Economic impact of data localization in five selected African countries
| Published date | 11 June 2018 |
| Pages | 337-357 |
| DOI | https://doi.org/10.1108/DPRG-01-2018-0002 |
| Date | 11 June 2018 |
| Author | Mona Farid Badran |
| Subject Matter | Information & knowledge management,Information management & governance,Information policy |
Economic impact of data localization in
five selected African countries
Mona Farid Badran
Abstract
Purpose –The purpose of this study is to quantifythe impact of laws and regulations that govern the
cross-border flow ofdata on the economies of five selected African countries, namely, Egypt, Morocco,
South Africa,Kenya and Mauritius. Moreover, this study addressesthe state of cloud computing in Africa.
Finally,policy recommendations are provided in this respect.
Design/methodology/approach –To reach accuratefinding the Global Trade AnalysisProject (GTAP)
data was used, and thenthe computable general equilibrium (CGE) was computedto estimate the total
cost on the economy. Using the three data regulations linkages indexes (DRLs), the increased
administrativecost effect was analyzed on five to six majoreconomic sectors in the target countries.This
was followed by estimating the loss in sector-wide total factor productivity (TFP) (for the five to six
shortlistedsectors). Using this data, the computable general equilibriummodel (CGE) was computed, in
order to estimate the economy-wide impact. Based on these findings, a set of recommendations were
offered to the policy maker, reflecting the obtained results and conclusions and their implications on
draftingdata-related policies.
Findings –The obtained data indexes reveal that Mauritius is the country with the most laws and
regulationsgoverning the cross border flow of data,followed by South Africa Egypt to a lesserextent and
finally Morocco and Kenya both showing an obvious lack of data regulations. The small value of the
estimated elasticityof the selected countries compared to the value of the estimatedelasticity in the EU-
0.347 shows that the impact of datalocalization is less in the selected African countries than in the other
set of EU countries examinedin the research paper. This is because the former has smaller economies
with fewer linkages to the global economy and are less reliant on sectors that are heavy usersof data.
Thus, the overall impact of data localization was not as profound on TFP as is the case in advanced
economies. This research paper arrives at the conclusion that fighting the trend of data localization is
crucial. In fact, data localization hinders the necessary and essential role of global trade in realizing
economic development.Specifically, this is evidentin the increase in production costs as reflectedin the
increaseof the prices of goods, which would lead to a declinein incomes.
Originality/value –Global studies lookedat the impact of data localization on the EU, as well as China,
India, Korea and Vietnam, providing some data on Asia Pacific. However, no study has ever been
conducted on the MiddleEast and Africa. This study aims to fill this gap. The approachof this study is to
capture the extentof data localization mandates encoded in the laws ofeach of the selected five African
countries showing how these mandates govern their cross-border data flow and, in turn, affect their
economies. Furthermore, the policy recommendations section of this research paper makes a
contributionto the existing literature.
Keywords Cloud computing, Africa, International trade, GTAP, Economic policy, Data localization
Paper type Research paper
1. Introduction
Access to foreign markets and integration with complex global supply chains are major
sources of economic growth, jobs and new investments for developing economies.
Similarly, domestic manufacturing, services and exports also depend on the availabilityof a
wide variety of competitively priced products, inputs and services. All these are possible
provided there is a secure and efficient exchange of information including cross-border
Mona Farid Badran is
Associate Professor at
Faculty of Economics &
Political Science, Cairo
University, Giza, Egypt.
Received 16 January 2018
Revised 5 March 2018
Accepted 28 March 2018
DOI 10.1108/DPRG-01-2018-0002 VOL. 20 NO. 4 2018,pp. 337-357, ©Emerald Publishing Limited, ISSN 2398-5038 jDIGITAL POLICY, REGULATION AND GOVERNANCE jPAGE 337
data flows. Restricting the free flow of data would affect any business that uses the internet
to produce and deliver goods and services (Kommerskollegium, 2015;Pelissie du Rausas
et al.,2011
).
Data localization refers to laws that require organizations to store customer data in a
specific country or in a geographic location, i.e. servers inside that country (Laviathan
Report, 2015). Moreover, the process of restoring data on local servers undermines many
benefits, especially theeconomic ones of cloud computing. Cloud hosted services–with no
localization restrictions –are consistently cheaper than locally hosted services, regardless
of geography (Laviathan Report,2015).
Free flow of data is essential for the expansion of international trade and co-operation
(Castro, 2013). New challenges such as protection of personal data have erupted,
especially since the increase in the intensity of data flow (Parker, 2012). Collective efforts
are being made to formulate international instruments on data protection and privacy with
many countries presently assessing their need and subsequently implementing these
measures (Kuner, 2012). However, in the absence of an internationally agreed upon
protocol, many countries are choosing to protect the privacy of their citizens by creating
“information silos”, through forced data localization mandates, like the ones enacted in
Russia. Another type of data that flows across borders is business data; this refers to the
big share of data used for management services inside multinational firms. These services
pertain to the supervision, control and organization of affiliates within the same enterprise.
While the management services constitutea small share of the entire value-added in export
services, they are instrumental for other types of services, such as finance (Van Der Marel,
2015).
Tightening control on transborder data flow seems to be encouraged by four policy
objectives, namely:
1. preventing circumvention of national data protection and privacy laws;
2. guarding against data processing risks in other countries;
3. addressing difficulties in asserting data protection and privacy rights abroad; and
4. enhancing the confidence of consumers and individuals (Kuner, 2012).
Today the cloud offers flexible and affordable software, platforms, infrastructure and
storage, available to all organizations, across industries, even those with limited budgets
and increasing growth demands; cloud computing presents an opportunity for
organizations to decrease costs, increase flexibility and improve IT capability (World Bank
Group, 2016).
The economic implications of data localization are evident with respect to increasing the
costs of doing business and trade. In Brazil, for example, a company would pay about 54
per cent less using cloud services located outside the country in comparison to what it
would pay to host the same services with local cloud data. So, if data localization was
evident in this country, local businesses would prefer to make major capital investments in
computer hardware and infrastructure rather than be able to take advantage of flexible and
cost savings offered by cloud service giants (Laviathan Report, 2015).
It is worth noting that on the firm level, adoption of cloud computing has raised many
challenges, such as the new and competing privacy regulations across variousjurisdictions
and cyber security threats. Moreover, organizations that rely on multiple cloud service
providers lose control over the movement of their data through the different data centers
across the world; in addition, cloud service providers are often reluctant to fully disclose
their security measures for protecting or processing data, due to privacy breaches. Finally,
there is a high level of ambiguity regarding the data protection laws that are applicable
(Deloitte, 2016).
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