Papers Containing Keywords(s): 'productivity size'
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Authors
Sang V Nguyen - 4
Viewing papers 1 through 10 of 12
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Working PaperEntry Costs Rise with Growth
October 2024
Working Paper Number:
CES-24-63
Over time and across states in the U.S., the number of firms is more closely tied to overall employment than to output per worker. In many models of firm dynamics, trade, and growth with a free entry condition, these facts imply that the costs of creating a new firm increase sharply with productivity growth. This increase in entry costs can stem from the rising cost of labor used in entry and weak or negative knowledge spillovers from prior entry. Our findings suggest that productivity-enhancing policies will not induce firm entry, thereby limiting the total impact of such policies on welfare.View Full Paper PDF
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Working PaperDecomposing 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.View Full Paper PDF
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Working PaperDo Short-Term Incentives Affect Long-Term Productivity?
March 2020
Working Paper Number:
CES-20-10
Previous research shows that stock repurchases that are caused by earnings management lead to reductions in firm-level investment and employment. It is natural to expect firms to cut less productive investment and employment first, which could lead to a positive effect on firm-level productivity. However, using Census data, we find that firms make cuts across the board irrespective of plant productivity. This pattern seems to be associated with frictions in the labor market. Specifically, we find evidence that unionization of the labor force may prevent firms from doing efficient downsizing, forcing them to engage in easy or expedient downsizing instead. As a result of this inefficient downsizing, EPS-driven repurchases lead to a reduction in long-term productivity.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 PaperComputer Networks and Productivity Revisited: Does Plant Size Matter? Evidence and Implications
September 2010
Working Paper Number:
CES-10-25
Numerous studies have documented a positive association between information technology (IT) investments and business- and establishment-level productivity, but these studies usually pay sole or disporportionate attention to small- or medium-sized entities. In this paper, we revisit the evidence for manufacturing plants presented in Atrostic and Nguyen (2005) and show that the positive relationship between computer networks and labor productivity is only found among small- and medium-sized plants. Indeed, for larger plants the relationship is negative, and employment-weighted estimates indicate computer networks have a negative relationship with the productivity of employees, on average. These findings indicate that computer network investments may have an ambiguous relationship with aggregate labor productivity growth.View Full Paper PDF
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Working PaperAn Alternative Theory of the Plant Size Distribution with an Application to Trade
May 2010
Working Paper Number:
CES-10-10
There is wide variation in the sizes of manufacturing plants, even within the most narrowly defined industry classifications used by statistical agencies. Standard theories attribute all such size differences to productivity differences. This paper develops an alternative theory in which industries are made up of large plants producing standardized goods and small plants making custom or specialty goods. It uses confidential Census data to estimate the parameters of the model, including estimates of plant counts in the standardized and specialty segments by industry. The estimated model fits the data relatively well compared with estimates based on standard approaches. In particular, the predictions of the model for the impacts of a surge in imports from China are consistent with what happened to U.S. manufacturing industries that experienced such a surge over the period 1997'2007. Large-scale standardized plants were decimated, while small-scale specialty plants were relatively less impacted.View Full Paper PDF
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Working PaperComputer Network Use and Firms' Productivity Performance: The United States vs. Japan
September 2008
Working Paper Number:
CES-08-30
This paper examines the relationship between computer network use and firms' productivity performance, using micro-data of the United States and Japan. To our knowledge, this is the first comparative analysis using firm-level data for the manufacturing sector of both countries. We find that the links between IT and productivity differ between U.S. and Japanese manufacturing. Computer networks have positive and significant links with labor productivity in both countries. However, that link is roughly twice as large in the U.S. as in Japan. Differences in how businesses use computers have clear links with productivity for U.S. manufacturing, but not in Japan. For the United States, the coefficients of the intensity of network use are positive and increase with the number of processes. Coefficients of specific uses of those networks are positive and significant. None of these coefficients are significant for Japan. Our findings are robust to alternative econometric specifications. They also are robust to expanding our sample from single-unit manufacturing firms, which are comparable in the two data sets, to the entire manufacturing sector in each country, as well as to the wholesale and retail sector of Japan.View Full Paper PDF
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Working PaperThe 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.View Full Paper PDF
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Working PaperHow Businesses Use Information Technology: Insights for Measuring Technology and Productivity
June 2006
Working Paper Number:
CES-06-15
Business use of computers in the United States dates back fifty years. Simply investing in information technology is unlikely to offer a competitive advantage today. Differences in how businesses use that technology should drive differences in economic performance. Our previous research found that one business use ' computers linked into networks ' is associated with significantly higher labor productivity. In this paper, we extend our analysis with new information about the ways that businesses use their networks. Those data show that businesses conduct a variety of general processes over computer networks, such as order taking, inventory monitoring, and logistics tracking, with considerable heterogeneity among businesses. We find corresponding empirical diversity in the relationship between these on-line processes and productivity, supporting the heterogeneity hypothesis. On-line supply chain activities such as order tracking and logistics have positive and statistically significant productivity impacts, but not processes associated with production, sales, or human resources. The productivity impacts differ by plant age, with higher impacts in new plants. This new information about the ways businesses use information technology yields vital raw material for understanding how using information technology improves economic performance.View Full Paper PDF
