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Socio-Economic Objective Classification (SEO) Codes
Relationship Between the SEO Classification and the ANZSIC
The ANZSIC is a classification of industries. Business units reporting data to a range of ABS censuses and surveys are classified to the ANZSIC on the basis of their predominant economic activity (e.g. what they do to generate income). Normally income is generated through the sale of goods and services produced by the business or bought in from other businesses. An industry as represented in ABS statistics is made up of businesses which are classified to it in accordance with the ANZSIC.
When comparing R&D data classified by the SEO with industrial statistics based on the ANZSIC, there are some important considerations to be noted:
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Classifying to an SEO category is subjective, i.e. the category is chosen by the data provider to indicate the main purpose of R&D. Classifying a business to an industry is generally derived objectively through information about its main income generating activity.
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SEO categories do not always correspond with ANZSIC categories on a one to one basis and do not also necessarily correspond with identifiable target industries. For example where the environment is the main potential beneficiary of the R&D, there is no set of business units equivalent and therefore no ANZSIC class is applicable.
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Some SEO categories are too broad and cannot be correlated to ANZSIC industries. For example, R&D towards improving road safety has potential benefits to a wide range of industries, community services and individuals. There would be some effect on businesses within the transport industry, but this may be incidental to attempts at generally reducing the burden on emergency services, medical services, insurance services, disability services, police services, legal services, etc.
- The nature of R&D is such that there may be no observable effect on ABS industry level statistics, or at least the effect may be difficult to assess. The positive effects of R&D may be concealed at the aggregate industry level because of variation, for a variety of reasons, in data from establishments in the same industry. Additionally, in particular instances, R&D may not lead to initiatives which proceed beyond the test environment.
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