This paper provides new facts on the nature of job reallocation over the business cycle, and addresses the question of whether reallocation causes recessions or recessions cause reallocation. Although we do not resolve the question of causality, two general findings emerge that advance our understanding of job reallocation and business cycles. First, much of the cyclical fluctuation in gross job flows occurs in larger plants with relatively moderate employment growth that tends to be transitory, especially at medium-term horizons (up to five years). Unusually large employment growth rates, especially plant startups and shutdowns, are primarily small-plant phenomena and tend to be permanent, less cyclical, and occur later in recessions. Further, high job flow rates occur primarily in plants previously experiencing sharp employment contractions or expansions. Second, key variables that should determine the allocation factors of production across plants and sectors do in fact appear to be related to gross job flows, particularly job destruction. Relative prices, productivity, and investment exhibit time series correlations with job reallocation that suggest that allocative driving forces may contribute significantly to business cycle fluctuations.
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Gross Job Flows and Firms
November 1999
Working Paper Number:
CES-99-16
This paper extends the work of Dunne, Roberts, and Samuelson (3) and Davis, Haltiwanger, and Schuh (2) on gross job flows among manufacturing plants. Gross job creation, destruction, and reallocation have been shown to be important in understanding the birth, growth, and death of plants, and the relation of plant life cycles to the business cycle. However, little is known about job flows between firms or how job flows among plants occur within firms (corporate restructuring). We use information on company organization from the Longitudinal Research database (LRD) to investigate the relationship between plant-level and firm-level job flows. We document: (1) the fraction of plant-level gross job flows occurring between firms; and (2) gross job flows by the extent of excess job reallocation occurring in firms.
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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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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 Missing Link: Technology, Productivity, and Investment
October 1995
Working Paper Number:
CES-95-12
This paper examines the relationship between productivity, investment, and age for over 14,000 plants in the U.S. manufacturing sector in the 1972-1988 period. Productivity patterns vary significantly due to plant heterogeneity. Productivity first increases and then decreases with respect to plant age, and size and industry are systematically correlated with productivity and productivity growth. However, there is virtually no observable relationship between investment and productivity or productivity growth. Overall, the results indicate that plant heterogeneity and fixed effects are more important determinants of observable productivity patterns than sunk costs or capital reallocation. Key Words: productivity, investment, technical change
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The Trend to Smaller Producers in Manufacturing in Canada and the U.S.
March 2002
Working Paper Number:
CES-02-06
This paper examines the trend in the importance of small producers in the Canadian and U.S. manufacturing sectors from the early 1970s to the late 1990s in order to investigate whether there was a common North American trend in changes in plant size. It finds that small plants in both countries increased their share of employment up to the 1990s, but their share remained stable in the 1990s. Small plants increased their share of output up to the 1990s, but then saw their share of output decline. Over the entire time period, their share of output increased less than their share of employment and, therefore, their relative labour productivity has fallen. The similarity in the trends in the two countries suggests that causes of this phenomenon should be sought in similarities such as the technological environment rather than in country-specific factors like unionization or trade intensities.
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Linking Investment Spikes and Productivity Growth: U.S. Food Manufacturing Industry
October 2008
Working Paper Number:
CES-08-36
We investigate the relationship between productivity growth and investment spikes using Census Bureau's plant-level data set for the U.S. food manufacturing industry. We find that productivity growth increases after investment spikes suggesting an efficiency gain or plants' learning effect. However, efficiency and the learning period associated with investment spikes differ among plants' productivity quartile ranks implying the differences in the plants' investment types such as expansionary, replacement or retooling. We find evidence of both convex and non-convex types of adjustment costs where lumpy plant-level investments suggest the possibility of non-convex adjustment costs and hazard estimation results suggest the possibility of convex adjustment costs. The downward sloping hazard can be due to the unobserved heterogeneity across plants such as plants' idiosyncratic obsolescence caused by different R&D capabilities and implies the existence of convex adjustment costs. Food plants frequently invest during their first few years of operation and high productivity plants postpone investing due to high fixed costs.
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Productivity Adjustments and Learning-by-Doing as Human Capital
November 1997
Working Paper Number:
CES-97-17
This paper measures plant-level productivity gains associated with learning curves across the entire manufacturing sector. We measure these gains at plant startups and also after major employment changes. We find: 1.) The gains are strongly associated with a variety of human capital measures implying that learning-by-doing is largely a firm-specific human capital investment. 2.) This implicit investment is large; many plants invest as much in learning-by-doing as they invest in physical capital and much more than they invest in formal job training. 3.) This investment differs persistently over industries and is higher with greater R&D. 4.) Consistent with a learning-by-doing interpretation, the human capital investment is much larger following employment decreases than increases. We conclude that learning-by-doing is a major factor in wage determination, technical progress and asymmetric employment adjustment costs.
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Estimating Capital Efficiency Schedules Within Production Functions
May 1992
Working Paper Number:
CES-92-04
The appropriate method for aggregating capital goods across vintages to produce a single capital stock measure has long been a contentious issue, and the literature covering this topic is quite extensive. This paper presents a methodology that estimates efficiency schedules within a production function, allowing the data to reveal how the efficiency of capital goods evolve as they age. Specifically we insert a parameterized investment stream into the position of a capital variable in a production function, and then estimate the parameters of the production function simultaneously with the parameters of the investment stream. Plant level panel data for a select group of steel plants employing a common technology are used to estimate the model. Our primary finding is that when using a simple Cobb Douglas production function, the estimated efficiency schedules appear to follow a geometric pattern, which is consistent with the estimates of economic depreciation of Hulten and Wykoff (1981). Results from more flexible functional forms produced much less precise and unreliable estimates.
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Firm Performance And Evolution Empirical Regularities In The U.S. Microdata
October 1996
Working Paper Number:
CES-96-10
This paper presents a view of firm performance, industry evolution, and economic growth that contrasts with the traditional representative firm model. The paper reviews recent empirical work, primarily studies using the Longitudinal Research Database (LRD), that explicitly focuses on individual business units. The major empirical regularity in the studies is that heterogeneity is pervasive -- it is found across and within all sectors and across all plant characteristics. Further, firms are not only different in the cross-section. They enter at different times, make different choices, and react differently to economic shocks. Thus, to understand economic performance and competition, one must move beyond representative firm models. Competition must be understood as a process in which some firms choose correctly and grow while other firms choose poorly and die; the growth of the successful firms at the expense of less successful rivals drives economic growth.
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MEASURES OF JOB FLOW DYNAMICS IN THE U.S.*
January 1999
Working Paper Number:
CES-99-01
This paper uses the new Longitudinal Establishment and Enterprise Microdata (LEEM) at CES to investigate gross and net job flows for the U. S. economy. Much of the previous work on U.S. job flows has been based on analysis of the Longitudinal Research Database (LRD), which is limited to establishments in the manufacturing sector. The LEEM is the first high-quality, nationwide, comprehensive database for both manufacturing and non-manufacturing that is suitable for measuring annual job flows. We utilize the LEEM data to measure recent gross and net job flows for the entire U. S. economy. We then examine the relationships between firm size, establishment size, and establishment age, and investigate differences resulting from use of two alternative methods for classification of job flows by size of firm and establishment. Cell-based regression analysis is used to help distinguish among the effects of age, firm size, and establishment size on gross and net job flows in existing establishments. We find that gross job flow rates decline with age, and with increasing establishment size when controlling for age differences, whether initial size or mean size classification is utilized. Firm size differences contribute little or nothing additional when establishment size and age are controlled for. However, the relationship of net job growth to business size is very sensitive to the size classification method, even when data and all other methodology are identical. When mean size classification is used, the coefficient on establishment size for net job growth is generally positive, but when initial size is used, this coefficient is negative. These results shed light on some of the apparently conflicting findings in the literature on the relationship between net growth and the size of businesses.
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