North American Industry Classification System Research Articles

7 Statistical modelling of occupational exposure to polycyclic aromatic hydrocarbons using osha data

ObjectivesPolycyclic aromatic hydrocarbons (PAHs) are a group of chemicals consisting primarily of fused aromatic rings. As environmental pollutants, PAHs are of concern because some variants are carcinogenic. Our objective is...

Examination of the relative importance of hospital employment in non-metropolitan counties using location quotients

The US Health Care and Social Services sector (North American Industrial Classification System 'sector 62') has become an extremely important component of the nation's economy, employing approximately 18 million workers and generating almost $753 billion in annual payrolls. At the county level, the health care and social services sector is typically the largest or second largest employer. Hospital employment is often the largest component of the sector's total employment. Hospital employment is particularly important to non-metropolitan or rural communities. A high quality healthcare sector serves to promote economic development and attract new businesses and to provide stability in economic downturns. The purpose of this study was to examine the intensity of hospital employment in rural counties relative to the nation as a whole using location quotients and to draw conclusions regarding how potential changes in Medicare and Medicaid might affect rural populations. Estimates for county-level hospital employment are not commonly available. Estimates of county-level hospital employment were therefore generated for all counties in the USA the Census Bureau's County Business Pattern Data for 2010. These estimates were used to generate location quotients for each county which were combined with demographic data to generate a profile of factors that are related to the magnitude of location quotients. The results were then used to draw inferences regarding the possible impact of the Patient Protection and Affordable Care Act 2010 (ACA) and the possible imposition of aspects of the Budget Control Act 2011 (BCA). Although a very high percentage of rural counties contain medically underserved areas, an examination of location quotients indicates that the percentage of the county workforce employed by hospitals in the most rural counties tends to be higher than for the nation as a whole, a counterintuitive finding. Further, when location quotients are regressed upon data related to poverty, county demographics, and the percentage of the population insured, a relationship between the proportion of the population over 65 years, the percentage of the population living in poverty, the percentage of the population without insurance and county density was found. The results of the analysis suggest that hospital employment in rural communities is higher than would be expected in the absence of programs that provide external funding to support hospital hiring. The most important public programs providing this support are Medicare and Medicaid. Social Security is another source of federal funding important for rural populations. Sequestration and other cuts in funding could impact rural communities significantly. This can be even worse in states that fail to expand Medicaid and in states that fail to increase Medicaid reimbursements for services important in rural communities.

A research case study: Difficulties and recommendations when using a textual data mining tool

Although many interesting results have been reported by researchers using numeric data mining methods, there are still questions that need answering before textual data mining tools will be considered generally useful due to the effort needed to learn and use them.In 2011, we generated a dataset from the legal statements (mainly privacy policy and terms of use) on the websites of 475 of the US Fortune 500 Companies and used it as input to see what we could detect about the organizational relationships between the companies by using a textual data mining tool. We hoped to find that the tool would cluster similar corporations into the same industrial sector, as validated by the company's self-reported North American Industry Classification System code (NAICS). Unfortunately, this proved only marginally successful, leading us to ask why and to pose our research question: What problems occur when a data-mining tool is used to analyze large textual datasets that are unstructured, complex, duplicative, and contain many homonyms and synonyms?In analyzing our large dataset we learned a great deal about the problem and fortunately, after significant effort, determined how to “massage” the raw dataset to improve the process and learn how the tool can be better used in research situations. We also found that NAICS, as self-reported by companies, are of dubious value to a researcher—a matter briefly discussed.

A sectoral analysis of the financial instability hypothesis

Abstract Hyman Minsky's Financial Instability Hypothesis (FIH) is applied to various North American Industrial Classification System (NAICS) industry groups, and it is found that some sectors develop much more closely in accordance with the FIH than others. Minsky categorized firms based on the relationship between cash flow and debt service requirements: hedge finance units, whose operating revenues are adequate to service current interest and principal on their debt; speculative finance units, which can meet interest payments but cannot pay down principal; and Ponzi finance units, which cannot meet current interest payments. The FIH is related to, as well as supportive of, Austrian Business Cycle (ABC) theory, because interest rates are negatively correlated with the proportion and market value of speculative firms in several sectors.

CEO duality: how many hats are too many?

PurposeThis paper aims to concentrate on the prevailing agency theory along with its complementary theory of stewardship as foundations for the authors' research. Recent economic turmoil within the USA has resulted in stakeholders demanding change within governance policies of corporations. One such adjustment has been the separation of the CEO and Chairman positions within organizations. The authors' study seeks to uncover the extent to which duality CEO relationships exist in large corporations within the USA. In light of the push towards splitting the dual roles, the authors further investigated new CEOs recently appointed into the CEO position.Design/methodology/approachCompanies selected for this study were the top 500 revenue‐producing companies in the USA as published by Fortune magazine in 2008. For comparison purposes, the authors' database included newly appointed CEOs coming on board with the original 2008 companies that had remained on the listing for both years as published by Fortune in 2010. The authors' 2008 database included 500 companies and their 2010 database included 86 companies. The North American Industry Classification System (NAICS) was the product classification used in order to establish the principal industry sector for companies under analysis.FindingsThe authors' 2008 analysis reveals that 303 CEOs hold a combination title of CEO and Chairman. The most frequent title combination is CEO and Chairman, with 156 executives holding this combined title. The authors' 2010 analysis reveals that 33 new CEOs hold a combination title of CEO and Chairman. The most frequent title combination is CEO and President with 43 executives holding the title. The authors' analysis of retired CEOs reveals that 15 retired CEOs continue serving in the capacity of Chairman of the Board of Directors.Research limitations/implicationsUsing the top 500 companies in the USA, based upon sales revenue, did limit the study to large corporations within the USA.Originality/valueThe agency theory does provide an explanation of the duality movement witnessed in corporations. The practice of splitting duality roles of CEO and Chairman within public corporations appears to be becoming a reality within the USA, whether on a voluntary or a mandatory basis in order to enhance corporate independence and transparency.

Scenario analysis: a review of methods and applications for engineering and environmental systems

Changing environment, uncertain economic conditions, and socio-political unrest have renewed interest in scenario analysis, both from theoretical and applied points of view. Nevertheless, neither the processes for scenario analysis (SA) nor evaluation criteria and metrics have been regularized. In this paper, SA-reported applica- tions and implementation methodology are discussed in the context of an extensive literature review covering papers published between 2000 and 2010. Over 340 papers were identified through a series of queries in the web of science database. The papers were classified based on the North American Industrial Classification System and SA appli- cation goals (environmental, business, and social). SA methodology used in each paper was assessed based on four main criteria: coverage, consistency, uncertainty assessment, and efficiency. We find a significant increase in SA applications, especially in the environmental field. Theoretical developments in the field represent a small fraction of published studies and do not increase in time. The methods used to develop different scenarios vary widely across the academic literature and applications reviewed. Similarly, the methods and data used to characterize the scenarios and develop response strategies are extremely diverse and are limited by factors such as computational tractability and available time and resour- ces. Based on this review, we recommend a regular process for scenario analysis that includes the steps of analysis, scenario definition, and evaluation.

USING THE TAX SYSTEM TO ADDRESS COMPETITION ISSUES WITH A CARBON TAX

This paper considers how tax reductions financed by a carbon tax could be designed to mitigate the need for specific relief for firms in select energy-intensive, trade-exposed (EITE) sectors. In particular, I consider impacts on manufacturing sectors at the six-digit North American Industry Classification System level, with a special focus on firms that would be presumptively eligible for competitiveness relief using the criteria in the Waxman–Markey bill (H.R. 2454). The paper has a number of findings. First, determination of eligibility for relief analogous to the free allowance allocation in H.R. 2454 is sensitive to energy intensity. Second, providing compensation to EITE sectors through the corporate income tax—analogous to the output-based allowance allocation in Waxman–Markey— is certainly feasible, but tax appetite within the EITE sectors is insufficient to fully use any credits that attempted to offset more than about one-quarter of their carbon tax liability. Third, certain reforms do better than others at providing disproportionate relief to EITE sectors. Finally, economic theory predicts a substantial cost to diverting carbon tax revenue toward compensation of specific sectors. Theory also suggests that firms should treat policy risk no differently from the way they treat the other risks they face as they do business. But politics may dictate otherwise; if so, the analysis here suggests that certain approaches may work better than others to ensure that relief is appropriately targeted at minimal cost.

Transportation Infrastructure, Industrial Productivity, and Return on Investment

This study examined the North American Industrial Classification System–based manufacturing industry (NAICS 31-33) from 1997 to 2010 in a cost-based framework. First, both profit and production function models were constructed and estimated for the U.S. manufacturing industry at the state level to allow for spatial spillovers and interactions. A model based on profit and production provided an alternative approach to the dual-cost function. Elasticities associated with infrastructure investment and industry total costs were determined by the inclusion of data on transportation infrastructure spending. Results of the spatial econometric models and the computed elasticities were then delivered in a geographic information system.

Common Analyst - Based Method for Defining Peer Firms

We develop a method for defining groups of peer firms on the basis of joint analyst coverage. Besides industry boundaries, analysts’ coverage choices can reflect other important aspects of firm relatedness. Our main performance tests concentrate on measuring peer group homogeneity. In these tests we pit the analyst-based method against common industry classifications such as SIC codes, Fama-French industries, The North American Industry Classification System (NAICS), and Global Industry Classification Standard (GICS). The analyst-based method consistently outperforms these common classifications. More generally, our results show that common analysts between firms offer a simple, yet powerful method for finding comparable firms.

The Industry-Specific Regulatory Constraint Database (IRCD): A Numerical Database on Industry-Specific Regulations for All U.S. Industries and Federal Regulations, 1997-2010

We introduce RegData, formerly known as the Industry-Specific Regulatory Constraint Database. RegData annually quantifies federal regulations by industry and by regulatory agency for all federal regulations from 1997 to 2012. The quantification of regulations at the industry level for all industries is without precedent. RegData measures regulation for industries at the two-, three-, and four-digit levels of the North American Industry Classification System. We created this database using text analysis to count binding constraints in the wording of regulations, as codified in the Code of Federal Regulations, and to measure the applicability of regulatory text to different industries. We validate our measures of regulation by examining known episodes of regulatory growth and deregulation as well as by comparing our measures to an existing, cross-sectional measure of regulation. We then demonstrate several plausible relationships between industry regulation and variables of economic interest. Researchers can use this database to study the determinants of industry regulations and to study regulations’ effects on a massive array of dependent variables, both across industries and across time.

Predictors of tobacco outlet density nationwide: a geographic analysis

ObjectiveTo elucidate how demographics of US Census tracts are related to tobacco outlet density (TOD).MethodThe authors conducted a nationwide assessment of the association between socio-demographic US Census indicators and the...

The Relationship Between Import Penetration and Operation of the U.S. Textile and Apparel Industries From 2002 to 2008

The U.S. textile and apparel (T&A) industries have respectively adopted various restructuring strategies in recent years which fundamentally changed the way the two industries operate and the shifting relationship of each sector with imports. This study empirically tests the relationship between import penetration and the operation of the U.S. T&A industries based on data at 4-digit North American Industry Classification System (NAICS) code level from 2002-2008. Results from the panel data model show that overall the U.S. textile industry formed a weak cooperative relationship with import penetration level in the U.S. market and a neutral relationship was suggested for the U.S. apparel industry with imports. These findings contribute to understanding the global nature of today's U.S. T&A industries and suggest useful perspectives for the U.S. textile trade policies.

Trade Openness and Vertical Integration: Evidence from the U.S. Manufacturing Sector

The present article aims to empirically examine a relationship between trade openness and the pattern of vertical integration using the six‐digit North American Industry Classification System (NAICS) of U.S. manufacturing data from 2002 to 2006. We use the index of vertical integration made out of inter‐plant transfers data by the U.S. Census Bureau, and we consider three proxies of trade openness—import penetration, export shares, and trade penetration. The empirical results substantiate theoretical proposition that trade openness undermines motives for vertical integration.

A Framework for the Construction of Ontology for ICT Experts

Systems that help to find answers to suitable experts have received the attention of many researchers. Pioneer researchers on the development of search system for experts emphasized the importance of a search system that required returning a list prioritizing the names of individuals. Among the issues raised related to locating experts are, the critical problem of maintaining up-to-date information in the expert database and the inadequacy in expert finding systems in returning search results that are expected to account for not only the list of the names of the experts, but any information related to the experts and those involved with them. In the last decade, researchers have examined the search for experts from various research perspectives such as expert tracking system and construction of expert profiles involving ontology. This paper aims to describe a new approach in designing a framework for the construction of ontology that will be used in the directory of ICT experts. The researchers propose to incorporate thesaurus in their construction of ontology on ICT experts by providing a profile of the experts including their social profile and whatever concerns that may be associated with the expert. The researchers constructed the ontology on ICT experts by extracting information from sources such as their resumes and personal web sites to obtain the index glossary of words that characterized experts to be used in the directory of experts system. In this study, the standards contained in the Performance Evaluation System of the National University of Malaysia are used to extract information on the academicians in the Faculty of Information Science and Technology. The researchers employed the index glossary, metadata of experts and integrate appropriate taxonomy, thesaurus and classification schemes; such as Association for Computing Machinery (ACM) taxonomy, web classification schemes such as Standard Industrial Classification (SIC), North American Industry Classification System (NAICS) to enrich the ontology of ICT expertise. The proposed framework aims at helping users find information on the expert they require and at the same time obtain other information related to the experts from various perspectives encompassing research, consultancy, links with research partners, other interest related to a particular field and other resources. With a semantically driven directory of ICT experts, matters related to ICT can be referred to the right experts. The framework will be validated by developing the directory of ICT experts prototype and by involving domain experts to evaluate the content of the ontology constructed. In addition, the researchers will evaluate the search results of users who will use the prototype to search for ICT experts.

The role of industry classification in estimating discretionary accruals

This study compares the properties of the Global Industry Classification Standard (GICS) with three alternatives: Standard Industrial Classification, North American Industry Classification System, and Fama–French classification. First, we demonstrate that GICS results in more reliable industry groupings for financial analysis and research; in particular, we find that estimations of performance-adjusted discretionary accruals (PADA) based on GICS significantly outperform estimates derived using each of the three alternative classifications systems in capturing discretionary accruals. Second, we show that the difference between GICS and the other systems can provide significantly different results, and hence different inferences, in empirical studies that rely on industry classification. Specifically, we revisit findings by Teoh et al. (J Financ 53[6]:1935–1970, 1998a) and assess the conclusion that initial public offering (IPO) issuers with high abnormal accruals during the IPO year experience subsequent poorer long-term stock performance than issuers with low discretionary accruals do. We find that this result disappears when PADA estimates are based on GICS. Our results call for serious consideration of using GICS classifications in research, either in the primary analysis or as a necessary corroboration.

Improving Data Accuracy of Commercial Food Outlet Databases

PURPOSE. Assessing food environments often requires using commercially available data. Disparate methods used for classifying food outlets in these databases call for creating a classification approach using common definitions. A systematic strategy for reclassifying food stores and restaurants, as they appear in commercial databases, into categories that differentiate the availability of healthy options is described here. DESIGN AND SETTING. Commercially available data on food outlets including names, addresses, North American Industry Classification System codes, and associated characteristics was obtained for five New Jersey communities. ANALYSIS. A reclassification methodology was developed using criteria and definitions from the literature to categorize food outlets based on availability of healthy options. Information in the database was supplemented by systematic Internet and key word searches, and from phone calls to food outlets. RESULTS. The methodology resulted in 622 supermarket/grocery stores, 183 convenience stores, and 148 specialty stores in the original data to be reclassified into 58 supermarkets, 30 grocery stores, 692 convenience stores, and 115 specialty stores. Outlets from the original list of 1485 full-service restaurants and 506 limited-service restaurants were reclassified as 563 full-service restaurants and 1247 limited-service restaurants. Reclassification resulted in less than one-seventh the number of supermarkets and grocery stores, more than three times the number of convenience stores, and twice as many limited-service restaurants-a much less healthy profile than the one generated by using exclusively the commercial databases. CONCLUSION. An explicit and replicable strategy is proposed for reclassifying food outlets in commercial databases into categories that differentiate on the basis of healthy food availability. The intent is to contribute towards building a consensus among researchers on definitions used in public health research for characterizing different types of food outlets.

Preliminary Analysis of the Distributions of Carbon and Energy Intensity for 27 Energy Intensive Trade Exposed Industrial Sectors

It is well documented that different manufacturing sectors require different amounts of energy. Primary materials conversion, e.g., iron ore and scrap into steel, limestone and sand into cement and glass, or wood and other fibers into paper, tend to be the most energy-intensive in the production process, while final consumer products like electronics and clothing require the least energy. This leads to something like the 80-20 rule, where a large portion of energy use is in a small number of industries. For example, the 2006 Manufacturing Energy Consumption Survey (MECS) reported that 75 percent of fuel use arises from only five of the 21 three-digit industries, using the North American Industry Classification System (NAICS). These five sectors are a small share of the total U.S. economy. The energy intensity for different industrial sectors is easily measured using published government statistics, but the plants within these industries are not homogeneous entities. This report measures the differences in energy use and associated CO2 emissions as a first step to understanding the within-sector heterogeneity of energy use.

Trade restriction indices and US trade policy

The proper way to measure differences in trade protection across countries and economic sectors has been a vexing problem for economists studying international trade. Based on research by Anderson and Neary (2005) and Kee et al. (KNO) (2009), this article proposes the use of Trade Restriction Indices (TRIs) when studying US trade policy. TRIs can potentially solve several problems related to measuring the restrictiveness of trade policy. To this end, this article creates a data set of TRIs for US imports by sector at several different levels of aggregation using the Harmonized Tariff Schedule (HS), the North American Industry Classification System (NAICS) and the Standard International Trade Classification industry coding systems.

Introduction to the symposium of presentations from the Plenary Sessions of the 2010 North American Productivity Workshop

The Plenary Sessions of the 2010 North American Productivity Workshop (NAPW) were particularly noteworthy as they brought together a remarkable collection of scholars whose contribution to productivity and efficiency has been seminal and classic as well as modern and innovative. The presentations were first rate. This symposium is composed of the presentations given in the Plenary Sessions. The idea of such a symposium was not only sparked by the presentations of remarkably gifted scholars, but also by the large number of conference participants whose conversations with us after the presentations indicated that something special was going on in the Plenary Sessions: that the participants were struck by the singular quality and uniqueness of the scholarship but also by the reverence the presenters commanded and the awe in which they were held by the participants. The first Plenary Session was meant to frame the conference and to set its tone. The title of the session was ‘‘Unresolved Research Topics in Productivity’’ and the presenters were Professors Erwin Diewert and Dale Jorgenson. Professor Jorgenson began his talk, ‘‘Information Technology and U.S. Productivity Growth: Evidence from a Prototype Industry Production Account’’ by pointing out that the NAPW’s long time friend and participant John W. Kendrick, to whom the 2010 NAPW was dedicated in memoriam, had been a proponent and strong advocate of the data collection protocols that Professor Jorgenson was able help put in place and which currently provide researchers with disaggregated production data that seamlessly links productivity analysis to the National Accounts. Professor Jorgenson’s presentation and the paper in the symposium co-authored with Mun S Ho and Jon Samuels presented the new data set on U.S. productivity growth covering 70 industries for the period 1960–2007 based on the North American Industry Classification System (NAICS), providing much greater detail on the service industries. The second presentation in the first Plenary Session was given by Erwin Diewert and was entitled ‘‘Measuring Productivity in the Public Sector: Some Conceptual Problems.’’ Professor Diewert pointed out a number of issues that have perplexed productivity researchers when attempting to measure the contribution of government services, which are either free or provided at highly subsidized prices, to the many sectors of the economy. Not only were the problems detailed in his presentation but general methods to measure the price and quantity of nonmarket government outputs were provided. Specifically, if quantity information on nonmarket outputs is available then either price valuations relying on purchaser based valuations or on cost based valuations can be used. If nonmarket outputs quantity information is not available then growth accounting procedures can be uses to indirectly control for the contribution of government services in productivity growth. We would like to thank the major financial supporters of the 2010 North American Productivity Workshop, held at the James A. Baker III Institute for Public Policy at Rice University: the James A. Baker III Institute for Public Policy and the Rice University School of Social Sciences. We would also like to thank Accumyn Consulting, Stata Corporation, and the Jesse H. Jones Graduate School of Business at Rice University for financial and in kind support for the conference.

A value chain statistical definition of construction and the performance of the sector

Existing statistical analyses often fail to capture the true scope of the economic impact of the construction sector. They account for the construction of buildings, civil engineering, and construction specialized activities, as defined by Section F of the Statistical Classification of Economic Activities (or NACE) used in the European Community, but overlook related activities such as the manufacture of construction products and architectural and engineering services. This shortcoming is addressed and a wider definition of the construction sector is proposed that encompasses the whole value chain of the industry. Going beyond the ‘core’ construction sector section (Section F), activities from other NACE sectors that fully or principally depend upon or are functional to core construction activities are considered. These ‘non-core’ classes relate to ‘pre-production’ activities, such as the provision of intermediate goods and services; various ‘support’ activities and ‘post-production’ functions such as maintenance and management services. Equivalent broad definitions of the construction sector based on the North American Industry Classification System (NAICS) and the International Standard Industrial Classification (ISIC) are also developed to allow for optimum comparisons across countries and over time. Using detailed data from Finland and the Community Innovation Survey 4 (CIS4), core and non-core activities are characterized and quantified. Evidence suggests that indicators measuring the composition, structure, value added, skills, and R&D input and output of the construction sector change substantially when a broader definition of the sector is applied. Policies targeting the ‘wide’ construction sector, and exploiting the innovation, growth and productivity leverage potential of non-core activities are thus advocated.