Micro employment adjustment costs affect not only establishment-level dynamics but can also affect aggregate employment dynamics. The difficulties in directly observing and measuring these adjustment costs necessitate an indirect approach in order to learn more about the sources and size of these costs. This paper examines differences in employment adjustments by worker and establishment characteristics using micro-level data for approximately 11,000 U.S. manufacturing plants. Differences in the speed of adjustment within the organizing framework of the traditional partial adjustment model are used to identify the source and size of employment adjustment costs. The estimates are undertaken using three different techniques and under a variety of assumptions concerning market structure, worker heterogeneity, and degree of interrelation of inputs. The estimates show that employment adjustment speeds differ over worker and establishment characteristics in a manner that is consistent with the underlying adjustment cost stories. These differences suggest that systematic changes in the distribution of establishments over these characteristics can influence aggregate employment dynamics in response to a shock through compositional effects.
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Employment Adjustment Costs and Establishment Characteristics
November 1999
Working Paper Number:
CES-99-15
Microeconomic employment adjustment costs affect not only employment adjustments at the micro level but may also profoundly impact aggregate employment dynamics. This paper sheds light on the nature of these microeconomic employment adjustment costs and quantifies their impact on aggregate employment dynamics. The empirical exercises in the paper analyze the differences in employment adjustments by establishment characteristics within a hazard model framework using micro data for approximately 10,000 U.S. manufacturing plants. I find that employment adjustments vary systematically by establishment characteristics; moreover, these variations suggest that employment adjustment costs reflect the technology of the plant, the skill of its workforce, and the plant's access to capital markets. Concerning the structure of the adjustment costs, the employment adjustments have significant nonlinearities and asymmetries consistent with nonconvex, asymmetric adjustment costs. Specifically, employment adjustment behavior shows substantial inertia in the face of large employment surpluses, varied adjustment behavior for small deviations from desired employment, and (S,s)-type of bimodal adjustments in response to large employment shortages. Finally, the micro level heterogeneity, asymmetries, and nonlinearities significantly impact sectoral and aggregate employment dynamics.
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Wage Dynamics along the Life-Cycle of Manufacturing Plants
August 2011
Working Paper Number:
CES-11-24R
This paper explores the evolution of average wage paid to employees along the life-cycle of a manufacturing plant in U.S. Average wage starts out low for a new plant and increases along with labor productivity, as the plant survives and ages. As a plant experiences productivity decline and approaches exit, average wage falls, but more slowly than it rises in the case of surviving new plants. Moreover, average wage declines slower than productivity does in failing plants, while it rises relatively faster as productivity increases in surviving new plants. These empirical regularities are studied in a dynamic model of labor quality and quantity choice by plants, where labor quality is reflected in wages. The model's parameters are estimated to assess the costs a plant incurs as it alters its labor quality and quantity in response to changes in its productivity over its life-cycle.
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Learning by Doing and Plant Characteristics
August 1996
Working Paper Number:
CES-96-05
Learning by doing, especially spillover learning, has received much attention lately in models of industry evolution and economic growth. The predictions of these models depend on the distribution of learning abilities and knowledge flows across firms and countries. However, the empirical literature provides little guidance on these issues. In this paper, I use plant level data on a sample of entrants in SIC 38, Instruments, to examine the characteristics associated with both proprietary and spillover learning by doing. The plant level data permit tests for the relative importance of within and between firm spillovers. I include both formal knowledge, obtained through R&D expenditures, and informal knowledge, obtained through learning by doing, in a production function framework. I allow the speed of learning to vary across plants according to characteristics such as R&D intensity, wages, and the skill mix. The results suggest that (a) Ainformal@ knowledge, accumulated through production experience at the plant, is a much more important source of productivity growth for these plants than is Aformal@ knowledge gained via research and development expenditures, (b) interfirm spillovers are stronger than intrafirm spillovers, (c) the slope of the own learning curve is positively related to worker quality, (d) the slope of the spillover learning curve is positively related to the skill mix at plants, (e) neither own nor spillover learning curve slopes are related to R&D intensities. These results imply that learning by doing may be, to some extent, an endogenous phenomenon at these plants. Thus, models of industry evolution that incorporate learning by doing may need to be revised. The results are also broadly consistent with the recent growth models.
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Energy Intensity, Electricity Consumption, and Advanced Manufacturing Technology Usage
July 1993
Working Paper Number:
CES-93-09
This paper reports on the relationship between the usage of advanced manufacturing technologies (AMTs) and energy consumption patterns in manufacturing plants. Using data from the Survey of Manufacturing Technology and the 1987 Census of Manufactures, we model the energy intensity and the electricity intensity of plants as functions of AMT usage and plant age. The main findings are that plants which utilize AMTs are less energy intensive than plants not using AMTs but consume proportionately more electricity as a fuel source. Additionally, older plants are generally more energy intensive and rely on fossil fuels to a greater extent than younger plants.
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Establishment and Employment Dynamics in Appalachia: Evidence from the Longitudinal Business Database
December 2003
Working Paper Number:
CES-03-19
One indicator of the general economic health of a region is the rate at which new jobs are created. The newly developed Longitudinal Business Database has been used in this paper to develop a detailed portrait of establishment formation and attrition and job creation and destruction in the Appalachian Region. The foremost finding is that the pace of reallocation in Appalachia is lower than it is for the U.S.. This is evident in Appalachia's relatively lower establishment birth and death rates and job creation and destruction rates. For example, on average over the study time period, the U.S. job creation rate exceeds 45 percent, while the Appalachian job creation rate is 43 percent. Similarly, the U.S. job destruction rate is about 35 percent, while the Appalachian job destruction rate is about 33 percent. Even when controlling for other differences, job creation rates are 1.2 percentage points lower and job destruction rates are 3.4 percentage points lower in Appalachia relative to the rest of the U.S. Another indicator of the general economic health of a region is the quality of its jobs. The quality of jobs is measured in this paper by the average wage paid at the establishment. Here too there is cause for concern about the economic health of Appalachia. The analysis shows that wages are about 10 percent lower in Appalachia than in the U.S. even when controlling for differences in other characteristics across the two areas. This wage discrepancy has not narrowed over the time of the study. Moreover, new establishments have a similar wage gap. Employees at new establishments earn wages 10 percent less than at new establishments in the rest of the U.S.
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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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Capital-Energy Substitution Revisted: New Evidence From Micro Data
April 1997
Working Paper Number:
CES-97-04
We use new micro data for 11,520 plants taken from the Census Bureau=s 1991 Manufacturing Energy Consumption Survey (MECS) and 1991 Annual Survey of Manufactures (ASM) to estimate elasticities of substitution between energy and capital. We found that energy and capital are substitutes. We also found that estimates of Allen elasticities of substitution -- which have been used as a standard measure of substitution -- are sensitive to varying data sets and levels of aggregation. In contrast, estimates of Morishima elasticities of substitution -- which are theoretically superior to the Allen elasticities -- are more robust (except when two-digit level data are used). The results support the views that (i) the Morishima elasticity is a better measure of factor substitution and (ii) micro data provide more accurate elasticity estimates than those obtained from aggregate data. Our findings appear to resolve the long-standing conflict among the estimates reported in the many previous studies regarding energy-capital substitution/complementarity.
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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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Measuring Plant Level Energy Efficiency and Technical Change in the U.S. Metal-Based Durable Manufacturing Sector Using Stochastic Frontier Analysis
January 2016
Working Paper Number:
CES-16-52
This study analyzes the electric and thermal energy efficiency for five different metal-based durable manufacturing industries in the United States from 1987-2012 at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days - HDD - and cooling degree days - CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. A Malmquist index is used to decompose aggregate plant technical change in energy use into indices of efficiency and frontier (best practice) change. Own energy price elasticities range from -.7 to -1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100 percent equals best practice level) range from a low of 32 percent (thermal 334 - Computer and Electronic Products) to a high of 86 percent (electricity 332 - Fabricated Metal Products). Electric efficiency is consistently better than thermal efficiency for all NAICS. There is no clear pattern to the decomposition of aggregate technical Thermal change. In some years efficiency improvement dominates; in other years aggregate technical change is driven by improvement in best practice.
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Immigration, Skill Mix, and the Choice of Technique
May 2005
Working Paper Number:
CES-05-04
Using detailed plant- level data from the 1988 and 1993 Surveys of Manufacturing Technology, this paper examines the impact of skill mix in U.S. local labor markets on the use and adoption of automation technologies in manufacturing. The level of automation differs widely across U.S. metropolitan areas. In both 1988 and 1993, in markets with a higher relative availability of lessskilled labor, comparable plants ' even plants in the same narrow (4-digit SIC) industries ' used systematically less automation. Moreover, between 1988 and 1993 plants in areas experiencing faster less-skilled relative labor supply growth adopted automation technology more slowly, both overall and relative to expectations, and even de-adoption was not uncommon. This relationship is stronger when examining an arguably exogenous component of local less-skilled labor supply derived from historical regional settlement patterns of immigrants from different parts of the world. These results have implications for two long-standing puzzles in economics. First, they potentially explain why research has repeatedly found that immigration has little impact on the wages of competing native-born workers at the local level. It might be that the technologies of local firms'rather than the wages that they offer'respond to changes in local skill mix associated with immigration. A modified two-sector model demonstrates this theoretical possibility. Second, the results raise doubts about the extent to which the spread of new technologies have raised demand for skills, one frequently forwarded hypothesis for the cause of rising wage inequality in the United States. Causality appears to at least partly run in the opposite direction, where skill supply drive s the spread of skill-complementary technology.
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