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Standard Industrial Classification (standard + industrial_classification)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting40%

Selected Abstracts

The North American Industry Classification System and Its Implications for Accounting Research,

CONTEMPORARY ACCOUNTING RESEARCH, Issue 4 2003
Jayanthi Krishnan
Abstract Industry classification is an important component of the methodological infrastructure of accounting research. Researchers have generally used the Standard Industrial Classification (SIC) system for assigning firms to industries. In 1999, the major statistical agencies of Canada, Mexico, and the United States began implementing the North American Industry Classification System (NAICS). The new scheme changes industry classification by introducing production as the basis for grouping firms, creating 358 new industries, extensively rearranging SIC categories, and establishing uniformity across all NAFTA nations. We examine the implications of the change for accounting research. We first assess NAICS's effectiveness in forming industry groups. Following Guenther and Rosman 1994, we use financial ratio variances to measure intra-industry homogeneity and find that NAICS offers some improvement over the SIC system in defining manufacturing, transportation, and service industries. We also evaluate whether NAICS might have an impact on empirical research by reproducing part of Lang and Lundholm's 1996 study of information-transfer and industry effects. Using SIC delineations, they focus on whether industry conditions or the level of competition is the main source of uncertainty resolved by earnings announcements. Across all levels of aggregation, we find inferences are similar using either SIC or NAICS. How-ever, we also observe that the regression coefficients in Lang and Lundholm's model show smaller intra-industry dispersion for NAICS, relative to SIC, definitions. Overall, the results suggest that NAICS definitions lead to more cohesive industries. Because of this, researchers may encounter some differences in using NAICS-industry definitions, rather than SIC, but these will depend on research design and industry composition of the sample. [source]

When Businesses Sue Each Other: An Empirical Study of State Court Litigation

LAW & SOCIAL INQUIRY, Issue 3 2000
Ross E. Cheit
Using a mixture of court docket data and case files, we construct a data set of business litigation in Rhode Island Superior Court during 1987 and 1988. Business litigation is defined as a suit involving an economic firm as both a plaintiff and a defendant. The empirical analysis complements recent scholarship providing answers to descriptive questions about the frequency, nature of, parties to, and intensity of the business litigation docket. Using Standard Industrial Classification (SIC) codes, indicators of industry participation in litigation are developed, and positive analysis undertaken to explain variation across industries. Several hypothesis are developed and tested using quantitative analysis. We conclude that contextual economic conditions favoring the creation of long-term business relationships help prevent litigation between firms. [source]

Population Synthesis: Comparing the Major Techniques Using a Small, Complete Population of Firms

GEOGRAPHICAL ANALYSIS, Issue 2 2009
Justin Ryan
Recently, disaggregate modeling efforts that rely on microdata have received wide attention by scholars and practitioners. Synthetic population techniques have been devised and are used as a viable alternative to the collection of microdata that normally are inaccessible because of confidentiality concerns or incomplete because of high acquisition costs. The two most widely discussed synthetic techniques are the synthetic reconstruction method (IPFSR), which makes use of iterative proportional fitting (IPF) techniques, and the combinatorial optimization (CO) method. Both methods are described in this article and then evaluated in terms of their ability to recreate a known population of firms, using limited data extracted from the parent population of the firms. Testing a synthetic population against a known population is seldom done, because obtaining an entire population usually is too difficult. The case presented here uses a small, complete population of firms for the City of Hamilton, Ontario, for the year 1990; firm attributes compiled are number of employees, 3-digit standard industrial classification, and geographic location. Results are summarized for experiments based upon various combinations of sample size and tabulation detail designed to maximize the accuracy of resulting synthetic populations while holding input data costs to a minimum. The output from both methods indicates that increases in sample size and tabulation detail result in higher quality synthetic populations, although the quality of the generated population is more sensitive to increases in tabular detail. Finally, most tests conducted with the created synthetic populations suggest that the CO method is superior to the IPFSR method. Los modelos desagregados basados en micro data han recibido la atención relativamente reciente de los círculos académicos y de aplicación. La colección de dicha data es una tarea difícil por cuestiones de accesibilidad, confidencialidad, datos incompletos o altos costos de adquisición. Por esta razón se han creado indicadores sintéticos como a alternativa a la recolección directa de datos. Los dos indicadores sintéticos mas discutidos/conocidos son el método de Reconstrucción Sintética (Sytnthetic Reconstruction method) (IPFSR) que hace uso de técnicas de Ajuste Proporcional Iterativo (IPF); y el método Optimización Combinatoria (CO). Ambos métodos son descritos en este artículo y luego evaluados en base a su habilidad de recrear una población de empresas ya conocidas o preestablecidas. Contrastar una población sintética versus una población conocida es una operación poco frecuente porque la obtención de una población entera es por lo general bastante difícil. El caso presentado en este estudio utiliza una población pequeña y completa de empresas en la ciudad de Hamilton, Ontario (Canadá) para el año 1990. Las variables recopiladas son el número de empleados, SIC (código estandarizado de clasificación industrial), y ubicación geográfica. Los resultados que se reportan en el presente estudio son producto de varios experimentos basados en varias combinaciones del tamaño de la muestra, y del detalle en la tabulación diseñados, los mismos que fueron diseñados para maximizar la exactitud de las poblaciones sintéticas calculadas y al mismo tiempo minimizar los costos de datos necesarios. Los resultados obtenidos por ambos métodos indica que los incrementos en el tamaño de la muestra y en el detalle de la tabulación resultan en un estimado de poblaciones mejor, aunque este estimado es particularmente sensible a incrementos en el detalle de las tabulaciones. Finalmente, la mayoría de pruebas realizadas con las poblaciones sintéticas generadas para este estudio sugieren que el método CO es superior al método IPFSR. [source]

Occupation and multiple myeloma: An occupation and industry analysis

AMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 8 2010
Laura S. Gold PhD
Abstract Background Multiple myeloma (MM) is an incurable plasma cell malignancy with a poorly understood etiology. The purpose of our research was to examine the relationships between lifetime occupations and MM in a relatively large case,control study. Methods MM cases (n,=,180) were identified through cancer registries in the Seattle-Puget Sound area and Detroit. Population-based controls (n,=,481) were identified using random digit dialing and Medicare and Medicaid Services files. In-person interviews were conducted to ascertain occupational histories. Standard occupational classification (SOC) and standard industrial classification (SIC) codes were assigned to each job held by each participant. Unconditional logistic regression was used to generate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between MM and having ever worked in each occupation/industry and according to duration of employment in an occupation/industry. Results The risk of MM was associated with several manufacturing occupations and industries, including machine operators and tenders, not elsewhere classified (SOC 76) (OR,=,1.8, CI,=,1.0,3.3); textile, apparel, and furnishing machine operators and tenders (SOC 765) (OR,=,6.0, CI,=,1.7,21); and machinery manufacturing, except electrical (SIC 35) (OR,=,3.3, CI,=,1.7,6.7). Several service occupations and industries, such as food and beverage preparation (SOC 521) (OR,=,2.0, CI,=,1.1,3.8), were also associated with MM. One occupation that has been associated with MM in several previous studies, painters, paperhangers, and plasterers (SOC 644) was associated with a non-significantly elevated risk (OR,=,3.6, CI,=,0.7,19). Conclusions We found associations between the risk of MM and employment in several manufacturing and service-related occupations and industries. Am. J. Ind. Med. 53:768,779, 2010. © 2010 Wiley-Liss, Inc. [source]

The Equilibrium Yen,Dollar Rate: 1976,91

ASIAN ECONOMIC JOURNAL, Issue 1 2002
Anthony De Carvalho
This paper presents a definition of the equilibrium exchange rate that is based on a modified version of purchasing power parity (PPP) for traded goods. Employing constant elasticity of substitution (CES) production functions and data from 28 three-digit international standard industrial classification (ISIC) manufacturing industries, the equilibrium Yen-Dollar rate is calculated for the period between 1976 and 1991 (a time in which the Yen appreciated markedly against the Dollar) showing that the actual Yen-Dollar rate closely tracked the equilibrium rate over that time. The results suggest that strong growth in Japanese labor productivity, coupled with Japan's relatively low capital-labor elasticity of sub-stitution, were the main contributors to the Yen's long-run appreciation. [source]