# **3. The Data**

Technological diffusion is defined in Gort and Klepper (1982) as "the spread in the number of producers engaged in manufacturing a new product". Given the nature of the Internet, we have to adapt this definition, whereby diffusion refers to the number of consumers of Internet. Although one could think of many indicators of Internet diffusion<sup>6</sup> , the two most widely used are: the number (and percentage) of Internet users and subscribers<sup>7</sup> . Tables 1A-2A in the Appendix present descriptive statistics for Internet users. Conceptually, both variables are different since users include intrahousehold access to Internet as well as access in public places (universities, libraries). The results using both measures of Internet diffusion are qualitatively similar. Hence, in this paper, we focus only on the results for Internet users.<sup>8</sup> The main dataset that we use in this paper is from the International Telecommunication Union Data (2006). This dataset contains information on a set of 199 countries for the period 1990-2005.<sup>9</sup> By including both developed and developing countries in our sample we take into account the importance of problems of sample selection raised by De Long (1988) in the context of the literature on growth convergence.

One important thing to note is that, for most technologies, the relevant measure of their diffusion is the ratio of actual users to _potential_ users. Measuring potential users is problematic since it requires access to micro data, which is unavailable for most of the countries in our sample. However, as noted by Dasgupta _et al._ (2001), in the case of Internet, human capital requirements to use its basic applications (electronic mail and information search) are relatively low. Therefore, it seems reasonable to assume, as we do, that the entire population is a potential user.

Finally, we use the _World Bank Country Classification_ to study potential different diffusion patterns across income levels<sup>10</sup> . The World Bank classifies countries in the year 2005 according to their GNI per capita in five different groups. These groups are _lowincome_ economies (54), _lower-middle-income_ economies (58), _upper-middle-income_ economies (40), _high-income_ economies (56), and _high-income OECD members_ (24). All the countries included in the last group are also present in the previous one, so we disregard OECD members throughout the analysis. The list of countries included in each

> 6 Press (2000) provides a long list of such indicators: connectivity, host count, number of web sites, language distribution, compound indices of pervasiveness, geographic dispersion, sectoral absorption, connectivity infrastructure, organizational infrastructure, and sophistication of use.

> 7 Ideally, we would also like to have measures of the quality and the intensive use of the Internet but this information is not available for a large enough group of countries. A developing nation might have a very slow connection to the Internet. For example, in the spring of 1999, Cuba's total international bandwidth was 832 kb/s, which is less than a home with high-speed DSL service or cable modem. Furthermore, connectivity was concentrated in Havana (though less concentrated than in many developing nations) and limited to relatively few people, almost exclusively through their work (See Martinez, 1999). The picture is much worse in Africa (see Jensen, 2005).

> 8 Results for Internet subscribers are available from the authors upon request.

> 9 See the Appendix 2 for a list of the countries considered in this study.

10 The income thresholds are: low income, $875 or less; lower middle income, $876-$3,465; upper middle income, $3,466-$10,725; and high income, $10,726 or more.

5