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The Management and Organizational Practices Survey (MOPS): An Overview*
January 2016
Working Paper Number:
CES-16-28
Understanding productivity and business dynamics requires measuring production outputs and inputs. Through its surveys and use of administrative data, the Census Bureau collects information on production outputs and inputs including labor, capital, energy, and materials. With the introduction of the Management and Organizational Practices Survey (MOPS), the Census Bureau added information on another component of production: management. It has long been hypothesized that management is an important component of firm success, but until recently the study of management was confined to hypotheses, anecdotes, and case studies. Building upon the work of Bloom and Van Reenen (2007), the first-ever large scale survey of management practices in the United States, the MOPS, was conducted by the Census Bureau for 2010. A second, enhanced version of the MOPS is being conducted for 2015. The enhancement includes two new topics related to management: data and decision making (DDD) and uncertainty. As information technology has expanded plants are increasingly able to utilize data in their decision making. Structured management practices have been found to be complementary to DDD in earlier studies. Uncertainty has policy implications because uncertainty is found to be associated with reduced investment and employment. Uncertainty also plays a role in the targeting component of management.
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Where Has All the Skewness Gone? The Decline in High-Growth (Young) Firms in the U.S.
November 2015
Working Paper Number:
CES-15-43
The pace of business dynamism and entrepreneurship in the U.S. has declined over recent decades. We show that the character of that decline changed around 2000. Since 2000 the decline in dynamism and entrepreneurship has been accompanied by a decline in high-growth young firms. Prior research has shown that the sustained contribution of business startups to job creation stems from a relatively small fraction of high-growth young firms. The presence of these high-growth young firms contributes to a highly (positively) skewed firm growth rate distribution. In 1999, a firm at the 90th percentile of the employment growth rate distribution grew about 31 percent faster than the median firm. Moreover, the 90-50 differential was 16 percent larger than the 50-10 differential reflecting the positive skewness of the employment growth rate distribution. We show that the shape of the firm employment growth distribution changes substantially in the post-2000 period. By 2007, the 90-50 differential was only 4 percent larger than the 50-10, and it continued to exhibit a trend decline through 2011. The reflects a sharp drop in the 90th percentile of the growth rate distribution accounted for by the declining share of young firms and the declining propensity for young firms to be high-growth firms.
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The Annual Survey of Entrepreneurs: An Introduction
November 2015
Working Paper Number:
CES-15-40R
The Census Bureau continually seeks to improve its measures of the U.S. economy as part of its mission. In some cases this means expanding or updating the content of its existing surveys, expanding the use of administrative data, and/or exploring the use of privately collected data. When these options cannot provide the needed data, the Census Bureau may consider fielding a new survey to fill the gap. This paper describes one such new survey, the Annual Survey of Entrepreneurs (ASE). Innovations in content, format, and process are designed to provide high-quality, timely, frequent information on the activities of one of the important drivers of economic growth: entrepreneurship. The ASE is collected through a partnership of the Census Bureau with the Kauffman Foundation and the Minority Business Development Agency. The first wave of the ASE collection started in fall of 2015 (for reference period 2014) and results will be released in summer 2016. Qualified researchers on approved projects will be able to access micro data from the ASE through the Federal Statistical Research Data Center (FSRDC) network.
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Wealth, Tastes, and Entrepreneurial Choice
October 2015
Working Paper Number:
CES-15-34
The nonpecuniary benefits of managing a small business are a first order consideration for many nascent entrepreneurs, yet the preference for business ownership is mostly ignored in models of entrepreneurship and occupational choice. In this paper, we study a population with varying entrepreneurial tastes and wealth in a simple general equilibrium model of occupational choice. This choice yields several important results: (1) entrepreneurship can be thought of as a normal good, generating wealth effects independent of any financing constraints; (2) nonpecuniary entrepreneurs select into small-scale firms; and (3) subsidies designed to stimulate more business entry can have regressive distributional effects. Despite abstracting from other important considerations such as risk, financing constraints, and innovation, we show that nonpecuniary compensation is particularly relevant in discussions of small businesses.
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OWNER CHARACTERISTICS AND FIRM PERFORMANCE DURING THE GREAT RECESSION
September 2014
Working Paper Number:
CES-14-36
Minority owned businesses are an increasing important component of the U.S. economy, growing at twice the rate of all U.S. businesses between 2002 and 2007. However, a growing literature indicates that minority-owned businesses may have been especially impacted by the Great Recession. As house prices declined, foreclosures fell disproportionately on urban minority neighborhoods and one of the sources of credit for business owners was severely constrained. Using 2002-2011 data from the Longitudinal Business Database linked to the 2002 Survey of Business Owners, this paper adds to the literature by examining the employment growth and survival of minority and women employer businesses during the last decade, including the Great Recession. At first glance, our preliminary findings suggest that black and women-owned businesses underperform white, male-owned businesses, that Asian-owned businesses outperform other groups, and that Hispanic-owned businesses outperform non-Hispanic ones in regards to employment growth. However, when we look only at continuing firms, black-owned businesses outperform white-owned businesses in terms of employment growth. At the same time, we also find that the recession appears to have impacted black-owned and Hispanic-owned businesses more severely than their counterparts, in terms of employment growth as well as survival. This is also the case for continuing black and Hispanic-owned firms.
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ENFORCING COVENANTS NOT TO COMPETE: THE LIFE-CYCLE IMPACT ON NEW FIRMS
June 2014
Working Paper Number:
CES-14-27
We examine the impact of enforcing non-compete covenants (CNC) on the formation and performance of new firms using matched employer-employee data on 30 US states. To identify the impact of CNC, we exploit the inter-state variation in CNC enforcement along with the fact that courts do not enforce such covenants between law firms and departing lawyers in any state. Using a difference-in-difference-in-difference specification with law firms and firms that are not withinindustry spinouts as the baseline, we find states with stricter CNC enforcement have fewer, but larger within-industry spinouts that are more likely to survive their nascent years, and conditional on survival, grow faster during those years. These results are consistent with CNC enforcement having a selection effect on within-industry spinouts. Particularly, with stricter enforcement, only founders with higher-quality ideas and resources choose to overcome CNC-related barriers, which reduces entry rate but increases observed short-term performance of these spinouts.
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REALLOCATION IN THE GREAT RECESSION: CLEANSING OR NOT?
August 2013
Working Paper Number:
CES-13-42
The high pace of output and input reallocation across producers is pervasive in the U.S. economy. Evidence shows this high pace of reallocation is closely linked to productivity. Resources are shifted away from low productivity producers towards high productivity producers. While these patterns hold on average, the extent to which the reallocation dynamics in recessions are 'cleansing' is an open question. That is, are recessions periods of increased reallocation that move resources away from lower productivity activities towards higher productivity uses? It could be recessions are times when the opportunity cost of time and resources are low implying recessions will be times of accelerated productivity enhancing reallocation. Prior research suggests the recession in the early 1980s is consistent with an accelerated pace of productivity enhancing reallocation. Alternative hypotheses highlight the potential distortions to reallocation dynamics in recessions. Such distortions might arise from many factors including, for example, distortions to credit markets. We find that in post-1980 recessions prior to the Great Recession, downturns are periods of accelerated reallocation that is even more productivity enhancing than in normal times. In the Great Recession, we find the intensity of reallocation fell rather than rose (due to the especially sharp decline in job creation) and the reallocation that did occur was less productivity enhancing than in prior recessions.
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How Firms Respond to Business Cycles: The Role of Firm Age and Firm Size
June 2013
Working Paper Number:
CES-13-30
There remains considerable debate in the theoretical and empirical literature about the differences in the cyclical dynamics of firms by firm size. This paper contributes to the debate in two ways. First, the key distinction between firm size and firm age is introduced. The evidence presented in this paper shows that young businesses (that are typically small) exhibit very different cyclical dynamics than small/older businesses. The second contribution is to present evidence and explore explanations for the finding that young/small businesses were hit especially hard in the Great Recession. The collapse in housing prices accounts for a significant part of the large decline of young/small businesses in the Great Recession.
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INNOVATION, REALLOCATION AND GROWTH
April 2013
Working Paper Number:
CES-13-23
We build a model of firm-level innovation, productivity growth and reallocation featuring endogenous entry and exit. A key feature is the selection between high- and low-type firms, which differ in terms of their innovative capacity. We estimate the parameters of the model using detailed US Census micro data on firm-level output, R&D and patenting. The model provides a good fit to the dynamics of firm entry and exit, output and R&D, and its implied elasticities are in the ballpark of a range of micro estimates. We find industrial policy subsidizing either the R&D or the continued operation of incumbents reduces growth and welfare. For example, a subsidy to incumbent R&D equivalent to 53 of GDP reduces welfare by about 1.53 because it deters entry of new high-type firms. On the contrary, substantial improvements (of the order of 53 improvement in welfare) are possible if the continued operation of incumbents is taxed while at the same time R&D by incumbents and new entrants is subsidized. This is because of a strong selection effect: R&D resources (skilled labor) are inefficiently used by low-type incumbent firms. Subsidies to incumbents encourage the survival and expansion of these firms at the expense of potential high-type entrants. We show that optimal policy encourages the exit of low-type firms and supports R&D by high-type incumbents and entry.
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Agglomerative Forces and Cluster Shapes
June 2012
Working Paper Number:
CES-12-09
We model spatial clusters of similar firms. Our model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate. Overlapping firm interactions yield agglomeration clusters that are much larger than the underlying agglomerative forces themselves. Empirically, we demonstrate that our model's assumptions are present in the structure of technology and labor flows within Silicon Valley and its surrounding areas. Our model further identifies how the lengths over which agglomerative forces operate influence the shapes and sizes of industrial clusters; we confirm these predictions using variations across both technology clusters and industry agglomeration.
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