What Is Behind the Persistent Digital Gap?
“Bad Neighborhood” and Internet Adoption in Poor Countries: What is behind the Persistent Digital Gap?
DIRK DOHSE AND CHENG YEE LIM
ABSTRACT The paper investigates the determinants of Internet adoption in poor countries, focusing on the role of
macro-geographic location (neighborhood). It is argued that neighboring countries are interconnected by various kinds of
spillovers, including knowledge spillovers as well as spillovers of norms and attitudes that affect individual adoption
behavior. The empirical findings support the view that Internet adoption is affected by adoption rates in neighboring coun-
tries, even when controlling for a wide range of covariates. Addressing potential endogeneity concerns using an instru-
mental variable approach moreover suggests these relationships to be causal. The findings imply that international policies
to support Internet adoption in poor countries might be more effective if they target groups of neighboring countries rather
than single countries in order to better exploit spillovers between neighboring countries.
Digitization is rewriting the rules of international competition, bringing about manifold opportunities for newcomers to enter global value chains and to catch up with incumbents. This applies not only to companies, but, in principle, also to countries. It is, however, by no means clear
whether the digital revolution will help poor countries to better integrate into the global economy and to catch up in terms of income and wealth, or whether the rich countries will be able to sustain or even accelerate their competitive advantage by means of digital technologies (World Bank 2016a).
The core enabling technology indispensable for reaping the fruits of the digital revolution is the Internet. Digital capabilities and, in particular, the capability to productively use the Internet increasingly determine which companies, industries, and countries create or lose value (Capello and Nijkamp 1996a,b; Hirt and Willmot 2014).
It is, therefore, of critical importance that developing countries swiftly abridge the digital gap that separates them from developed economies. Empirical reality looks different, however. As can be seen from Figure 1 and Table 1, the differential in Internet usage between developed and developing countries has in fact widened from 43.1 to 47.4 percent between 2005 and 2013.1 The rise of the digital gap2 is even more pronounced if one compares the developed countries with Africa, the poorest continent on earth (Table 1).
Hence, contrary to the rosy picture of the Internet enabling new possibilities in communication and productivity in developing countries, the benefits from information technologies may be widening the chasm between richer nations and those that lack the infrastructure, skills, and resources (Norris 2001; Warf 2001).
“Access to the Internet is deeply conditioned by where one is” (Warf 2001: 16), and there is little indication that the importance of geography is decreasing in the digital age. The point of the ICT-inequality Dirk Dohse is a Senior Researcher in the Kiel Institute for the World Economy, Kiellinie 66, Kiel 24105, Germany.
His e-mail address is: email@example.com. Cheng Yee Lim is a graduate student in the University of Chicago, 5801 South Ellis Avenue, Chicago, IL 60637, USA. Her e-mail address is: firstname.lastname@example.org. An earlier version of this paper (Dohse and Lim 2016) is available as a working paper. The authors are grateful to the editor and two anonymous referees for most helpful comments. The usual disclaimer applies.
Submitted December 2016; revised May 2017; accepted July 2017.
VC 2017 Wiley Periodicals, Inc
Growth and Change DOI: 10.1111/grow.12220 Vol. 49 No. 1 (March 2018), pp. 241–262
nexus is well put by Rodriguez and Wilson, who argue that “when a new technology is introduced into a social setting where scarce resources and opportunities are distributed asymmetrically, the greater likelihood is that those with more resources will employ them to gain additional one, including ICTs” (Rodriguez and Wilson 2000: 11).
Moreover, access to the Internet is more multidimensional than adoption of telephones, televisions, and radios in the past. The binary division of users and non-users only captures one facet of Internet access. DiMaggio et al. (2001) define the digital divide as “inequalities in access to the Internet, extent of use, knowledge of search strategies, quality of technical connections and social support ability to evaluate the quality of information, and diversity of uses” (DiMaggio et al. 2001: 310).
Thus, the quality of use of the Internet will also result in a second level digital divide among users (Hargittai 1999), reiterating concerns that the lack of digitalization may further marginalize developing countries from mainstream economic growth (Davison et al. 2000).
Although there is a rich and growing literature dealing with the determinants of Internet adoption and the digital divide (discussed in more detail in the second section), the possibility of cross-country interactions in the adoption process has attracted relatively little attention so far. The current paper contributes to a better understanding of the effects of macro-geographic location (and of urban structure within countries) on Internet adoption in poor countries.
Our core hypothesis is that, apart from the usual suspects (including per capita income, education, telecommunications infrastructure, institutions), the neighborhood of a country, i.e., its geographic location, has a crucial impact on the propensity of the country’s population to adopt and productively use the Internet.
The paper is structured as follows: We begin with a brief review of the pertinent literature in the second section and develop our basic hypotheses in the third section. The fourth section presents the
Figure 1. Internet adoption rates in developed and developing countries 2005–2013.
Source: ITU (2016), own compilation.
Table 1. Digital gap (in percentage points) between developed and developing countries.
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013
Gap Developed–Developing 43.1 44.1 47.1 46.7 45.5 45.4 43.6 46.8 47.4
Gap Developed–Africa 47.4 49.0 53.9 55.0 56.3 57.0 56.4 61.1 62.5
Source: ITU (2016), own compilation.