Papers Containing Keywords(s): 'productivity distribution'
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Viewing papers 1 through 8 of 8
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Working PaperAllocating Misallocation: Decomposing Measures of Aggregate Allocative Efficiency
April 2026
Working Paper Number:
CES-26-26
We explore sources of measured misallocation using establishment data from U.S. manufacturing industries. We decompose standard revenue productivity dispersion statistics into contributions by dispersion in revenue margins over costs and dispersion in input cost shares across plants. We establish a formal link between these components and measured allocative efficiency. The results indicate the components contribute similarly to apparent rising misallocation in US manufacturing. We use the mapping between distortions that influence these distinct components to explore the relationship between inferred distortions and mechanisms that influence one or both sources of revenue productivity dispersion. Finally, we show rising misallocation in the US manufacturing sector in the last several decades is pervasive, and yet a few industries account for over half of the aggregate decline.View Full Paper PDF
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Working PaperNational Chains and Trends in Retail Productivity Dispersion
September 2025
Working Paper Number:
CES-25-64
Productivity dispersion within an industry is an important characteristic of the business environment, potentially reflecting factors such as market structure, production technologies, and reallocation frictions. The retail trade sector saw significant changes between 1987 and 2017, and dispersion statistics can help characterize how it evolved over this period. In this paper, we shed light on this transformation by developing public-use Dispersion Statistics on Productivity (DiSP) data for the retail sector for 1987 through 2017. We find that from 1987 through 2017, dispersion increased between retail stores at the bottom and middle of the productivity distribution. However, when we weight stores by employment dispersion, the middle of the distribution is lower initially and decreases over time. These patterns are consistent with a retail landscape featuring more and more activity taking place in chain stores with similar productivity. Firm-based dispersion measures exhibit a similar pattern. Further investigation reveals that there is substantial heterogeneity in dispersion levels across industries.View Full Paper PDF
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Working PaperProductivity Dispersion, Entry, and Growth in U.S. Manufacturing Industries
August 2021
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.View Full Paper PDF
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Working PaperMisallocation or Mismeasurement?
February 2020
Working Paper Number:
CES-20-07
The ratio of revenue to inputs differs greatly across plants within countries such as the U.S. and India. Such gaps may reflect misallocation which hinders aggregate productivity. But differences in measured average products need not reflect differences in true marginal products. We propose a way to estimate the gaps in true marginal products in the presence of measurement error. Our method exploits how revenue growth is less sensitive to input growth when a plant's average products are overstated by measurement error. For Indian manufacturing from 1985'2013, our correction lowers potential gains from reallocation by 20%. For the U.S. the effect is even more dramatic, reducing potential gains by 60% and eliminating 2/3 of a severe downward trend in allocative efficiency over 1978'2013.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 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 PaperProductivity Dispersion and Plant Selection in the Ready-Mix Concrete Industry
September 2011
Working Paper Number:
CES-11-25
This paper presents a quantitative model of productivity dispersion to explain why inefficient producers are slowly selected out of the ready-mix concrete industry. Measured productivity dispersion between the 10th and 90th percentile falls from a 4 to 1 difference using OLS, to a 2 to 1 difference using a control function. Due to volatile productivity and high sunk entry costs, a dynamic oligopoly model shows that to rationalize small gaps in exit rates between high and low productivity plants, a plant in the top quintile must produce 1.5 times more than a plant in the bottom quintile.View Full Paper PDF
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Working PaperMisallocation and Manufacturing TFP in China and India
February 2009
Working Paper Number:
CES-09-04
Resource misallocation can lower aggregate total factor productivity (TFP). We use micro data on manufacturing establishments to quantify the potential extent of misallocation in China and India compared to the U.S. Compared to the U.S., we measure sizable gaps in marginal products of labor and capital across plants within narrowly-defined industries in China and India. When capital and labor are hypothetically reallocated to equalize marginal products to the extent observed in the U.S., we calculate manufacturing TFP gains of 30-50% in China and 40-60% in India.View Full Paper PDF
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