Facets of the digital divide in Europe: Determination and extent of internet use

Abstract

The primary objective of this article is to identify, given Internet accessibility, the factors that shape the decisions of individuals for personal Internet usage and its extent. Cross-sectional data from the European Social Survey database were utilized and an ordered probit model with selectivity was employed. The hypothesized link between the decision to use the Internet and the extent of usage was confirmed by the data. Household income, cost of access, demographics, media use, regional characteristics and general skill acquisition by individuals appear to correlate with Internet use and the extent of usage. In addition, a non-linear decomposition analysis was applied in order to identify the causes of the observed south/north divide. The results indicate that the observed differences in the probability of Internet use constitute a structural problem.

Keywords:

• Internet use
• Self-selection
• Non-linear decomposition
• North–South Europe

Acknowledgements

The authors wish to acknowledge two anonymous referees for their helpful comments and suggestions.

Notes

¹The term refers to the ‘gap between individuals, households, businesses and geographic areas at different socioeconomic levels with regard to their opportunities to access information and communication technologies and to their use for a wide variety of activities’ (OECD, 2001, pp. 8–9).

²For example, Internet is a convenient tool for consumers to search information, evaluate, purchase and use products more efficiently and effectively than other channels (i.e. traditional marketing channels) (Byeong-Joon Moon, 2004).

³Economists have begun to speculate on the potential effects of the above developments on labor markets. For example, commentators and analysts have argued that extensive Internet use could lead to higher average match quality (Krueger, 2000), to a reduction of non-competitive wage differentials (Autor, 2001) and to an augmentation of ability-related wage differentials (Kuhn, 2000). Recently, Kuhn and Skuterud (2004) argued that unemployed Internet searchers achieve faster re-employment rates.

⁴Rappoport et al. (2002); Madden and Simpson (1997); Madden et al. (1999); Eisner and Waldon (2001); Madden and Coble-Neal (2002); Kridel et al. (1999); Kelly and Lewis (2001).

⁵Recently, Rappoport et al. (2002) utilized an alternative procedure in analyzing broadband or dial-up access (self-selected discrete choice) and observed Internet usage (continuous variable) for US households.

⁶Distributor: Norwegian Social Science Data Services (http://ess.nsd.uib.no).

⁷Weights have been applied according to the procedure described in the www.europeansocialsurvey.org: Weighting European Social Survey Data.

⁸Beilock and Dimitrova (2003) provide a comprehensive review of the literature on the typology of Internet users in many countries worldwide. The typical Internet user is young, male and well educated.

⁹See Arulampalam et al. (2004) for calculating such average predicted probabilities.