RUMS – how to compare structures of enterprise groups?
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| Title: | RUMS – how to compare structures of enterprise groups? |
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| Authors: | Rommelspacher, Simon1 (AUTHOR) Simon.Rommelspacher@destatis.de, Urban, Adrian1 (AUTHOR) |
| Source: | Statistical Journal of the IAOS. Nov2024, Vol. 40 Issue 4, p941-948. 8p. |
| Subjects: | Commercial statistics, Data structures, Data quality, Rum, Statistics |
| Abstract: | In a globalised and interconnected world, enterprise groups play an increasingly important role in the economy. At the same time, it is becoming more difficult for official statistics to map these structures correctly to be able to analyse them for the various statistical areas. Enterprise groups have complex data structures that often come from different data sources of varying quality and need to be compared at different points in time. Comparing these complex and growing entities is not trivial and has therefore rarely been done in the past across countries and sources. To fill this gap, inspired by other similarity metrics, a new similarity metric has been developed in the German statistical business register: RUMS – Rommelspacher-Urban Metric for Similarity of enterprise groups. RUMS enables the comparison of enterprise groups within and between statistical business registers. This allows the quantification of changes over time or deviations in different business registers, which can help to detect data inconsistencies to increase data quality. RUMS is defined in a way that allows flexible adjustments to the weightings of the properties that are considered in the calculation based on the specific needs of the use case. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | In a globalised and interconnected world, enterprise groups play an increasingly important role in the economy. At the same time, it is becoming more difficult for official statistics to map these structures correctly to be able to analyse them for the various statistical areas. Enterprise groups have complex data structures that often come from different data sources of varying quality and need to be compared at different points in time. Comparing these complex and growing entities is not trivial and has therefore rarely been done in the past across countries and sources. To fill this gap, inspired by other similarity metrics, a new similarity metric has been developed in the German statistical business register: RUMS – Rommelspacher-Urban Metric for Similarity of enterprise groups. RUMS enables the comparison of enterprise groups within and between statistical business registers. This allows the quantification of changes over time or deviations in different business registers, which can help to detect data inconsistencies to increase data quality. RUMS is defined in a way that allows flexible adjustments to the weightings of the properties that are considered in the calculation based on the specific needs of the use case. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 18747655 |
| DOI: | 10.1177/18747655241298573 |
