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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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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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Using Census Business Data to Augment the MEPS-IC
December 2005
Working Paper Number:
CES-05-26
This paper has two aims: first to describe methods, issues, and outcomes involved in matching data from the Insurance Component of the Medical Expenditure Panel Survey (MEPSIC) to other business microdata collected by the U.S. Census Bureau, and second to present some simple results that illustrate the usefulness of such combined data. We present the results of linking the MEPS-IC with data from the 1997 Economic Censuses (EC), but also discuss other possible sources of business data. An issue in any linkage is whether the linked sample remains representative and large enough to be useful. The EC data are attractive because, given the survey's broad coverage and large sample, most of the MEPS-IC sample can be matched to it. We use the combined EC/MEPS-IC data to construct productivity measures that are useful auxiliary data in examining employers' health insurance offering decisions.
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Micro and Macro Data Integration: The Case of Capital
May 2005
Working Paper Number:
CES-05-02
Micro and macro data integration should be an objective of economic measurement as it is clearly advantageous to have internally consistent measurement at all levels of aggregation ' firm, industry and aggregate. In spite of the apparently compelling arguments, there are few measures of business activity that achieve anything close to micro/macro data internal consistency. The measures of business activity that are arguably the worst on this dimension are capital stocks and flows. In this paper, we document, quantify and analyze the widely different approaches to the measurement of capital from the aggregate (top down) and micro (bottom up) perspectives. We find that recent developments in data collection permit improved integration of the top down and bottom up approaches. We develop a prototype hybrid method that exploits these data to improve micro/macro data internal consistency in a manner that could potentially lead to substantially improved measures of capital stocks and flows at the industry level. We also explore the properties of the micro distribution of investment. In spite of substantial data and associated measurement limitations, we show that the micro distributions of investment exhibit properties that are of interest to both micro and macro analysts of investment behavior. These findings help highlight some of the potential benefits of micro/macro data integration.
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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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Job Flow Dynamics in the Service Sector
November 1999
Working Paper Number:
CES-99-14
This paper uses the new comprehensive Longitudinal Establishment and Enterprise Microdata at CES to investigate gross and net job flows for 1990 to 1995 for all establishments in the service sector. After examining the recent shifts in the distribution of employment in non-financial services, from single unit firms to multi-unit firms, and from smaller firms to larger ones, we calculate five year gross and net job flow rates for these various types of establishments. This shows that the increasing share of service employment in large firms is not due to higher growth in larger firms. Seeking the dynamics behind the shift of employment to larger firms, we investigate how job flow rates are related to firm and establishment size, using alternative size classification methods. Gross job flow rates vary inversely with the age of establishments in services, as do net growth rates of surviving establishments, even after controlling for size. To help distinguish among the effects of age, firm size, and establishment size on gross and net job flows in services, multivariate regression analysis is used. We find that all gross job flow rates decline with increasing age of establishments when size and industry differences are controlled. Because the job destruction rate falls faster than the creation rate as age increases, net growth rates increase with age for services as a whole. Gross and net job creation also declines with increasing size of establishments, but destruction rates increase with size when controlling for age and industry differences. Firm size differences contribute little or nothing additional when we control for establishment size and age.
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ON THE SOURCES AND SIZE OF EMPLOYMENT ADJUSTMENT COSTS
May 1999
Working Paper Number:
CES-99-07
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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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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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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The Census of Construction Industries Database
August 1998
Working Paper Number:
CES-98-10
The Census of Construction Industries (CCI) is conducted every five years as part of the quinquennial Economic Census. The Census of Construction Industries covers all establishments with payroll that are engaged primarily in contract construction or construction on their own account for sale as defined in the Standard Industrial Classification Manual. As previously administered, the CCI is a partial census including all multi-establishments and all establishments with payroll above $480,000, one out of every five establishments with payroll between $480,000 and $120,000 and one out of eight remaining establishments. The resulting database contains for each year approximately 200,000 establishments in the building construction, heavy construction and special trade construction industrial classifications. This paper compares the content, survey procedures, and sample response of the 1982, 1987 and 1992 Censuses of Construction.
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