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Learning and the Value of Relationships in International Trade
February 2016
Working Paper Number:
CES-16-11
How valuable are long-term supplier relationships? To address this question, this paper explores relationships between U.S. importers and their suppliers abroad. We establish several facts: almost half of U.S. imports involve relationships three years or older, relationship survival and traded quantity increase as a relationship ages, and long-term relationships were more resilient in the 2008-09 financial crisis. We present a model of importer learning and calibrate it using our data. We estimate large differences in the value of relationships across countries. Counterfactuals show that relationships are central to trade dynamics.
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Business Dynamics Statistics of High Tech Industries
January 2016
Working Paper Number:
CES-16-55
Modern market economies are characterized by the reallocation of resources from less productive, less valuable activities to more productive, more valuable ones. Businesses in the High Technology sector play a particularly important role in this reallocation by introducing new products and services that impact the entire economy. Tracking the performance of this sector is therefore of primary importance, especially in light of recent evidence that suggests a slowdown in business dynamism in High Tech industries. The Census Bureau produces the Business Dynamics Statistics (BDS), a suite of data products that track job creation, job destruction, startups, and exits by firm and establishment characteristics including sector, firm age, and firm size. In this paper we describe the methodologies used to produce a new extension to the BDS focused on businesses in High Technology industries.
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Measuring Plant Level Energy Efficiency and Technical Change in the U.S. Metal-Based Durable Manufacturing Sector Using Stochastic Frontier Analysis
January 2016
Working Paper Number:
CES-16-52
This study analyzes the electric and thermal energy efficiency for five different metal-based durable manufacturing industries in the United States from 1987-2012 at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days - HDD - and cooling degree days - CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. A Malmquist index is used to decompose aggregate plant technical change in energy use into indices of efficiency and frontier (best practice) change. Own energy price elasticities range from -.7 to -1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100 percent equals best practice level) range from a low of 32 percent (thermal 334 - Computer and Electronic Products) to a high of 86 percent (electricity 332 - Fabricated Metal Products). Electric efficiency is consistently better than thermal efficiency for all NAICS. There is no clear pattern to the decomposition of aggregate technical Thermal change. In some years efficiency improvement dominates; in other years aggregate technical change is driven by improvement in best practice.
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Taking the Leap: The Determinants of Entrepreneurs Hiring their First Employee
January 2016
Working Paper Number:
CES-16-48
Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of startups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a non-employer to employer firm among startups. Several interesting patterns emerge regarding the dynamics of non-employer startups hiring their first employee. Hiring rates among the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses such as incorporated and EIN businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. After this point in time relatively few non-employer startups hire an employee. Focusing on more growth- and employment-oriented startups in the KFS, we find that Asian-owned and Hispanic-owned startups have higher rates of hiring their first employee than white-owned startups. Female-owned startups are roughly 10 percentage points less likely to hire their first employee by the first, second and seventh years after startup. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.
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A Portrait of Firms that Invest in R&D
January 2016
Working Paper Number:
CES-16-41
We focus on the evolution and behavior of firms that invest in research and development (R&D). We build upon the cross-sectional analysis in Foster and Grim (2010) that identified the characteristics of top R&D spending firms and follow up by charting the behavior of these firms over time. Our focus is dynamic in nature as we merge micro-level cross-sectional data from the Survey of Industrial Research and Development (SIRD) and the Business Research & Development and Innovation Survey (BRDIS) with the Longitudinal Business Database (LBD). The result is a panel firm-level data set from 1992 to 2011 that tracks firms' performances as they enter and exit the R&D surveys. Using R&D expenditures to proxy R&D performance, we find the top R&D performing firms in the U.S. across all years to be large, old, multinational enterprises. However, we also find that the composition of R&D performing firms is gradually shifting more towards smaller domestic firms with expenditures being less sensitive to scale effects. We find a high degree of persistence for these firms over time. We chart the history of R&D performing firms and compare them to all firms in the economy and find substantial differences in terms of age, size, firm structure and international activity; these differences persist when looking at future firm outcomes.
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Disconnected Geography: A Spatial Analysis of Disconnected Youth in the United States
January 2016
Working Paper Number:
CES-16-37
Since the Great Recession, US policy and advocacy groups have sought to better understand its effect on a group of especially vulnerable young adults who are not enrolled in school or training programs and not participating in the labor market, so called 'disconnected youth.' This article distinguishes between disconnected youth and unemployed youth and examines the spatial clustering of these two groups across counties in the US. The focus is to ascertain whether there are differences in underlying contextual factors among groups of counties that are mutually exclusive and spatially disparate (non-adjacent), comprising two types of spatial clusters ' high rates of disconnected youth and high rates of unemployed youth. Using restricted, household-level census data inside the Census Research Data Center (RDC) under special permission by the US Census Bureau, we were able to define these two groups using detailed household questionnaires that are not available to researchers outside the RDC. The geospatial patterns in the two types of clusters suggest that places with high concentrations of disconnected youth are distinctly different in terms of underlying characteristics from places with high concentrations of unemployed youth. These differences include, among other things, arrests for synthetic drug production, enclaves of poor in rural areas, persistent poverty in areas, educational attainment in the populace, children in poverty, persons without health insurance, the
social capital index, and elders who receive disability benefits. This article provides some preliminary evidence regarding the social forces underlying the two types of observed geospatial clusters and discusses how they differ.
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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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OFFSHORING POLLUTION WHILE OFFSHORING PRODUCTION*
January 2016
Working Paper Number:
CES-16-09R
We examine the role of firm strategy in the global combat against pollution. We find that U.S. plants release less toxic emissions when their parent firm imports more from low-wage countries (LWCs). Consistent with the Pollution Haven Hypothesis, goods imported by U.S. firms from LWCs are in more pollution-intensive industries; U.S. plants shift production to less pollution-intensive industries, produce less waste, and spend less on pollution abatement when their parent imports more from LWCs. The negative impact of LWC imports on emissions is stronger for U.S. plants located in counties with greater institutional pressure for environmental performance, but weaker for more-capable U.S. plants and firms. These results highlight the role of local institutions and firm capability in explaining firms' choice of offshoring and environmental strategy.
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Cheap Imports and the Loss of U.S. Manufacturing Jobs
January 2016
Working Paper Number:
CES-16-05
This paper examines the role of international trade, and specifically imports from low-wage countries, in determining patterns of job loss in U.S. manufacturing industries between 1992 and 2007. Motivated by intuitions from factor-proportions-inspired work on offshoring and heterogeneous firms in trade, we build industry-level measures of import competition. Combining worker data from the Longitudinal Employer-Household Dynamics dataset, detailed establishment information from the Census of Manufactures, and transaction-level trade data, we find that rising import competition from China and other developing economies increases the likelihood of job loss among manufacturing workers with less than a high school degree; it is not significantly related to job losses for workers with at least a college degree.
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Why is Pollution from U.S. Manufacturing Declining?
The Roles of Environmental Regulation, Productivity, and Trade
January 2015
Working Paper Number:
CES-15-03R
Between 1990 and 2008, air pollution emissions from U.S. manufacturing fell by 60 percent despite a substantial increase in manufacturing output. We show that these emissions reductions are primarily driven by within-product changes in emissions intensity rather than changes in output or in the composition of products produced. We then develop and estimate a quantitative model linking trade with the environment to better understand the economic forces driving these changes. Our estimates suggest that the implicit pollution tax that manufacturers face doubled between 1990 and 2008. These changes in environmental regulation, rather than changes in productivity and trade, account for most of the emissions reductions.
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