Papers Containing Keywords(s): 'estimates productivity'
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Sang V Nguyen - 3
Viewing papers 1 through 10 of 16
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Working PaperHousing Booms and the U.S. Productivity Puzzle
January 2020
Working Paper Number:
CES-20-04
The United States has been experiencing a slowdown in productivity growth for more than a decade. I exploit geographic variation across U.S. Metropolitan Statistical Areas (MSAs) to investigate the link between the 2006-2012 decline in house prices (the housing bust) and the productivity slowdown. Instrumental variable estimates support a causal relationship between the housing bust and the productivity slowdown. The results imply that one standard deviation decline in house prices translates into an increment of the productivity gap -- i.e. how much an MSA would have to grow to catch up with the trend -- by 6.9p.p., where the average gap is 14.51%. Using a newly-constructed capital expenditures measure at the MSA level, I find that the long investment slump that came out of the Great Recession explains an important part of this effect. Next, I document that the housing bust led to the investment slump and, ultimately, the productivity slowdown, mostly through the collapse in consumption expenditures that followed the bust. Lastly, I construct a quantitative general equilibrium model that rationalizes these empirical findings, and find that the housing bust is behind roughly 50 percent of the productivity slowdown.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 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 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 PaperThe Impact of Plant-Level Resource Reallocations and Technical Progress on U.S. Macroeconomic Growth
December 2009
Working Paper Number:
CES-09-43
We build up from the plant level an "aggregate(d) Solow residual" by estimating every U.S. manufacturing plant's contribution to the change in aggregate final demand between 1976 and 1996. We decompose these contributions into plant-level resource reallocations and plant-level technical efficiency changes. We allow for 459 different production technologies, one for each 4- digit SIC code. Our framework uses the Petrin and Levinsohn (2008) definition of aggregate productivity growth, which aggregates plant-level changes to changes in aggregate final demand in the presence of imperfect competition and other distortions and frictions. On average, we find that aggregate reallocation made a larger contribution than aggregate technical efficiency growth. Our estimates of the contribution of reallocation range from 1:7% to2:1% per year, while our estimates of the average contribution of aggregate technical efficiency growth range from 0:2% to 0:6% per year. In terms of cyclicality, the aggregate technical efficiency component has a standard deviation that is roughly 50% to 100% larger than that of aggregate total reallocation, pointing to an important role for technical efficiency in macroeconomic fluctuations. Aggregate reallocation is negative in only 3 of the 20 years of our sample, suggesting that the movement of inputs to more highly valued activities on average plays a stabilizing role in manufacturing growth.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 PaperComputer Investment, Computer Networks and Productivity
January 2005
Working Paper Number:
CES-05-01
Researchers in a large empirical literature find significant relationships between computers and labor productivity, but the estimated size of that relationship varies considerably. In this paper, we estimate the relationships among computers, computer networks, and plant-level productivity in U.S. manufacturing. Using new data on computer investment, we develop a sample with the best proxies for computer and total capital that the data allow us to construct. We find that computer networks and computer inputs have separate, positive, and significant relationships with U.S. manufacturing plant-level productivity. Keywords: computer input; information technology; labor productivityView Full Paper PDF
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Working PaperPollution Abatement Expenditures and Plant-Level Productivity: A Production Function Approach
August 2003
Working Paper Number:
CES-03-16
In this paper, we investigate the impact of environmental regulation on productivity using a Cobb-Douglas production function framework. Estimating the effects of regulation on productivity can be done with a top-down approach using data for broad sectors of the economy, or a more disaggregated bottom-up approach. Our study follows a bottom-up approach using data from the U.S. paper, steel, and oil industries. We measure environmental regulation using plant-level information on pollution abatement expenditures, which allows us to distinguish between productive and abatement expenditures on each input. We use annual Census Bureau information (1979-1990) on output, labor, capital, and material inputs, and pollution abatement operating costs and capital expenditures for 68 pulp and paper mills, 55 oil refineries, and 27 steel mills. We find that pollution abatement inputs generally contribute little or nothing to output, especially when compared to their '''productive''' equivalents. Adding an aggregate pollution abatement cost measure to a Cobb-Douglas production function, we find that a $1 increase in pollution abatement costs leads to an estimated productivity decline of $3.11, $1.80, and $5.98 in the paper, oil, and steel industries respectively. These findings imply substantial differences across industries in their sensitivity to pollution abatement costs, arguing for a bottom-up approach that can capture these differences. Further differentiating plants by their production technology, we find substantial differences in the impact of pollution abatement costs even within industries, with higher marginal costs at plants with more polluting technologies. Finally, in all three industries, plants concentrating on change-in-production-process abatement techniques have higher productivity than plants doing predominantly end-of-line abatement, but also seem to be more affected by pollution abatement operating costs. Overall, our results point to the importance using detailed, disaggregated analyses, even below the industry level, when trying to model the costs of forcing plants to reduce their emissions.View Full Paper PDF
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Working PaperThe Relation among Human Capital, Productivity and Market Value: Building Up from Micro Evidence
December 2002
Working Paper Number:
tp-2002-14
This paper investigates and evaluates the direct and indirect contribution of human capital to business productivity and shareholder value. The impact of human capital may occur in two ways: the specific knowledge of workers at businesses may directly increase business performance, or a skilled workforce may also indirectly act as a complement to improved technologies, business models or organizational practices. We use newly created firm-level measures of workforce human capital and productivity to examine links between those measures and the market value of the employing firm. The new human capital measures come from an integrated employer-employee data base under development at the US Census Bureau. We link these data to financial information from Compustat at the firm level, which provides measures of market value and tangible assets. The combination of these two sources permits examination of the link between human capital, productivity, and market value. There is a substantial positive relation between human capital and market value that is primarily related to the unmeasured personal characteristics of the employees, which are captured by the new measures.View Full Paper PDF
