Standard Industrial Classification Research Articles

Real Estate Market Structure: Industrial Organization Perspectives

Existing studies of housing markets assume that property developers is a homogenous, perfectly competitive industry. It concentrates on advanced economies and the impacts of market conditions, regulatory constraints, production characteristics, institutional structure and land supply. Motivated by these circumstances and fewer literature on concentration studies in Malaysia we try to bridging the gap. This paper utilized 5-digit firm level industry data of the Malaysian Standard Industrial Classification (MSIC, 2008) on the average size of property developer establishments and market concentration to test the appropriateness of this paradigm. Our concentration ratio (CR4) results show Malaysian real estate services are considered as competitive market. Keywords: Concentration, competition, market power, real estate services. JEL: L1, L11, L85

Web Footprints of Firms: Using Online Isomorphism for Competitor Identification

Competitive isomorphism refers to the phenomenon of competing firms becoming similar as they mimic each other under common market forces. With the growing presence of firms as well as their consumers and suppliers on the Web, we discover a parallel phenomenon of online isomorphism wherein the Web footprints of competing firms are found to overlap. We propose new online metrics based on the content, in-links, and out-links of firms' websites to measure the presence of online isomorphism as well as uncover its utility in predicting competitor relationships. Through rigorous analysis involving more than 2,600 firms, we find that predictive models for competitor identification based on online metrics are largely superior to those using offline data such as Standard Industrial Classification codes and market values of firms. In addition, combining online and offline metrics can boost the predictive performance. We also find that such models are valuable for identifying nuances of competitor relationships such as asymmetry and the role of industrial divisions. Furthermore, the suggested predictive models can effectively rank firms in an industrial division by their likelihood of being competitors to a focal firm as well as identify new future competitors, thus adding to a portfolio of evidence indicating their utility for managers and analysts.

Diseño de un indicador adelantado para la actividad económica de Costa Rica

Este documento presenta los resultados de la estimación de tres indicadores adelantados de los puntos de giro de la actividad económica en Costa Rica. Lo anterior sigue la metodología propuesta por la Organización para la Cooperación y el Desarrollo Económico (OCDE). Se seleccionó el Índice Mensual de Actividad Económica (IMAE) como variable de referencia y se analizaron 270 variables que contienen información de los sectores monetario, real, mercado laboral, así como índices de precios, indicadores del sector externo y variables del sector fiscal. La información del sector real se desagregó en tres niveles que incluían una clasificación con datos a nivel de la Clasificación Industrial Internacional Uniforme (CIIU) con dos dígitos, información del sector agrícola de acuerdo con la Clasificación Central de Productos (CCP) e información a nivel de producto del sector manufacturero. Para cada nivel de agregación se desarrolló un indicador adelantado, con adelantos promedio de entre 7 y 12 meses respecto a la variable de referencia.

Measuring the Construction Industry’s Productivity Performance: Critique of International Productivity Comparisons at Industry Level

AbstractThe authors review work on international comparisons of construction productivity performance by providing an in-depth critique of the existing literature and highlighting the existing methodological challenges. Using studies and data on the United Kingdom’s relative construction productivity performance as an exemplar, it is suggested that any investigation of international productivity differences in construction at the industry level is highly problematic because these productivity estimates do not compare like for like. Data definitions and coverage differ substantially across countries. In addition, deflators and exchange rates used to convert output into a common currency are unreliable. While the new standard industrial classifications 2007 could provide a better basis of cross-country productivity comparisons and further research on deflators, conversion rates, labor inputs, and capital stock estimates could improve the robustness of international comparisons, there are conceptual limitati...

A methodology for combining multiple commercial data sources to improve measurement of the food and alcohol environment: applications of geographical information systems.

Commercial data sources have been increasingly used to measure and locate community resources. We describe a methodology for combining and comparing the differences in commercial data of the food and alcohol environment. We used commercial data from two commercial databases (InfoUSA and Dun&Bradstreet) for 2003 and 2009 to obtain information on food and alcohol establishments and developed a matching process using computer algorithms and manual review by applying ArcGIS to geocode addresses, standard industrial classification and North American industry classification taxonomy for type of establishment and establishment name. We constructed population and area-based density measures (e.g. grocery stores) and assessed differences across data sources and used ArcGIS to map the densities. The matching process resulted in 8,705 and 7,078 unique establishments for 2003 and 2009, respectively. There were more establishments captured in the combined dataset than relying on one data source alone, and the additional establishments captured ranged from 1,255 to 2,752 in 2009. The correlations for the density measures between the two data sources was highest for alcohol outlets (r = 0.75 and 0.79 for per capita and area, respectively) and lowest for grocery stores/supermarkets (r = 0.32 for both). This process for applying geographical information systems to combine multiple commercial data sources and develop measures of the food and alcohol environment captured more establishments than relying on one data source alone. This replicable methodology was found to be useful for understanding the food and alcohol environment when local or public data are limited.

The Entrepreneur's Cost of Capital: Incorporating Downside Risk

Abstract The capital asset pricing model (CAPM) suggests that an investor's cost of equity capital is determined by beta, a measure of systematic risk based on how returns co-move with the overall market. We propose to replace beta with downside beta, a measure more consistent with investors' perception of risk. Recent empirical evidence suggests that downside beta better captures the risk-return relationship in both emerging markets and developed markets. Grouping companies into industries by two-digit Standard Industrial Classification (SIC) code, we show that the average downside beta can be very different from traditional beta. We discuss the implications of using downside beta on valuation and provide a simple example to illustrate the application in valuation for both diversified and undiversified investors.

우리나라 근로자들의 업종별 뇨중 N-methylformamide 분석 및 N,N-dimethylformamide 노출관리 대책

Objectives: This study is aimed to describe the current situation about urinary biomarker N-methylformamide(NMF) for workers exposed to N,N-dimethylformamide(DMF) according to industrial classification. Materials: Special health examination records of the workers who had undergone urinary biological monitoring in 2013 were collected. The numbers and percentage of workers, whose urinary NMF values were above the limit of detection(LOD) and above the biological exposure index(BEI) were calculated. Health relatedness with DMF as judged by their doctors was also described. All description was classified according to the <TEX>$9^{th}$</TEX> Korean Standard Industrial Classification(KSIC). Results: It appeared that most workers exposed to DMF belong to manufacturing section(80.7%). The geometric mean(GM) values of urinary NMF were 6.25 mg/L, 3.54, and 3.86 for the manufacturing section, professional, scientific and technical activities section, and for the construction section respectively. In detail, it seemed that division of textiles(except apparel) (GM 7.51 mg/L), division of leather, luggage and footwear(11.59 mg/L), and division of rubber and plastic products(6.89 mg/L) were highly exposed to DMF with a high percentage of workers with urinary NMF values above BEI. This was probably due to the effect of skin absorption that the division of leather, luggage and footwear showed the highest urine NMF GM. Conclusions: It seemed that workers in manufacture industries such as textile, leather, luggage, footwear, rubber and plastic products were highly exposed to DMF. So, efforts should be focused on those industries in order to effectively diminish worker's exposure. Further studies to compare DMF air-monitoring with bio-monitoring according to industrial classification should be considered.

The Economic Contribution of the Ocean Sector in South Africa

The contribution of the ocean sector in South Africa is of interest to many - from researchers of ocean resources and environments to firms using the ocean and government departments and nongovernmental organizations with interest in, or responsibility for, the ocean resources and environment. For the purpose of identifying the overall economic contribution this paper describes and applies alternative methods of apportioning GDP into ocean and non-ocean parts. One method uses ocean closeness as the reference for apportioning GDP. It has been estimated that in 1995 the ocean sector contributed about 33% of South Africa's GDP. A major weakness of the closeness to ocean basis for apportioning GDP is that many of the economic activities taking place near to the ocean use little, if anything, of the ocean resources and its environment as inputs in production. A preferred method of identifying ocean and non-ocean parts of GDP is to divide the value added per economic sub-sector (and sub-set) into ocean and non-ocean parts and summing the ocean parts. This method is outlined and demonstrated using South African data for the 2010 year at the third digit level of the standard industrial classification code list (ICCL or SIC). It is found that in 2010 the overall contribution of the ocean-linked sector to GDP was about 4.4 per cent.

B-Corps—A Growing Form of Social Enterprise

B-Corps are a growing group of social enterprises with a high level of commitment to maintaining a balance between profit motive and corporate social responsibility (CSR). This study has two purposes. First, it reviews the 6-year history of the rapid development of B-Corps (which currently number more than 800). Second, the study investigates the growth rate of total revenue and of employee productivity of B-Corps during a recent period and compares it with that of approximately 1,206 public companies and 3,600 non–B-Corps private firms. These measurements add to the discussion about whether socially and environmentally responsible firms generate revenue and productivity at levels similar to their competitors. The study also examines differences in the financial and productivity performance among B-Corps based on their scores on qualitative CSR performance factors. These measurements add to the discussion as to whether or not stronger CSR performance is associated with stronger financial performance and whether productivity increases in this type of firm. One finding is that B-Corps had a statistically significant revenue growth rate that outpaced the average revenue growth of the public companies that operate in the same 4-digit Standard Industrial Classification (SIC) code as B-Corps. In comparison with non–B-Corps small-to-medium size private firms, we found no significant difference in revenue growth. In those comparisons, B-Corps did not outperform both their public and private competitors with regard to employee productivity growth rate. There was no significant correlation within the sample of B-Corps with regard to revenue and productivity increases and B-Corps’ performance on qualitative CSR factors.

Occupational exposure and ovarian cancer risk.

Relatively little work has been done concerning occupational risk factors in ovarian cancer. Although studies conducted in occupational settings have reported positive associations, their usefulness is generally limited by the lack of information on important confounders. In a population-based case-control study, we assessed risk for developing epithelial ovarian cancer (EOC) associated with occupational exposure while accounting for important confounders. Participants were identified through provincial population-based registries. Lifetime occupational history and information on potential confounding factors were obtained through a self-administered questionnaire. Unconditional logistic regression and the likelihood ratio test were used to assess EOC risk with each occupation (or industry), relative to all other occupations (or industries), adjusting for potential confounders including body mass index, oral contraceptive use, menopausal hormone therapy, parity, age at first childbirth, age at menarche, age at menopause, family history of breast and ovarian cancer in mother and sister(s), tubal ligation, partial oophorectomy, and hysterectomy. Occupations and industries were coded according to the Canadian Standard Occupational Classification (SOC) and Standard Industrial Classification (SIC). Significant excess risk was observed for several groups of teaching occupations, including SOC 27, teaching and related (adjusted OR 1.77, 95% CI 1.15-2.81) and SOC 279, other teaching and related (adjusted OR 3.11, 95% CI 1.35-8.49). Significant excess was also seen for a four-digit occupational group SOC 4131, bookkeepers and accounting clerks (adjusted OR 2.80, 95% CI 1.30-6.80). Industrial sub-groups showing significant excess risk included SIC 65, other retail stores (adjusted OR 2.19, 95 % CI 1.16-4.38); SIC 85, educational service (adjusted OR 1.45, 95% CI 1.00-2.13); and SIC 863, non-institutional health services (adjusted OR 2.54, 95% CI 1.13-6.52). Our study found an elevated EOC risk for teaching occupations and is the first study to observe such an increased risk after adjustment for potential confounders. Further studies with more detailed assessment of the work environment and unique lifestyle characteristics may be fruitful in elucidating this etiology.

Industry classification and the efficiency of intra-industry information transfers

Purpose – Motivated by recent studies that demonstrate the superiority of the Global Industry Classification System (GICS) relative to the Standard Industry Classification (SIC) system in capital market research, the authors revisit the stock market anomaly documented by Thomas and Zhang (TZ) (“Overreaction to intra-industry information transfers?” Journal of Accounting Research, Vol. 46, pp. 909-940) and analyze whether the anomaly based on SIC remains evident when intra-industry information transfers are based on the GICS. The paper aims to discuss these issues. Design/methodology/approach – The authors first replicate TZ and test whether stock prices of late announcers in response to earnings reported by early announcers in the same SIC industry are significantly related to subsequent price responses of late announcers to their own earnings reports. In the multivariate setting, the authors then evaluate whether the magnitude and significance of the overreaction anomaly changes under the more comprehensive GICS and across different time periods. Findings – The authors first confirm the over-reaction anomaly based on SIC as documented by TZ. Utilizing a larger sample of firms based on the GICS and extending TZ for a new time period, the authors then demonstrate that the overreaction anomaly disappears during recent years, a period that is characterized by markedly higher trading activity. Research limitations/implications – The findings provide new insights and contributions to the debate on whether or not market significantly misprices information transfers. Originality/value – The authors are first to utilize the GICS in evaluating intra-industry information transfers.

Characterising spatial logistics employment clusters

Purpose– The purpose of this paper is twofold. First to identify economic activities and broader spatial logistics functions that characterise an urban setting, and second to delineate significant spatial logistics employment clusters to represent the underlying regional geography of the logistics landscape.Design/methodology/approach– Using the four-digit Australian and New Zealand Standard Industrial Classification, industries “explicitly” related to logistics were identified and aggregated with respect to employment. A principal component analysis was conducted to capture the functional interdependence of inter-related industries and measures of spatial autocorrelation were also applied to identify spatial logistics employment clusters.Findings– The results show that the logistics sector accounts for 3.57 per cent of total employment and that road freight, postal services, and air and space transport are major employers of logistics managers. The research shows significant spatial clustering of logistics employment in the western and southern corridors of Melbourne, associated spatially with manufacturing, service industry and retail hubs in those areas.Research limitations/implications– This research offers empirically informed insights into the composition of spatial logistics employment clusters to regions that lack a means of production that would otherwise support the economy. Inability to measure the size of the logistics sector due to overlaps with other sectors such as manufacturing is a limitation of the data used.Practical implications– The research offers policymakers and practitioners an empirically founded basis on which decisions about future infrastructure investment can be evaluated to support cluster development and achieve economies of agglomeration.Originality/value– The key value of this research is the quantification of spatial logistics employment clusters using spatial autocorrelation measures to empirically identify and spatially contextualize logistics hubs.

LAS CLASIFICACIONES EN LAS EMPRESAS

A través de este breve trabajo deseamos resaltar diversos aspectos de la aplicación de los métodos clasificatorios en la organización de la información en la empresa y revisar la conveniencia de introducir en ella de técnicas clasificatorias aplicadas en el campo estadístico como en la Clasificación Internacional Industrial Uniforme (CIIU), la Clasificación Central de Productos (CPC), entre otros, con el propósito de establecer su utilidad como herramienta en la elaboración de indicadores de gestión que sirvan para realizar análisis comparativos entre la empresa y su entorno. En ese sentido, al lado del plan de cuentas, que es el conjunto mayor en la empresa y a partir del cual se desarrollan distintos agrupamientos como los catálogos de materiales y de productos, de maquinarias y de equipos, etc., existe la necesidad de incluir equivalencias entre ellos con los códigos internacionales de bienes y servicios y de actividades económicas usados en el comercio interno y externo, entre ellos, por ejemplo, las nomenclaturas arancelarias, la clasificación de bienes y servicios en las compras del Estado, los códigos de barras, etc. como complemento a los estados financieros.

An intra- and inter-industry evaluation of three classification schemes common in capital market research

We compare the Standard Industry Classification (SIC), the North American Industry Classification System (NAICS) and the Global Industry Classification Standard (GICS) schemes in their effectiveness to group stocks with similar operating characteristics. We are the first to analyse and compare individual functional category levels within and across each industry classification and test whether the three industry classifications show significant improvement in homogeneity with finer industry partitions across a wide range of research applications. Our results suggest that the GICS system offers advantages over the other two systems in grouping firms across all its levels of industry categories and across different application schemes common to capital market research. However, the SIC and NAICS offer additional advantages across their finest industry partitions. Our study has important implications for users of industry classifications in various financial and economic analyses, research settings and regulatory contexts.

EMPIRICAL ANALYSIS OF AGGLOMERATION ECONOMIES IN THE JAPANESE ASSEMBLY‐TYPE MANUFACTURING INDUSTRY FOR 1985–2000: USING AGGLOMERATION AND COAGGLOMERATION INDICES

This empirical study finds that positive but weak agglomeration economies resulted from the agglomeration of Japan's assembly‐type manufacturing industry during 1985–2000. Estimation results particularly indicate positive externalities from coagglomeration and very slightly increasing returns to scale. Traditional studies conceive of agglomeration economies as being related to localization and urbanization. We, however, estimate a flexible translog production function using four‐digit Standard Industrial Classification industry panel data and Ellison and Glaeser's agglomeration index with the same industry and coagglomeration index with different industry groups. We theoretically obtain appropriate and significant results without the homotheticity restriction.

Predicting a promising fusion technology in geoscience and mineral resources engineering using Korean patent data

This study uses patent analysis to identify those sectors in Korean geoscience and mineral resources engineering where technology fusion is possible, and those that seem to hold the promise of fusion technologies. The analysis is conducted using geoscience and mineral engineering technology 2008–2012 patent data and Korean Standard Industrial Classification-International Patent Classification concordance table. Specifically, we use fusion and promising indexes proposed by Kang [Kang, H. J. (2006). A study on the projection of the promising fusion technologies by US patent analysis. Kookmin University] to calculate and identify promising fusion technologies. The empirical results indicate that technologies in IPC subclass separation (B01D); mixing, e.g., dissolving, emulsifying, dispersing (B01F); chemical or physical process, e.g., catalysis, colloid chemistry (B01J); fuels, natural gas, synthetic natural gas (C10L); production or refining of metals (C22B); earth or rock drilling (E21B); investigating or analyzing materials by determining their chemical or physical properties (G01N); image data processing or generation (G06T); and signaling or calling systems (G08B) are promising fusion technologies. The technologies in these subclasses have been researched actively in recent years, and can be combined with other technologies more easily, based on our quantitative results. Therefore, assuming that this trend will continue at least for a few more years, the technologies in these subclasses could be promising fusion technologies.

Mapping Spatial Tourism and Hospitality Employment Clusters: An Application of Spatial Autocorrelation

This article analyzes the characteristics and spatial clustering of tourism and hospitality employment clusters in Victoria, Australia. Using cluster theory as the theoretical base, three interrelated research questions are specifically addressed: What industries constitute the tourism and hospitality sector? What broader “groupings” does the sector exhibit? Are these tourism and hospitality industries clustered around strategic areas of economic and resource advantage? Using the Australian and New Zealand Standard Industrial Classification (at the four-digit level), industries explicitly related to tourism and hospitality were first identified and total numbers of individuals working within these industries were aggregated at a level of Statistical Local Area (similar to a suburb or a neighborhood). Results show that in 2006 employment in tourism and hospitality equate to 7.74% of total employment in Australia. “Cafés and restaurants” (22%) is the single largest tourism and hospitality-related employer, followed by “takeaway food services” (20%) and “accommodation” (16%). Using factor analysis, four broader functions were extracted to characterize the underlying structure and functional interdependency among tourism and hospitality industries. These functions include: tourism operational services, hospitality services, entertainment services, and infrastructure operational facilities services. Spatial autocorrelation measures have identified five established tourism and hospitality spatial clusters in Victoria, which we argue hold the potential to act as tourism growth foci to create business synergy and generate spill-over effects through regional collaboration, competition, and sharing of pooled resources between firms.

Microfinance Institutions (MFIs) Profit Sharing Pattern for the Development of Micro and Small Enterprises (MSEs) in Indonesia

MSEs have a strategic role in the Indonesian economy. MSEs face some obstacles that do not provide optimal role in the economic development. Internal problem, MSEs operate only with limited capital and external problem is the absence of financial institutions that can lend capital to all MSEs. This paper is a study of literature with a case study on MSEs in Indonesia by Indonesian standard industrial classification codes. Data were obtained from the Central Bureau of Statistics and the Indonesian Islamic Banking Statistics. Data were analyzed with descriptive comparatif on frequency of five variables of MSE. Conclusions and implication, it is necessary MFIs are close physically and psychologically with MSEs, friendly, easy and fast in process of lending, growing from initiative of MSEs, by MSEs and for MSEs community, and operate in accordance with the traditional values of indigenous people of Indonesia. These MFIs are MFIs profit sharing pattern. MFIs profit sharing pattern which should be developed are MFIs that have a good track record. For the sustainability of MFIs activities, the government needs to help increase funding MFIs in the form of grant and loan.

A method to address the effectiveness of the SIC code for selecting comparable firms

To find peer firms is very important in several situations, for example in equity valuation using multiples for publicly traded firms, as well as for not publicly traded ones. Very often the pay of CEOs is set at the basis of a peer compensation group. Financial policies are often driven by a response to peers. It is a very common approach to use industry membership given by the SIC code to form peer groups. In the paper the effectiveness of the SIC (Standard Industrial Classification) code for selecting comparable firms is evaluated through nonparametric testing for difference in firm financial ratios.

An Intra and Inter-Industry Evaluation of Three Classification Schemes Common in Capital Market Research

We compare the Standard Industry Classification (SIC), the North American Industry Classification System (NAICS) and the Global Industry Classification Standard (GICS) schemes in their effectiveness to group stocks with similar operating characteristics. We are the first to analyse and compare individual functional category levels within and across each industry classification and test whether the three industry classifications show significant improvement in homogeneity with finer industry partitions across a wide range of research applications. Our results suggest that the GICS system offers advantages over the other two systems in grouping firms across all its levels of industry categories and across different application schemes common to capital market research. However, the SIC and NAICS offer additional advantages across their finest industry partitions. Our study has important implications for users of industry classifications in various financial and economic analyses, research settings and regulatory contexts.