Recent research maintains that the observed variation in productivity within industries reflects resource misallocation and concludes that large GDP gains may be obtained from market-liberalizing polices. Our theoretical analysis examines the impact on productivity dispersion of reallocation frictions in the form of costs of entry, operation, and restructuring, and shows that reforms reducing these frictions may raise dispersion of productivity across firms. The model does not imply a negative relationship between aggregate productivity and productivity dispersion. Our empirical analysis focuses on episodes of liberalizing policy reforms in the U.S. and six East European transition economies. Deregulation of U.S. telecommunications equipment manufacturing is associated with increased, not reduced, productivity dispersion, and every transition economy in our sample shows a sharp rise in dispersion after liberalization. Productivity dispersion under central planning is similar to that in the U.S., and it rises faster in countries adopting faster paces of liberalization. Lagged productivity dispersion predicts higher future productivity growth. The analysis suggests there is no simple relationship between the policy environment and productivity dispersion.
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Entry, Growth, and the Business Environment: A Comparative Analysis of Enterprise Data from the U.S. and Transition Economies
September 2010
Working Paper Number:
CES-10-20
What role does new firm entry play in economic growth? Are entrants and young firms more or less productive than incumbents, and how are their relative productivity dynamics affected by financial constraints and the business environment? This paper uses comprehensive manufacturing firm data from seven economies (United States, Georgia, Hungary, Lithuania, Romania, Russia, and Ukraine) to measure new firm entry and the productivity dynamics of entrants relative to incumbents in the same industries. We contrast hypotheses based on 'leapfrogging,' in which entrants embody superior productivity, with an 'experimentation' approach, in which entrants face uncertainty and incumbents can innovate. The results imply that leapfrogging is typical of early and incomplete transition, but experimentation better characterizes both the US and mature transition economies. Improvements in financial markets and the business environment tend to raise both the entry rate and productivity growth, but they are associated with negative relative productivity of entrants and smaller contributions of reallocation to growth among both entrants and incumbents.
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Misallocation 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.
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The Impact of Vintage and Survival on Productivity: Evidence from Cohorts of U.S. Manufacturing Plants
May 2000
Working Paper Number:
CES-00-06
This paper examines the evolution of productivity in U.S. manufacturing plants from 1963 to 1992. We define a 'vintage effect' as the change in productivity of recent cohorts of new plants relative to earlier cohorts of new plants, and a 'survival effect' as the change in productivity of a particular cohort of surviving plants as it ages. The data show that both factors contribute to industry productivity growth, but play offsetting roles in determining a cohort's relative position in the productivity distribution. Recent cohorts enter with significantly higher productivity than earlier entrants did, while surviving cohorts show significant increases in productivity as they age. These two effects roughly offset each other, however, so there is a rough convergence in productivity across cohorts in 1992 and 1987. (JEL Code: D24, L6)
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Productivity 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.
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The Life Cycle of Plants in India and Mexico
September 2012
Working Paper Number:
CES-12-20
In the U.S., the average 40 year old plant employs almost eight times as many workers as the typical plant five years or younger. In contrast, surviving Indian plants exhibit little growth in terms of either employment or output. Mexico is intermediate to India and the U.S. in these respects: the average 40 year old Mexican plant employs twice as many workers as an average new plant. This pattern holds across many industries and for formal and informal establishments alike. The divergence in plant dynamics suggests lower investments by Indian and Mexican plants in process efficiency, quality, and in accessing markets at home and abroad. In simple GE models, we find that the difference in life cycle dynamics could lower aggregate manufacturing productivity on the order of 25% in India and Mexico relative to the U.S.
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Punctuated Entrepreneurship (Among Women)
May 2018
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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Decomposing Aggregate Productivity
July 2022
Working Paper Number:
CES-22-25
In this note, we evaluate the sensitivity of commonly-used decompositions for aggregate productivity. Our analysis spans the universe of U.S. manufacturers from 1977 to 2012 and we find that, even holding the data and form of the production function fixed, results on aggregate productivity are extremely sensitive to how productivity at the firm level is measured. Even qualitative statements about the levels of aggregate productivity and the sign of the covariance between productivity and size are highly dependent on how production function parameters are estimated. Despite these difficulties, we uncover some consistent facts about productivity growth: (1) labor productivity is consistently higher and less error-prone than measures of multi-factor productivity; (2) most productivity growth comes from growth within firms, rather than from reallocation across firms; (3) what growth does come from reallocation appears to be driven by net entry, primarily from the exit of relatively less-productive firms.
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Nature Versus Nurture in the Origins of Highly Productive Businesses: An Exploratory Analysis of U.S. Manufacturing Establishments
September 2011
Working Paper Number:
CES-11-26
This paper investigates the origins of productivity leaders, those that operate close to and help push out the production frontier. Do such businesses emerge as top performers from the very beginning of their lives, for example as the consequence of an outstanding founding idea, technology, or location? Or, at the other extreme, do they appear initially as completely average (or even underperformers) that exhibit gradual improvement as they learn and develop with age? To answer this question we draw upon five decades of U.S. Census of Manufacturing (CM) establishment-level data, tracing the productivity leaders of the most recent CM (2007) back over their observed life spans. We also examine possible industry-level correlates of variation in the extent of nature versus nurture that are suggested by theories of industry dynamics and economic growth.
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Dispersion 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.
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Are We Undercounting Reallocation's Contribution to Growth?
January 2013
Working Paper Number:
CES-13-55R
There has been a strong surge in aggregate productivity growth in India since 1990, following
significant economic reforms. Three recent studies have used two distinct methodologies to decompose the sources of growth, and all conclude that it has been driven by within-plant increases in technical efficiency and not between-plant reallocation of inputs. Given the nature of the reforms, where many barriers to input reallocation were removed, this finding has surprised researchers and been dubbed 'India's Mysterious Manufacturing Miracle.' In this paper, we show that the methodologies used may artificially understate the extent of reallocation. One approach, using growth in value added, counts all reallocation growth arising from the movement of intermediate inputs as technical efficiency growth. The second approach, using the Olley-Pakes decomposition, uses estimates of plant-level total factor productivity (TFP) as a proxy for the marginal product of inputs. However, in equilibrium, TFP and the marginal product of inputs are unrelated. Using microdata on manufacturing from five countries ' India, the U.S., Chile, Colombia, and Slovenia ' we show that both approaches significantly understate the true
role of reallocation in economic growth. In particular, reallocation of materials is responsible for over half of aggregate Indian manufacturing productivity growth since 2000, substantially larger than either the contribution of primary inputs or the change in the covariance of productivity and size.
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