Papers Containing Keywords(s): 'production'
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Authors
Sang V Nguyen - 17
John Haltiwanger - 16
Lucia Foster - 16
Andrew Bernard - 13
J. Bradford Jensen - 11
Viewing papers 31 through 40 of 246
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Working PaperGrowing Oligopolies, Prices, Output, and Productivity
November 2018
Working Paper Number:
CES-18-48
American industries have grown more concentrated over the last forty years. In the absence of productivity innovation, this should lead to price hikes and output reductions, decreasing consumer welfare. Using public data from 1972-2012, I use price data to disentangle revenue from output. Difference-in-difference estimates show that industry concentration increases are positively correlated to productivity and real output growth, uncorrelated with price changes and overall payroll, and negatively correlated with labor's revenue share. I rationalize these results in a simple model of competition. Productive industries (with growing oligopolists) expand real output and hold down prices, raising consumer welfare, while maintaining or reducing their workforces, lowering labor's share of output.View Full Paper PDF
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Working PaperA Portrait of U.S. Factoryless Goods Producers
October 2018
Working Paper Number:
CES-18-43
This paper evaluates the U.S. Census Bureau's most recent data collection efforts to classify business entities that engage in an extreme form of production fragmentation called 'factoryless' goods production. 'Factoryless' goods-producing entities outsource physical transformation activities while retaining ownership of the intellectual property and control of sales to customers. Responses to a special inquiry on the incidence of purchases of contract manufacturing services in combination with data on production inputs and outputs, intellectual property, and international trade is used to identify and document characteristics of 'factoryless' firms in the U.S. economy.View Full Paper PDF
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Working PaperAutomation, Labor Share, and Productivity: Plant-Level Evidence from U.S. Manufacturing
September 2018
Working Paper Number:
CES-18-39
This paper provides new evidence on the plant-level relationship between automation, labor and capital usage, and productivity. The evidence, based on the U.S. Census Bureau's Survey of Manufacturing Technology, indicates that more automated establishments have lower production labor share and higher capital share, and a smaller fraction of workers in production who receive higher wages. These establishments also have higher labor productivity and experience larger long-term labor share declines. The relationship between automation and relative factor usage is modelled using a CES production function with endogenous technology choice. This deviation from the standard Cobb-Douglas assumption is necessary if the within-industry differences in the capital-labor ratio are determined by relative input price differences. The CES-based total factor productivity estimates are significantly different from the ones derived under Cobb-Douglas production and positively related to automation. The results, taken together with earlier findings of the productivity literature, suggest that the adoption of automation may be one mechanism associated with the rise of superstar firms.View Full Paper PDF
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Working PaperRegulating Mismeasured Pollution: Implications of Firm Heterogeneity for Environmental Policy
August 2018
Working Paper Number:
CES-18-03R
This paper provides the first estimates of within-industry heterogeneity in energy and CO2 productivity for the entire U.S. manufacturing sector. We measure energy and CO2 productivity as output per dollar energy input or per ton CO2 emitted. Three findings emerge. First, within narrowly defined industries, heterogeneity in energy and CO2 productivity across plants is enormous. Second, heterogeneity in energy and CO2 productivity exceeds heterogeneity in most other productivity measures, like labor or total factor productivity. Third, heterogeneity in energy and CO2 productivity has important implications for environmental policies targeting industries rather than plants, including technology standards and carbon border adjustments.View Full Paper PDF
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Working PaperDispersion in Dispersion: Measuring Establishment-Level Differences in Productivity
April 2018
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.View Full Paper PDF
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Working PaperMissing Growth from Creative Destruction
April 2018
Working Paper Number:
CES-18-18
Statistical agencies typically impute inflation for disappearing products based on surviving products, which may result in overstated inflation and understated growth. Using U.S. Census data, we apply two ways of assessing the magnitude of 'missing growth' for private nonfarm businesses from 1983'2013. The first approach exploits information on the market share of surviving plants. The second approach applies indirect inference to firm-level data. We find: (i) missing growth from imputation is substantial ' at least 0.6 percentage points per year; and (ii) most of the missing growth is due to creative destruction (as opposed to new varieties).View Full Paper PDF
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Working PaperInnovation, Productivity Dispersion, and Productivity Growth
February 2018
Working Paper Number:
CES-18-08
We examine whether underlying industry innovation dynamics are an important driver of the large dispersion in productivity across firms within narrowly defined sectors. Our hypothesis is that periods of rapid innovation are accompanied by high rates of entry, significant experimentation and, in turn, a high degree of productivity dispersion. Following this experimentation phase, successful innovators and adopters grow while unsuccessful innovators contract and exit yielding productivity growth. We examine the dynamic relationship between entry, productivity dispersion, and productivity growth using a new comprehensive firm-level dataset for the U.S. We find a surge of entry within an industry yields an immediate increase in productivity dispersion and a lagged increase in productivity growth. These patterns are more pronounced for the High Tech sector where we expect there to be more innovative activities. These patterns change over time suggesting other forces are at work during the post-2000 slowdown in aggregate productivity.View Full Paper PDF
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Working PaperMacro and Micro Dynamics of Productivity: From Devilish Details to Insights
January 2017
Working Paper Number:
CES-17-41R
Researchers use a variety of methods to estimate total factor productivity (TFP) at the firm level and, while these may seem broadly equivalent, how the resulting measures relate to the TFP concept in theoretical models depends on the assumptions about the environment in which firms operate. Interpreting these measures and drawing insights based upon their characteristics thus must take into account these conceptual differences. Absent data on prices and quantities, most methods yield 'revenue productivity' measures. We focus on two broad classes of revenue productivity measures in our examination of the relationship between measured and conceptual TFP (TFPQ). The first measure has been increasingly used as a measure of idiosyncratic distortions and to assess the degree of misallocation. The second measure is, under standard assumptions, a function of funda- mentals (e.g., TFPQ). Using plant-level U.S. manufacturing data, we find these alternative measures are (i) highly correlated; (ii) exhibit similar dispersion; and (iii) have similar relationships with growth and survival. These findings raise questions about interpreting the first measure as a measure of idiosyncratic distortions. We also explore the sensitivity of estimates of the contribution of reallocation to aggregate productivity growth to these alternative approaches. We use recently developed structural decompositions of aggregate productivity growth that depend critically on estimates of output versus revenue elasticities. We find alternative approaches all yield a significant contribution of reallocation to productivity growth (although the quantitative contribution varies across approaches).View Full Paper PDF
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Working PaperWhat Drives Differences in Management?
January 2017
Working Paper Number:
CES-17-32
Partnering with the Census we implement a new survey of 'structured' management practices in 32,000 US manufacturing plants. We find an enormous dispersion of management practices across plants, with 40% of this variation across plants within the same firm. This management variation accounts for about a fifth of the spread of productivity, a similar fraction as that accounted for by R&D and twice as much as explained by IT. We find evidence for four 'drivers' of management: competition, business environment, learning spillovers and human capital. Collectively, these drivers account for about a third of the dispersion of structured management practices.View Full Paper PDF
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Working PaperAn Empirical Analysis of Capacity Costs
January 2017
Working Paper Number:
CES-17-26
A central premise of management accounting is that including the cost of unused capacity in product costs can distort these costs and misguide users. Yet, there is little large-scale empirical evidence on the materiality of the cost of unused capacity. This study uses a confidential Census sample of 151,900 U.S. manufacturing plants from 1974-2011 to investigate the impact of separating the cost of unused capacity. We find that excluding the cost of unused capacity increases operating profit margins by approximately 26 percent. This order of magnitude is economically significant, and is pervasive across industries and over time. In additional analyses, we find that separating the cost of unused capacity largely smooths the time-series variation in unitized product costs and profit margins. Our finding of higher mean and lower variation of adjusted margins should be of considerable interest to both investors and managers.View Full Paper PDF
