Music Industry Mapping
The copyright and neighboring right royalty is the wage-like earning of the music performer, the composer and producer. In popular music performers usually play their own composition and sing their own lyrics. If the musician is self-published, all the three royalties directly pay the artist’s work. If a professional publisher is helping the artist as a composer, or a record producer as a recorded performer, they usually share the respective royalty revenues. In emerging markets fewer, in mature markets more composers are represented by publishers and performers by record labels.
Classification of Industries
The nature of the creative jobs is that they contain a wide range of activities. Economists and government policymakers classify industries with the Nomenclature statistique des activités économiques dans la Communauté européenne, in short, with the NACE classification in Europe. This classification is largely harmonized on UN level and can be used to compare almost all economies in the world. The NACE classification has its origins in the economic structure of the middle 20th century, and it is more appropriate for the classification of manufacturing and trading activities, such as car manufacturing, or retail sale of cars.
The music industry is not even recognized by the NACE classification. For example, musicians often perform music (NACE group 90), compose music (NACE group 90), and at the same time do sound recordings (NACE group 58) and teach music (NACE group 85). Many EU member states do not even create government economic statistics for the NACE 90 classes.
This is the main reason why music is not well represented in governmental statistics, which is mainly based on tax returns data from ‘clear’ activity groups, such as sound recordings only. Most creative enterprises, and music businesses are no excemptions, do not have a clear economic activity.
Microenterprises & Freelancers
The music industry, for various reasons, is not part of the NACE industry, and music industry data must be mapped from different data sources. A further difficulty is that music industry, similarly to the other creative and cultural industries, mainly works in freelancer networks and microenterprises. All over Europe, microenterprises are exempted from many statistical reporting, and they are filing simplified tax and financial reports.
The government statistics are largely based on tax returns and other filings of corporate entities with at least 5 employees. While most manufacturing or trading activities, or licensed service activities such as insurance or banking, are easy to classify, the creative industries are different. Because most creative enterprises are smaller than 5 people, they do not file many data for the government or the tax authorities, and they often carry out heterogeneous activities. For example, the music industry is not even recognized by the NACE classification – the live music and compositions can be found in the NACE 90 class, and the sound recordings in the NACE 58 class, and many countries do not even create government economic statistics for the NACE 90 classes.
Standardized mapping
CEEMID has been mapping data sources for composer, producer and performer royalties, and other data sources since 2014, based on the standard mapping technique developed originally in the United States and later adopted to the EU ^[Hull, Geoffrey P., Thomas W. Hutchison, Richard Strasser, and Geoffrey P. Hull. 2011. The Music Business and Recording Industry Delivering Music in the 21st Century. New York: Routledge; Leurdijk, Adnra, and Nieuwenhuis Ottilie. 2012. Statistical, Ecosystems and Competitiveness Analysis of the Media and Content Industries. The Music Industry. 25277 EN. Edited by Jean Paul Simon. Luxembourg: Publications Office of the European Union, 2012: Joint Research Centre Institute for Prospective Technological Studies (IPTS).].
CEEMID designed and administered the world’s biggest data collection on how musicians work and earn their living. Over the course of 6 years we collected anonymous data among musicians related to their touring habits, income, costs, recording expenses and income in various channels.
About 100 stakeholders, among them many collective management organizations helped our work. Some collective management organizations provided us with anonymous payout lists, which was essential to validate the representativeness of our samples. We reconstructed the density function of actual payouts, and collected data until our anonymous responses showed a very accurately similar shape.
Because the music industry all over Europe is mainly made of microenterprise and freelancers, getting an overal picture of the music industry is very difficult.