The Role of Industry Classification in the Estimation of Research and Development Expenditures
November 2014
Working Paper Number:
CES-14-45
Abstract
This paper uses data from the National Science Foundation's surveys on business research and development (R&D) expenditures that have been linked with data from the Census Bureau's Longitudinal Business Database to produce consistent NAICS-based R&D time-series data based on the main product produced by the firm for 1976 to 2008.The results show that R&D spending has shifted away from domestic manufacturing industries in recent years. This is due in part to a shift in U.S. payrolls away from manufacturing establishments for R&D-performing firms.These findings support the notion of an increasingly fragmented production system for R&D-intensive manufacturing firms, whereby U.S. firms control output and provide intellectual property inputs in the form of R&D, but production takes place outside of the firms' U.S. establishments.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
production,
manufacturing,
payroll,
enterprise,
industrial,
sale,
company,
manufacturer,
acquisition,
industry productivity,
produce,
producing,
expenditure,
revenue,
gdp,
manufacturing industries
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
National Science Foundation,
Bureau of Economic Analysis,
Census Bureau Longitudinal Business Database,
Longitudinal Business Database,
Survey of Industrial Research and Development,
North American Industry Classification System
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'The Role of Industry Classification in the Estimation of Research and Development Expenditures' are listed below in order of similarity.
-
Working PaperAllocation of Company Research and Development Expenditures to Industries Using a Tobit Model🔥
November 2015
Working Paper Number:
CES-15-42
This paper uses Census microdata and a regression-based approach to assign multi-division firms' pre-2008 Research and Development (R&D) expenditures to more than one industry. Since multi-division firms conduct R&D in more than one industry, assigning R&D to corresponding industries provides a more accurate representation of where R&D actually takes place and provides a consistent time-series with the National Science Foundation R&D by line of business information. Firm R&D is allocated to industries on the basis of observed industry payroll, as befits the historic importance of payroll in Census assignments of firms to industry. The results demonstrate that the method of assigning R&D to industries on the basis of payroll works well in earlier years, but becomes less effective over time as firms outsource their manufacturing function.View Full Paper PDF
-
Working PaperA 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.View Full Paper PDF
-
Working PaperA Guide To R&D Data At The Center For Economic Studies U.S. Bureau Of THe Census
August 1994
Working Paper Number:
CES-94-09
The National Science Foundation R&D Survey is an annual survey of firms' research and development expenditures. The survey covers 3000 firms reporting positive R&D. This paper provides a description of the R&D data available at the Center for Economic Studies (CES). The most basic data series available contains the original survey R&D data. It covers the years 1972-92. The remaining two series, although derived from the original files, specialize in particular items. The Mandatory Series contains required survey items for the years 1973-88. Items reported at firms' discretion are in the Voluntary Series, which covers the years 1974-89. Both of the derived series incorporate flags that track quality of the data. Both also include corrections to the data based on original hard copy survey evidence stored at CES. In addition to describing each dataset, we offer suggestions to researchers wishing to use the R&D data in exploring various economic issues. We report selected response rates, discuss the survey design, and provide hints on how to use the data.View Full Paper PDF
-
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
-
Working PaperCharacteristics of the Top R&D Performing Firms in the U.S.: Evidence from the Survey of Industrial R&D
September 2010
Working Paper Number:
CES-10-33
Innovation drives economic growth and productivity growth, and as such, indicators of innovative activity such as research and development (R&D) expenditures are of paramount importance. We combine Census confidential microdata from two sources in order to examine the characteristics of the top R&D performing firms in the U.S. economy. We use the Survey of Industrial Research and Development (SIRD) to identify the top 200 R&D performing firms in 2003 and, to the extent possible, to trace the evolution of these firms from 1957 to 2007. The Longitudinal Business Database (LBD) further extends our knowledge about these firms and enables us to make comparisons to the U.S. economy. By linking the SIRD and the LBD we are able to create a detailed portrait of the evolution of the top R&D performing firms in the U.S.View Full Paper PDF
-
Working PaperThe 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.View Full Paper PDF
-
Working PaperTesting the Advantages of Using Product Level Data to Create Linkages Across Industrial Coding Systems
October 1993
Working Paper Number:
CES-93-14
After the major revision of the U.S. Standard Industrial Classification system (SIC) in the 1987, the problem arose of how to evaluate industrial performance over time. The revision resulted in the creation of new industries, the combination of old industries, and the remixing of other industries to better reflect the present U.S. economy. A method had to be developed to make the old and new sets of industries comparable over time. Ryten (1991) argues for performing the conversion at the "most micro level," the product level. Linking industries should be accomplished by reclassifying product data of each establishment to a standard system, reassigning the primary activity of the establishment, reaggregating the data to the industry level, and then making the desired statistical comparison (Ryten, 1991). This paper discusses linking the data at the very micro, product level, and at the more macro, industry level. The results suggest that with complete product information the product level conversion is preferable for most industries in manufacturing because it recognizes that establishments may switch their primary industry because of the conversion. For some industries, especially those having no substantial changes in SIC codes over time, the conversion at the industry level is fairly accurate. A small group of industries lacks complete product information in 1982 to link the 1982 product codes to the 1987 codes. This results in having to rely on the industry concordance to create a time series of statistics.View Full Paper PDF
-
Working PaperR&D or R vs. D? Firm Innovation Strategy and Equity Ownership
April 2020
Working Paper Number:
CES-20-14
We analyze a unique dataset that separately reports research and development expenditures for a large panel of public and private firms. Definitions of 'research' and 'development' in this dataset, respectively, correspond to definitions of knowledge 'exploration' and 'exploitation' in the innovation theory literature. We can thus test theories of how equity ownership status relates to innovation strategy. We find that public firms have greater research intensity than private firms, inconsistent with theories asserting private ownership is more conducive to exploration. We also find public firms invest more intensely in innovation of all sorts. These results suggest relaxed financing constraints enjoyed by public firms, as well as their diversified shareholder bases, make them more conducive to investing in all types of innovation. Reconciling several seemingly conflicting results in prior research, we find private-equity-owned firms, though not less innovative overall than other private firms, skew their innovation strategies toward development and away from research.View Full Paper PDF
-
Working PaperThe Effects Of Leveraged Buyouts On Productivity And Related Aspects Of Firm Behavior
July 1989
Working Paper Number:
CES-89-05
We investigate the economic effects of leveraged buyouts (LBOs) using large longitudinal establishment and firm-level Census Bureau data sets linked to a list of LBOs compiled from public data sources. About 5 percent, or 1100, of the manufacturing plants in the sample were involved in LBOs during 1981-1986. We find that plants involved in LBOs had significantly higher rates of total-factor productivity (TFP) growth than other plants in the same industry. The productivity impact of LBOs is much larger than our previous estimates of the productivity impact of ownership changes in general. Management buyouts appear to have a particularly strong positive effect on TFP. Labor and capital employed tend to decline (relative to the industry average) after the buyout, but at a slower rate than they did before the buyout. The ratio of nonproduction to production labor cost declines sharply, and production worker wage rates increase, following LBOs. LBOs are production-labor-using, nonproduction-labor-saving, organizational innovations. Plants involved in management buyouts (but not in other LBOs) are less likely to subsequently close than other plants. The average R&D- intensity of firms involved in LBOs increased at least as much from 1978 to 1986 as did the average R&D-intensity of all firms responding to the NSF/Census survey of industrial R&D.View Full Paper PDF
-
Working PaperBusiness 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.View Full Paper PDF
