1980 recessions prior to the Great Recession, downturns are periods of accelerated reallocation that is even more productivity enhancing than in normal times. In the Great Recession, we find the intensity of reallocation fell rather than rose (due to the especially sharp decline in job creation) and the reallocation that did occur was less productivity enhancing than in prior recessions.
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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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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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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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How Credit Constraints Impact Job Finding Rates, Sorting & Aggregate Output*
January 2016
Working Paper Number:
CES-16-25
We empirically and theoretically examine how consumer credit access affects dis- placed workers. Empirically, we link administrative employment histories to credit reports. We show that an increase in credit limits worth 10% of prior annual earnings allows individuals to take .15 to 3 weeks longer to find a job. Conditional on finding a job, they earn more and work at more productive firms. We develop a labor sorting model with credit to provide structural estimates of the impact of credit on employ- ment outcomes, which we find are similar to our empirical estimates. We use the model to understand the impact of consumer credit on the macroeconomy. We find that if credit limits tighten during a downturn, employment recovers quicker, but output and productivity remain depressed. This is because when limits tighten, low-asset, low- productivity job losers cannot self-insure. Therefore, they search less thoroughly and take more accessible jobs at less productive firms.
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