Data, operationalization and sample 1. Data and operationalization

3. Data, operationalization and sample

units. Therefore, we assign weights to the formats in the following way. Every sold music album is assigned a weight of 1 (i.e., CD-, MC-, LP-, and digital albums). We follow the IFPI’s official reporting practice and convert physical singles to album units by assigning a weight of 1/3 to every sold unit (i.e., 3 singles = 1 album; IFPI 2005). Following the same underlying logic, we convert digital track downloads to album units by assigning a weight of 1/10 to every downloaded track (i.e., 10 tracks = 1 album). By summing up the weighted units across the different formats we obtain the focal dependent variables for our analyses:

the per capita music sales of country i in year t. The mean of this variable across countries and years is 1.28 units. Over the observation period, per capita sales decayed by 55% from 1.66 units in 1996 to .75 units in 2010. The sales development for the 38 analyzed countries is graphically depicted in Figure 2.

>>> Figure 2 about here <<<

3.1.2. Internet piracy. Because data on Internet music piracy rates is not available, we fol-low previous research and rely on Internet penetration as a proxy for file-sharing (e.g., Liebowitz 2008). Specifically, we use broadband Internet penetration as a proxy for piracy, while conditioning on dial-up Internet penetration, i.e., the speed of the Internet connection serves as the proxy for Internet piracy (see Zentner 2009). Information on broadband Internet penetration was collected from the World Bank’s world development indicators databank.

The variable is defined as the number of fixed broadband Internet subscribers per 100 people.

The numbers are derived based on insights from the International Telecommunication Union, the World Telecommunication/ICT Development report and database, as well as World Bank estimates. The mean broadband Internet penetration over the observation period was 8.30%.

Broadband penetration was zero in 1996 and 1997 and increased from 1% in 1998 to 21% in 2010 (see Figure 2).

3.1.3. ICT diffusion. Data on Internet penetration rates that include dial-up access and data regarding mobile cellular subscriptions were also collected from the World Bank’s world development indicators databank. The definition and data sources are analogous to the broad-band variable. The mean Internet (cell phone) penetration over the observation period was 35% (62%). Internet penetration increased from 4.05% in 1996 to 62.48% in 2010 (see Fig-ure 2). The cell phone penetration was 9% in 1996 and increased to 110% in 2010.⁶

3.1.4. Marketing. Because we observe annual music sales in terms of both units and reve-nues, we are able to compute the average price per unit.⁷ To do this, the revenue variable, which is measured in local currencies at current retail prices, is first inflation-adjusted using the country-level consumer price index from the World Bank with 2010 serving as the base year so that a comparison across years is possible. These inflation-adjusted values are then converted to US dollars at the official exchange rate for the year 2010 from the World Bank.

The country- and year-specific retail revenue is then divided by the sold units. This yields the average retail price in constant 2010 US dollars of a sold unit in country i in year t. The mean price of a music album across countries and years was US$ 15.01. The average retail price has declined by approximately 28% over the observation period from US$ 16.78 in 1996 to US$ 12.14 in 2010, which appears realistic, considering the lower retail prices of digital sic albums (e.g., 9.99 US$) compared to physical music products and the possibility that mu-sic companies adjusted prices in response to piracy (Hui and Png 2003).

6 The cell phone penetration rate may exceed 100% if consumers in a given country on average own more than one device.

7 Note that revenues are reported in retail value before 2001, in retail and trade value from 2001 to 2005 and in trade value since 2006. The trade value “refers to record companies revenue, net of discounts, net of returns, net of taxes,” whereas the retail value represents an “estimate of the final value paid by the consumer for the pur-chase of a music product, inclusive of relevant sales taxes and retailer markup” (IFPI 2005).We opt for retail values in our analyses to better reflect the prices that had to be paid by the consumer. To allow for a comparison across years, we convert the trade values for the years after 2005 to retail values using the country-specific

aver-To control for the fact that an increasing level of single purchases may influence overall sales levels, we compute the share of single format sales in country i in year t as follows:

, (1) where ! "#!" refers to the single format sales volume (i.e., CD-singles and digital track downloads) and $%!&# "#!" refers to the overall sales volume in country i in year t.

3.1.5. Economy. Data on per capita gross domestic product (GDP) and unemployment were collected from the World Bank’s world development indicator databank. The GDP serves as a proxy for per capita income and is measured in ‘000 constant PPP adjusted 2005 US dol-lars. We opt for a PPP-based measure to allow for a more realistic comparison of the coun-tries’ income development over time relative to the other countries.⁸

3.1.6. Policy. In the previous section we formulated our expectations that economic policies will be relevant to our research context because they proxy for both the level of IP protection as well as the existence of a sound business environment. Thus, we needed a measure which covers both of these aspects and which is available for the whole observation period. The Economic Freedom Index is compiled annually by The Heritage Foundation in cooperation with The Wall Street Journal based on 10 quantitative and qualitative factors, grouped into the four categories (1) rule of law (i.e., property rights, freedom from corruption), (2) open markets, (3) regulatory efficiency, and (4) limited government (please see The Heritage

8 We follow Talukdar, Sudhir, and Ainslie (2002) and rely on a PPP adjusted income measure to account for differences in prices across countries. This approach captures the true differences in purchasing potential of income across countries, especially when analyzing a diverse group of countries as it is the case here (The World Bank 1993; United Nations 1990). For example, if the value of a given domestic currency devalues by 50% against the US dollar, this country’s GDP measured in US dollars will also decrease by halve. However, this does not necessarily mean that individuals in this country are worse off by 50% if the income and prices measured in domestic currency remain stable and imported goods are not crucial to the quality of life. We also estimate the model with other routine GDP measures (e.g., in constant US dollars using national deflators), which does not alter the conclusions.

Foundation (2014) for details). Thus, this measure represents a good candidate for our pur-poses.⁹

We validate whether this measure represents a valid proxy for the level of IP protection based on two alternative indices that both aim to capture the level of IP protection, but that are not available for the full observation period. First, the World Economic Forum’s (WEF) annual survey of 15,000 executives from 138 countries includes a question pertaining to the IP protection under the second pillar “Political and Regulatory Environment” as part of its

“Global Information Technology Report” (Dutta and Mia 2011). The question reads “How would you rate the intellectual property protection, including anti-counterfeiting measures, in your country? [1 = very weak; 7 = very strong]”. This variable is available since 2002 and is positively correlated with the Economic Freedom Index (r = .73; p < .001; n = 342). Second, the Intellectual Property Rights Index (IPRI) is constructed annually based on secondary data from various sources and, besides IP rights, also captures physical property rights as well as the legal and political environment (Jackson 2011). The IPRI is available from 2006 and ranges from 0 to 10, with 10 indicating the strongest level of property rights protection. The high degree of correlation between the IPRI and the economic freedom measure of r = .83 (p

< .001; n = 183) again indicates that the Economic Freedom Index constitutes a reasonable proxy for the level of IP protection.

As a measure of policy continuity, we used the Political Constraints Index proposed by Henisz (2000), which measures the feasibility of policy change in a country (please refer to Henisz (2000) for details). For example, Henisz (2002) shows that political environments that limit the feasibility of policy change, i.e., that exhibit a high degree of policy continuity, are an important driver of infrastructure investments.

9 An alternative measure of economic freedom is available from the Fraser Institute. Unfortunately, this measure

3.1.7. Global connectedness. We use the KOF index of social globalization as the first measure of a country’s global connectedness (Dreher 2006; Dreher, Gaston, and Martens 2008; KOF 2014). The measure comprises various indicators that are grouped into three cat-egories: (1) data on personal contacts (i.e., telephone traffic, transfers, international tourism, foreign population, and international mail), (2) data on information flows (i.e., internet, tele-vision, and newspapers), and (3) data on cultural proximity (i.e., number of McDonald's res-taurants, number of Ikea shops, and trade in books) (please refer to Dreher, Gaston, and Mar-tens (2008) for details). Moreover, we use the Freedom of the Press Index compiled by Free-dom House to control for the degree to which a country’s government imposes restrictions on information flows (see Freedom House (2014) for details).

3.1.8. Infrastructure and interpersonal communication. We operationalize the degree of urbanization, using data regarding “the population in urban agglomerations of more than 1 million,” which is provided by The World Bank. Furthermore, we collect information regard-ing the “road sector energy consumption” and the “female labor participation rate,” which were also retrieved from The World Bank, as proxies for the degree of mobility, as well as a country’s openness to change and the level of heterophilous influence, respectively.

3.1.9. Individualism. Finally, we obtain our measure of the degree of individualism versus collectivism in a society from Hofstede (2014).

3.2. Sample

Overall, the IFPI reports contain data regarding the music sales of 49 countries. To ensure the validity of our results, we restrict our analyses to 38 countries for which we could obtain suf-ficient data with respect to the aforementioned variables during our observation period (i.e., 1996 - 2010). The time series of 11 countries exhibited gaps of 1/3 (i.e., 5 years) or more so that we discarded these countries from the analyses. Note, however, that the excluded

coun-tries are rather small music markets.¹⁰ Based on the 2010 trade value, the 38 countries in our sample include the 20 largest music markets worldwide and together account for more than 95% of the global music industry’s revenue (IFPI 2011b). Table 4 reports the mean per capita sales of the 38 countries over the observation period.

>>> Table 4 about here <<<