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Collaborative Micro-productivity Project: Establishment-Level Productivity Dataset, 1972-2020

December 2023

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The 10 most similar working papers to the working paper 'Collaborative Micro-productivity Project: Establishment-Level Productivity Dataset, 1972-2020' are listed below in order of similarity.

• Working Paper

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  Dispersion in Dispersion: Measuring Establishment-Level Differences in Productivity
  

  April 2018

  Authors: John Haltiwanger, Lucia Foster, Cheryl Grim, Zoltan Wolf, Cindy Cunningham, Sabrina Wulff Pabilonia, Jay Stewart

  Working Paper Number:

  CES-18-25RR

  We describe new experimental productivity statistics, Dispersion Statistics on Productivity (DiSP), jointly developed and published by the Bureau of Labor Statistics (BLS) and the Census Bureau. Productivity measures are critical for understanding economic performance. Official BLS productivity statistics, which are available for major sectors and detailed industries, provide information on the sources of aggregate productivity growth. A large body of research shows that within-industry variation in productivity provides important insights into productivity dynamics. This research reveals large and persistent productivity differences across businesses even within narrowly defined industries. These differences vary across industries and over time and are related to productivity-enhancing reallocation. Dispersion in productivity across businesses can provide information about the nature of competition and frictions within sectors, and about the sources of rising wage inequality across businesses. Because there were no official statistics providing this level of detail, BLS and the Census Bureau partnered to create measures of within-industry productivity dispersion. These measures complement official BLS aggregate and industry-level productivity growth statistics and thereby improve our understanding of the rich productivity dynamics in the U.S. economy. The underlying microdata for these measures are available for use by qualified researchers on approved projects in the Federal Statistical Research Data Center (FSRDC) network. These new statistics confirm the presence of large productivity differences and we hope that these new data products will encourage further research into understanding these differences.
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• Working Paper

  
  
  Punctuated Entrepreneurship (Among Women)
  

  May 2018

  Authors: Matt Marx

  Working Paper Number:

  CES-18-26

  The gender gap in entrepreneurship may be explained in part by employee non-compete agreements. Exploiting exogenous state-level variation in non-compete policy, I find that women more strictly subject to non-competes are 11-17% more likely to start companies after their employers dissolve. This result is not explained by the incidence of non-competes or lawsuits; however, women face higher relative costs in defending against potential litigation and in returning to paid employment after abandoning their ventures. Thus entrepreneurship among women may be 'punctuated' in that would-be female founders are throttled by non-competes, their potential unleashed only by the failure of their employers.
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• Working Paper

  
  
  Large Plant Data in the LRD: Selection of a Sample for Estimation
  

  March 1999

  Authors: Phoebus J Dhrymes, Linda Moeller

  Working Paper Number:

  CES-99-06

  This paper describes preliminary work with the LRD during our tenure at the Census Bureau as participants in the ASA/NSF/Census Research Program. The objective of the work described here were two-fold. First, we wanted to examine the suitableness of these data for the calculation of plant-level productivity indexes, following procedures typically implemented with time series data. Second, we wanted to select a small number of 2-digit industry groups that would be well suited to the estimation of production functions and systems of factor share equations and factor demand forecasting equations with system-wide techniques. This description of our initial work may be useful to other researchers who are interested in the LRD for the analysis of productivity growth and/or the estimation of systems of factor equations, because the specific results reported in this memo suggest that the data are of good quality, or because the nature of the tasks undertaken provides insight into issues that arise in the analysis of longitudinal establishment data.
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• Working Paper

  
  
  Productivity Dispersion, Entry, and Growth in U.S. Manufacturing Industries
  

  August 2021

  Authors: John Haltiwanger, Lucia Foster, Cheryl Grim, Zoltan Wolf, Cindy Cunningham, Sabrina Wulff Pabilonia, Jay Stewart

  Working Paper Number:

  CES-21-21

  Within-industry productivity dispersion is pervasive and exhibits substantial variation across countries, industries, and time. We build on prior research that explores the hypothesis that periods of innovation are initially associated with a surge in business start-ups, followed by increased experimentation that leads to rising dispersion potentially with declining aggregate productivity growth, and then a shakeout process that results in higher productivity growth and declining productivity dispersion. Using novel detailed industry-level data on total factor productivity and labor productivity dispersion from the Dispersion Statistics on Productivity along with novel measures of entry rates from the Business Dynamics Statistics and productivity growth data from the Bureau of Labor Statistics for U.S. manufacturing industries, we find support for this hypothesis, especially for the high-tech industries.
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• Working Paper

  
  
  Measuring Total Factor Productivity, Technical Change And The Rate Of Returns To Research And Development
  

  May 1991

  Authors: Sang V Nguyen, Edward C Kokkelenberg

  Working Paper Number:

  CES-91-03

  Recent research indicates that estimates of the effect of research and development (R&D) on total factor productivity growth are sensitive to different measures of total factor productivity. In this paper, we use establishment level data for the flat glass industry extracted from the Census Bureau's Longitudinal Research Database (LRD) to construct three competing measures of total factor productivity. We then use these measures to estimate the conventional R&D intensity model. Our empirical results support previous finding that the estimated coefficients of the model are sensitive to the measurement of total factor productivity. Also, when using microdata and more detailed modeling, R&D is found to be a significant factor influencing productivity growth. Finally, for the flat glass industry, a specific technical change index capturing the learning-by-doing process appears to be superior to the conventional time trend index.
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• Working Paper

  
  
  The Dynamics of Plant-Level Productivity in U.S. Manufacturing
  

  July 2006

  Authors: Arpad Abraham, T. Kirk White

  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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• Working Paper

  
  
  Evaluation And Use Of The Pollution Abatement Costs And Expenditures Survey Micro Data
  

  January 1996

  Authors: Mary L Streitwieser

  Working Paper Number:

  CES-96-01

  The Pollution Abatement Costs and Expenditures Survey (PACE) is an annual survey of manufacturing establishment=s operating costs and capital investment expenditures for pollution abatement purposes. This paper provides a description and evaluation of the PACE micro data available at the Center for Economic Studies (CES). The paper provides an overview of the survey, how the sample is drawn, how the survey questionnaire has changed over time, an assessment of the data quality, and suggestions for the use of the data, as well as its limitations. Also included are suggestions for modifying the survey design and data processing procedures. The PACE data series, linked to the economic data in CES= Longitudinal Research Database (LRD), covers the years 1979-1993, excluding 1983 and 1987.
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• Working Paper

  
  
  Efficiency Implications of Corporate Diversification: Evidence from Micro Data
  

  November 2006

  Authors: Ekaterina Emm, Jayant Kale

  Working Paper Number:

  CES-06-26

  In this study, we contribute to the ongoing research on the rationales for corporate diversification. Using plant-level data from the U.S. Census Bureau, we examine whether combining several lines of business in one entity leads to increased productive efficiency. Studying the direct effect of diversification on efficiency allows us to discern between two major theories of corporate diversification: the synergy hypothesis and the agency cost hypothesis. To measure productive efficiency, we employ a non-parametric approach'a test based on Varian's Weak Axiom of Profit Maximization (WAPM). This method has several advantages over other conventional measures of productive efficiency. Most importantly, it allows one to perform the efficiency test without relying on assumptions about the functional form of the underlying production function. To the best of our knowledge, this study is the first application of the WAPM test to a large sample of non-financial firms. The study provides evidence that business segments of diversified firms are more efficient compared to single-segment firms in the same industry. This finding suggests that the existence of the so-called 'diversification discount' cannot be explained by efficiency differences between multi-segment and focused firms. Furthermore, more efficient segments tend to be vertically integrated with others segments in the same firm and to have been added through acquisitions rather than grown internally. Overall, the results of this study indicate that corporate diversification is value-enhancing, and that it is not necessarily driven by managers' pursuit of their private benefits.
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• Working Paper

  
  
  Newly Recovered Microdata on U.S. Manufacturing Plants from the 1950s and 1960s: Some Early Glimpses
  

  September 2011

  Authors: Randy Becker, Cheryl Grim

  Working Paper Number:

  CES-11-29

  Longitudinally-linked microdata on U.S. manufacturing plants are currently available to researchers for 1963, 1967, and 1972-2009. In this paper, we provide a first look at recently recovered manufacturing microdata files from the 1950s and 1960s. We describe their origins and background, discuss their contents, and begin to explore their sample coverage. We also begin to examine whether the available establishment identifier(s) allow record linking. Our preliminary analyses suggest that longitudinally-linked Annual Survey of Manufactures microdata from the mid-1950s through the present ' containing 16 years of additional data ' appears possible though challenging. While a great deal of work remains, we see tremendous value in extending the manufacturing microdata series back into time. With these data, new lines of research become possible and many others can be revisited.
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• Working Paper

  
  
  Testing the Advantages of Using Product Level Data to Create Linkages Across Industrial Coding Systems
  

  October 1993

  Authors: Suzanne Peck

  Working Paper Number:

  CES-93-14

  After the major revision of the U.S. Standard Industrial Classification system (SIC) in the 1987, the problem arose of how to evaluate industrial performance over time. The revision resulted in the creation of new industries, the combination of old industries, and the remixing of other industries to better reflect the present U.S. economy. A method had to be developed to make the old and new sets of industries comparable over time. Ryten (1991) argues for performing the conversion at the "most micro level," the product level. Linking industries should be accomplished by reclassifying product data of each establishment to a standard system, reassigning the primary activity of the establishment, reaggregating the data to the industry level, and then making the desired statistical comparison (Ryten, 1991). This paper discusses linking the data at the very micro, product level, and at the more macro, industry level. The results suggest that with complete product information the product level conversion is preferable for most industries in manufacturing because it recognizes that establishments may switch their primary industry because of the conversion. For some industries, especially those having no substantial changes in SIC codes over time, the conversion at the industry level is fairly accurate. A small group of industries lacks complete product information in 1982 to link the 1982 product codes to the 1987 codes. This results in having to rely on the industry concordance to create a time series of statistics.
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