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Jun 1, 2009 - juggernaut. And there is some suggestive evidence of this in the music context that we study: since 2000,

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Idea Transcript


Pop Internationalism: Globalization of the Music Industry, 1960-2006

June 1, 2009 Very Preliminary – please do not cite or circulate Fernando Ferreira The Wharton School University of Pennsylvania Joel Waldfogel The Wharton School University of Pennsylvania and NBER Abstract Advances in communication technologies over the past half century have made the cultural goods of one country more readily available to consumers in another, raising concerns that cultural products from large economies – in particular the US - will displace the indigenous cultural products of smaller economies. The debate over trade in cultural products has been better informed by theory than evidence. The goal of this project is to document some facts about the global music industry since 1960, using data on popular music charts from 11 countries (Austria, Brazil, Canada, France, Germany, Italy, Norway, Sweden, Switzerland, UK, US). Who buys whose music? How has it changed over time? And how do music trade patterns compare with trade patterns for movies? We find that while Hollywood fare dominates world trade in movies, music is quite different. While domestic musical repertoire is disproportionately popular everywhere, repertoire shares among imports are closer proportional to exporting countries’ GDP shares. Overall, different countries’ musical repertoires have world shares roughly equal to their GDP shares. Surprisingly, as the world has become better linked over the past half century, the US has grown less dominant in music relative to GDP. Since 2000 the trade in music has been more balanced – in line with GDP shares – than at any time since 1960, and domestic artists have increasing market shares in almost all markets. These facts are surprising against the backdrop of technological change that makes trade easier.

I.

Introduction

Advances in communication technologies over the past half century have made the cultural goods of one country more readily available to consumers in another. While reduced trade costs are generally good news for consumers – they make a wider range of products available to more people – reduced trade costs in cultural goods are greeted with even less enthusiasm than usually accompanies trade in goods. First, a large group outside economics is concerned with possible negative effects of cultural products from large economies on the local cultural products of smaller economies. Observers inside of economics have begun to explore these arguments seriously, with models that take account of returns to scale, habit formation, and other features.1 These models point to a possible welfare-enhancing role for trade restrictions. The US is often held out as the 800-pound gorilla, spreading its vulgar popular culture around the world and abusing its large home market effect to produce an unstoppable cultural juggernaut. And there is some suggestive evidence of this in the music context that we study: since 2000, 18 artists have appeared simultaneously on at least 10 countries’ charts in at least one year. Thirteen of these artists – Black Eyed Peas, Britney Spears, Destiny's Child, Eminem, Evanescence, Gnarls Barkley, Gwen Stefani, Jennifer Lopez, Justin Timberlake, Madonna, Outkast, P!Nk, Pussycat Dolls – are American. See Table 1. While it has become easier for the world’s consumers to get access to US music, at the same time it may also have become easier for the world’s music producers to get access to the US – and other – markets (Cowan, 2002). The remaining five artists appearing on charts around the world are from a variety of countries of varying sizes: Enrique Iglesias (Spain), Kylie                                                              1  See, for example, Bala, Venkatesh and Van Long (2005), Janeba (2004), Francois and van Ypersele (2002), Rauch and Trindade (2004), and Suranovic and Winthrop (2005).   

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Minogue (Australia), Nelly Furtado (Canada), Santana (Mexico), and Shakira (Colombia). So while it’s possible that artists from large countries would displace artists from smaller countries, it is also possible that in a connected world, small-country artists could find new export audiences. The debate over trade in cultural products has been better informed by theory than evidence.2 The goal of this project is to document some facts about the global music industry since 1960, using data on popular music charts from 11 countries (Austria, Brazil, Canada, France, Germany, Italy, Norway, Sweden, Switzerland, UK, US). Who buys whose music? How has it changed over time? And how do music trade patterns compare with trade patterns for movies, a cultural product perceived as sufficiently threatening to lead some countries, such as France, to subsidize domestic production? Before proceeding, we note that by “globalization,” we simply mean greater access of consumers to music from other countries. The paper proceeds in four sections after the introduction. Section 1 reviews the literature and provides theoretical background that motivates the questions we ask. Section 2 describes the data used in the study. Section 3 reports results on music. Section 4 then turns to a comparison of trade patterns for music and movies. We find that while the industry of a single country dominates world trade in movies, music is quite different. In music, different countries’ repertoires have world shares roughly equal to their GDP shares. While domestic repertoire is disproportionately popular everywhere, repertoire shares among imports are closer proportional to exporting countries’ GDP shares. Surprisingly, as the world has become better linked over the past half century, the US has grown                                                              2

 As we discuss below, there have been some significant empirical studies, including Hanson and Xiang (2008) and Disdier, et al (2007, 2009). 

3   

less dominant in music relative to GDP. Since 2000 the trade in music has been more balanced – in line with GDP shares – than at any time since 1960, and domestic artists have increasing market shares in almost all markets. These facts are surprising against the backdrop of technological changes that makes trade easier. MTV and the Internet may have played a role, but more research is needed.

I.

Background

1. Theory Music and movies are differentiated products that are produced subject to increasing returns. The motivations for trade in such products are outlined in Krugman (1979): consumers like variety, and trade makes a wider variety of products available to consumers in each country. Because of increasing returns, each variety is produced in only one country. It is not clear which product gets produced where, but trade is balanced in the sense that the representative consumer’s product bundle has proportional representation from each producing country (according to the respective countries’ sizes). This simple model, with identical tastes and capabilities throughout the world gives simple predictions: artists from each country will have a world music market share equal to their countries’ share of the world economy/labor force. Or, more specifically, and

⁄∑

⁄∑

, where

= the sales of music by artists from country (i)

= GDP of country (i). When transport costs are introduced to the model (Krugman, 1980), producers have

incentives to agglomerate production in locations with large home markets, an effect exacerbated

4   

by stronger increasing returns. When these effects operate, we expect larger countries’ products to have disproportionately larger world market shares. Transport costs have both literal and figurative interpretations. Literally, it can be costly to ship products around the world, although these costs have declined sharply for information products since the development of the Internet.3 Figuratively, cultural goods may be thought to have “transport costs” in that people of one country may find products from another country – and another culture – less appealing. Sutton (1991) provides a complementary set of ideas for thinking about possible dominance of the world market by large-market producers. When product quality is determined by investments in fixed costs – as is clearly the case for media products – and when consumers agree on what constitutes quality, so that competition is vertical – not so obviously applicable to all media products - then market enlargement need not lead to fragmentation.4 The opening of trade is a form of market enlargement, explicitly so if the tastes of the trading countries are identical. With a larger market, a firm can profitably maintain market share by larger investments in quality, maintaining market share even as market size increases. While some features of media products – heavy reliance on fixed costs – correspond well to the Sutton setup, others may not. First, while competition may indeed have some vertical aspects, it is also clear that music products are horizontally differentiated (think, for example, of different genres of popular music, including country, rap, and pop). Moreover, different countries quite possibly have different taste distributions.                                                              3

 See Blum and Goldfarb (2006) for an interesting documentation of distance effects in cross‐national Internet use,  where literal transport costs are zero.  4  Berry and Waldfogel (forthcoming) draw on Sutton (1991) to interpret the relationship between market size and  concentration in US newspaper markets. 

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So while Sutton provides a way to organize thinking about how the worldwide availability of Britney Spears could result in her domination of the world market for popular music, the framework also provides ways to rationalize continued fragmentation and continued attachment to domestic products in the face of globalization, or greater trade possibilities.

2. Relevant Literature Economists have recently developed theoretical models in which the effect of trade in cultural goods has ambiguous benefit. Francois and Ypersele (2002) develop a model in which domestic consumers value both a global (“Hollywood) and a local good. Because of fixed costs, the local good can be driven out by trade, so depending on the distribution of tastes, it’s possible for a tariff on foreign movies to be welfare-improving. Janeba (2003) develops a model of trade in cultural goods in which consumers derive identity from their domestic goods. Individuals derive their identity from both their own and their peers’ consumption choices, giving rise to a mechanism that operates similar to a network externality. Janeba shows, among other things, that trade can be welfare improving if the world is culturally homogeneous but may not be if countries are culturally diverse. Bala and Van Long (2005) develop an evolutionary model in which trade can allow the preferences of a large country to take over the preferences of a smaller country. If the price of some good, say the domestic cultural product, rises, then consumers of that good become less evolutionarily fit, and their population can dwindle toward extinction. Such results can, in turn, justify restrictions on cultural imports into smaller countries. All of these models suggest problems with displacement of local products. But the concerns they raise are relevant only if 6   

the products of some countries actually drive out the products of others, a question this paper seeks to address. Despite the recent outpouring of theoretical interest in cultural trade, there is relatively little empirical work in economics that speaks to these issues. Cowan (2002), critical of naïve anti-globalizationists, provides anecdotal evidence that globalization allows promotion of smallcountry cultures. Another related strand of work examines the effect of distant, as opposed to local, media products on behaviors. Research in this vein includes Oster and Jensen’s (2007) work on the spread of cable television to remote regions of India and concomitant effects on treatment of local women, research on the effect of the spread of national newspapers on the targeting of local newspaper products (George and Waldfogel, 2006), and work on the effect of local media products on voter turnout (Oberholzer Gee and Waldfogel, 2005, forthcoming). Disdier, Head and Mayer (2009) provide evidence that the introduction of foreign television in France causes substantial changes in baby naming, away from traditional French names such as Sebastien drawn from saint names and toward American names such as “Dylan” or “Brenda.” This is evidence that trade in cultural products – in this case television programming – affects a symbolically important aspect of culture, how children are named.

3. Music Industry The recorded music industry generated roughly $30 billion in annual revenue in 2006, and in 2007 the ten largest markets for recorded music were the US, Japan, UK, Germany, France, Canada, Australia, Italy, Russia, Netherlands, and Spain. These countries collectively 7   

accounted for about three quarters of world recorded music sales. Sample countries account for roughly two thirds. See Figures 1 and 2. Music sales vary across countries with GDP. As Figure 3 indicates the ratio of music sales to GDP increases in GDP, suggesting that the income elasticity of demand for music exceeds 1 and that music is a luxury good.5 As with other cultural industries, music’s contribution to GDP may understate its importance to citizens and consumers. The promotion of domestic musical artists is of sufficient importance that many countries mandate their carriage on domestic radio. Since 1972 Canada has mandated that a certain share – now 35 percent – of music be of Canadian origin. Since 1996, France has required 40 percent of music on the radio to be French. See Bernier (2003).

The foregoing section serves to organize the descriptive analysis that follows, in which we seek to examine two questions: 1) Who trades with whom in the popular music market? Is trade balanced, or do artists from large play a disproportionate share? 2) How have patterns of trade changed over the past half century as “transport costs” of various sorts (literal, based on cultural distance) have declined? Has globalization promoted increased or decreased dominance by artists from large countries?

II.

Data

                                                             5

 Strictly speaking, one should examine the relationship between expenditure on music and total expenditure, not  GDP.  But the figure is suggestive nonetheless. 

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The basic data for this study are the chart entries from 11 countries, 1960-2006. Charts are collected from disparate sources, so they differ in frequency and length (number of positions). For many countries and years, we have weekly top 20 charts. For others, we have the weekly top 10. We have weekly charts for 10 of the countries over at least some years. For one country – Brazil – we have only an annual top 100 chart. The data include a total of 345,699 chart entries. Tables 2 and 3 describe the underlying data’s frequency (e.g. weekly or monthly) and the length of the periodic music charts (e.g. top 10 vs top 40). A full chart entry is both an artist and a song. Ideally, we would have a dataset with clean artist-song entries – the artist and song are spelled and punctuated the same in every country’s chart. In reality, a great deal of data cleaning is required. To keep the task manageable, we have focused on artist names only rather than artist-song combinations. Focusing on artists rather than songs allows us to get at our basic question, which countries’ musics are being consumed by whom. But even with this shortcut we need to do a few things to make the data usable. First, we needed to clean the artist names so that they are the same in each country. We accomplished this through tedious visual inspection. We also need to determine the nationality of each artist. To this end we undertook a laborious process of searching various sources (including music encyclopedias, allmusic.com, and Wikipedia) to determine the nationality of each artist. Through this process we have (so far) been able to attach nationalities to three quarters of the artist entries appearing in the sample. We also have a mechanical process to determining nationality, the first country in which an artist appears on the charts. We use this method in the minority of cases in which we cannot determine the artist nationality directly. Our approach associates products with origin countries according to artist nationalities, not to the corporate home of the recording labels. 9   

To create a dataset that is comparable across countries, we reduce each country to a top N (say 100) artists in each year. To this end we produce a crude sales index that is N- rank. We then rank the sum of this “sales” value to produce a top N for each country and year. Because we only have 100 entries per year from Brazil, for some exercises we use only the top 100 from each country. While we have far more than 100 entries in countries with, say, a weekly top 40, the total number of distinct artist entries falls far short of the number of weekly chart entries due to songs’ persistence on the charts. In addition to data on music sales (based on charts) we also employ data on GDP and population for each of the sample countries. We obtain these from the Penn World Tables. Our data on movie box office revenue are from Eurostat (2003), and our data on recorded music expenditure by country are from the IFPI (xx).

III.

Results on Music

1. Who Trades with Whom? a. World Market Shares The first benchmark for empirical comparison is balanced trade, such that each country’s artists have a share equal to the country’s share of the world economy. In Krugman’s model, each country offers a number of varieties proportional to the size of its labor force. We will summarize the size of each country crudely with its GDP. As above, if artists from country (i) and ⁄∑

track

⁄∑

= GDP of country (i), then the question is, how closely does

? This comparison, of course, requires a method for calculating

our chart data. To do this, define

as music sales for each country (j) and 10 

 

= the sales of music by

from

as the share of

chart entries in country (j) that are for artists from country (i). Then we calculate the worldwide6 sales of artists from country as ∑ ∑



and country (i)’s share of the world market as

. We have direct measures of music sales by country for 1999-2004. To perform

calculations for years prior to 1999, we substitute country GDP for music sales, implicitly assuming that music sales are proportional to GDP. Table 4 reports world music market and GDP shares based on the period 1999-2004. The US, for example, has 52 percent of world GDP and 41 percent of the music market. The UK, by contrast, has 9 percent of world GDP and 18 percent of the music market. Figure 4 depicts these data, logarithmically to prevent the size differences from obscuring the relationship. To a first approximation, world music market shares are proportional to GDP shares. The UK, as well as Norway, Sweden, and Austria have disproportionately large music shares. The US share is disproportionately small, although only slightly so. This is perhaps the first surprise among our results: while the US has a large world market share, its share is not large relative to its role in GDP in the past decade. Figure 5 depicts music market shares relative to GDP, averaged over the entire sample period (1960-2006), using GDP weights rather than music sales weights, with a similar message: the UK has a disproportionate share of the world music market and over this longer period the US did as well. Among the other countries – for this longer period – Sweden is closest to proportionate. If tastes were identical, then with zero transport costs, we would expect not only repertoire music shares proportional to origin countryGDP but also equal shares for each origin                                                              6

 We use the term “worldwide” as a succinct but inaccurate way to refer to all of the countries in the sample. 

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country’s product in each destination country. That is, US artists’ share of consumption would be the same in Germany, the US, and Norway, for example. Table 5 explores this, depicting the share of chart entries for artists from each origin country in each destination country. The first column shows the origin of artists appearing on the Austrian chart: 18 percent are domestic, 16 percent are from Germany, 26 are from the UK, and 24 are from the UK. Column entries sum to 100 percent. Contrary to balanced trade, the columns are not identical across countries. The most striking deviation from equality is the main diagonal, showing the share of consumption in each country accounted for by domestic artists. For example, while Brazil has 6 percent of worldwide GDP, Brazilian artists garner 61 percent of domestic Brazilian chart entries. France, Germany, and Italy’s domestic shares are 47, 44, and 49 percent, respectively, while their GDP shares are 9, 12, and 8, respectively. Figure 6 depicts the relationship between the domestic artist share (

) and the GDP

share for each country. The relationship is positive, as it would be under balanced trade: domestic shares are larger in higher-GDP countries. But in every country the domestic share exceeds its GDP share, reflecting a preference for domestic artists. Table 5 also reveals some interesting patterns off the main diagonal. First, artists from linguistically similar countries have elevated shares, a finding recalling the gravity literature. German artists account for 16 percent of Austrian and 12 percent of Swiss consumption. Outside of Austria, Austrian artists appear only on German and Swiss charts. While US artists have substantial shares everywhere, they have even higher shares in largely-English-speaking Canada and the UK.

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Putting aside the preference for domestic artists, are imports balanced among countries in proportion to their GDP levels? For example is the US share of imports constant across countries? Figure 7 explores this, depicting the US and UK shares of imports in each destination country, or

. Except for the other English-speaking countries (and except for the US share

in Brazil), the US and UK shares of imports are fairly steady at 40 percent each across nonEnglish-speaking countries. Figure 8 depicts the import shares for artists from the Germanspeaking countries. Outside of German-speaking destinations, German artists’ music makes up about 5 percent of imports. Instead of showing the origin of a destination country’s consumption – in Table 5 – we can rearrange the data to show the destinations to which each country’s music is exported, in Table 6. For example, the first row shows that 78 percent of chart entries for Austrian artists’ music appear in Austria, while 8 and 10 percent occur in Germany and Switzerland, respectively. The main diagonals of Table 6, showing the shares of a repertoires’ consumption that are domestic, tend to be large. Except for music from the US, the UK, and Canada, the main diagonals exceed 50 percent, meaning that most chart entries for those countries’ artists occur at home, or that these repertoires have little export appeal. The data in Tables 5 and 6 can be used to compute simple indices of consuming countries’ taste for international variety, as well as the export appeal of each country’s repertoire. We can characterize the breadth of domestic consumption using the consumption shares of each as the share of

origin country in the consuming (“destination”) country. If we define destination country (j)’s consumption from origin country i (such that

 i

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ij

 1 ), then our index

of consumption breadth in country (j) is B j  1

  

2

ij

. This is an “inverse HHI” with the

i

following interpretation. If the consumers in destination (j) consume equal shares of art from N countries, then this index simplifies to N, the number of sources. To the extent that consumption is skewed, say, toward domestic artists, the index is less than N. One can view it as the number of “source equivalents.” We can define an analogous measure showing the international appeal of domestic artists. Now define



ij

as the share of art from origin country i consumed in destination j (where

 1 ). The number of destination equivalents for each origin country’s music is

j

Di  1

  

2

ij

. This provides a measure of the international export appeal of each origin

j

country’s music. Table 7 provides estimates of these measures using data from the entire sample period. Small countries, such as Switzerland, Austria, and Norway have breadth of taste for international variety, while large countries (US and UK) and linguistically distinct countries (Brazil, Italy, France) have low taste for international variety.

2. Changing Trade Patterns and Cultural Dominance over Time Advances in communication technologies have reduced various kinds of transport costs over the past half century. It has literally become cheaper to ship music from one region to another, particularly in the past decade as music has become illegally transportable over the Internet. Under the figurative interpretation of transport costs as measures of cultural distance, 14   

costs have shrunk with the spread of means for exposing consumers to music from other countries. Mechanisms include television and music videos in particular. We can begin with world market shares, in relation to GDP shares, in Figure 9. In the 1960s US and UK artists had disproportionately large world market shares while the repertoires of all other countries were disproportionately small. The 1970s saw sharply increasing UK dominance, accompanied by shrinking US dominance. The repertoires of most other countries grew less under-represented. The UK dominance increased strikingly in the 1980s, with a world music market share four times the UK’s GDP share. In the 1990s the UK’s ratio fell to 2.5 while Sweden rose to nearly 2. Since 2000 only the UK’s share is much above par with GDP, at 1.7. The US share stands at 1.1, and Sweden’s is roughly 1. Even as trade has become easier among countries, sample countries’ music market shares are closer to proportionate to GDP now than at any time in the past half century. The trade accompanying globalization appears not to have favored the large countries. Instead, small countries have become less under-represented in the past half century. In addition to the world market shares, we can also examine the evolution of repertoire market shares within each country. Figure 10 depicts the chart shares of each origin country in each destination country by decade. The figure reveals some already-familiar patterns: domestic shares are disproportionately large everywhere, and US and UK shares are large everywhere, although not necessarily disproportionately so. One curious feature of the figure is that the domestic share appears to been growing recently in most countries.

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Figure 11 shows the domestic shares alone, revealing some interesting patterns. In a number of countries – including Brazil, Germany, Italy, and the US – the domestic share fell from the 1960s through the mid-1980s. The UK has the opposite pattern, a rising domestic share until the mid-1980s. The recent rise in domestic shares suggested in Figure 10 is more clearly visible in Figure 11 for almost all sample countries, except the UK (and Canada, where we lack data past 1980). Rising domestic shares, especially in small countries, stand in contrast to concerns about increasing large-country dominance brought about by globalization. Measures of chart overlap provide another way to characterize how the music market has fared under globalization. We can measure international convergence by an “overlap ratio” quantifying the similarity between the charts in different countries. One simple measure of convergence asks how the number distinct songs are needed to fill out multiple countries’ charts. For example, there are – by definition – 100 slots in the top 10 charts of ten countries. If the countries each have entries that appear in no other countries, then 100 distinct songs will appear. The ratio of distinct entries to possible entries will be 1.00. Overlap reduces this ratio. If the same ten songs appear in each country’s top ten, the ratio is 1/10, or 1/N for N-countries. We have (as many as) 11 countries in our sample, so the depending on overlap, the ratio can be between about 0.1 - meaning no overlap across countries’ charts - and 1.0 – meaning the same chart entries in each country. Computing the ratio from the top 100 songs in each country, this ratio stood at two thirds in the early 1960s. Figure 12 shows that the overlap ratio declined from throughout the 1960s , reaching about 0.5 in 1968, rose to 0.6 in the 1970s, then declined below 0.45 in the mid-1980s. That is, the overlap across countries’ top 100 lists reached a

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maximum in the mid/late 1980s. Since the late 1980s, music consumption has diverged, and the overlap measure has risen as countries’ top 100 lists have become more distinct. In 2006 the measure stood at its mid-1960s level. Over the first quarter century of the sample – from 1960 to 1985 – music consumption across these countries converged sharply toward a popular music world monoculture. But consumption patterns have diverged since then, echoing the finds on world market share and domestic shares reported above. In addition to calculating the evolution of overlap and market share measures over time, we can also calculate our indices of export appeal and taste for international variety. These appear in Table 8. Tastes for variety rose through the 1980 or 1990s and have since declined in Brazil, France, Germany, Norway, Sweden, and the US. Tastes for variety are currently rising in Austria, Italy, Switzerland, and the UK. Export appeal of most repertoires – including Italy, Norway, the US, and the UK – peaked in the 1980s and is currently declining.

IV.

Comparison with Movies

Concerns about large-market cultural dominance has been more prominent for film than music. Waterman (2005) explores reasons for Hollywood dominance, documenting high – and generally rising - box office shares for US movies throughout Europe and, to a lesser extent,

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Japan since 1950.7 In response to Hollywood’s dominance, the French tax box office revenue to subsidize domestic film production. As with music, the quality of movies is determined by investments in fixed costs. A comparison of the trade patterns for music and movies in instructive. We have not undertaken original data collection on movies. Instead, we rely on Eurostat (2003) statistics on trade in audiovisual services. Eurostat provides data since 1980, and it is clear – as Waterman documents - that the US share of box office revenue is very high. While it was 92 percent in the US itself in 2001, it averaged 64 percent across the 15 countries of the EU 15, ranging from 90 percent in Ireland to 47 percent in France. Figure 13 shows how since 1980, domestic box office revenue in seven countries (Germany, Spain, France, Italy, Japan, the UK, and the US) is divided among films from the seven countries (as well as “other” countries). The US is the leading supplier everywhere. Domestic shares are nontrivial, averaging 13 percent in Germany since 1980, 15 percent in Spain, 40 percent in France, 28 percent in Italy, 42 percent in Japan, 12 percent in the UK, and 96 percent in the US. But the US shares in these countries are even larger: 71 percent in Germany, 64 percent in Spain, 49 percent in France, 55 percent in Italy, and 58 percent in Japan. Eurostat (2003) provides data on box office revenue by exhibiting country and country of film origin back to 1980. Figure 14 shows how origin shares have evolved over time in each of six destinations. The US has had large shares everywhere throughout the period. With the

                                                             7

Hanson and Xiang (2008) study the determinants of US motion picture exports to Europe. They document that the US box office share in Europe averages about 70 percent since the mid-1990s. They also document greater exports to countries that are closer and those that are linguistically similar to the US.  

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possible exception of the UK, where domestic shares appear to have risen over the past decade, domestic shares are steady. US shares appear to have risen fairly steadily over the period. Figure 15 manipulates the music data analyzed earlier in the paper into a figure comparable to Figure 12. It is clear that global trade in movies and music are quite different. While the US has a large share of the music market in all countries, this large share is roughly commensurate with the US GDP share. The US movie share – in Germany, Spain, Italy, the UK, and even France – is clearly disproportionate to its GDP share. The dominance of Hollywood movies throughout the world has been attributed to a number of causes including, principally a home market advantage (see Waterman 2005). The larger home market, the argument goes, allows for larger investments in US movies that, as it turns out, international audiences find appealing. These arguments are familiar to readers of Sutton (1991). The movie industry produces quality with endogenous investments in fixed costs. If consumers around the world agree on what constitutes quality – if competition is vertical and not too horizontal – then the movie market need not fragment as it grows large. This may be what explains the differential between music and movies.

V.

Conclusion and Discussion

We have documented a few facts about globalization in music. While one country – Hollywood - dominates the movie industry, music is different. In music, different countries’ repertoires have world shares roughly equal to their GDP shares. While domestic repertoire is disprortionately popular everywhere, repertoire shares among imports are nearly proportional to GDP shares. Moreover, as the world has become better linked over the past half century, the US 19   

has grown less dominant in music (relative to GDP). Since 2000 the trade in music has been more balanced than at any time since 1960, and domestic artists have increasing market shares in almost all markets. These facts are surprising against the backdrop of technological changes that makes trade easier. These facts beg explanation; and at this time we can offer the following provisional explanations. At the same time that technology has made it easier for consumers everywhere to get access to Britney Spears, there have also been changes in communication technology – such as MTV and the Internet - that may have promoted local artists. Beginning in 1981 MTV broadcast music videos over cable television in the US. While MTV was not allowed to operate in Canada, a Canadian firm launched a Canadian music television station, CHUM MuchMusic, in 1984. But for roughly half a decade, there was only one MTV station throughout the world. Beginning in 1987, MTV began to splinter regionally, creating region or coutry-specific channels carrying some local programming (and local music). In 1987 MTV Europe was launched, broadcasting common programming throughout Europe in English. Since then, MTV has increasingly customized programming to particular countries. MTV Brasil launched in 1990. In 1997, MTV launched MTV Central, serving German-speaking countries of Europe – Germany, Austria, Switzerland, and Liechtenstein - in German. The network also launched MTV Italy, in Italian, and MTV One for the UK (in English). MTV launched MTV France in 2000, along with English-language MTV Nordic for Scandinavia. In 2005, MTV launched separate channels for Norway (MTV Norge) and Sweden (MTV Sverige) in their respective languages. In 2006 Austria got its own flavor of MTV.

20   

Table 9 summarizes the local customization of MTV. If locally targeted MTV channels have promoted local artists, the timing of MTV’s regional customization – following the mid1980s – makes it a candidate explanation of the reversal of the 1960 to 1985 trend of increasing chart overlap across countries. The Internet provides a second possible explanation of the resurgence of local art. While the Internet is often viewed as a technology that undermines the importance of geography, the actual evidence on this proposition is mixed. That is, while one can use the Internet as a means for getting access to things that are available far away but not within this country, the Internet also can serve as a complement to local products. Sinai and Waldfogel (2004) document the availability of more local Internet content targeted at bigger US cities, indicating that the Internet can serve as a complement to agglomeration. In the music context, it is possible that the Internet allows artists to market themselves in ways that may be complementary with physical presence, for example by communicating with fans about live concerts or to otherwise aid their marketing efforts in their home countries. This is a possibility we hope to explore in further research. Whatever the explanation, though, trade has not silenced local music over the past half century.

21   

References

Bala, Venkatesh and Ngo Van Long. “International Trade and Cultural Diversity with Preference Selection.” European Journal of Political Economy, 25 (2005):143-162. Berry, Steven T. and Joel Waldfogel. “Product Quality and Market Size.” Forthcoming, Journal of Industrial Economics. Blum, Bernardo S. and Avi Goldfarb. “Does the Internet Defy the Law of Gravity?” Journal of International Economics 70 (2006): 384-405. Cowen, Tyler. Creative Destruction: How Globalization is Changing the World Cultures, Princeton University Press, Princeton, 2002. Disdier, Anne-Celia and Keith Head. “The Puzzling Persistence of the Distance Effect on Bilateral Trade.” Unpublished Paper, 2006 (at http://strategy.sauder.ubc.ca/head/Papers/meta.pdf) Disdier, Anne-Celia, Keith Head, and Thierry Mayer. “Exposure to Foreign Media and Changes in Cultural Traits: Evidence from Naming Patterns in France.” Mimeo, University of British Columbia, 2009. Disdier, Anne Celia, Silvio H.T. Tai, Lionel Fontagne, Thierry Mayer. “Bilateral Trade of Cultural Goods.” CEPII Paper 2007-20, November 2007. European Commission, Office for Official Publications of the European Communities. “Cinema, TV, and Radio in the EU, Statistics on Audiovisual Services, Data 1980-2002.”Luxembourg, 2003. Francois, P. and T. van Ypersele (2002): On the Protection of Cultural Goods, Journal of International Economics 56, 359-369. George, Lisa M., and Joel Waldfogel. 2006. "The New York Times and the Market for Local Newspapers." American Economic Review, 96(1): 435–447. Hanson, Gordon H. and Chong Xiang. “International Trade in Motion Picture Services.” Unpublished Paper. January 2008. Heston, Alan, Robert Summers and Bettina Aten, Penn World Table Version 6.2, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania, September 2006 Janeba, Eckhard. “International Trade and Cultural Identity.” NBER Working Paper 10426. April 2004. 22   

Krugman, Paul. “Increasing Returns, Monopolistic Competition, and International Trade.” Journal of International Economics 9 (1979): 469-479. Krugman, Paul. “Scale Economies, Product Differentiation, and the Pattern of Trade.” American Economic Review 70 (1980): 950-959. Oberholzer Gee, Felix and Joel Waldfogel. “Strength in Numbers: Group Size and Political Mobilization.” Journal of Law & Economics, October 2005. Oberholzer Gee, Felix and Joel Waldfogel. “Media Markets and Localism: Does Local News en Español Boost Hispanic VoterTurnout?”, forthcoming, American Economic Review Oster, Emily and Robert Jensen. “The Power of TV: Cable Television and Women’s Status in India.” NBER Working paper 13305, August 2007. Rauch, James E. and Vitor Trindade. “Neckties in the Tropics: A Model of International Trade and Cultural Diversity.” Unpublished Paper. University of California, San Diego, May 2004. Sinai, Todd and Joel Waldfogel. “Geography and the Internet: Is the Internet a Complement or a Substitute for Cities?” Journal of Urban Economics, 2004. Suranovic, Steve and Robert Winthrop. “Cultural Effects of Trade Liberalization.” mimeo, George Washington University, September 2005. Sutton, John. Sunk Costs and Market Structure. MIT Press, Cambridge. 1991. United Nations, Creative Economy Report 2008, 2008. Waterman, David. Hollywood’s Road to Riches. Harvard University Press, Cambridge, MA, 2005.

23   

Figure 1 

World Market for Recorded Music in 2007 $29.9 bn

Switzerla Swed India nd So uth Belgiu m en Bra zilAfrica stria M exico Sou thAu Kore a Ne therla Sp ain nds Ru ssia Ita ly Au stralia C ana da

US

Fra nce

Germa ny

Othe r Japan

UK

  Figure 2 

World Market for Recorded Music in 2007 $29.9 bn

Switzerla Brazil Swed en nd Au stria Ita Ca nad aly France German y

Re mainde r

UK

US

   

 

24   

Figure 3 

Music Sales and GDP 2000 .002

Japan Ic eland

.0015

UK

Denmark Ireland Sweden

US

.001

Aus tria Switz erland Germany France Australia Netherlands Cy prus Belgium Canada Finland

.0005

M exico

Portugal Spain

0

Greece T aiwan Brazil Slovenia Hungary Poland Lebanon Colombia South Africa Est onia Israel Italy Chile Z imbabwe Bahrain T urkVenezuela ey LatviUruguay a Czech Republic Thailand Romania Croatia Malays ia Jamaica Saudi Arabia Egypt Rus sia Ecuador Indonesia Philippines Lithuania India Peru Paraguay Oman Bulgaria Uk raine PakiChina stan

0

10000

Hong Kong Singapore Kuwait

20000 30000 Per Capita GDP Music Sales/GDP

Qatar

40000

Sample Countries

25   

Norway

50000

Figure 4 

Countries' World Music and GDP Shares -1

US

-2

UK France

Sw eden

-3

Italy

-4

Norway

Austria

Germany

Canada

-5

Switzerland

Brazil

-5

-4

-3 Log GDP Share

Log Origin Music Share

-2

-1

Log GDP Share

  Figure 5 

U S

U K

en w itz er la nd S

S w ed

ly

rw ay N o

Ita

m an y

nc e

G er

Fr a

B ra zi l C an ad a

A us tr

ia

0

.5

mean of relshare 1 1.5 2

2.5

Market Share Relative to GDP Share

    26   

Figure 6 

Do Large Economies Import Less?

.6

.8

US

Brazil UK Italy Germany

.4

France

Sweden

.2

Norway Austria Canada

0

Switzerland

18

19

20 Log GDP Domestic Share

21

22

GDP Share

  Figure 7  90.0% 80.0%

share of imports from US, UK

70.0% 60.0% 50.0% 40.0%

UK

30.0%

US

20.0% 10.0% 0.0%

 

27   

0

1

2

  3

4

1990

28  st C Br ar ia an z i G F r aad l er n a c m e a N It n y Sw S o rwal y i tzw ed a y er e la n nd U UK S

Au

Au st C Br ar ia an z i G F r aad l er n a m ce a N I ny S S o r wtal y w w a itz e y er de la n nd U K U S

us t C Br ari a an z G F r aa d il er n a m ce a N It n y S S o r wal y w w a itz e y er de la n nd U K U S

A

0

m e a n o f re lsh a re 1

2

3

4

1960

Au st C Br ar ia an z G F r a ad il er n a m ce a N It n y S S or wa l y w w a itz e y er de la n nd U K U S

us t C Br ari a an z G F r aad il er n a m ce a N It n y S S or wa l y w w a itz e y er de la n nd U K U S

A

  Figure 8: Share of Imports from German‐Speaking Countries  25.0%

20.0%

15.0%

10.0% Austria

Germany

5.0% Switzerland

0.0%

 

Figure 9 

Music Market Share Relative to GDP Share

1970 198 0

2000

Graphs by decade

 

Switzerland

  0 .2 .4 .6 .8 1

0 .2 .4 .6 .8 1

Canada

Italy Norway

UK

Figure 11 

 

29 

19 1 9 60 19 65 1 97 0 1 97 5 1980 1 98 5 1 99 0 20 9 5 2 00 0 05

19 6 19 0 1965 1 97 0 19 75 1 98 0 1 9 85 1990 2 09 5 2 00 0 05

19 1 96 0 1 96 5 1970 1975 1 98 0 19 85 1 99 0 2 0 95 2000 05

19 1 96 0 19 65 1 97 0 1 97 5 1980 1 98 5 1 99 0 20 9 5 2 00 0 05

Brazil

19 1 9 60 19 65 1 97 0 1 97 5 1980 1 98 5 1 99 0 20 9 5 2 00 0 05

19 6 19 0 1965 1 97 0 19 75 1 98 0 1 9 85 1990 2 09 5 2 00 0 05

19 1 96 0 1 96 5 1970 1975 1 98 0 19 85 1 99 0 2 0 95 2000 05

19 1 96 0 19 65 1 97 0 1 97 5 1980 1 98 5 1 99 0 20 9 5 2 00 0 05

Germany

19 6 19 0 1965 1 97 0 19 75 1 98 0 1 9 85 1990 2 09 5 2 00 0 05

0 .2 .4 .6 .8 1

Austria

19 1 96 0 1 96 5 1970 1975 1 98 0 19 85 1 99 0 2 0 95 2000 05

19 1 96 0 19 65 1 97 0 1 97 5 1980 1 98 5 1 99 0 20 9 5 2 00 0 05

Figure 10 

Origin Shares over Time France

Sweden

US

Graphs by country

 

Share Domestic, Hybrid Approach annual top 100 Brazil

Canada

France

Germany

Ital y

Norway

Sweden

Switzerland

UK

US

1 .5 0

1960

1980

2000

2020

0

.5

1

Domestic Share

0

.5

1

Austria

1960

1980

2000

2020 1960

1980

2000

2020 1960

1980

2000

2020

year Grap hs by coun try

  Figure 12  

.45

Distinct Artists/Entries .5 .55 .6 .65

.7

Globalization and Top 20 Artist Convergence

1960

1970

1980

year

1990

2000

2010

  Figure 13 

30   

0

20

40

60

80

100

Box Office Share by Film Origin Country

DE

ES

FR

IT

JP

Germany US Spain Japan

UK

US

France UK Italy

    Figure 14 

Origin Country Share over Time ES

FR

1980 1985 1990 1995 2000

1980 1985 1990 1995 2000

1980 1985 1990 1995 2000

IT

UK

US

1980 1985 1990 1995 2000

1980 1985 1990 1995 2000

1980 1985 1990 1995 2000

0 20406080100

0 20406080100

DE

Germany France UK Other

Spain Italy US

Graphs by inhere

  31   

  20

France Italy US

32 

05

00

95

UK

20

90

85

80

05

00

95

90

85

80

0 .2 .4 .6 .8 1

20

05

00

95

90

85

80

05

00

95

90

85

80

05

00

95

90

85

80

0 .2 .4 .6 .8 1

Germany

20

19

19

19

19

20

20

19

19

19

19

20

20

19

19

19

19

France

19

19

19

19

20

20

19

19

19

19

Figure 15 

Music Origin Shares over Time Italy

US

Germany UK Other

Graphs by country

 

Table 1: Artists on All Charts, 2000-2006 Artist

Nationality

Alicia Keys Black Eyed Peas Britney Spears Destiny's Child Eminem Enrique Iglesias Evanescence Gnarls Barkley Gwen Stefani Jennifer Lopez Justin Timberlake Kylie Minogue Madonna Nelly Furtado Outkast P!Nk Pussycat Dolls Santana Shakira

US US US US US Spain US US US US US Australia US US US US US Mexico Colombia

# times 1 1 3 1 3 1 1 1 1 4 1 1 3 1 1 2 1 1 1

2000

2001

2003

2004

2005

2006

1 1 1

1 1

1 1 1

1

1

1 1 1

1

1 1

1

1 1 1

1

1 1 1

1 1 1

33   

2002

1 1

Table 2: Chart Frequency Availability Country Austria Brazil Canada France Germany Italy Norway Sweden Switzerland UK US Total

N

annual 26,671 5,702 31,491 24,641 18,488 38,170 33,313 24,020 35,180 57,451 50,572

monthly

twice monthly 1980-1989

1965-1979

1990-2008

1950-2006

1960-1964, 1978-2008

1965-1970

1976-1993

345,699

34   

weekly

1957-1986 1985-2008 1971-1977 1959-2008 1959-2008 1994-2008 1968-2008 1953-2008 1960-2008

Table 3: Chart Length Availability Austria Brazil Canada France Germany Italy Norway Sweden Switzerland UK US

Top 10 1965-1966

Top 15

Top 20 1967-2008

Top 100 1950-2006

1958-1984 1958-1994 1968-1974 1952-1953

19751982

1957-1986 1984-2008 1960-2008 1985-2008 1995-2008 1975-2008 1983-2008 1954-2008 1960-2008

35   

Table 4: World GDP and Music Shares country

Austria Brazil Canada France Germany Italy Norway Sweden Switzerland UK US

GDP Share 1.2% 6.0% 4.3% 8.6% 12.0% 7.8% 0.7% 1.6% 1.5% 9.2% 51.6%

Music Share 3.0% 0.5% 2.8% 9.4% 6.5% 5.8% 3.1% 8.0% 1.8% 17.8% 41.3%

Table 5: Where Do Music Imports Come From? Austria Origin: Austria Brazil Canada France Germany Italy Norway Sweden Switzerland UK US Rest-of-World

18% 0% 1% 2% 16% 4% 1% 2% 3% 26% 24% 5%

Brazil 0% 61% 1% 1% 1% 1% 0% 0% 0% 8% 25% 2%

Canada 0% 0% 15% 0% 0% 0% 0% 0% 0% 18% 64% 2%

France 0% 0% 2% 47% 3% 2% 0% 1% 1% 16% 19% 8%

Destination Germany 2% 0% 1% 2% 44% 2% 0% 2% 1% 23% 20% 4%

37   

Italy 0% 0% 1% 2% 2% 49% 0% 1% 1% 20% 20% 4%

Norway 0% 0% 2% 1% 3% 1% 22% 5% 0% 29% 32% 5%

Sweden 0% 0% 1% 1% 3% 1% 0% 34% 0% 25% 27% 6%

Switzerland 2% 0% 2% 4% 12% 5% 0% 2% 10% 28% 29% 5%

UK

US 0% 0% 1% 1% 1% 1% 0% 1% 0% 55% 38% 3%

0% 0% 2% 0% 1% 0% 0% 0% 0% 14% 80% 2%

Table 6: Where is Origin Music Consumed? (“Where Do Exports Go?”) Austria Origin: Austria Brazil Canada France Germany Italy Norway Sweden Switzerland UK US Rest-of-World

Brazil 78% 0% 5% 4% 18% 6% 3% 4% 17% 9% 6% 12%

0% 99% 6% 1% 1% 2% 1% 1% 1% 4% 8% 5%

Canada 0% 0% 45% 0% 0% 0% 0% 0% 0% 5% 13% 3%

France 0% 0% 5% 69% 2% 2% 1% 2% 2% 4% 3% 11%

Destination Germany 8% 0% 4% 4% 55% 3% 2% 4% 9% 9% 6% 10%

38   

Italy

Norway 1% 0% 3% 4% 2% 74% 2% 3% 4% 7% 5% 9%

1% 0% 5% 2% 3% 1% 87% 11% 3% 9% 7% 10%

Sweden 1% 0% 4% 3% 3% 2% 2% 67% 2% 8% 6% 12%

Switzerland 10% 0% 6% 9% 12% 7% 2% 4% 62% 9% 7% 12%

UK

US 1% 0% 6% 2% 2% 1% 0% 3% 1% 29% 14% 11%

0% 0% 10% 0% 1% 0% 0% 1% 0% 6% 26% 6%

Table 7: Taste for International Variety and Repertoire Export Appeal, by Country

country

Austria Brazil Canada France Germany Italy Norway Sweden Switzerland UK US Rest of World

taste for international variety 5.4 2.3 2.1 3.4 3.5 3.1 4.2 3.9 5.2 2.2 1.5 NA

export appeal

1.6 1.0 4.3 2.0 2.8 1.8 1.3 2.1 2.3 7.2 7.6 9.9

39   

Table 8: Taste for International Variety in Consumption, and International Appeal of Exports, 1960-2006 country Austria Brazil Canada France Germany Italy Norway Sweden Switzerland UK US Rest-of-World

Domestic consumers’ taste for international variety 1960 1970 1980 1990 2000 4.74 5.84 4.65 5.51 5.56 2.03 2.48 2.84 2.86 2.06 1.69 2.11 2.82 2.98 4.38 2.67 2.64 3.80 3.70 3.55 2.96 2.11 1.96 3.28 3.54 3.63 3.44 3.87 3.70 4.66 4.00 4.17 3.76 4.24 2.98 3.39 5.91 4.19 4.91 5.55 2.13 2.22 1.98 2.44 2.42 1.28 1.55 1.82 1.53 1.27

International appeal of country’s music exports 1960 1970 1980 1990 2000 1.81 1.46 1.63 1.32 1.77 1.04 1.03 1.03 1.02 1.02 1.28 2.23 2.46 1.76 1.50 1.66 1.41 2.44 3.86 4.39 2.39 1.54 1.54 2.39 1.95 1.51 1.32 1.87 1.26 1.31 1.16 2.70 1.85 3.09 1.56 1.32 2.40 2.37 2.56 2.05 4.40 6.50 8.97 7.92 5.84 4.59 5.66 8.16 7.88 7.91 7.53 8.78 9.83 8.50 8.77

Note: each table entry is an inverse hhi. In the left half of the table, and entry is the number of country-equivalent in domestic consumption. For example, if domestic consumption is divided evenly among artists from N countries, this will be N. As consumption is concentrated more heavily in a few countries’ artists, this measure declines. Similarly, the right half of the table uses an analogous measure for export appeal: if a country’s artists derive equal shares of consumption in each of N countries, the index takes a value of N.

40   

Table 9: Localization of MTV Programming, 1981- 2006 1981

1984

1987

1990

1997

2000

2005

2006

Europe

Europe

Central

Central

Central

Austria

Brasil

Brasil

Brasil

Brasil

Brasil

CHUM MuchMusic

CHUM MuchMusic

CHUM MuchMusic

CHUM MuchMusic

CHUM MuchMusic

CHUM MuchMusic

CHUM MuchMusic

MTV

Europe Europe Europe Europe Europe Europe Europe MTV

Europe Europe Europe Europe Europe Europe Europe MTV

Europe Central Italy Europe Europe Central One MTV

France Central Italy Nordic Nordic Central One MTV

France Central Italy Norge Sverige Central One MTV

France Central Italy Norge Sverige Central One MTV

Austria Brazil Canada France Germany Italy Norway Sweden Switzerland UK US

MTV

Source: “List of MTV Channels,” http://en.wikipedia.org/wiki/List_of_MTV_channels , accessed April 16, 2009.

origin artist Opus Mikis Theodorakis Wes Edelweiss Francesco Napoli Nino Ferrer Alain Barrière Franck Pourcel Twins Roger Williams Bryan Adams Shania Twain Nelly Furtado Celine Dion Crash Test Dummies Patrick Hernandez Modjo Kaoma Break Machine Mr. Oizo Enigma Lou Bega Silver Convention Haddaway Milli Vanilli Black Box Baltimora Corona Eiffel 65 Sabrina Middle Of The Road Rapsody Pop Tops Lene Marlin Nancy & Frank Sinatra Ace Of Base Aqua Abba Eagle Eye Cherry Roxette Robert Miles Double Bellini Al Corley Mattafix Culture Club Phil Collins Paul Young

Austria Austria Austria Austria Austria Brazil Brazil Brazil Brazil Brazil Canada Canada Canada Canada Canada France France France France France Germany Germany Germany Germany Germany Italy Italy Italy Italy Italy Norway Norway Norway Norway Norway Sweden Sweden Sweden Sweden Sweden Switzerland Switzerland Switzerland Switzerland Switzerland UK UK UK

chart appearances

export appeal 16 4 4 11 5 5 5 4 4 5 81 30 31 76 9 10 10 17 7 7 28 11 15 21 28 24 11 17 19 17 16 10 8 12 3 39 23 75 12 57 18 8 5 5 13 37 80 26

R 4.27 4.00 4.00 3.90 3.57 3.57 2.78 2.67 2.67 2.27 10.33 9.57 9.33 9.03 9.00 10.00 8.33 8.26 7.00 7.00 9.56 9.31 9.00 9.00 8.91 9.60 9.31 8.26 8.02 7.41 5.82 5.00 4.00 3.79 3.00 9.22 8.97 8.36 8.00 7.87 8.53 8.00 5.00 5.00 4.83 10.78 10.70 10.24

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3

Elton John Dire Straits Usa For Africa Lionel Richie Michael Jackson Madonna Snow Bee Gees Ini Kamoze Shakira Rihanna Savage Garden

UK UK US US US US US Rest-of-world Rest-of-world Rest-of-world Rest-of-world Rest-of-world

143 40 11 52 131 199 10 108 11 39 35 23

43   

10.18 10.00 11.00 10.48 10.33 10.14 10.00 9.80 9.31 9.22 8.94 8.67

4 5 1 2 3 4 5 1 2 3 4 5

44   

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