3 Methodology
3.1 O1. Map the data landscape
In the past decades, the music industry was disrupted first by technological innovations that gave rise to mass piracy, then to the emergence of new streaming platforms, which replaced a significant part of the previous mechanical licensing sales model (physical sales and digital downloads) and public performance (a gradual shift from radio and music television to licensed streaming platforms and user-upload platforms like YouTube.) While new business models in advanced markets have brought back revenue growth into the music business, this business has been uneven. The previous research of our Consortium shows that emerging markets in Europe, and smaller music businesses (self-published creators, small labels) did not participate significantly in this growth. The large presence of zero-priced alternatives in licensed and not licensed, unauthorized forms (radio, YouTube, home copying, torrents) resulted in some markets in an overall decline in the value of music. Measuring such a change requires innovations in both measurement and valuation. Economic modelling and valuations are usually made when both quantity and price data is available (from accounting systems of ticket sales, or record sales), but on zero price platforms we do not have such information.
Our Consortium has extensive experience in using all recognized music valuation methods in practice.20 The recognized fair valuation principles stipulated that the “most applicable method” must be used in valuations, which almost always leaves out in copyright contests the (historical) “cost approach,” and leaves open the use of the “income approach” and the “market approach,” however, these approaches require modification when there are many zero-priced elements are present. Both the market approach, that we discuss first, and the income approach has particularly difficult methodological challenges.
IViR and Sant’Anna have similar experience in empirically researching and economic modeling the impacts of various free (legal and illegal) uses, but in international comparison and natural experiment settings, including a study for the European Commission on unlicensed content displacing licensed contents.21 Such studies require either natural experiments, or carefully designed and harmonized surveying. The former CEEMID partners, Artisjus, SOZA, and Reprex have been particularly focused carrying out such surveying following the methodological guidelines of ESSNet-Euroope to make the “market approach,” and IFPI’s “market comparators model” work with zero-priced platforms and unlicensed (private copying and illegal torrenting) environments in a national context, i.e., with a valuation purpose for an entire copyright jurisdiction22. Furthermore, given that Artisjus and SOZA are collective management societies that need to defend their valuations facing various national regulators, authorities, and potentially in court, we placed a big emphasis on reconciling such models with the jurisprudence of the Court of the European Union23.
One of our methodological aims is to further improve and harmonize surveying.
Surveying….
In Europe, after the implementation of the new Copyright Directive, the various royalty payment models of music streaming platforms, and user-uploaded content (UUC) platforms like YouTube will become more similar. In the licensed streaming model, subscription feels (and the distribution models of subscriptions feels, i.e., the pro-rata versus user-centric or other models) will pay an important role; the UUC model will rely more on shadow prices from sales of commercial, like radio. In streaming, however, we have long time series of notionally monthly royalty payments per recording/work, which allows the use of the “income approach” or DCF model on the level of individual songs, or aggregated to all the songs of an artist, or a label, or all songs of artists of a music export office, or even a nation.
However, currently, the basic transparency is missing from streaming markets. Market participants lack the data, the royalty accounting, data processing and economics know-how to understand the information that they receive. These problems related to the methodological problems of selectivity in big data, as understood by national statistics offices, but goes beyond that: it requires a professional separation of time accruals (some songs receive not one, but several months pay), weighted currency rate effects (artists receive a mix of payment from euro, dollar, yen, forint and other subscription and advertising fees), distribution model (pro-rata or user-centric with different distortions), volume and actual price. Only the separation of economic forces at play can provide easy-to-understand information to be revealed. Is Slovakia’s music exports getting more popular? Is a label present in markets where the value of music is shrinking or growing?
Our Consortium members have piloted the use of methods from quantitative finance and the creation of streaming indexes, like stock exchange and bond indexes. This methodological innovation is also in line with the policy proposal of the Finnish stakeholders to share and exploit information in some synthetic form that does not infringe business or personal data protection rules. With the economics expertise of SAAA, and the practical expertise of Reprex with the already published, 20-country CEEMID-CI indexes, and the help of Aloaded, a digital distributior. Relying on dynamic portfolio optimizmation models that are used to the creation of representative stock exchange indexs, like the Dow Jones Industrial Average (which do not reveal individual stock information, yet represent well the price movements of many stocks), we will create an algorithm of
After having individuated a suited stochastic process to describe the time series of the song’s performance, we will use valuation techniques derived from the financial literature, building of the work of the task leader24 for estimating its value. These models will be possibly augmented by fixed song-specific, correction resulting from the clustering analysis. This shall be instrumental to build valuations at the artist or label level by means of aggregation. Moreover, it will allow us to perform out-of-sample predictions about the future value of an artist or a label.
We will have access to streaming data from a) rightsholders and b) our digital distribution partner, Aload. Furthermore, using the spotifyr software maintained by our Consortium, we will access data from the Spotify Rest API directly. We will use biased, but large data samples, and we will employ advanced statistical, quantitative finance and computer science experience to improve our large, but biased datasets until they become representative.
3.1.1 Economic contributions
We calculate direct, indirect, and induced gross-value added, employment, and tax base effects with our iotables software. The methodological difficulty is working with a linear combination of NAcE 59 and NACE 90 in calculations. For such a combination, we use the music professional surveys and enterprise surveys.
3.1.2 Reconciliation of fair value and equitable remuneration
In our work, we will place a great emphasis to reconcile the legal concepts of intellectual properties, and particularly copyrights and neighboring rights with economics. This is both a scientific and practical necessity, because righsholders are selling rights created by intellectual property and copyright law. These rights are, from an economic point of view, artificial monopolies. As monopolies, they are protected by the TEU and national law, therefore they are not anti-competitive, but their exploitation must abide competition law, too.
Socio-legal scholars, economists, and royalty accountants and finance professionals use the concepts of their professions. Equitable remuneration is a legal concept which has an economic aspect. In international law, it was first enshrined as Convention C100 of the ILO, stipulating that men and women should receive equal pay for equal work. This convention is ratified by almost all countries in the world, with the notable exception of the United States. Within the context of international copyright law, it was introduced as a modification of the Berne Convention by the Rome Convention for the remuneration of the broadcasting of recorded fixation of music works (recordings) since 1971. These copyright conventions are administered by the WIPO (WIPO 1996a, 1996b). However, these international treaties do not set an international standard on how to calculate equitable remuneration, and do not apply to all uses of music works and their recordings, and various countries have a large leeway to set such rules.
The actual application of music valuation must not only abide by these rules, but also the accounting (which is harmonized on EU level, and under IFRS), particularly royalty accounting, and the economics of intellectual properties. Our valuation models transcent copyright jurisdiction—the fair value standard, for example, is incorporated in the law of every EU member state. Therefore, our economic indicators as benchmarks, and our valuation techniques will be applicable in all EU countries, but national copyright law (also governing neighboring rights) will certainly limit the practical applicability of our findings. In an international context, a study of Europe Economics and IViR has shown that there are notable differences in how equitable remuneration is understood – and it is often used as a synonym to fair remuneration (Europe Economics & IVIR 2015). In our understanding, the equitable remuneration should happen at fair value as defined by economics and international accounting standards. In our research output, we will always make sure that we make a sound analysis from statistical, economic, and copyright law perspectives, too.
3.1.3 Enterprise surveys
Enterprise surveying is very challenging, because most music enterprises are microenterprises, and they are exempted from standard statistical data collections (which in Europe usually start with an employee count of at least 10 people, a very rare phenomenon in music.) Cultural microenterprises usually do not have a clear activity profile, and it is very difficult to find out which microenterprises are active in the music industry, and which are not. Our approach in the past 8 years had been the use and perfection of a music professional survey, which is a microenterprise appropriate, personal survey. Making sure that such a survey remains representative is a difficult task.
3.2 O3. Empower stakeholders to take data-driven actions
In the last decade, the evidence-based policy movement gained significant traction in Europe, not only globally. The primary focus of reproducible research is to increase the rigour of the evidence generated, to improve the credibility and understandability of evidence created for policy purposes. Because evidence-based policies often rely on scientific evidence, the evidence-based policy movement went hand in hand with the efforts to increase the transparency and reproducibility of scientific research (See: (Munafò et al. 2017) and in an EU context [J (2015).)
The OPA Guidelines give practical guidance on how to improve the transparency, replicability, and as a result, the reusability of the policy-making work with a scientific underpinning. These goals are very well aligned with the policy recommendations and goals of the DG Research & Innovation, the directorate of the European Commission in charge (Commission et al. 2020; European Commission and Directorate-General for Research and Innovation 2020).
In the last decade, the evidence-based policy movement gained significant traction in Europe as well as globally. Its focus has been to increase the rigour of the evidence generated, to improve the credibility and understandability of evidence created for policy purposes. As evidence-based policies often rely on scientific evidence, the evidence-based policy movement went hand in hand with the efforts to increase the transparency and reproducibility of scientific research25
Knowledge4Policy (K4P) is the EU Commission’s platform for evidence-based policymaking. Our goal: to bridge the science-policy gap by bringing together evidence for policy from scientists across Europe, to policymakers across Europe.
, which grew out from several initiatives in research transparency, such as the Berkeley Initiative for Transparency in the Social Sciences, the Data Access and Research Transparency (DA-RT) group, the Center for Open Science and their TOP Guideline, the Meta-Research Innovation Center at Stanford University. Globally, the World Bank promotes this framework (Hoces de la Guardia, Grant, and Miguel 2020a; Berkeley Initiative for Transparency in the Social Sciences et al. 2020) and they are fully in line with the Open Science objectives of . For further details please refer to
3.3 O2. Bridge the data gap
Our policy tools will produce the first, large scale European application of the Open Policy Analysis.^ [The OPA Guidelines (Hoces de la Guardia, Grant, and Miguel 2020a; Berkeley Initiative for Transparency in the Social Sciences et al. 2020) are fully in line with the objectives of the European Union (Commission et al. 2020), but provide more technical guideance and checklists to follow.] We will support existing European efforts like the European Commissions’s Knowlege For Policy website, or the European Open Science Cloud, with very practical guideance on how to make and reproduce policies that aim to increase the value and visibility of the European music repertoires, increase the diversity of use, better match auidence expectations and artist supply, and to successfully incorporate innovation in trustwrothy AI, NFT and blockhain.
Following the state-of-the-art in reproducible, open policy analysis, we will introduce the “live policy document” developed by Reprex in cooperation with IVIR (in science), and Artisjus and SOZA (in music industry application.). This will follow the highest, Level 3 reproducability standard of OPA: there are no spreadsheets, separate word processor files. The valuation report on Bulgarian music is contained in a clearly documented dynamic document that contains the assumptions, software code to read in the data from the data sources, perform the modelling, create the visualizations, document citations, and place it in the same file with the conclusions. You can view such a dynamic document in the making for the UK Competition & Markets Authority here, or the results of this work with Europe’s first multi-country music industry report, the Central European Music Industy Report. Our “live policy documents” with a press of a button are reading in new information, change model outputs and visualizations, update the bibliography, place the results on the Zenodo open science repository with an authoritative copy and DOI
References
See @ref(#obj-economic-value) and references to (PwC 2008; IFRS 2011; Flignor and Orozco 2006; Puca and Zyla 2019).↩︎
On the decline of unathorized file sharing: (J. Poort and Rutten 2012; Joost Poort and Weda 2015), on displacements (Commission et al. 2017), and international comparisons: (Joost Poort et al. 2018).↩︎
The full market comparator model was used in Hungary by Artisjus (Antal 2019c), in Slovakia by SOZA (Antal 2019b), and also in Croatia (Antal 2019a)↩︎
Particularly OSA v Léčebné lázně Mariánské Lázně (InfoCuria 2014) and AKKA/LAA vs Konkurences padome (InfoCuria 2017), and respecting the settlement in the Commission v CISAC case (InfoCuria 2013).↩︎
Botazzi et al: Uncertainty in Firm Valuation and a Cross-Sectional Misvaluation Measure (Bottazzi et al. 2020).↩︎
See: (Munafò et al. 2017) and in an EU context (J 2015; Commission et al. 2020; European Commission and Directorate-General for Research and Innovation 2020).↩︎