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Redesigning the Longitudinal Business Database
May 2021
Working Paper Number:
CES-21-08
In this paper we describe the U.S. Census Bureau's redesign and production implementation of the Longitudinal Business Database (LBD) first introduced by Jarmin and Miranda (2002). The LBD is used to create the Business Dynamics Statistics (BDS), tabulations describing the entry, exit, expansion, and contraction of businesses. The new LBD and BDS also incorporate information formerly provided by the Statistics of U.S. Businesses program, which produced similar year-to-year measures of employment and establishment flows. We describe in detail how the LBD is created from curation of the input administrative data, longitudinal matching, retiming of economic census-year births and deaths, creation of vintage consistent industry codes and noise factors, and the creation and cleaning of each year of LBD data. This documentation is intended to facilitate the proper use and understanding of the data by both researchers with approved projects accessing the LBD microdata and those using the BDS tabulations.
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Business-Level Expectations and Uncertainty
December 2020
Working Paper Number:
CES-20-41
The Census Bureau's 2015 Management and Organizational Practices Survey (MOPS) utilized innovative methodology to collect five-point forecast distributions over own future shipments, employment, and capital and materials expenditures for 35,000 U.S. manufacturing plants. First and second moments of these plant-level forecast distributions covary strongly with first and second moments, respectively, of historical outcomes. The first moment of the distribution provides a measure of business' expectations for future outcomes, while the second moment provides a measure of business' subjective uncertainty over those outcomes. This subjective uncertainty measure correlates positively with financial risk measures. Drawing on the Annual Survey of Manufactures and the Census of Manufactures for the corresponding realizations, we find that subjective expectations are highly predictive of actual outcomes and, in fact, more predictive than statistical models fit to historical data. When respondents express greater subjective uncertainty about future outcomes at their plants, their forecasts are less accurate. However, managers supply overly precise forecast distributions in that implied confidence intervals for sales growth rates are much narrower than the distribution of actual outcomes. Finally, we develop evidence that greater use of predictive computing and structured management practices at the plant and a more decentralized decision-making process (across plants in the same firm) are associated with better forecast accuracy.
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Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey
December 2020
Working Paper Number:
CES-20-40
We introduce a new survey module intended to complement and expand research on the causes and consequences of advanced technology adoption. The 2018 Annual Business Survey (ABS), conducted by the Census Bureau in partnership with the National Center for Science and Engineering Statistics (NCSES), provides comprehensive and timely information on the diffusion among U.S. firms of advanced technologies including artificial intelligence (AI), cloud computing, robotics, and the digitization of business information. The 2018 ABS is a large, nationally representative sample of over 850,000 firms covering all private, nonfarm sectors of the economy. We describe the motivation for and development of the technology module in the ABS, as well as provide a first look at technology adoption and use patterns across firms and sectors. We find that digitization is quite widespread, as is some use of cloud computing. In contrast, advanced technology adoption is rare and generally skewed towards larger and older firms. Adoption patterns are consistent with a hierarchy of increasing technological sophistication, in which most firms that adopt AI or other advanced business technologies also use the other, more widely diffused technologies. Finally, while few firms are at the technology frontier, they tend to be large so technology exposure of the average worker is significantly higher. This new data will be available to qualified researchers on approved projects in the Federal Statistical Research Data Center network.
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How Does State-Level Carbon Pricing in the United States Affect Industrial Competitiveness?
June 2020
Working Paper Number:
CES-20-21
Pricing carbon emissions from an individual jurisdiction may harm the competitiveness of local firms, causing the leakage of emissions and economic activity to other regions. Past research concentrates on national carbon prices, but the impacts of subnational carbon prices could be more severe due to the openness of regional economies. We specify a flexible model to capture competition between a plant in a state with electric sector carbon pricing and plants in other states or countries without such pricing. Treating energy prices as a proxy for carbon prices, we estimate model parameters using confidential plant-level Census data, 1982'2011. We simulate the effects on manufacturing output and employment of carbon prices covering the Regional Greenhouse Gas Initiative (RGGI) in the Northeast and Mid-Atlantic regions. A carbon price of $10 per metric ton on electricity output reduces employment in the regulated region by 2.7 percent, and raises employment in nearby states by 0.8 percent, although these estimates do not account for revenue recycling in the RGGI region that could mitigate these employment changes. The effects on output are broadly similar. National employment falls just 0.1 percent, suggesting that domestic plants in other states as opposed to foreign facilities are the principal winners from state or regional carbon pricing.
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The Disappearing IPO Puzzle: New Insights from Proprietary U.S. Census Data on Private Firms
June 2020
Working Paper Number:
CES-20-20
The U.S. equity markets have experienced a remarkable decline in IPOs since 2000, both in terms of smaller IPO volume and entrepreneurial firms' greater tendency to exit through acquisitions rather than IPOs. Using proprietary U.S. Census data on private firms, we conduct a comprehensive analysis of the above two notable trends and provide several new insights. First, we find that the dramatic reduction in U.S. IPOs is not due to a weaker economy that is unable to produce enough 'exit eligible' private firms: in fact, the average total factor productivity (TFP) of private firms is slightly higher post-2000 compared to pre-2000. Second, we do not find evidence supporting the conventional wisdom that the disappearing IPO puzzle is mainly driven by the decline in IPO propensity among small private firms. Third, we do not find a significant change in the characteristics of private firms exiting through acquisitions from pre- to post-2000. Fourth, the decline in IPO propensity persists even after we account for the changing characteristics of private firms over time. Fifth, we show that the difference in TFP between IPO firms and acquired firms (and between IPO firms and firms remaining private) went up considerably post-2000 compared to pre-2000. Finally, venture-capital-backed (VC-backed) IPO firms have significantly lower postexit long-term TFP than matched VC-backed private firms in the post-2000 era relative to the pre- 2000 era, while this pattern is absent among IPO and matched private firms without VC backing. Overall, our results strongly support the explanations based on standalone public firms' greater sensitivity to product market competition and entrepreneurial firms' access to more abundant private equity financing in the post-2000 era. We find mixed evidence regarding the explanations based on the smaller net financial benefits of being standalone public firms or the increased need for confidentiality after 2000.
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The Micro-Level Anatomy of the Labor Share Decline
March 2020
Working Paper Number:
CES-20-12
The labor share in U.S. manufacturing declined from 62 percentage points (ppts) in 1967 to 41 ppts in 2012. The labor share of the typical U.S. manufacturing establishment, in contrast, rose by over 3 ppts during the same period. Using micro-level data, we document five salient facts: (1) since the 1980s, there has been a dramatic reallocation of value added toward the lower end of the labor share distribution; (2) this aggregate reallocation is not due to entry/exit, to 'superstars" growing faster or to large establishments lowering their labor shares, but is instead due to units whose labor share fell as they grew in size; (3) low labor share (LL) establishments benefit from high revenue labor productivity, not low wages; (4) they also enjoy a product price premium relative to their peers, pointing to a significant role for demand-side forces; and (5) they have only temporarily lower labor shares that rebound after five to eight years. This transient pattern has become more pronounced over time, and the dynamics of value added and employment are increasingly disconnected.
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Do 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.
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Misallocation 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.
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What Do Establishments Do When Wages Increase?
Evidence from Minimum Wages in the United States
November 2019
Working Paper Number:
CES-19-31
I investigate how establishments adjust their production plans on various margins when wage rates increase. Exploiting state-by-year variation in minimum wage, I analyze U.S. manufacturing plants' responses over a 23-year period. Using instrumental variable method and Census Microdata, I find that when the hourly wage of production workers increases by one percent, manufacturing plants reduce the total hours worked by production workers by 0.7 percent and increase capital expenditures on machinery and equipment by 2.7 percent. The reduction in total hours worked by production workers is driven by intensive-margin changes. The estimated elasticity of substitution between capital and labor is 0.85. Following the wage increases, no statistically significant changes emerge in revenue, materials or total factor productivity. Additionally, I nd that when wage rates increase, establishments are more likely to exit the market. Finally, I provide evidence that when the minimum wage increases the wages of some of the establishments in a firm, the firm also increases the wages for its other establishments.
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MANAGING TRADE: EVIDENCE FROM CHINA AND THE US
May 2019
Working Paper Number:
CES-19-15
We present a heterogeneous-firm model in which management ability increases both production efficiency and product quality. Combining six micro-datasets on management practices, production and trade in Chinese and American firms, we find broad support for the model's predictions. First, better managed firms are more likely to export, sell more products to more destination countries, and earn higher export revenues and profits. Second, better managed exporters have higher prices, higher quality, and lower quality-adjusted prices. Finally, they also use a wider range of inputs, higher quality and more expensive inputs, and imported inputs from more advanced countries. The structural estimates indicate that management is important for improving production efficiency and product quality in both countries, but it matters more in China than in the US, especially for product quality. Panel analysis for the US and a randomized control trial in India suggest that management exerts causal effects on product quality, production efficiency, and exports. Poor management practices may thus hinder trade and growth, especially in developing countries.
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