Free Music Downloads: Petty Theft or Purchase Inducement? [Preliminary]

1. Free Music Downloads: Petty Theft or Purchase Inducement?[Preliminary] Dr. John P. Haisken-DeNew (RWI-Essen, DIW-Berlin and IZA-Bonn) jhaiskendenew@rwi-essen.de Guido Olschewski (Uni Mannheim)

2. Music Downloads • Background • Never before has there been so much interest on the side of consumers in downloading or sharing music, stored as files. • Until recently, these high quality compressed music files had been distributed essentially in violation of copyright restrictions. • Induce the music industry to counter with aggressive lawsuits against providers of peer-to-peer sharing software, internet providers and individual internet users involved in distributing music. • Claim by music industry that music downloads are leading to the demise of industry. • What can be said about music online purchases in the face of free music (MP3) downloads ? © e-Living Consortium, 2003

3. Music Downloads • Broadband vs Music • In 2002, ISPs reported that 60% of data traffic through their connections were in the form of large music, file and software files: ZDNet UK (2002). • Recent attempts by ISPs to prevent disclosing their customers identities may be simply protecting the large number of users who pay fees for flat-rate and broadband-access.   • Ironically, major record companies generally belong to very large conglomerates which earn revenue in broadband. • For example Warner Music belongs to AOL Time Warner, which is earns revenue through one of the worlds biggest ISPs, America Online (AOL). Sony Music is a branch of Sony Corporation, a huge manufacturer of computer hardware. © e-Living Consortium, 2003

4. Estimation Strategy • Discrete Events (Yes, No) • Downloaded Free MP3 Music File • Purchased CDs Online • Can estimate by Probit • Examine Marginal Effects • Compare Relative Magnitudes • However are these correlated ?? • JOINT decision to Download AND Purchase • Suggests BIVARIATE Probit • Error terms allowed to correlate • Test significance of “rho” correlation term © e-Living Consortium, 2003

5. Estimation Strategy Cont’d • Conditional Probabilities … • (a) What is unconditional Prob of Purchase ? • (b) What is conditional Prob of Purchase ? Prob (Purchase=Yes | Download=Yes) • How do these probabilities differ by group ? • Complementary Behaviour • [ Prob(Conditional) - Prob(Unconditional) ] > 0 • Prob(Purchase) increases given download • Substitution Behaviour • [ Prob(Conditional) - Prob(Unconditional) ] < 0 • Prob(Purchase) decreases given download © e-Living Consortium, 2003

6. Does Conditional Probability of Online Music Purchase Increase with Online Music Download?Demographics © e-Living Consortium, 2003

7. Does Conditional Probability of Online Music Purchase Increase with Online Music Download?Labour Market / Income © e-Living Consortium, 2003

8. Does Conditional Probability of Online Music Purchase Increase with Online Music Download?ICT Access / Profile © e-Living Consortium, 2003

9. Does Conditional Probability of Online Music Purchase Increase with Online Music Download?Country / Time Differences © e-Living Consortium, 2003

10. Conclusions Which Factors Increase Online Purchase ? • Very Strong Effects: • High Internet Use Frequency • High PC Use • Early Adopter • Strong Effects • High Internet Use Duration • High PC Use Duration • Male, Upper Social, Employed, ISDN/Broadband © e-Living Consortium, 2003

11. Conclusions Positive Correlation Download + PurchaseNo Substitution Effects ! • Unconditional Prob 0.0339 • Conditional Prob 0.0467 • Increase in Prob 0.0128 • Increase in % 37.76 Complements: Great Britain, Germany,Norway Substitutes: Italy, Israel © e-Living Consortium, 2003

12. Thank You! © e-Living Consortium, 2003

13. Estimation Bivariate probit regression Number of obs = 11533 Wald chi2(46) = 1859.25 Log likelihood = -3776.5303 Prob > chi2 = 0.0000 ------------------------------------------------------------------------------ | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- mudownl | age | -.0265072 .0021004 -12.62 0.000 -.030624 -.0223904 sex | .2341732 .0420907 5.56 0.000 .1516769 .3166695 uni | -.1720576 .0510052 -3.37 0.001 -.272026 -.0720892 dumIsdn | .1277579 .0514209 2.48 0.013 .0269749 .2285409 social | .0166154 .0027923 5.95 0.000 .0111427 .0220881 freqPcUse | .041728 .0150388 2.77 0.006 .0122525 .0712034 pctime | -.0104552 .0070213 -1.49 0.136 -.0242166 .0033062 tvsets | .1313765 .0172888 7.60 0.000 .097491 .1652619 early | .0127147 .0026396 4.82 0.000 .0075412 .0178881 netfreqhom | .2571731 .0176602 14.56 0.000 .2225597 .2917866 netperday | .1126703 .0156744 7.19 0.000 .0819491 .1433915 dumMar | -.08491 .0483833 -1.75 0.079 -.1797395 .0099195 jobstatus | .0959997 .1108964 0.87 0.387 -.1213533 .3133527 student | .1142265 .1155038 0.99 0.323 -.1121567 .3406097 noworkforce | -.0572187 .1300324 -0.44 0.660 -.3120776 .1976401 respon | -.0252674 .0133805 -1.89 0.059 -.0514927 .0009579 monthinc | -.0000187 .0000108 -1.73 0.083 -.0000398 2.46e-06 dumUK | -.179158 .0710558 -2.52 0.012 -.3184248 -.0398912 dumIt | -.1112875 .0743304 -1.50 0.134 -.2569723 .0343974 dumNo | .0723801 .0663971 1.09 0.276 -.0577558 .202516 dumIs | .2298413 .074217 3.10 0.002 .0843786 .375304 satisf | -.0108374 .0067784 -1.60 0.110 -.0241229 .0024481 dum2002 | .1205202 .0412746 2.92 0.004 .0396234 .201417 _cons | -2.83889 .1998663 -14.20 0.000 -3.230621 -2.44716 -------------+---------------------------------------------------------------- © e-Living Consortium, 2003

14. Estimation -------------+---------------------------------------------------------------- onlshopCD | age | -.0100921 .0028111 -3.59 0.000 -.0156016 -.0045825 sex | .1234441 .0603814 2.04 0.041 .0050987 .2417895 uni | -.018232 .0707144 -0.26 0.797 -.1568297 .1203658 dumIsdn | .0803341 .0690373 1.16 0.245 -.0549764 .2156446 social | .0106944 .0038676 2.77 0.006 .003114 .0182748 freqPcUse | .0749615 .0286828 2.61 0.009 .0187443 .1311787 pctime | -.0022825 .0096153 -0.24 0.812 -.0211282 .0165633 tvsets | .0766748 .0238573 3.21 0.001 .0299153 .1234344 early | .0239991 .003847 6.24 0.000 .0164591 .0315391 netfreqhom | .186352 .0311492 5.98 0.000 .1253006 .2474033 netperday | .0231634 .0236754 0.98 0.328 -.0232396 .0695664 dumMar | -.0690333 .0663172 -1.04 0.298 -.1990126 .060946 jobstatus | .1941767 .2146144 0.90 0.366 -.2264599 .6148133 student | -.0225209 .2235367 -0.10 0.920 -.4606448 .415603 noworkforce | .4177816 .2298023 1.82 0.069 -.0326226 .8681858 respon | .0180751 .0187075 0.97 0.334 -.0185909 .054741 monthinc | -1.31e-06 .0000132 -0.10 0.921 -.0000272 .0000246 dumUK | .075807 .0845872 0.90 0.370 -.0899809 .2415948 dumIt | -.9233313 .133345 -6.92 0.000 -1.184683 -.66198 dumNo | -.424074 .0874926 -4.85 0.000 -.5955563 -.2525917 dumIs | -.735795 .1233982 -5.96 0.000 -.9776512 -.4939389 satisf | -.0090422 .0094556 -0.96 0.339 -.0275748 .0094904 dum2002 | -.0214423 .0577932 -0.37 0.711 -.1347148 .0918302 _cons | -4.091618 .3360348 -12.18 0.000 -4.750234 -3.433002 -------------+---------------------------------------------------------------- /athrho | .1710371 .0391085 4.37 0.000 .0943859 .2476883 -------------+---------------------------------------------------------------- rho | .1693886 .0379864 .0941066 .2427444 ------------------------------------------------------------------------------ Likelihood-ratio test of rho=0: chi2(1) = 19.3495 Prob > chi2 = 0.0000 © e-Living Consortium, 2003