Papers Containing Keywords(s): 'manufacturing'
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Viewing papers 61 through 70 of 246
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Working PaperAn 'Algorithmic Links with Probabilities' Crosswalk for USPC and CPC Patent Classifications with an Application Towards Industrial Technology Composition
March 2016
Working Paper Number:
CES-16-15
Patents are a useful proxy for innovation, technological change, and diffusion. However, fully exploiting patent data for economic analyses requires patents be tied to measures of economic activity, which has proven to be difficult. Recently, Lybbert and Zolas (2014) have constructed an International Patent Classification (IPC) to industry classification crosswalk using an 'Algorithmic Links with Probabilities' approach. In this paper, we utilize a similar approach and apply it to new patent classification schemes, the U.S. Patent Classification (USPC) system and Cooperative Patent Classification (CPC) system. The resulting USPC-Industry and CPC-Industry concordances link both U.S. and global patents to multiple vintages of the North American Industrial Classification System (NAICS), International Standard Industrial Classification (ISIC), Harmonized System (HS) and Standard International Trade Classification (SITC). We then use the crosswalk to highlight changes to industrial technology composition over time. We find suggestive evidence of strong persistence in the association between technologies and industries over time.View Full Paper PDF
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Working PaperBusiness 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.View Full Paper PDF
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Working PaperThe Management and Organizational Practices Survey (MOPS): Cognitive Testing*
January 2016
Working Paper Number:
CES-16-53
All Census Bureau surveys must meet quality standards before they can be sent to the public for data collection. This paper outlines the pretesting process that was used to ensure that the Management and Organizational Practices Survey (MOPS) met those standards. The MOPS is the first large survey of management practices at U.S. manufacturing establishments. The first wave of the MOPS, issued for reference year 2010, was subject to internal expert review and two rounds of cognitive interviews. The results of this pretesting were used to make significant changes to the MOPS instrument and ensure that quality data was collected. The second wave of the MOPS, featuring new questions on data in decision making (DDD) and uncertainty and issued for reference year 2015, was subject to two rounds of cognitive interviews and a round of usability testing. This paper illustrates the effort undertaken by the Census Bureau to ensure that all surveys released into the field are of high quality and provides insight into how respondents interpret the MOPS questionnaire for those looking to utilize the MOPS data.View Full Paper PDF
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Working PaperHigh Growth Young Firms: Contribution to Job, Output and Productivity Growth
January 2016
Working Paper Number:
CES-16-49
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.View Full Paper PDF
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Working PaperThe Role of Start-Ups in StructuralTransformation
January 2016
Working Paper Number:
CES-16-38
The U.S. economy has been going through a striking structural transformation'the secular reallocation of employment across sectors'over the past several decades. We propose a decomposition framework to assess the contributions of various margins of firm dynamics to this shift. Using firm-level data, we find that at least 50 percent of the adjustment has been taking place along the entry margin, owing to sectors receiving shares of start-up employment that differ from their overall employment shares. The rest is mostly the result of life cycle differences across sectors. Declining overall entry has a small but growing effect of dampening structural transformation.View Full Paper PDF
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Working PaperThe 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.View Full Paper PDF
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Working PaperThe Impact of Bank Credit on Labor Reallocation and Aggregate Industry Productivity
January 2016
Working Paper Number:
CES-16-26
Using a difference-in-difference methodology, we find that the state-level deregulation of local U.S. banking markets leads to significant increases in the reallocation of labor within local industries towards small firms with higher marginal products of labor. Using plant-level data, we propose and examine an approach that quantifies the industry productivity gains from labor reallocation and find that these gains are economically important. Our analysis suggests that labor reallocation is a significant channel through which local banking markets affect the aggregate productivity and performance of local industries.View Full Paper PDF
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Working PaperData in Action: Data-Driven Decision Making in U.S. Manufacturing
January 2016
Working Paper Number:
CES-16-06
Manufacturing in America has become significantly more data-intensive. We investigate the adoption, performance effects and organizational complementarities of data-driven decision making (DDD) in the U.S. Using data collected by the Census Bureau for 2005 and 2010, we observe the extent to which manufacturing firms track and use data to guide decision making, as well as their investments in information technology (IT) and the use of other structured management practices. Examining a representative sample of over 18,000 plans, we find that adoption of DDD is earlier and more prevalent among larger, older plants belonging to multi-unit firms. Smaller single-establishment firms adopt later but have a higher correlation with performance than similar non-adopters. Using a fixed-effects estimator, we find the average value-added for later DDD adopters to be 3% greater than non-adopters, controlling for other inputs to production. This effect is distinct from that associated with IT and other structured management practices and is concentrated among single-unit firms. Performance improves after plants adopt DDD, but not before ' consistent with a causal relationship. However, DDD-related performance differentials decrease over time for early and late adopters, consistent with firm learning and development of organizational complementarities. Formal complementarity tests suggest that DDD and high levels of IT capital reinforce each other, as do DDD and skilled workers. For some industries, the benefits of DDD adoption appear to be greater for plants that delegate some decision making to frontline workers.View Full Paper PDF
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Working PaperCheap 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.View Full Paper PDF
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Working PaperPlant Exit and U.S. Imports from Low-Wage Countries
January 2016
Working Paper Number:
CES-16-02
Over the past twenty years, imports to the U.S. from low-wage countries have increased dramatically. In this paper we examine how low-wage country import competition in the U.S. influences the probability of manufacturing establishment closure. Confidential data from the U.S. Bureau of the Census are used to track all manufacturing establishments between 1992 and 2007. These data are linked to measures of import competition built from individual trade transactions. Controlling for a variety of plant and firm covariates, we show that low-wage import competition has played a significant role in manufacturing plant exit. Analysis employs fixed effects panel models running across three periods: the first plant-level panels examining trade and exit for the U.S. economy. Our results appear robust to concerns regarding endogeneity.View Full Paper PDF