1 ‘Social Sharing’ By Means of Distributed Computing: Some Results From A Study of Hans-Jürgen Engelbrecht Massey University August

2 1.Introduction Information and Communication Technologies (ICT) are General Purpose Technologies. One of many associated innovations: Distributed computing, grid computing. Enables non-commercial sharing of physical, rivalrous goods via the Internet: Such ‘social sharing’ is a form of economic production (Benkler, 2004).

3 ‘Shareable goods’ Sharing of computing power and bandwidth. Two features of ‘shareable goods’ (Benkler, 2004):  They are lumpy (PCs come in discrete units).  They are of ‘mid-grained’ granularity (PCs are widely privately owned and systematically have slack capacity).

4 ‘Shareable goods’ ctd. What determines the extent of ‘social sharing’? Technological conditions, but also cultural practices and tastes (Benkler, 2004) and social and legal conditions (David, 2004).

5 Prime example of a voluntary non- commercial Internet-based distributed computing project: Launched in May Download screen saver. Analysis of Arecibo radio telescope data. the most powerful special purpose supercomputer in the world.

6 ctd. Worldwide phenomenon (except for Mauritius, Palestine and Vatican City). Incentives build into client interface, e.g. user and results data. By Dec. 2004, there had been:  More than 5 million contributors.  Providing over 2 million years of CPU time (more than 1000 years of CPU time during the last day alone).

7 ctd. SETI country data available for: Dec. 10 th, 2002; Dec. 11 th, 2003; Dec. 13 th, Dependent variables used in the regression model:  SETI participants per capita.  SETI results per capita (measures actual outcomes and is arguably a better Internet- intensity variable than ‘hours of use’).

8 3.Explanatory variables What determines cross-country participation and its intensity? Aim: To include as many countries as possible. Therefore, modelling is severely restricted and I use only a few key explanatory variables in the regressions:  ITU’s ‘Digital Access Index’ (DAI).  GDP per capita (gdp).  The ‘Human Development Index’ (HDI).  Country group dummy variables.

9 The Digital Access Index (DAI) ITU: The DAI tries to measure “the overall ability of individuals in a country to access and use ICTs…”. It provides the first truly global ICT ranking. The DAI is a composite index made up of 8 underlying indicators to capture:  infrastructure (fixed telephone & mobile telephone subscribers),  affordability (Internet access price),  ‘knowledge’ (adult literacy, school enrolment),  quality (broadband subscribers, international Internet bandwidth),  actual usage of ICTs (Internet users).

10 Components of the Digital Access Index (DAI), 2002:

11 The DAI ctd. Hypothesis: The DAI is a positive and statistically significant determinant of participation and its intensity.  This would mean: On average, participation and its intensity across countries matches inter-country differences in ICT accessibility.

12 Other explanatory variables GDP per capita (in PPP adjusted US $):  Traditional proxy for ‘standard of living’. Key explanatory variable in numerous ICT and Internet diffusion studies.  It is expected to be a positive and statistically significant determinant of participation and its intensity.

13 Other explanatory variables ctd. The HDI:  A composite index which has emerged as the preferred measure of ‘development’.  It measures important dimensions of human development neglected by gdp, such as: living a long and health life and being educated.  It is best included alongside DAI and gdp as an additional explanatory variable.

14 Other explanatory variables ctd. Country group dummy variables:  ITU’s “developed & advanced countries” versus ‘the rest’.  Alternatively: 6 regional dummy variables (similar to Caselli and Coleman II, 2001). See “Appendix: Country List”.

15 4.Regression analysis Matching data for 172 countries. Dependent variables alternatively in 2004 levels and changes. Most regressions estimated in double-log form. OLS with White’s heteroscedasticity correction. Box-Cox regressions.

16 Regression results

17 Regression results ctd. Increasing DAI and gdp by 1% increases dependent variables by a similar %tage (elasticity of ‘change in results per capita’ with respect to DAI somewhat lower). DAI, gdp, and the general divide between rich&poor countries can explain most of the cross-country variation in participation and its intensity (see R 2 s). HDI dropped from preferred regressions (DAI and HDI highly correlated).

18 5.The global digital divide By Dec. 2004, developed & advanced countries (about 15% of the sample population) accounted for over 90% of submitted results. But: Indications of a slowly narrowing global digital divide!  Growth rates for ‘users’ and ‘results’ higher in ”the rest”.

19 Developed & advanced countries versus ‘the rest’:

20 Developed & advanced countries versus ‘the rest’ ctd.:

21 Developed & advanced countries versus ‘the rest’ ctd.:

22 6. Concluding comments Further research needed:  For a less heterogeneous group of countries. This would allow more sophisticated modelling.  More sophisticated models are needed to enable more specific policy conclusions. Will non-commercial ‘social sharing’ via the Internet become a dominant mode of economic production?  There is huge potential for it, but commercial distributed computing might greatly affect its realization.