Localising data in a Globalised World

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Localising data in a
Globalised World
Javier Lopez Gonzalez, James Messent,
Magnus Rentzhog, Dorothee Flaig, MarieAgnes Jouanjean and Peter Walkenhorst
Session 2: Data Protection and International Trade:
What is at stake?
Geneva 19th April 2016
Context
• Globalisation is underpinned by the movement of data across international borders.
• The ubiquitous exchange of data has raised concerns related to the privacy and
security of consumers leading to the emergence of new regulations seeking to
provide protection.
• Policy challenge: To enact policies that protect privacy and security in the least trade
distorting way.
• The role of economic analysis: to provide information to weigh the existing tradeoffs.
• Aim of our project: to measure the impact of the emerging data regulation on
business activity and trade.
• Quantifying the impact of emerging measures is hard.
• Value of data is not easily measured (data valued at use, bytes and bits vs
value, inherent and potential value, etc.)
• Restrictiveness of the measures uncertain
• Little knowledge on how firms use data or how they choose its location.
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UNDERSTANDING THE
MEASURES
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Data regulation database
• Identified pieces of legislation, regulation or policies that are
implemented by governments and currently in force.
• To be included, measures must treat foreign senders/receivers
differently from domestic equivalents, or explicitly regulate the
geographic location of data storage.
• Over 100 measures across 68 economies identified.
• Analysis of measures informs a broad taxonomy.
• Measures fall into two categories:
• Cross-border flow measures (75)
• Local storage requirements (41)
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Cross-border flow measures - Taxonomy
Conditional
Free /
No specific
mention
One-of
Combination
Private sector safeguards
Private sector safeguards
Actionable
Non-actionable
Actionable
Non-actionable
Government safeguards
Government safeguards
Domestic focus
International focus
Domestic focus
International focus
Prohibition
General level of restrictiveness
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Cross-border flow measures – Evolution and
nature
80
Nubmer of measures
70
Public
4
60
Health
3
Telecommunications
3
50
40
Prohibition
Financial
9
Conditions - Combination
30
Conditional - One of
20
10
0
1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013
Horizontal
56
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Local Storage Requirement - Taxonomy
Compulsory
Conditional
Free/
No specific
mention
•
•
•
Guarantee of
government
Time specific storage
requirement
Foreign storage is
necessary
Compulsory &
other data
restriction
Compulsory &
prohibitive
data restriction
General level of restrictiveness
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Local Storage Requirement – Evolution and type
45
40
Public
2
Health
2
Number of measures
35
All data
1
Personal
7
30
25
20
Compulsory
Conditional
15
10
Telecommunications
14
5
0
1972 1976 1980 1984 1988 1992 1996 2000 2004 2008 2012
Financial
15
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QUANTIFYING THE ECONOMIC
IMPACT OF THE DATA
REGULATION
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Understanding the economic implications can
help policy makers weigh the existing trade-offs
• Although measures generally restrict transfers of personal data, OECD
research suggests that firms may not be able to easily separate personal
from non-personal data so the measures will have a broader reach.
• The use of international data by businesses is endemic:
• Coordinating GVCs relies on data transfers (fro production, coordination
of processes, HR management, accountancy, traceability…).
• Data enabled digital solutions can help increase productivity and reduce
supplier search costs;
• Data can help deliver new services previously hard to trade (i.e. medical
diagnostic services , accountancy etc.)
• Medical research organisations researching cures for diseases require
analysing personal health records to identify cures (i.e. Cancer
Research).
• Data transfers can be particularly important for SMEs and firms in
developing countries which are more constrained in the
internationalisation processes.
• But quantification of the impact is hard. No data on data, little knowledge
of how companies value data or how restrictive measures are. It is an
ongoing exercise.
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Quantification (ongoing)
• Dearth of statistics and importance of inter-linkage (input) effects
favours use of ex-ante modelling techniques Computable General
Equilibrium models.
• Data sector is split from GTAP database
• Cross-border flow restrictions:
• Impose compliance cost (ad-valorem- akin to iceberg costs)
related to;
I.
II.
Splitting personal and non-personal data. Cost will depend on
importance of personal information and costs of splitting.
Compliance associated to meeting the grounds of the
conditional flow restriction.
• Storage restriction:
• Cost increase modelled as modified local content requirement.
Input-cost mark-up to be satisfied by the domestic market.
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Simulations
• Scenario 1: Measuring the impact of current measures
• Measures identified (over 100) to be added collectively.
• Scenario 2: Measuring the impact of data autarky
• To obtain an upper bound to compare other scenarios.
Hypothetical exercise to highlight possible impact of
continued proliferation..
• Scenario 3: A new policy environment
• Attempt to model what adopting a common international
agreement on use of data might be and costs
associated to not adopting this standard.
• Scenarios are tentative.
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Trade and Agriculture Directorate | Organisation for Economic Co-operation and Development (OECD) | www.oecd.org/tad | tad.contact@oecd.org
OECD Ministerial on the Digital Economy
Cancun, Mexico 21-23 June
• Cancún marks another pivotal point in the evolution of the digital economy, one in which the economy is in
fact becoming fully digital.
• Ministers from OECD and partner countries, international organisations, business, labour, civil society and
the Internet technical community will meet to discuss better policies for Internet openness and global data
flows, convergence, IoT, trust and digital risk management, and new jobs & skills.
• These discussions will consider the trade-offs, complementarities and possible unintended consequences
of policy actions.
oecd.org/cancun2016
Contact us
We look forward to hearing from you!
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Difficulty of separating personal and nonpersonal data (percent of responses)
Wood, paper, paper products, printing and publishing
Other manufacturing, including recycling
Food products, beverages and tobacco
Transport equipment
Textiles, textile products, leather and footwear
Construction
Mining and quarrying
Post and telecommunications
Chemicals and non-metallic mineral products
Research and development
Agriculture, hunting and forestry and fishing
Other manufacturing of machinery and equipment
Computer and related activities
Other business activities
Electrical and optical equipment
Electricity, gas and water supply
Wholesale and retail trade; Hotels and Restaurants
Financial intermediation
Community, social and personal services
Real estate, and renting
0%
Costly or Very costly
20%
Somewhat costly
40%
60%
80%
100%
Not at all costly
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