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Locally Owned Bank Commuting Zone Concentration and Employer Start-Ups in Metropolitan, Micropolitan and Non-Core Rural Commuting Zones from 1970-2010
August 2018
Working Paper Number:
CES-18-34
Access to financial capital is vital for the sustainability of the local business sector in metropolitan and nonmetropolitan communities. Recent research on the restructuring of the financial industry from local owned banks to interstate conglomerates has raised questions about the impact on rural economies. In this paper, we begin our exploration of the Market Concentration Hypothesis and the Local Bank Hypothesis. The former proposes that there is a negative relationship between the percent of banks that are locally owned in the local economy and the rate of business births and continuations, and a positive effect on business deaths, while that latter proposes that there is a positive relationship between the percent of banks that are locally owned in the local economy and the rate of business births and continuations, and a negative effect on business deaths. To examine these hypotheses, we examine the impact of bank ownership concentration (percent of banks that are locally owned in a commuting zone) on business establishment births and deaths in metropolitan, micropolitan and non-core rural commuting zones. We employ panel regression models for the 1980-2010 time frame, demonstrating robustness to several specifications and spatial spillover effects. We find that local bank concentration is positively related to business dynamism in rural commuting zones, providing support to the importance of relational lending in rural areas, while finding support for the importance of market concentration in urban areas. The implications of this research are important for rural sociology, regional economics, and finance.
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The Effects of Industry Classification Changes on US Employment Composition
June 2018
Working Paper Number:
CES-18-28
This paper documents the extent to which compositional changes in US employment from 1976 to 2009 are due to changes in the industry classification scheme used to categorize economic
activity. In 1997, US statistical agencies began implementation of a change from the Standard Industrial Classification System (SIC) to the North American Industrial Classification System (NAICS). NAICS was designed to provide a consistent classification scheme that consolidated declining or obsolete industries and added categories for new industries. Under NAICS, many activities previously classified as Manufacturing, Wholesale Trade, or Retail Trade were re-classified into the Services sector. This re-classification resulted in a significant shift of measured activities across sectors without any change in underlying economic activity. Using a newly developed establishment-level database of employment activity that is consistently classified on a NAICS basis, this paper shows that the change from SIC to NAICS increased the share of Services employment by approximately 36 percent. 7.6 percent of US manufacturing employment, equal to approximately 1.4 million jobs, was reclassified to services. Retail trade and wholesale trade also experienced a significant reclassification of activities in the transition.
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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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New Perspectives on the Decline of U.S.
Manufacturing Employment
April 2018
Working Paper Number:
CES-18-17
We use relatively unexplored dimensions of US microdata to examine how US manufacturing employment has evolved across industries, rms, establishments, and regions. We show that these data provide support for both trade- and technology-based explanations of the overall decline of employment over this period, while also highlighting the di-culties of estimating an overall contribution for each mechanism. Toward that end, we discuss how further analysis of these trends might yield sharper insights.
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Small and Large Firms Over the Business Cycle
February 2018
Working Paper Number:
CES-18-09
Drawing on a new, con dential Census Bureau dataset of financial statements of a representative sample of 80000 manufacturing firms from 1977 to 2014, we provide new evidence on the link between size, cyclicality, and financial frictions. First, we only find evidence of lower cyclicality among the very largest firms (the top 1% by size). Second, due to high and rising concentration of sales and investment, the lower sensitivity of the top 1% firms dominates the behavior of aggregate fluctuations. Third, we show that this differential sensitivity does not appear to be driven by financial frictions. The higher sensitivity of the bottom 99% does not disappear after controlling for measures of financial strength, is not statistically significant after
identified monetary policy shocks, and does not appear in debt financing flows. Evidence from 3-digit industries suggests a non-financial explanation: the largest 1% of firms are less sensitive due to a more diversified customer base.
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Estimating Unequal Gains across U.S. Consumers with Supplier Trade Data
January 2018
Working Paper Number:
CES-18-04
Using supplier-level trade data, we estimate the effect on consumer welfare from changes in U.S. imports both in the aggregate and for different household income groups from 1998 to 2014. To do this, we use consumer preferences which feature non-homotheticity both within sectors and across sectors. After structurally estimating the parameters of the model, using the universe of U.S. goods imports, we construct import price indexes in which a variety is defined as a foreign establishment producing an HS10 product that is exported to the United States. We find that lower income households experienced the most import price inflation, while higher income households experienced the least import price inflation during our time period. Thus, we do not find evidence that the consumption channel has mitigated the distributional effects of trade that have occurred through the nominal income channel in the United States over the past two decades.
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High Growth Young Firms: Contribution to Job, Output and Productivity Growth
February 2017
Working Paper Number:
carra-2017-03
Recent research shows that the job creating prowess of small firms in the U.S. is better attributed to startups and young firms that are small. But most startups and young firms either fail or don't create jobs. A small proportion of young firms grow rapidly and they account for the long lasting contribution of startups to job growth. High growth firms are not well understood in terms of either theory or evidence. Although the evidence of their role in job creation is mounting, little is known about their life cycle dynamics, or their contribution to other key outcomes such as real output growth and productivity. In this paper, we enhance the Longitudinal Business Database with gross output (real revenue) measures. We find that the patterns for high output growth firms largely mimic those for high employment growth firms. High growth output firms are disproportionately young and make disproportionate contributions to output and productivity growth. The share of activity accounted for by high growth output and employment firms varies substantially across industries - in the post 2000 period the share of activity accounted for by high growth firms is significantly higher in the High Tech and Energy related industries. A firm in a small business intensive industry is less likely to be a high output growth firm but small business intensive industries don't have significantly smaller shares of either employment or output activity accounted for by high growth firms.
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Business Dynamic Statistics of Innovative Firms
January 2017
Working Paper Number:
CES-17-72
A key driver of economic growth is the reallocation of resources from low to high productivity activities. Innovation plays an important role in this regard by introducing new products, services, and business methods that ultimately lead to increased productivity and rising living standards. Traditional measures of innovation, particularly those based on aggregate inputs, are increasingly unable to capture the breadth and depth of innovation in modern economies. In this paper, we describe an effort at the
US Census Bureau, the Business Dynamics Statistics of Innovative Firms (BDS-IF) project, which aims to address these challenges by extending the Business Dynamics Statistics data to include new measures of innovative activity. The BDS-IF project will produce measures of firm, establishment, and employment flows by firm age, firm size, and industry for the subset of firms engaged in activities related to innovation. These activities include patenting and trademarking, the employment of STEM workers, and R&D expenditures. The exibility of the underlying data infrastructure allows this measurement agenda to be extended to include copyright activity, management practices, and high growth firms.
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The Annual Survey of Entrepreneurs: An Update
January 2017
Working Paper Number:
CES-17-46
We provide an update on the Annual Survey of Entrepreneurs (ASE), which is a relatively new Census Bureau business survey. About 290,000 employer firms in the private, non-agricultural U.S. economy are in the ASE sample. Its content is relatively constant over collections, allowing for comparability over time; however, each year there are approximately ten new questions in a changing topical module. Earlier topical modules covered innovation (2014) and management practices (2015). The topical module for reference year 2016 covers business advice and planning, finance, and regulations. The ASE is collected through a partnership of the Census Bureau with the Kauffman Foundation and the Minority Business Development Agency. Qualified researchers on approved projects may request access to the ASE micro data through the Federal Statistical Research Data Center (FSRDC) network.
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Macro 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).
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