Preliminary and Incomplete. Please do not cite without permission 

Music as a Capital Asset 

By Rachel Soloveichik 

Abstract 

In 2002, I estimate that musicians and recording studios created original songs, including 

recorded performances, with an estimated value of $7.1 billion. These songs were sold on CDs 

in 2003 and will be played on the radio, on television and at live concerts for decades to come. 

Because of their long working life, the international guidelines for national accounts, System of 

National Accounts 2008, recommends that countries classify production of music and other 

entertainment, literary and artistic originals as an investment activity and then depreciate those 

songs over time. As a first step in changing the treatment of music in the National Income and 

Product Accounts (NIPA), I collected data on music production and calculate what the NIPA 

would be if songs were classified as a capital asset. 

To preview, my empirical results are: 1)In 2002, musicians and record studios created 

original music with a nominal value of $7.1 billion producing recorded music, approximately 

0.07% of real GDP; 2)The recorded music industry has been shrinking dramatically since 2000. 

Between 2000 and 2007, real GDP growth is reduced by 0.005 percentage points per year if 

recorded music is treated as a capital asset; 3) Original music remains valuable for decades after 

it is first produced. I calculate that the aggregate capital value of all original music was $34 

billion in 2002. 

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Introduction

The music industry has changed dramatically since 2000. Real sales of CD’s have 

decreased by almost 50% from 2000 to 2007. At the same time, nominal concert revenue has 

more than doubled since 2000. There are many papers in the economics literature documenting 

these changes and analyzing why those changes occurred (Krueger 2005) (Mortimer and 

Sorenson 2005) (Liebowitz 2004). However, there are few papers tracking the aggregate music 

industry over time. In this paper, I will examine three separate channels for musicians to earn 

money: sales of music, royalty income and live concerts. I will then combine those three 

revenue sources to estimate the total value of original music created each year. 

In 2002, I estimate that musicians and recording studios created original songs with a 

value of $7.1 billion, including the expected revenue from live concert tickets. I define “original 

songs”as the complete intellectual property associated with music, including the musical 

composition, lyrics, original records and even music videos. The cost of producing this $7.1 

billion in music could be treated either as a current expense or it could be treated as an 

investment. If original songs have a useful life of less than one year, then the production costs 

for music should be treated as a current expense. In that case, the final revenue from the sale of 

music is all that matters for gross domestic product (GDP), and production costs for music are an 

expense in the same way that CD manufacturing and music advertising is an expense. The BEA 

currently uses this method to account for music production. 

In contrast, items with a useful lifespan of more than one year are generally classified as 

capital assets. If original songs have a long useful life, then the production costs for music 

should be treated as a capital investment. In that case, the capital investment in music is added to 

GDP as part of private investment and added to the pre-existing captial stock of music to get the 

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total capital stock of original music. This capital stock of copyrighted music then returns a flow 

of value to its owner, and that flow is counted in GDP as part of capital services. GDP counts 

both the flow of value and the initial investment. As a result, GDP is always higher when a good 

is changed method 1) to method 2). Finally, the total capital stock of copyrighted music is 

depreciated, which is known as consumption of fixed capital (CFC). In addition to the well 

known GDP, BEA also estimates net domestic production (NDP). NDP = GDP – CFC. Because 

NDP does not include the cost of maintaining the capital stock, it is generally viewed as a better 

long-term measure of the total sustainable output of an economy. 

In this paper, I will show that it is possible to calculate GDP, CFC and NDP when music 

production is treated as a capital investment (method 2). I can’t directly observe total 

expenditures creating original music, the total amount of music capital or the flow of services 

provided by music capital. Nevertheless, I can observe the revenues earned by a song over time. 

I define the value of a song as the net present value of the future revenues it will earn for its 

copyright holders, starting from the first time the song is performed and ending when consumers 

lose interest and switch to newer songs. I also assume that unobserved production costs for 

music are, on average, equal to the net present value of songs created. In other words, a group of 

musicians who create songs worth $1 million spent $1 million worth of time and energy 

composing it. As a result, it is possible to account for song production and song depreciation in 

the same framework that is already used to account for physical capital production and 

depreciation. This is the framework recommended by the international guidelines for national 

accounts, System of National Accounts 2008, for all expenses releated to the production of 

entertainment, literary and artistic originals (SNA 2008 10.115). 

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From a theoretical point of view, whether live concert revenue should be included in 

estimating the value of artistic capital is controversial. On the one hand, musicians typically 

perform pre-existing songs at concerts rather than composing new songs for each concert. This 

suggests that live concert revenues could be viewed as a return on pre-existing capital stock of 

copyrighted music. On the other hand, musicians expend substantial amounts of time and energy 

performing their songs at concerts. This suggests that the musician’s profits from ticket sales 

could be viewed as a wage payment for labor, not capital. In this paper, I will treat live concert 

revenues as a return on pre-existing copyrighted music. I choose this method because musicians 

typically earn money from CD sales, airplay royalties and live concerts simultaneously. In 

recent years, musicians have been raising prices on live concerts to compensate for CD piracy 

(Krueger 2005). As a result, excluding live concerts would cause my estimates to miss the 

substitution that is occurring. 

To preview, my empirical results are: 

1) Original songs have a useful lifespan of at least 50 years, but more than half of their value 

comes from sales in the first year. 

2) The nominal sales of recorded music fell from $12.6 billion in 2000 to $10.4 billion in 2007. 

The nominal royalty revenues rose from $0.9 billion in 2000 to $1.5 billion in 2007. The 

nominal revenue from live concerts has increased from $1.7 billion in 2000 to $3.9 billion in 

2007. 

3) Prices for live concerts have risen significantly faster than the rest of the music industry. This 

price growth cannot be explained by quality improvements or input cost growth (Mortimer and 

Sorenson 2005). Instead, bands are simply raising the ticket price for concerts over the last 

decade (Krueger 2005). 

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Taken together, results 2) and 3) show that the treatment of live concert revenue has little 

effect on real GDP growth since 2000 with music classified as a capital asset. When concert 

revenues are included in the industry, nominal revenue remains steady and prices increase. 

When concert revenues are excluded, nominal revenue falls dramatically and prices remain 

steady. Real music production drops between 2000 and 2007 in both scenarios. Under both 

scenarios, real GDP growth falls by approximately 0.005% per year when music production is 

classified as an investment activity. 

This research on capitalizing music production is part of a broader research project on 

changing the treatment of intangible assets in the national income and product accounts. Other 

researchers at the BEA have developed a satellite account measuring the annual investment and 

capital value of R & D (Robbins and Moylan 2007), educational investments (Fraumeni, 

Reinsdorf, Robinson and Williams 2008) and the role of intangible assets in foreign direct 

investment (Bridgman 2008). In a previous paper, I estimated the quarterly investment and 

capital value of theatrical movies (Soloveichik 2008). I am currently working to estimate the 

annual investment and capital value of other forms of artistic capital such as books, television 

programs and plays. 

This paper consists of four sections. In section 1, I describe my data on nominal revenues 

earned by the music industry and calculate the nominal value of music production back to 1929. 

In section 2, I describe my price index and calculate the real value of music production back to 

1929. In section 3, I describe the various way in which an original song can earn money and 

estimate the total revenues earned by recording studios and musicians over time. Finally, in 

section 4, I estimate the total stream of revenue received and expenses incurred by musicians for 

every year after a song is released. I then use that revenue stream to estimate the depreciation 

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schedule for original songs. Finally, I combine the real production data from section 2 with the 

depreciation schedule to estimate capital stocks of music from 1929 to 2006. 

1. Nominal Music Production 

Musicians earn money from their original songs in four possible ways: 1)They can record the 

songs and sell them, either on CD or as a download for computers, Ipods or ringtones for 

cellphones (or records or tapes, etc.). In order to simplify the discussion, I will often refer to this 

market as CD sales, but my data includes all legal media; 2)They can license the songs for radio 

play, television broadcast, commercials, theatrical films or live performance by another artist; 

3)They can sell the songs on sheet music for individuals to play themselves; 4)They can perform 

the songs at a live concert and earn money by selling tickets. 

In this paper, I define the value of a copyrighted song as the expected present value of 

future revenues minus future costs. For example, suppose that a song earns $X in Year 0, $Y in 

Year 1 and $Z in Year 2. Given a discount rate, ρ, the value of a song at release is: 

Net Present Value at Release = $X+$Y/(1+ ρ)+$Z/(1+ ρ)

2 

In this paper, I discount future revenues at the ρ = 10% real. In other words, a musician 

is indifferent between being paid $1 now and $1.10 (inflation adjusted) next year. I chose the 

discount rate of 10% real because the music industry is extremely risky, and so discount rates 

should be high enough to compensate for the risk.1  Because I am focusing on revenues, I do not 

 

1 My estimates of nominal production, real production, depreciation and capital stock are all sensitive to the discount 

rate used to calculate the net present value of music. Please e-mail me for alternative estimates when a different 

discount rate is used. 

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include any piracy or other illegal copies which do not pay royalties to the musicians or 

recording studios. 

Revenues Across Distribution Channels 1985-2007 

Figure 1 shows the net present value of music sales by year of initial release. The main 

data source for Figure 1 is the Recording Industry Association of America (RIAA) annual reports 

on sales for CD’s, Internet downloads, ringtones, etc. (Vogel 2004) (RIAA 2003-2007). I then 

adjusted the RIAA data to account for retailer mark-up (Cohen 2004), classic CD’s sold for years 

after initial release, re-release of old songs on compilation albums, imports of songs by non-US 

musicians and exports of songs by US musicians to abroad. Taken together, these adjustments 

allow me to calculate annual production of music by US musicians using the RIAA data on US 

sales. Appendix 1 contains much more detail on the exact adjustment procedures used. 

The most striking result from Figure 1 is that nominal revenues from the sale of music 

have been plummeting since 2000. The RIAA data include digital downloads and ringtones – so 

the decline isn’t just a shift from CD’s to Ipods. Instead, consumers are not buying as much 

music. These findings are not new to this paper. A number of industry and academic experts 

have discussed this phenomenon in recent years. The industry sources are adamant that the main 

cause the revenue decline is illegal downloading (Hiatt and Serpick 2007) (RIAA website). 

The economic literature is more mixed, but generally agrees that illegal downloads are a major 

cause of revenue declines (Oberholzer-Gee and Strumpf 2005) (Mortimer and Sorenson 2005) 

(Krueger 2004) (Liebowitze 2004).2  

 

2Many of the economic papers focus on a much more micro level than the RIAA is concerned with. For example, 

Oberholzer-Gee and Strumpf (2005) found that CD sales did not drop during time when Napster worked better for 

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Figure 2 shows the net present value of music royalties by year of initial release for every 

year from 1985 to 2007. Most royalty payments are for performance royalties, which are paid 

every time a song is played on the radio, broadcast on television or performed live by another 

artist. The main data source for performance royalties is the annual reports by ASCAP and BMI 

(Brabec and Brabec 2008). ASCAP and BMI handle more than 95% of performance royalties in 

the US, and so their annual reports are a very good proxy for the total performance royalties paid 

in the US. The remainder of royalties are synchronization royalties, which are payments for the 

right to include a song in a television program, theatrical film or commercial.3 Finally, I adjusted 

the performance royalty and synchronization royalty data to account for non-US musicians, 

exports and classic songs played years after their original release. These adjustments allow me 

to calculate the value of US music production from revenue data. Appendix 1 gives much more 

detail on the data used on the process for adjusting revenue. 

The most striking result from Figure 2 is that the net present value of royalties from new 

music grows much slower than overall royalty revenue. Intuitively, more music is being 

produced each year than is destroyed through depreciation. Therefore, revenues from the 

licensing of old music are rising even though the production of new music is relatively flat.4  

Figure 3 shows the net present value of live concert revenues by year of initial release. 

The main datasource for Figure 3 is Pollstar, an industry group that tracks the live concert market 

(Krueger 2005), (Pollstar 2006), (USA Today 2005), (Cohan 2007), (Grossberg 2003) and 

 

reasons completely exogenous to the US music industry. They use that short-term stability as evidence that Napster 

did not affect CD sales in the long-term. However, it possible that piracy does affect CD sales, but it takes more 

than a few days for the results to be seen. 

On the other hand, the RIAA seems to assume that all downloads are illegal. It is common for new artists to post 

songs for their fans to legally download. These new artists may be responsible for some of the drop in CD sales. 

3

I have not been able to locate any annual data on synchronization royalties. Based on the 2002 Economic Census 

and the industry literature, I estimate that synchronization royalties are about 15% of performance royalties for every 

year from 1985 to 2007. 

4 The results in Figure 2 are quite sensitive to my price index for royalties. 

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(Weaver 2003). In order to construct Figure 3, I assume that people attend live concerts in order 

to hear particular songs. Therefore, concert revenues should be allocated to the year when the 

songs played were initially written. When there are multiple songs with different composition 

dates performed, revenue is allocated in proportion to the number of songs for each date. My 

dataset on which songs are played at live concerts will be described in more detail in section 3. I 

then adjusted the Pollstar data for imports and exports of music. These adjustments allow me to 

calculate the value of US music production from revenue data. Appendix 1 gives much more 

information on the process used for adjusting revenue. 

The most striking result from Figure 3 is that nominal concert revenues increased by 

119% between 2000 and 2007. This increase has already been analyzed in earlier papers. 

Mortimer and Sorenson (2005) argue that this increase can be attributed to music piracy. They 

show that the expected revenue from recording an album has shrunk significantly since 2000. 

Therefore, musicians devote less of their time and energy to recording new albums, and more to 

touring. Krueger (2005) also finds a large increase in nominal prices for concert tickets. He 

argued that the price increase occurred because CD albums and live concerts by the same artists 

are complementary goods. In the past, artists underpriced their live concerts to encourage CD 

sales. However, artists now get very little revenue for CDs (because they’re mostly pirated), and 

so they charge the market clearing price for live concerts. 

\Total Music Production 1985-2007 

I estimate aggregate music production in a three stage process. First, I benchmark the 

revenue statistics given in Figure 1, 2 and 3 to the 2002 Economic Census. Next, I deduct non-

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music production costs such as advertising, packaging and retailer profits. I was not able to 

obtain a time series on sheet music sales, which accounted for 6% of the music market in 2002. 

For simplicity, I will assume that sheet music is always 6% of total industry revenue.5  Finally, I 

add the benchmarked revenue for CD’s, royalties, live concerts and sheet music together to get 

total music production. 

My primary dataset for benchmarking music revenues is the 2002 Economic Census. 

According to the 2002 Economic Census, the sound recording industry earned $0.66 billion 

dollars from the sale of sheet music and music books, $1.21 billion from performance royalties, 

$0.19 billion from synchronization royalties for commercials6 and $9.17 billion from the sale of 

CD’s, records and cassettes. In a separate section, the 2002 Economic Census also reports that 

taxable music groups earned $2.42 billion from concerts.7  The numbers from the Economic 

Census are quite consistent with the industry statistics given earlier. In Figure 1, total CD, tape 

and download sales for 2002 was $8.2 billion, about 20% below the Economic Census’s estimate 

for 2002. In Figure 2, total performance royalties received were $1.25 billion and 

synchronization royalties were $0.19 billion, only slightly above the Economic Census’s 

estimate of $1.21 billion in performance royalties and $0.19 billion. Finally, in Figure 3, concert 

revenues were $2.23 billion in 2002, only slightly below the Economic Census’s estimate of 

$2.42 billion. The small discrepancies between industry data and the Economic Census could be 

 

5The 1997 Economic Census does not split out sheet music licensing from other royalties. 

According to my dataset, about 10% of sheet music are public domain songs. These songs can be (legally) 

downloaded free or printed by any publisher without payments to the original musician’s family. I will therefore 

reduce the Economic Census’s revenues by 10%. 

6 In this paper, I will not include synchronization royalties paid by theatrical films or television programs because 

these royalties have already been counted in the value of theatrical films or will be counted in the value of television 

programs. However, I will include synchronization royalties paid by advertisers because commercials are not 

considered artistic originals (SNA 2008).

7 Non-taxable musical groups earned an additional $1.6 billion. I exclude this revenue because I believe that most 

of the revenue is for classical orchestras, which rarely compose original songs. 

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explained by slightly different industry classifications, different treatment of imports and 

exports8 or other differences in survey methodology. 

Figure 4 shows the aggregate revenues and the aggregate value of newly released songs. 

Overall, I find that nominal revenues and nominal production have been stagnant since 2000. On 

the other hand, nominal revenues and nominal production were growing at approximately 9% per 

year between 1985 and 2000. However, I need to know non-music costs such as manufacturing 

and marketing to estimate the value of music production over time. 

Selling, manufacturing and distribution expenses are the easiest non-music cost to 

calculate. According to the industry literature, recording studios spend 15% of their CD or 

cassette revenues for manufacturing & shipping (Cohen 2004). For digital music such as Itunes, 

manufacturing and shipping is free. Based on the ASCAP and BMI annual reports, I estimate 

that royalty organizations keep about 15% of the royalties they collect to pay for their 

administration costs.9  Finally, I estimate that bands earn enough money from merchandise sales 

(such as T-shirts) to cover their touring costs and the promoter’s share of ticket sales. 

Accordingly, sales, manufacturing and distribution costs for live concerts are effectively 0% 

(Krueger 2005). I was unable to find any industry-specific estimate of the production costs for 

sheet music, but in a separate paper I calculate that printing, shipping and other production costs 

account for approximately 40% of the wholesale price for books (Soloveichik 2009). 

 

8

 In my industry analysis, I first collected data on total US sales, and then adjusted those US sales for imports and 

exports using industry data. As an alternative to the industry data on imports and exports, I also examined BEA’s 

own data on imports and exports of music. Based on careful analysis of BEA’s own data, I concluded that BEA’s 

trade in services survey measures a different definition of trade in services and a different sample universe than the 

industry data. As a result, I cannot combine BEA’s data on imports and exports with industry data on domestic 

consumption. Accordingly, I will rely exclusively on industry data to estimate domestic consumption, imports and 

exports of music. I will then benchmark the industry data to the 2002 Economic Census to derive total domestic 

production of music. 

9 Synchronized royalty payments are not negotiated through an organization. However, I assume that agents charge 

the same 15% for handling negotiations. 

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Marketing expenses are much more complex to calculate. According to the industry 

literature, advertising accounts for about 1/3rd of the non-manufacturing costs for CD’s (Cohen 

2004 and my own calculations). I have not been able to find any industry literature on 

advertising for royalties and live concerts. In this paper, I will assume that advertising is always 

1/3rd of total industry revenue net of manufacturing, and advertising is distributed between 

recording studios, royalty organizations and live concert promoters in proportion to their market 

share. I will also assume that all marketing expenses occur in the first year after a song is 

released. 

Figure 5 shows my estimate of the annual value of music released from 1985 to 2007. 

One interesting finding from Figures 4 and 5 is that the ratio of Artistic Capital to Total Music 

Revenue was a little over 40% in 2002. In a previous paper on the movie industry, I found a 

similar ratio of Artistic Capital to Total Movie Revenue (Soloveichik 2008). This ratio might be 

a subject for future research. 

Historical Music Production 1929-1984 

I have not been able to find any consistent industry data tracking music revenue from 

1929 to 1984. I have located a paper that estimates the unit volume of record sales from 1920 

onwards, but that paper does not report revenues or manufacturing cost (Gronow 1983).10  I have 

also found isolated quotes reporting the licensing revenue for ASCAP or BMI in a particular year 

(Sterling and Kittross 1978), but no consistent time series. Early in the century, sheet music was 

a major money-maker for musicians (Sanjek 1988), but the only data I could find on sheet music 

 

10 Prior to the 1970s, jukeboxes accounted for a large portion of record sales. Based on Mortimer’s work with 

DVDs (2008), I conjecture that records were significantly more expensive when jukeboxes accounted for most of 

the market. 

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sales is from the Census of Manufacturers – which gives inconsistent estimates over time. 

Finally, I could not find any consistent data on live concert revenues over time. 

Because of the lack of good industry data on sales, I will use Census data to estimate 

music production over time.11  Every 10 years, the Census counts the US population and also 

surveys a sample population on their employment, earnings, occupation and other interesting 

variables. I use the employment and salary for musicians as an extrapolator for music profits.12  

In 1990, the Census reported aggregate earnings for all musicians at $2.7 billion (nominal), about 

40% lower than the total music industry profits estimated earlier in Figure 5. This discrepancy is 

consistent with the fact that recording studios keep a substantial portion of CD profits to pay for 

inputs like sound equipment, talent scouts and administrative overhead. In my analysis, I assume 

that musician’s salaries were 60% of total industry profits for the entire time period 1929 to 

1985. 

Figure 6 shows my estimate of nominal music revenues from 1929 to 1984. I find that 

music revenues growth remained steady from 1930 to 1940 and then grew steadily over time. 

Because my data are based on the decennial Census, I am forced to impute nominal revenues for 

intermediate years. The exact imputation procedures are available upon request. One important 

result of my imputation is the music production appears artificially smooth. Therefore, I cannot 

estimate the exact growth rate for any given year – only the long-term average growth rate. 

In a previous paper on theatrical movie production, I used IMDB data on exact filming 

dates to produce quarterly production estimates for the entire movie industry. These aggregate 

 

11 I also considered using the Current Population Survey, which provides annual employment data. Unfortunately, 

the sample sizes were too small to get reliable annual data. I also could not use the Consumer Expenditure Survey 

because the survey does not track non-consumer spending like royalty payments. I also could not use the BLS 

employment data because the time series for musicians started in 1990, too late for my historical needs. Finally, I 

considered using union membership data as a count of musicians, but that procedure misses early African-American 

musicians, who were banned from most unions. 

12 A random sample of the Census data is available at Ipums.org. The Census samples are large enough that the 

standard error for my aggregate estimate is relatively small. 

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production estimates sometimes changed dramatically from quarter to quarter when studios 

started or stopped filming big movies (Soloveichik 2008). Unfortunately, I can’t provide the 

same quarterly data for music with any degree of confidence. The music industry generally does 

not report the exact dates a song was first recorded in the studio. Furthermore, the final 

recording accounts for relatively little of the time spent producing a CD. Much of the musician’s 

time is devoted to writing the song, practicing the song and editing the song before final 

recording (Thall 2006). In all of my analysis I will assume that music production takes one year 

and production is uniform over that year. Therefore, inventory is assumed to be around half of 

annual production. 

2. Real Production 

It is difficult to develop a price index for copyrighted songs. Each song is a unique 

artistic creation, and so I can never compare the cost of producing two identical songs over time. 

Furthermore, the main input to producing a song is the musician’s time and energy. It is 

impossible for me to determine which songs the musician slaved over, and which ones were easy 

to write. In this paper, I will create a consumer-based price index to estimate the cost of 

purchasing a unit of music over time. I define a unit of music as one song purchased on tape, CD 

or legal download, one minute of radio listening, one live concert and one book of sheet music. 

My price index assumes that the quality of musical composition has remained constant 

over time. I do not assume that the quality of the music listening experience has remained fixed 

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over time.13 Ipods are a big improvement over CD players and CD players were a big 

improvement over records and tapes. Similarly, radio sound quality has improved with the 

introduction of FM radio, satellite radio and digital radio. However, I believe that these quality 

improvements should be attributed to the consumer electronics market and not the music 

industry. After all, recording studios can and do re-release classic songs on CD or Itunes. These 

songs are often digitally remastered so their sound quality is better than the first release on record 

or tape. 

My consumer-based price index only tracks legal music consumption. In other words, 

the number or price of illegal downloads and pirated CD’s has no impact on my price index. The 

number and market share of illegal downloads has been increasing rapidly over the last decade 

(RIAA website). By 2006, consumers downloaded approximately 1 billion tracks per month 

(Hiatt and Serpick 2007) – more than ten times the legal sales of music. Accordingly, the 

average consumer price for music has fallen substantially even while the legal price for music 

stays fixed. However, BEA’s general practice is to ignore illegal activity when measuring 

prices. For example, we don’t discount prices for goods which are shoplifted frequently. 

Furthermore, I don’t have good time series data on how many songs are pirated per year.14 As a 

result, I can’t calculate the average consumer price for music over time. Instead, I will only track 

prices for legal music consumption. 

 

13 This index may produce flawed results if the market size for music has changed over time for reasons 

unconnected to music quantity, music quality or music prices. For example, the invention of CD’s might suddenly 

double the demand for music. Holding the quality and quantity of songs fixed, this doubled demand means that 

each new song is worth twice the value of an identical song last year. However, the supply of music is elastic, and 

so music production is likely to rise if an exogenous shock raises the interest level in music. Furthermore, new 

music technology is also associated with lower costs of music production. In the long-term, new music technologies 

have an ambiguous effect on profits earned by musicians per song. 

14 There are industry groups that estimate the number of tracks downloaded from peer to peer networks. However, 

there is much less data on less organized piracy such as copying CD’s or e-mailing songs between friends. 

Even if I had good data on total piracy, I still wouldn’t be able to create a quantity index without knowing the 

relative weight to use for legal versus illegal songs. 

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There are a variety of ways in which music is purchased. In this section, I will construct 

four separate consumer price indexes for music: 1) A per-song price index for CD albums, 

cassettes, downloads and other music sales; 2) A per-minute price index for radio airplay and 

television broadcast; 3) A per-event price index for live concerts; 4)A per-book price index for 

sheet music and song books. I will then combine those four price indexes into a single 

composite price index, and use that composite to deflate nominal production from Figure 5 and 

6. 

Price Index for Retail Sales 1976-2007 

My price data for retail sales is taken from RIAA’s annual reports. These annual reports 

provide both the units shipped and the retail value of shipments for a variety of formats such as 

ringtones, digital albums, CD albums, etc. I can then calculate average retail prices for each 

format according to the simple formula: 

Average Price for Format X= (Total Value of X)/(# Units of X). 

As a robustness check, I also computed the average price for audio products as a whole 

and compared it to BLS’s price index for “Audio discs, tapes and other media”.15 

 I find that the 

two track reasonably closely from 1999 to 2007, suggesting that the RIAA data is a valid proxy 

for actual retail data. 

In this paper, I want to measure the price of the intellectual property contained on a CD, 

but not the price of the CD as a physical good. I will do that by comparing the retail prices for 

 

15In the past, recording studios charged $2-$4 more for a CD album than the same album on tape. Therefore, the 

average price per album rose faster than the average price per CD album or tape album. The BLS’s price index for 

audio media started in 1999. By that time, CD’s had almost completely replaced tapes, and so the BLS’s price index 

will not biased by this substitution. 

As I discussed earlier, I believe that the quality improvement from tapes to CD’s should be attributed to the 

electronics industry – not the music industry. Accordingly, I consider the price increase from tapes to CD’s to be 

inflation from the standpoint of musicians. In other words, a musician produces the exact same music for a CD and 

tape – he or she just charges more to compensate for better electronics. 

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albums and singles. Physically speaking, a single and an album look identical, and they cost the 

same amount for the recording industry to manufacture, ship or sell on-line. However, an album 

typically contains 10-20 songs and are sold for $15-$25 in stores. At the same time, a single 

contains 1 song and is sold for approximately $5 in stores. The price difference between the two 

is the value of the artistic assets contained on the CD. I can therefore estimate the price of an 

individual song: 

Price Per Song = (Album Price – Single Price)/(Average # of Songs Per Album17 – 1)18 

Price per physical CD = (Price per single CD – Price Per Song) 

Price for digital file = (Price for single download – Estimated Price Per Song) 

This formula provides a price per physical CD of around $4 in 2004. By comparison, an 

independent market research firm estimates that it costs around $3.39 cents to manufacture, ship 

and sell a CD at a big box retailer like Walmart. The same industry report also states that small 

music retailers have higher costs, but does not provide any specific numbers. Even without an 

exact number, this analysis is quite close to my estimate of $4 per physical CD in 2004. (Cohen 

2004).19  

Figure 7 shows a price index for songs from 1976 to 2007. I find that average price per 

song has only increased by 77% from 1976 to 2007. In comparison, the PCE services deflator 

has risen by 300% over the same time period. The slow growth in song prices is particularly 

surprisingly in light of the fact that the price of a physical CD or cassette has risen by 500% 

 

17 In this analysis, I use that overall average # of songs per album for each year (about 15). I also experimented with 

using a separate average for each year. This yielded very similar results on average, but the yearly data was noisier. 

18 It might seem that this formula only works when the average quality of singles and albums is identical. In fact, 

creative industries have a general practice to charge the same price for all their products, regardless of quality 

(Orbach and Einav 2007). 

19 In particular, the article reports that CD’s cost $1.70 to manufacture and ship and $3.69 for retailer overhead for 

each sale. However, Walmart uses CD’s as a loss leader for other products, and therefore is willing to lose about 

$2.00 per CD. Independent music stores typically charged higher prices for CD’s. 

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Preliminary and Incomplete. Please do not cite without permission 

since 1976 (based on the formula described earlier).20  In other words, the area with little 

technological improvement, composing music, has enjoyed a very low inflation rate. In contrast, 

the area with rapid technological improvement, listening to music, has increased in price much 

faster. I 

Price Index for Broadcast Royalties 1984-2007 

I will compute a price index for royalties on a per minute per listener basis. The two 

main licensing organizations, ASCAP and BMI, both charge a fixed fee to radio or television 

stations for playing their songs.21  In 2007, radio stations and television stations paid 

approximately the same amount of money for licensing rights (Brabec and Brabec 2008). 

Furthermore, Americans spend approximately the same amount of time watching television and 

listening to the radio.22  Therefore, I can calculate royalty prices according to the simple formula: 

Price Per Minute = (Royalties Paid)/[(#Minutes TV + # Minutes Radio)*#Americans] 

Figure 8 shows the price index for broadcast music over time. I find that the royalty rate 

has increased steadily over time. In 1984, musicians charged an average of 0.076 cents per 

person per minute. In other words, a musician would receive $76 if a television station played a 

one-minute song on a show watched by 100,000 people. In 2007, musicians charged an average 

of 0.27 cents per minute. This is equivalent to a 5.4% per year increase in royalty prices. By 

comparison, the PCE services deflator only increases at the rate of 3.5% per year and CD prices 

increased by only 2.6% per year. 

 

20 This price index combines CD’s and cassettes into one homogenous good. Inflation rates would be even lower if I 

tracked CD’s and cassettes separately. 

21 This fee only covers the right to play over the radio or television. Advertisers and broadcasters must pay 

additional royalties if they use a song as part of their program (like a jingle or theme song). 

22Radio stations are much more likely to play music than television stations, and so it might seem that they should 

pay higher licensing revenue. However, this is balanced out by the fact that radio is often used as background noise, 

and so commands much less attention for each song. 

My time data is taken from the American Time Use Survey, Arbitron data and other industry sources. 

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Preliminary and Incomplete. Please do not cite without permission 

Price Index for Live Concerts 

I take my price index for live concerts from the paper “Rockonomics: The Economics of 

Popular Music” (Krueger and Connolly, 2005). They calculate a large number of possible price 

indexes. In this paper, I will use their Fisher price index by artist. Krueger and Connoly’s price 

index goes until 2003. I then collected Pollstar’s reports of average ticket prices for 2003-2007 

in order to extend the time series further. For simplicity, I assume that average ticket prices rose 

at exactly the same rate as Krueger and Connolly’s carefully constructed price index. I have data 

on average ticket prices back to 1995. I found that annual growth rates don’t match up perfectly 

with Krueger and Connolly’s data, but overall price growth is quite similar. 

I find that concert prices increase significantly faster than inflation, as shown in Figure 9. 

Between 1981 and 2007, concert prices increased by an average of 7.8% per year, more than 

double the overall PCE service deflator. Concert prices also rose much faster than the BEA’s 

general deflator for live entertainment, which rose at 4.2% per year.23  So, the price growth for 

concerts cannot be explained by a general trend in the live entertainment industry. Furthermore, 

the quality of concerts has remained relatively fixed over time (Mortimer and Sorenson 2005). 

Instead, bands are simply raising the ticket price for concerts over the last decade (Krueger 

2005). 

Price Index for Sheet Music and Song Books 

 

23 This deflator includes music concerts as well as plays, dance performances, etc. I calculate that non-music 

concert prices rose at 3.7% per year from 1981 to 2007, 

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Preliminary and Incomplete. Please do not cite without permission 

As discussed earlier in section 1, I was not able to find any time series data on sheet 

music sales or sheet music prices. Instead, I will use the consumer price index for recreational 

reading as a proxy for sheet music and song book prices. This price index is available from the 

BLS website for anybody to download. 

I find that songbook prices increase slightly slower than inflation, as shown in Figure 10. 

Between 1981 and 2007, retail prices for recreational reading increased by only 3.4% per year. 

Over that same time period, the PCE services deflator increased by only 3.8% per year. 

Overall Price Index & Real Production for Music 1984-2007 

Figure 11 combines the separate price indexes in Figures 7, 8, 9 and 10 to get a single 

overall price index.24 I find that prices for the entire music industry track the PCE services price 

index reasonably well. Figure 12 uses the prices indexes developed earlier to estimate real 

production of music from 1985 to 2007. I find that real music revenue shrunk by 4%-5% per 

year between 2000 and 2007. The decrease is similar when live concerts and included and when 

live concerts are excluded. On the one hand, nominal music revenue grew faster when live 

concerts are included in the music industry. On the other hand, prices also rose faster when live 

concerts are included in the music industry. The two effects almost cancel out, so real growth 

does not change much when the treatment of live concerts is changed. 

Historical Price and Real Production Indexes 1929-2007 

 

24The price index shown is a chain weighted index, which uses the previous year’s revenues shares to determine 

weights. Contrary to economic theory, I find that the revenue share for CD’s are falling even as their relative prices 

fall. Therefore, the Fisher index would be slightly above my chain-weighted index. 

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Preliminary and Incomplete. Please do not cite without permission 

The price indexes developed earlier in this section are all consumer based. 

Unfortunately, I don’t have consumer price information before 1985, and so I can’t construct a 

consumer-based price index back to 1929. Instead, I will use musician’s wages to construct a 

labor-based price index. This labor-based price index assumes that musicians produce the same 

amount of music per hour in 1929 and 2009. Such a labor-based index still allows for 

technological improvements like CD’s, satellite radio and Ipods that may improve the music 

listening experience – but it assumes no technological progress for music composition. I drew 

my dataset on labor inputs from the 1920 – 2000 US Census and the 2001-2007 American 

Community Survey (ACS). 

The labor-based price index matches closely with the retail-based price index from 1985 

to 2007, as shown in Figure 13. On the other hand, the labor-based quantity index does not 

match nearly so well from 2000 to 2007, as shown in Figure 14.25  According to the retail-based 

index, real music production fell by 20% between 2000 and 2007. At the same time, aggregate 

hours worked by musicians rose by 21% from 2000 to 2007. These results are consistent with 

research by Mortimer and Sorenson (2005). They found that artists were able to compensate for 

music piracy by increasing the number and price of live concerts. In contrast, recording studios 

have experienced sharp declines in revenues from music piracy. Therefore, the earnings for 

musicians have risen even as the music industry has declined. 

As a robustness check, I also experimented with creating an alternative historical index 

based on music consumption, as shown in Figure 15. This index is based on historical data on a 

number of possible proxies for music consumption, including jukebox production, musicial 

instrument sales, etc. I find that my index of music consumption is much lower than the labor-

 

25 This labor index does not require any assumptions about nominal revenues or prices of music over time. Instead, 

I simply aggregate the hours worked by all musicians in the Census without quality adjustment. 

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Preliminary and Incomplete. Please do not cite without permission 

based production index from 1929 to 1940, tracks the labor-based production index reasonably 

closely from 1940 to 2000 and then diverges again after 2000. Therefore, I have some 

confidence that the labor-based quantity index produces historical estimates within the right 

ballpark. Please e-mail me for more details about the music consumption index. 

Section 3: Revenue Streams From Original Music 

In this section, I will estimate the revenue streams and costs separately for each channel. 

I will then combine the separate revenue streams to get an overall depreciation rate for original 

songs. 

In this paper, I will use four separate datasets to estimate the rate at which studios receive 

revenue from their copyrighted movies: 1)Billboard charts of album sales in the United States; 2) 

Music Monitor’s tracking of radio airplay by month of airplay and year of original song release; 

3)A website listing the songs played in a sample of television programs and theatrical movies; 

worldwide box office charts; and 4) A webiste listing the songs played in a sample of live 

concerts. All of these datasets required extensive cleaning before they could be used. Please 

contact me for more information on the exact data cleaning procedures. 

Purchased Music Sales (CD’s, Itunes, Records, Cassettes, etc.) 

Figure 16 shows the lifespan for an individual song on CD. I found that the typical song 

sells most of its copies soon after release. More than half of all album sales occur in the first 

quarter after an album is released, and only 13% of album sales occur more than one year after 

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Preliminary and Incomplete. Please do not cite without permission 

release. Because a popular song can be re-released on compilation albums, the lifespan for songs 

is slightly longer than the lifespan for an particular album. However, compilations account for 

only 12% of CD sales on average. In addition, many compilation albums are released within 

five years of the original song release. Therefore, the vast majority of sales revenue occurs 

within the first two years after a song is released on CD. 

The lifespan on CD given in Figure 16 relies on a number of assumptions. Billboard’s 

charts only report sales for best-selling 250 albums. According to industry sources, the bestselling albums account for approximately 70% of total sales. In my analysis, I adjust for the 

missing data by over-weighting sales for CD’s ranked 150-250. This procedure implicitly 

assumes that CD’s ranked 150-250 have the same average age as CD’s ranked 250+. In addition, 

Billboard’s charts do not provide actual sales figures, only ranked sales. My estimates of the 

lifespan of songs change significantly when I use different formulas to impute gross sales based 

on chart rank. 

As a robustness test, I also experimented with using an alternative dataset on CD sales 

from the Recording Industry Association of America (RIAA).26 I find that the RIAA and 

Billboard dataset produce almost identical depreciation profiles, as shown in Figure 16. 

According to both datasets, more than 75% of CD sales occur in the first year after a song is 

released. Sales then decrease rapidly, and very few albums sell any significant quantities more 

than five years after initial release. In the remainder of my paper, I will use the the Billboard 

revenue data to estimate depreciation profiles for songs. Results remain very similar when I use 

the RIAA depreciation profile. 

 

26 The RIAA does not directly measure sales. Instead, they give out awards for albums that ship 0.5 million, 1 

million, 2 million, etc. copies. This awards data is available on their website. I use Billboard data to estimate sales 

of compilation albums and movie soundtracks. It would have been extremely labor intensive to recalculate these 

small revenue sources. I then adjusted the Billboard data to account for the fact that compilation albums and 

soundtracks account for a lower market share in the RIAA data than on Billboard. 

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Preliminary and Incomplete. Please do not cite without permission 

It is important to note that the short lifespan for CD sales does not necessarily mean that 

nobody is listening to old songs. CD’s are durable goods, and so consumers may be buying a 

CD soon after release and then listening for decades. In fact, the main reason for the short 

lifespan of CD sales is probably saturation of the target market. In other words, fans want to 

own a new CD as soon as it is released. Furthermore, there is an active resale market for used 

CD’s, and so new fans of an artist can buy his or her CD’s without the recording studio making 

any money. 27 

Royalties and Sheet Music Sales 

Musicians earn royalties in a variety of ways. Musicians earn performance royalties 

whenever a radio station rebroadcasts an pre-existing song. Musicians also earn synchronization 

royalties whenever a television program, commercial or theatrical movie combines their song 

with film to create a new artistic work.28  Finally, musicians earn performance royalties once 

again when a television station broadcasts a program with a pre-existing song, even though the 

producer has already paid synchronization royalties for the song. In addition to all of these 

royalties, composers also earn royalties whenever their songs are sold on sheet music or music 

books. 

My radio royalty data is taken the company Music Monitor. This company tracks airplay 

by song more than 2,000 radio stations across the US. In my analysis, I requested a dataset 

 

27 During the 1990’s, recording studios earned significant amounts of money from consumers who replaced their 

record collection with CD’s of the same songs. However, it is straightforward to transfer songs from CD to digital 

files, and so consumers are unlikely to pay for new releases on a digital format. 

28 As discussed in Section 1, I will not count synchronization royalties in the aggregate music market because they 

have already been counted in the theatrical movie industry or will be counted in the television industry. However, I 

will still count those royalties when I calculate depreciation rates. 

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Preliminary and Incomplete. Please do not cite without permission 

tracking market share by month and year of airplay. For example, songs composed in 1946 

accounted for 0.016% of the radio market in March of 2006. I can then estimate the depreciation 

rate by tracking the radio market share for a year over time. Because the sample of radio stations 

is very large, it might seem that this procedure produces a very precise estimate of the 

depreciation rate. In fact, I only observe 41 months of data, from January of 2006 to May of 

2009.29  My estimates may be biased if this period was unusual in any way. 

My television and movie royalty data is taken from the website tvtunefinder.com. This 

website identifies the songs performed for a sample of popular TV shows. I then looked up the 

release date for a stratified sample of songs listed on tvtunefinder. It is important to note that the 

shows listed in tvtunefinder.com are not necessarily representative of the entire industry, and 

they may be biased in any number of ways. Nevertheless, I was not able to find any more 

authoritative datasets. 

Figure 17 show the average market share by age of songs for radio royalties, 

synchronization royalties and television broadcast royalties. I find that radio royalties, 

synchronization royalties and sheet music sales decrease extremely fast at first. For example, 

songs released in 2005 acounted for 27% of the radio market in January of 2006, but only 16% 

of the radio market in December of 2006. On the other hand, I find that royalties from television 

broadcast diminish significantly slower. Intuitively, the slower decrease can be explained by the 

fact that the original musician gets new royalties each time the show is re-run in syndication.30  

 

29 The dataset provided by Music Monitor starts in January of 2004. However, the market share for classic songs 

dropped dramatically during 2004 and 2005. This market share decline is not a data error by Music Monitor – 

Arbitron data reports a similar decline in the market share for Oldies stations. Nevertheless, I believe that including 

this unusual time period would produce a misleading depreciation curve. I therefore started the sample in January of 

2006, after the taste shift had already occurred. 

30 I do not yet have any data on the lifespan for television programs. In this analysis, I assume that television 

programs depreciate at the rate of 40% per year. I also assume that theatrical movies account for 10% of songs 

played on TV, and those movies depreciate at 3% per year (Soloveichik 2008) 

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Preliminary and Incomplete. Please do not cite without permission 

Based on the radio airplay data, I estimate that older songs depreciate much slower. In 

January of 2006, songs released before 1995 accounted for 26.4% of the total radio market. 

These same songs accounted for 23.7% of the total radio market in May of 2009. This is 

equivalent to an annual depreciation rate of 3.8% per year. I found similar results for 

synchronization royalties and sheet music sales, but the datasets for those revenue sources were 

too small to estimate the long-term depreciation rate precisely. I will therefore use the same 

3.8% rate to depreciate those royalties. 

I also experimented with estimating the lifespan for sheet music sales. My sheet music 

data is taken from the website musicnotes.com. Unfortunately, I found that musicnotes.com data 

had so much random noise that I could not compute a meaningful depreciation curve. However, 

the general depreciation pattern was similar to that of television performance royalties. 

Therefore, I will assume that sheet music sales depreciate at the same rate as television 

performance royalties. Please e-mail me for more information about the sheet music results. 

Live Concert Revenues

All of my data on concert songs is taken from the website Setlist.com. This website 

collects the program of songs performed (called a set) at concerts for a sample of 379 artists. 

The main data starts with concerts during the 1960s, and continues until concerts at the end of 

2008. It is important to note that the musicians listed on Setlist.com are not a comprehensive 

sample of the industry, or even a random sample of the most influential artists. Setlist.com is a 

website created by unpaid fans of a particular musician or band. Individual fans e-mail in set 

lists or post the set lists on the website. I do not know if the musicians on Setlist.com are 

representative of the entire industry, or whether the concerts posted on Setlist.com are 

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Preliminary and Incomplete. Please do not cite without permission 

representative of the entire concert market. I was also unable to check directly whether the songs 

posted on Setlist.com are accurate. Nevertheless, Setlist.com is the best data I could find to 

estimate the vintage of songs performed at concerts. I then weighted each concert by the venue’s 

reported capacity (as listed on Onlinegigs.com). For example, a concert at Madison Square 

Garden, which holds more than 20,000, counts for more than a concert at a local bar.31 

Similar to the earlier results, I find that songs depreciate by rapidly at first, as shown in 

Figure 18. On average, songs less than one year old account for 29% of the market share, more 

than double the market share for songs one year old. I also find that old songs depreciate very 

slowly. 32 Based on a sample of all songs played at least five time, I estimate that classic songs 

depreciate at approximately 8%-9% per year. This is slightly higher than the depreciation rate 

for radio royalties, which I estimated at approximately 4% per year. 

Section 4: Depreciation Rates of Music Over Time

Combined Depreciation Rates 

In Figures 15-17, I showed that the lifespan for songs is different on CD, radio, television 

and live concerts. Therefore, the average lifespan for a song depends enormously on the weights 

given to each revenue stream. In my analysis, I will use the net revenue statistics given by the 

2002 Economic Census and the industry literature to weight each revenue stream. In particular, I 

assume that CD sales account for 66% of industry net revenue, royalties account for 10% of 

industry net revenue, sheet music accounts for 3% of industry net revenue and live concerts 

 

31 I restrict the sample to concert venues that were listed in onlinegigs.com. Depreciation is slightly faster when I 

impute capacities for venues with missing data or weight all venues equally. 

32 This depreciation rate assumes that bands continue to charge the same price over time. Anecdotal evidence 

suggests that bands charge much higher ticket prices later in their career, after they have built a devoted fan base. 

The higher ticket prices would reduce depreciation rates. 

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Preliminary and Incomplete. Please do not cite without permission 

account for 20% of industry net revenue. The depreciation schedule would be very different if I 

used a different weighting method. 

There are many possible reasons why a copyright might decrease in value over time. For 

example, all consumers in a target market might have already bought the CD. Alternatively, a 

song might fall out of fashion because of cultural change. In this paper, I will not attempt to 

distinguish between the various reasons a consumer might stop buying an old song. I will simply 

attempt to estimate the schedule at which musicians and recording studios earn money from their 

songs, and the costs associated with those revenues. 

Figure 19 shows the depreciation schedule for original songs based on net revenue after 

subtracting sales and advertising costs. These costs are discussed in much more detail in section 

1. I find that original songs depreciate by approximately 50% in the first year of life. This is still 

high, but much lower than I estimated earlier. The depreciation rate then slows dramatically and 

finally stabilizes at approximately 4%. 

Comparing My Estimate of Depreciation Rates with Market Transactions 

I will check the depreciation schedule show in Figure 19 by comparing it to known 

market transactions. My dataset of music catalog sales is primarily taken from the book “The 

Business of Music” (Krasilovsky and Shemel 2007). That book describes a number of 

acquisitions in the music industry from 1988 to 2002. I also include the multiple sales of the 

Beatle catalog, as described in a New York Times article about Michael Jackson (O’Brien 2006). 

I then used the depreciation schedules given in Figure 19 to predict the price for each catalog at 

the time of sale.33 Table 2 gives more details about each transaction.34 

 

33I use RIAA award data and total production data to proxy for aggregate production. For example, Beatles songs 

earned 56% of all gold awards in 1969. I therefore assume that Beatles songs accounted for 56% of the aggregate 

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Preliminary and Incomplete. Please do not cite without permission 

It is important to note that a recording studio might sell for more or less than the value of 

its music. On the one hand, recording studios only own partial rights to most songs in their 

catalog. For example, the recording studio might own the right to sell records of a song – but 

they are required to pay a fee to the musician for every copy they sell. Furthermore, musicians 

generally keep the right to perform their songs in concert without paying any royalties to the 

recording studio. The exact ownership of each song depends on the contract between studios and 

musicians, and is often kept private. On the other hand, recording studios own many more assets 

than just music catalogs. For example, a studio might have pre-existing contracts with popular 

artists, a well developed brand image, relationships with retailers and general industry 

experience. 

Overall, I find that my predicted prices are significantly lower than the actual acquistion 

prices, as shown in Table 2. I also find that the mark-up between predicted price and actual price 

varies enormously across catalog sales. Nevertheless, I am reassured by the fact that the two 

prices are within the same general ballpark. The observed differences in price can easily be 

explained by non-music intangible assets mentioned in the last paragraph. I will continue to use 

the depreciation schedules described in Figure 20 for my empirical analysis.35 

Capital Stocks of Music Over Time 

Figure 19 combines the real production estimates given in Figures 11 and 13 with the 

depreciation schedules given in Figure 18. Consistent with the decline in music production, I 

 

value released in 1969. My estimates of prices for individual catalogs are quite sensitive to the exact method used to 

estimate initial value. 

34Music catalogs may include foreign musicians in addition to US production. In addition, music catalogs may 

include synchronization royalties, which I choose to count in theatrical movie and television accounts. I increase the 

value of music production by approximately 25% a year to adjust. 

35 It is also possible that depreciation profiles have changed over time. In theory, BEA could use separate 

depreciation profiles for 1960s songs and 1990s. However, that would be extremely difficult to implement. 

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Preliminary and Incomplete. Please do not cite without permission 

find that the real capital stock of music has declined since 2000. In 2007, the total value of all 

music capital was $34 billion, about six times annual production. As a robustness check, I also 

computed the capital stocks using a simple geometric depreciation rate of 20% per year. I found 

that the aggregate capital stock of music did not change much when I used this simplification 

Conclusion 

In this paper, I showed that it is possible to calculate GDP, CFC and NDP when music 

production is treated as a capital investment and songs are treated as a capital asset. Using my 

calculations, BEA could bring the GDP statistics in line with System of National Accounts 

recommendation for music production (SNA 2008). 

To review, my empirical results were: 

1)In 2002, musicians and record studios created original music with a nominal value of $7.1 

billion producing recorded music, approximately 0.07% of real GDP; 

2)The recorded music industry has been shrinking dramatically since 2000. Between 2000 and 

2007, real GDP growth falls by 0.005% per year if recorded music is treated as a capital asset; 

3)Original music remains valuable for decades after it is first produced. I calculate that the 

aggregate capital value of all original music was $34 billion in 2002. 

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Preliminary and Incomplete. Please do not cite without permission 

Table 1: List of Datasets Used and How They Are Used 

 

 

 

 

 

 

 

 

 

Dataset Description of Dataset Used to Create 

2002 Economic 

Census

The Economic Census is conducted 

every 5 years by the Census 

Department. It surveys businesses in 

the United States. 

Nominal Music 

Revenue, Nominal 

Music Production & 

Depreciation Schedules

Allmusic.com

This website lists the release date, # of 

tracks, original source, and other 

information for albums & singles. It 

also lists the nationality for musicians. 

Nominal Music 

Production, Price Index 

for Purchased Songs 

Billboard.biz 

This website ranks songs by weekly

popularity. It also provides sales rank, 

title, musician, recording studio and 

suggested retail price for all major 

songs since 1985. In addition, I also 

found summarized Billboard 

information for earlier songs. 

Nominal Music 

Production, Price Index 

for Purchased Songs & 

Depreciation Schedules

MusicMonitor

This company tracks radio airplay for a 

wide variety of songs across the 

United States. In particular, they list 

% Airplay by year of first release Depreciation Schedules

Setlist.com 

This website reports the songs play 

(sets) at individual concerts for 

selected musicians. Depreciation Schedules

Arbitron Radio 

Surveys

Arbitron tracks radio listening time 

across the United States. 

Price Index for 

Royalites 

American Time 

Use Survey & 

TVB 

The ATUS tracks all time use in the 

US, included television watching time. 

The TVB tracks only television 

watching 

Price Index for 

Royalties 

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Preliminary and Incomplete. Please do not cite without permission 

Table 2: Selected Music Catalog Sales

Predicted Price 

Year Description of Deal 

Without 

Concerts

Including 

Concert Actual Sales Price 

1985 

Michael Jackson bought 

the Beatles catalog $171 million $209 million $47 million

1988 

Sony acquired Columbia 

Records $1.60 billion $2.21 billion $2 billion 

1989 

A consortium led by MCA 

acquired Motown records $101 million $143 million $61 million 

1990 

EMI acquired Virgin 

Records $235 million $293 million $872 million 

1990 

MCA acquired Geffen 

Records $313 million $454 million $550 million 

1992 

Polygram acquired Motown

records. $237 million $303 million $301 million 

1995 

Michael Jackson sold a 

50% stake in the Beatles 

catalog to Sony $149 million $196 million 

$200 million+ 

($100 million+ for 

50% stake) 

2002 BMG acquired Jive $1.05 billion $1.57 billion $3 billion 

2005 

Michael Jackson sold a 

25% stake in the Beatle 

catalog to Citibank $141 million $200 million 

$1 billion 

($250 million for a 

25% stake) 

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Revenue from CD's, Cassettes, Downloads, Etc.,

Based on Wholesale Prices

$0

$2,000

$4,000

$6,000

$8,000

$10,000

Millions of $'s (Nominal)

1985 1990 1995 2000 2005

Year of Ship or CD Release

Actual Sales NPV of Sales for New Music

Source Data: RIAA Annual Reports (Vogel 2004 and RIAA Website), Billboard Charts, IFPI sales data 

 

 

 

Preliminary and Incomplete. Please do not cite without permission 

Figure 1 

Figure 2 

Royalties Received

$0

$500

$1,000

$1,500

$2,000

$2,500

1984 1989 1994 1999 2004

Year of Receipt

Millions of $'s (Nominal)

Royalties Paid This Year NPVof Royalties from New Music

Source Data: BMI and ASCAP Annual Reports (Brabec and Brabec 2008), Economic Census, Industry 

literature, Billboard Charts and NMPA 

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Preliminary and Incomplete. Please do not cite without permission 

Figure 3 

Source Data: Pollstar Concert Prices (Krueger 2005 and media reports), Setlist.com 

Live Concert Revenue

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

$4,500

1984 1989 1994 1999 2004

Year of Concert or Composing

Millionsof $'s (Nominal)

Annual Concert Revenues NPV of Concert Revenues from New Music

Figure 4

Aggregate Revenue From Music,

Benchmarked to 2002 Economic Census

$0

$5,000

$10,000

$15,000

$20,000

1984 1989 1994 1999 2004 2009

Year of First Release

Billions of $'s (Nominal)

NPV of Revenues for New Music Annual Music Revenue

Source Data: 2002 Economic Census (Sound Production Industry), Figures 1-3 

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Preliminary and Incomplete. Please do not cite without permission 

Figure 5 

Source Data: 2002 Economic Census, Figures 1-3, Industry Literature 

Annual Value of Music Production,

Expected Revenue - Manufacturing, Administration and Advertising Costs

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

1984 1989 1994 1999 2004

Year of Release

Millions of $'s (Nominal)

Figure 6 

Annual Value of Historical Production, 

Benchmarked to 1990 Data

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

1920 1930 1940 1950 1960 1970 1980 1990 2000

Year of Production

Millionsof$'s (Nominal)

Source Data: 1920-1990 US Census, 1929-1990 GDP Per Capita 

- 35 -
 

 

 

 

 

 

 

 

Preliminary and Incomplete. Please do not cite without permission 

Figure 7 

Price Indexes for Purchased Music

0

0.5

1

1.5

1975 1980 1985 1990 1995 2000 2005

Year of Release

Base Year 2000 =1

Song Index Physical CD or Cassette Index PCE Service Price Deflator

Source Data: RIAA Annual Reports (Vogel 2004 and RIAA Website), Billboard Charts 

Figure 8 

Price Index for Broadcast Music

0

0.5

1

1.5

2

1984 1989 1994 1999 2004

Year of Broadcast

Base Year 2000

= 1

Music Royalty Prices PCE Services Deflator

Source Data: ASCAP and BMI Annual Reports (Brabec and Brabec 2008), American Time Use Survey, 

Television Bureau of Advertising, Arbitron Radio Tracking Data 

- 36 -
 

 

 

Preliminary and Incomplete. Please do not cite without permission 

Figure 9 

Price Index for Live Concerts

0

0.5

1

1.5

2

1980 1985 1990 1995 2000 2005

Year of Performance

Base Year 2000 = 1

Price Index for Live Concerts PCE Services Deflator

Source Data: Krueger 2005, Pollstar Reports (Various Media Stories) 

Figure 10 

 

 

 

 

 

 

Overall Prices for the Music Industry

0

0.5

1

1.5

1984 1989 1994 1999 2004

Year of Release

Base Year 2000 = 1

Combined Music Price Index PCE Services Sector

Price Index for Sheet Music and Song Books

Base Year2000 =1

0

0.5

1

1.5

1984 1989 1994 1999 2004

Year of Sale

PCE Services Deflator Sheet Music Prices

Source Data: BLS Retail Price Index for Recreational Books 

- 37 -
Preliminary and Incomplete. Please do not cite without permission 

Figure 11 

 

 

 

Overall Prices for the Music Industry

Base Year 2000 = 1

0

0.5

1

1.5

1984 1989 1994 1999 2004

Year of Release

Combined Music Price Index PCE Services Sector

Source Data: Price Index from Figures 7, 8, 9 and 10. Revenue shares from Figures 1, 2, 3 

Figure 12 

Real Production in the Music Industry

Millions of $'s (2000)

$0

$2,000

$4,000

$6,000

$8,000

1984 1989 1994 1999 2004

Year of Release

Source Data: Nominal Production from Figure 5, Price Index from Figure 10 

- 38 -
 

 

 

 

 

 

 

Preliminary and Incomplete. Please do not cite without permission 

Figure 13 

Labor-Based Music Price Index

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1928 1938 1948 1958 1968 1978 1988 1998 2008

Year Artist Receives Money

Base Year 2000 = 1

Labor-Based Price Index Retail Price Index, Including Concerts

Source Data: Retail Price Index from Figure 11. Labor-Based Price Index from 1920-2000 US Censuses 

and 2000-2007 American Community Survey. 

Figure 14

Real Music Production

0

0.2

0.4

0.6

0.8

1

1.2

1928 1938 1948 1958 1968 1978 1988 1998 2008

Year of Release

Millions of $'s (2000 Real)

Labor Based Quantity Index Retail Based Index

Source Data: Retail Based Quantity Index from Figure 12. Labor Based Quantity Index from 1920-2000 

US Censuses and 2000-2007 American Community Survey 

- 39 -
 

 

 

 

Preliminary and Incomplete. Please do not cite without permission 

Figure 15 

Robustness Test for Labor Based Production Index

0

2,000

4,000

6,000

8,000

1928 1938 1948 1958 1968 1978 1988 1998 2008

Year of Production

Millions of $'s (2000

real)

Consumption Based Music Index Labor Based Music Index

Source Data: Labor Based Index from Figure 14, Consumption-Based Index from Piano Sales Data 1880-

1959, BEA Musical Instrument Sales 1959-2007, Jukebox sales from tomszone.com, # Musicians from 

1920-2000 US Census and 2000-2007 ACS, Record Sales from Gronow (1983), Radio and Television time 

from Sterling & Kittross, Arbitron data and TVB data 

Figure 16 

Market Share by Age of Song

0%

5%

10%

15%

20%

25%

30%

0 5 10 15 20

Years Since Release

(#Songs ofAgeX)/(Total # Songs)

Radio Royalties Synchronization Royalties Television Royalties

Source Data: Billboard Charts, RIAA awards from RIAA.com 

- 40 -
 

 

 

 

 

Preliminary and Incomplete. Please do not cite without permission 

Figure 17 

Market Share by Age of Song

0%

5%

10%

15%

20%

25%

30%

0 5 10 15 20

Years Since Release

(# Songs of Age X)/(Total

#

Songs)

Radio Royalties Synchronization Royalties Television Royalties

Source Data: Radio Royalties from Music Monitor, Synchronization Royalties and Television Performance 

Royalties from tvtunefinder.com 

Figure 18 

Market Share for Concert Songs Over Time

0%

5%

10%

15%

20%

25%

30%

35%

0 5 10 15 20

Years Since First Performance

(# TimesPlayed)/(Total # Plays That Year)

Source Data: Setlist.com 

- 41 -
 

 

 

 

 

 

Preliminary and Incomplete. Please do not cite without permission 

Figure 19 

Depreciation Schedule for Original Songs

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25

Years Since First Release

NPV Now/NPV At

Release

Net Revenue After Sales Costs Gross Revenue

Source Data: Depreciation Schedule from Figures 16-18. Revenue Shares from 2002 Economic Census 

Figure 20 

Aggregate Capital Stock

0

5

10

15

20

25

30

35

40

1929 1949 1969 1989

Year of Valuation

Billions if $'s (2000 Real)

Source Data: Real Production from Figures 12 and 14. 1880, 1900 & 1920 Censuses, Depreciation 

Schedule from Figure 19 

- 42 -
Preliminary and Incomplete. Please do not cite without permission 

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Preliminary and Incomplete. Please do not cite without permission 

Fraumeni, Barbara, Robinson, Brooks, Reinsdorf, Marshall and Williams, Matthew 

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- 47 -
 

 

 

 

 

 

Preliminary and Incomplete. Please do not cite without permission 

Appendix 1: Description of Revenue Adjustments 

Adjustments for Figure 1 (CD Sales) 

I use Billboard chart data to translate RIAA’s annual sales data to an estimate of 

net present value of music sales by year of release. I first downloaded Billboard’s top 

200 and top pop charts from 1985 to 2007. I then imputed sales according to the formula: 

CD’s Sold = (1/Rank ^.667)*(Average Monthly Sales). I calibrated this formula with 

data from Music Media’s global sales charts, which report both sales rank and also 

estimated sales numbers. 

I then selected a stratified subsample of albums and looked up whether the album 

is a new release CD (versus re-release of old songs) and what year the album was first 

released. On average, I estimate that two thirds of CD’s sold are new release albums that 

are within one year of initial release. Based on the depreciation profile estimated in 

Figure 17, I estimate that sales after the first year account for 28% of the total value of a 

song. Accordingly, I calculate the following formula: 

Net Present Value of New Releases = (Total RIAA Sales) * (% Sales that Are New 

Releases) * (1+28%) 

I estimate imports of music using Billboard chart data and online databases. In 

order to calculate US imports, I assume that all country of production follows the 

musician’s nationality. For example, all profits from the Beatles music are attributed to 

the United Kingdom (where the Beatles were born), all profits from Michael Jackson are 

attributed to the United States, etc.36 On average, about 80% of CD’s sold in the United 

States are produced by US musicians,37 and the market share for imports has been rising 

over time. Accordingly, the RIAA sales data slightly understate the true growth in US 

production. 

I estimate exports of music using international sales data from the IFPI, 

international charts from a wide variety of countries and online sale database. I first 

downloaded IFPI’s estimates of annual CD sales by country. I then collected charts for 

each major country and looked up nationality for a stratified subsample of artists on those 

charts. I find that the share of American music varies enormously across countries: 

approximately 4% of Japanese CD’s were produced by Americans, 15% of French CD’s, 

28% of German CD’s, 32% of British CD’s and 73% of Canadian CD’s. On average, I 

estimate that American artists account for 24% of European sales and 12% of sales in the 

rest of the world (excluding US). I then weighted each country’s % American by the

total CD sales in that country. Based on those figures, I estimate that exports account for 

only 20% of the total value of an American musician’s songs. My dataset was detailed 

 

36 I use the country of residence at the time a musician started their career to determine nationality. It is 

common for popular musicians to maintain several homes in various countries, and sometimes change their 

legal residence for tax reasons. 

Recording studios often retain a large portion of the profits from a CD, and so I could potentially adjust for 

nationality of recording studio. However, musicians generally work with a recording studio from their 

home country (Cite), and so that adjustment would add complexity without changing results. 

37Excluding re-release CD’s and classic CD’s. The US share is slightly smaller over the full sample. 

- 48 -
Preliminary and Incomplete. Please do not cite without permission 

enough to estimate yearly export shares, and so I will assume that export shares have 

been roughly constant over time.38  Accordingly, I calculate the following formula: 

Value of US Production = (Total RIAA Sales) * (1-% Sales that Are Imports) * (1+20%) 

Table 3: Annual Adjustment Factors 1985-2007 for Digital and Analog Sales 

 

Wholesale % CD's 

Revenue, produced NPV of 

(NPV of Sales Based on % New by Value of Revenue Year 1-100) / RIAA Release (Value of Sales American Exports/(Value by Year of 

Year Data CD's Year 0) Artists of All Sales) Release 

2007 $5,297 67.7% 0.31 80.8% 0.21 $4,593

2006 $6,551 68.0% 0.31 80.9% 0.21 $5,718

2005 $7,404 67.1% 0.31 82.7% 0.21 $6,522

2004 $8,073 65.5% 0.31 83.1% 0.21 $6,969

2003 $7,811 67.5% 0.31 82.0% 0.21 $6,865

2002 $8,162 68.2% 0.31 80.6% 0.21 $7,121

2001 $8,755 64.9% 0.31 80.9% 0.21 $7,292

2000 $8,979 67.1% 0.31 82.5% 0.21 $7,889

1999 $9,221 65.9% 0.31 84.3% 0.21 $8,126

1998 $8,597 67.4% 0.31 78.5% 0.21 $7,213

1997 $7,622 65.4% 0.31 79.9% 0.21 $6,313

1996 $7,610 66.0% 0.31 79.5% 0.21 $6,327

1995 $7,480 61.9% 0.31 81.4% 0.21 $5,980

1994 $7,327 66.7% 0.31 80.1% 0.21 $6,216

1993 $6,100 65.3% 0.31 79.1% 0.21 $4,999

1992 $5,479 66.1% 0.31 79.3% 0.21 $4,552

1991 $4,756 68.8% 0.31 79.0% 0.21 $4,104

1990 $4,578 66.4% 0.31 73.8% 0.21 $3,557

1989 $3,995 66.4% 0.31 72.8% 0.21 $3,065

1988 $3,798 66.4% 0.31 67.7% 0.21 $2,707

1987 $3,380 66.4% 0.31 71.1% 0.21 $2,532

1986 $2,824 66.4% 0.31 69.9% 0.21 $2,079

1985 $2,664 66.4% 0.31 67.0% 0.21 $1,881

Billboard IFPI Sales Data, 

RIAA Charts Depreciation miscellaneous 

Data Annual 1985- Curve from Billboard charts across the

Source Reports 2007 Figure 15 Chart Data World 

 

38The two top importers of US songs are UK and Germany. I downloaded their charts from 1980 to 2007 

and estimate % American for each year. I found a lot of random variation, but no consistent trend in the 

US share. As a robustness check, I also compared US sales to world sales for a sample of 97 top albums. 

Restricting the sample to US musicians, I found that US sales account for about 80% of total worldwide 

sales, and the ratio has remained relatively constant over time, though there is considerable variation across 

artists. 

- 49 -
 

Preliminary and Incomplete. Please do not cite without permission 

Adjustments for Figure 2 (Royalty Revenue) 

Because my paper is focused on the production of music, I would like to report 

the annual value of royalties by year of first release rather than year of sale. In other 

words, a 2008 replay of ‘Lucy in the Sky with Diamonds’ should be attributed to the 

1960s, when the Beatlers originally wrote the books. I will estimate annual production 

according to the formula: 

Production = [(Actual Sales)-(Predicted Sales With No New Production)]*[(NPV 

of all Sales)/(Sales in First Year)] 

For example, suppose that revenue from a new song decreases at 50% per year 

($1 Year 0, $0.50 Year 1, $0.25 Year 2, etc.). Using that hypothetical depreciation rate, 

the net present value (NPV) of a new song is 1.82 times its sales in the first year (at 10% 

discount rate). In 2006, annual sales of all songs were $1.9 billion. Without any new 

production, sales in 2007 would be $1.9*0.5 = $0.95 billion. In fact, annual sales were 

$2 billion. Therefore, I calculate that NPV of royalties for all songs released in 2007 

were ($2-$0.95)*(1.82) = $1.94 billion. Of course this formula requires a known price 

index for royalties and a known depreciation curve. I use the price index given in Figure 

8 and the depreciation curve given in Figure 17 to calculate the real royalties, the real 

stock of pre-existing music and the real value of new music production from 1985 to 

2007. 

I estimate imports and exports for royalties using methods very similar to the 

methods used earlier to estimate imports and exports for CD’s. In particular, I take my 

import share for new music royalties exactly from Table 1. I also assumed the share of 

American music is the same for CD sales and royalties for each individual country. 

However, average export share is slightly different because I use royalty revenue rather 

than CD sales to weight each country’s data. Once again, I don’t have detailed enough 

data to estimate annual export share. I will assume that export shares are fixed over time. 

- 50 -
Preliminary and Incomplete. Please do not cite without permission 

Table 4 Adjustments for Figure 2 (Royalty Revenues) 

 

NPV of 

(NPV of Sales ASCAP % New % Songs Value of Revenue Year 1-100) / and BMI Songs/Total (Value of Sales by Exports/(Value by Year of 

Year Royalty Sales Year 0) American of All Sales) Release 

2007 $2,029 17% 2.07 81% 0.20 $1,024

2006 $1,864 17% 2.07 81% 0.20 $967

2005 $1,763 18% 2.07 83% 0.20 $959

2004 $1,633 18% 2.07 83% 0.20 $903

2003 $1,548 18% 2.07 82% 0.20 $860

2002 $1,441 19% 2.07 81% 0.20 $804

2001 $1,415 19% 2.07 81% 0.20 $809

2000 $1,285 20% 2.07 83% 0.20 $763

1999 $1,208 20% 2.07 84% 0.20 $745

1998 $1,130 20% 2.07 78% 0.20 $659

1997 $1,075 20% 2.07 80% 0.20 $646

1996 $1,040 21% 2.07 79% 0.20 $627

1995 $973 20% 2.07 81% 0.20 $599

1994 $911 20% 2.07 80% 0.20 $547

1993 $853 20% 2.07 79% 0.20 $498

1992 $798 20% 2.07 79% 0.20 $467

1991 $758 20% 2.07 79% 0.20 $446

1990 $721 21% 2.07 74% 0.20 $405

1989 $685 21% 2.07 73% 0.20 $389

1988 $651 22% 2.07 68% 0.20 $359

1987 $581 23% 2.07 71% 0.20 $353

1986 $519 24% 2.07 70% 0.20 $328

1985 $464 25% 2.07 67% 0.20 $292

NMPA Royalty

BMI and Revenue, 

Data ASCAP Depreciation Curve from Billboard international 

Source Reports Figure 16 Chart Data music charts

- 51 -
- 52 -

 

Preliminary and Incomplete. Please do not cite without permission 

Adjustments for Figure 3 (Concert Revenue) 

I estimate annual production according to the formula: 

Production =[(# New Songs Played)/(Total # Songs Played)]*[(NPV of all 

Sales)/(Sales in First Year)] 

For example, suppose that songs composed in 1985 accounted for 5% of industry 

revenue from 1985 to 2005, and total industry revenue was fixed at $1 billion per year 

from 1985. With a 10% discount rate, (NPV of all Sales)/(Sales in First Year) = 9.08. 

The total value of new production in 1985 is 5%*$1 billion *9.08 = $0.45 billion. In my 

actual statistics, I use the price index given in Figure 9 and the market share breakdown 

given in Figure 18. 

I estimate imports and exports for live concerts using data from Setlist.com. This 

dataset gives the locations, dates and songs performed from a sample of live concerts 

from 1960s on. Based on that dataset, I estimate that approximately 92% of concert in 

the US are performed by American musicians and American musicians perform 

approximately 8% of their concerts abroad. Unfortunately, my dataset is not large 

enough to produce annual estimates. Therefore, I take the average for each year. 

Table 5 Adjustments for Figure 3 (Live Concert Revenue) 

(NPV of Sales NPV by % Market Year 1-100) / Pollstar Share for (Value of Sales Imports - Year of 

Year Data New Songs Year 0) Exports Release 

2007 $3,900 33% 1.77 -1% $3,632 

2006 $3,600 33% 1.77 -1% $3,348 

2005 $3,100 33% 1.89 -1% $3,013 

2004 $2,800 33% 1.90 -1% $2,730 

2003 $2,500 33% 1.93 -1% $2,465 

2002 $2,100 33% 2.09 -1% $2,177 

2001 $1,750 33% 2.23 -1% $1,901 

2000 $1,700 33% 2.03 -1% $1,729 

1999 $1,500 33% 2.07 -1% $1,548 

1998 $1,300 33% 2.14 -1% $1,373 

1997 $1,300 33% 1.91 -1% $1,270 

1996 $1,050 33% 2.16 -1% $1,115 

1995 $950 33% 2.09 -1% $988 

1994 $1,400 33% 1.27 -1% $1,066 

1993 $900 33% 1.99 -1% $904 

1992 $1,000 33% 1.57 -1% $864 

1991 $830 33% 1.77 -1% $771 

1990 $1,100 33% 1.23 -1% $826 

1989 $935 33% 1.46 -1% $772 

1988 $1,100 33% 1.18 -1% $805 

1987 $1,128 33% 1.18 -1% $826 

1986 $825 33% 1.62 -1% $725 

1985 $660 33% 1.86 -1% $633 

Krueger Data (2005) & Age Market Share Curve 

Source media stories from Figure 18 Setlist.com 
Preliminary and Incomplete. Please do not cite without permission 

- 53 -