155 Part II: Aligning data governance with the social contract

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Today’s unprecedented growth of data and their ubiquity in our lives are signs that the data revolution is transforming the world. And yet much of the value of data remains untapped. Data collected for one purpose have the potential to generate economic and social value in applications far beyond those originally anticipated. But many barriers stand in the way, ranging from misaligned incentives and incompatible data systems to a fundamental lack of trust. World Development Report 2021: Data for Better Lives explores the tremendous potential of the changing data landscape to improve the lives of poor people, while also acknowledging its potential to open back doors that can harm individuals, businesses, and societies. To address this tension between the helpful and harmful potential of data, this Report calls for a new social contract that enables the use and reuse of data to create economic and social value, ensures equitable access to that value, and fosters trust that data will not be misused in harmful ways.

This Report begins by assessing how better use and reuse of data can enhance the design of public policies, programs, and service delivery, as well as improve market efficiency and job creation through private sector growth.

Because better data governance is key to realizing this value, the Report then looks at how infrastructure policy, data regulation, economic policies, and institutional capabilities enable the sharing of data for their economic and social benefits, while safeguarding against harmful outcomes. The Report concludes by pulling together the pieces and offering an aspirational vision of an integrated national data system that would deliver on the promise of producing high-quality data and making them accessible in a way that promotes their safe use and reuse. By examining these opportunities and challenges, the Report shows how data can benefit the lives of all people, but particularly poor people in low- and middle-income countries.

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Softcover ISSN: 0163-5085 ISBN: 978-1-4648-1600-0 e-ISBN: 978-1-4648-1601-7 DOI: 10.1596/978-1-4648-1600-0 Hardcover

ISSN: 0163-5085 ISBN: 978-1-4648-1607-9 DOI: 10.1596/978-1-4648-1607-9

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xi Foreword xiii Acknowledgments xvii Abbreviations

1 Overview

3 Overview

3 Advancing development objectives through data 10 Aligning data governance with the social contract 16 Moving toward an integrated national data system 18 Notes

19 References

21 Part I: Advancing development objectives through data

23 Chapter 1: Harnessing the value of data for the poor 24 The untapped potential of data to serve development objectives 25 A brief history of data

27 A data typology

30 The economics of data and political economy issues 33 Data for development: A conceptual framework

38 A data governance framework to enforce the social contract for data 41 Putting it all together: Establishing an integrated national data system 42 Organization of this Report

43 Notes 44 References

48 Spotlight 1.1: Helping communities to gain the ability to collect and analyze their own data

50 Spotlight 1.2: The importance of good data in helping low- and middle-income countries to manage debt during and after the COVID-19 pandemic

53 Chapter 2: Data as a force for public good 54 The central role of public intent data

54 Public intent data and development: Three pathways for adding value 59 Gaps in the coverage, quality, and usability of public intent data 65 Why data gaps persist: The political economy of public intent data 71 Realizing the potential of public intent data

75 Notes

78 References

155 Part II: Aligning data governance with the social contract

157 Chapter 5: Data infrastructure policy: Ensuring equitable access for poor people and poor countries

158 Data infrastructure as a source of inequity 160 Connecting poor people

168 Connecting poor countries 174 Conclusions and recommendations 178 Notes

180 References

184 Spotlight 5.1: How the COVID-19 pandemic has recalibrated expectations of reasonable data consumption and highlighted the digital divide

186 Spotlight 5.2: Data’s carbon footprint

189 Chapter 6: Data policies, laws, and regulations: Creating a trust environment 190 A trust framework of data safeguards and enablers

191 Building safeguards for trusted data use 199 Creating enablers for data sharing

206 Recommendations for crafting a holistic legal framework

208 A maturity model for strengthening the legal and regulatory framework 209 Notes

215 References

222 Spotlight 6.1: The evolving social contract on data: Balancing data sharing and data protection to facilitate contact tracing to control COVID-19

224 Spotlight 6.2: The debate over ownership of personal data

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227 Chapter 7: Creating value in the data economy: The role of competition, trade, and tax policy

228 Shaping data regulation to support competition, trade, and taxation 229 Competition policy

237 Trade policy 246 Tax policy 250 Conclusion 250 Notes

254 References

259 Spotlight 7.1: Understanding the interface between data protection and competition policy

261 Spotlight 7.2: The role of regional and international cooperation in addressing data governance challenges

265 Chapter 8: Institutions for data governance: Building trust through collective action

266 How can institutions help govern data for development?

267 Data management across the data life cycle 269 Data governance functions

271 Mapping data governance functions to illustrative institutions 277 Data intermediation and collaboration

280 Making data governance institutions effective

284 Sustainable outcomes through inclusive multistakeholder governance 286 Assessing the institutional foundation through the lens of a maturity model 288 Notes

291 References

297 Spotlight 8.1: The need for a new global consensus on data: A call to action 299 Spotlight 8.2: Promoting citizen science in the Amazon basin

301 Part III: Moving toward an integrated national data system

303 Chapter 9: Creating an integrated national data system 304 Toward an integrated national data system

305 The vision of an integrated national data system 309 Realizing the vision

322 Notes 324 References

Boxes

O.1 18 Toward an integrated national data system: Country examples 1.1 24 What this Report means by data 1.2 29 Innovation in traditional surveys:

A COVID-19 example in Brazil 1.3 32 The challenges of trading data

through markets

1.4 36 Using private intent data to tackle COVID-19

2.1 55 Six types of public intent data 2.2 60 The World Bank’s Statistical

Performance Indicators

2.3 61 Gender data and the COVID-19 pandemic

3.1 94 Technologies and methods that support data-driven decision-making and intermediation

4.1 122 Using cellphones to combat COVID-19

4.2 126 Leveraging private intent data to tackle COVID-19

4.3 131 Preventing illegal fishing in protected maritime areas

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4.4 135 Using statistical methods and private intent data to improve representativeness and geospatial precision

5.1 174 The brain drain—ICT professionals 8.1 266 Uruguay’s whole-of-government

approach to data governance 8.2 269 The importance and complexity of

data governance institutions: The example of digital identification systems

8.3 279 Increased scrutiny of and constraints on private data intermediaries 8.4 286 Building multistakeholder data

governance into smart city initiatives through “digital democracy”

9.1 304 Relationship between an integrated national data system and a national statistical system

Figures

O.1 4 How data can support development:

A theory of change

O.2 6 A social contract for data founded on value, trust, and equity

O.3 11 Data governance layers at the national and international levels O.4 13 The legal and regulatory framework

for data governance remains a work in progress across all country income groupings

O.5 14 Since 1990, the global trade in data-driven services has grown exponentially and now constitutes half of trade in services

O.6 17 What happens in an integrated national data system?

1.1 26 The share of people counted in a census grew from about 1 in 10 in 1850 to 9 in 10 today

1.2 30 The data life cycle

1.3 34 Three pathways along which data can foster development

B1.4.1 36 Use of repurposed data to study COVID-19: Published articles, by type of private intent data used

1.4 39 Data governance layers at the national and international levels 1.5 41 Data flow safely across all

stakeholders in an integrated national data system

S1.1.1 49 A citizen-led method to ascertain who has authority in household decision- making in rural Indian villages

S1.2.1 50 In six years, the composition of debt has shifted dramatically

2.1 55 Certain data features can maximize the value of public intent data 2.2 56 Improving access to water: Using

real-time sensor data to reduce repair time for broken hand pumps in Kenya

2.3 60 Gaps in geospatial datasets are especially large in lower-income countries

B2.3.1 61 Proportion of COVID-19 cases reported with sex-disaggregated data by 190 countries

2.4 63 Lower-income countries, especially those affected by fragility and conflict, have less comparable poverty data than other country groups

2.5 64 Lower-income countries are less likely than other countries to adhere to international best- practice statistical standards and methodologies

2.6 65 A positive feedback loop can connect enablers and features of public intent data with greater development value 2.7 66 Most countries do not fully fund

their national statistical plans 2.8 68 The older a country’s statistical

laws, the lower is its statistical performance and the less open are its data

2.9 69 Greater NSO independence and freedom of the press are positively correlated with better statistical performance

2.10 70 Data supply and demand can generate either virtuous or vicious cycles of data production and use 2.11 71 Policies to realize the potential of

public intent data

S2.1.1 85 Prevalence of female genital mutilation in women ages 15–49, by country income level, 2010–19 3.1 94 The role of data in the production

process: Pathways to development 3.2 96 The role of data in economic activity 3.3 97 Platform firms are numerous in some

lower-income countries, but tend to be small

3.4 97 The importance of domestic versus foreign-headquartered firms differs across countries as indicated by firm share of top websites

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3.5 98 Users visit and spend more time on Facebook, Google, and YouTube than other websites

3.6 99 Internet traffic in low- and middle- income countries is concentrated in several US-based firms

3.7 108 Risks to market structure and market power stemming from platform firms

S3.1.1 118 Private company use of public data is extremely valuable in the United States, suggesting the value of open government data

B4.1.1 123 Smartphone location data reveal the changes in the time users spend at home in Jakarta

B4.2.1 126 Use of repurposed data to study COVID-19: Published articles, by type of private intent data used

B4.3.1 131 Public intent and private intent data can be combined to detect illegal fishing activity

4.1 134 Gaps in network coverage differ across farm sizes, affecting agricultural extension services 4.2 137 Artificial intelligence specialists

gravitate to the US market, no matter where they are educated

5.1 158 The data infrastructure supply chain 5.2 160 The developing world overwhelmingly

accesses data using wireless networks 5.3 161 Gaps in 3G wireless broadband

internet coverage have been shrinking, but usage gaps remain stubbornly high

5.4 162 Globally, the coverage of wireless technologies reflects their constant upgrading

5.5 164 In low- and middle-income countries, nearly 70 percent of those who do not use the internet are held back by deficiencies in digital literacy 5.6 166 Inequities in mobile data

consumption across country income groups and regions are huge 5.7 167 The monthly price for 1 gigabyte of

data is unaffordable in low-income countries

5.8 167 Data consumption is very sensitive to market prices and service affordability

5.9 168 The presence of domestic data infrastructure facilitates national data exchanges

5.10 170 Data infrastructure is relatively scarce in low- and middle-income countries

5.11 171 Countries develop domestic data infrastructure in stages

B5.1.1 174 Low- and middle-income countries are educating ICT professionals but not retaining them

B5.1.2 175 Major wage differentials for ICT professionals create a brain drain, especially in low- and middle-income countries

S5.2.1 186 Worldwide greenhouse gas emissions from data consumption have been flat, even though electricity consumption has been growing

6.1 191 Envisioning the multidimensional nature of the legal framework for trust

6.2 192 The evolution of data protection 6.3 194 Gaps in the regulatory framework

for cybersecurity are glaring across country income groups

6.4 195 Progress on personal data protection legislation differs markedly across country income groups

6.5 200 Adoption of e-commerce and related legislation is widespread across country income groups 6.6 201 Regulations enabling access to

and reuse of public intent data are unevenly developed across country income groups

6.7 204 Adoption of enablers for sharing private intent data lags those for public intent data across country income groups

7.1 228 The unusual characteristics of data-driven businesses pose complex challenges for policy makers in the areas of competition, trade, and taxation

7.2 230 In the digital economy, antitrust cases related to passenger transport are more prevalent in middle-income countries than in high-income countries

7.3 231 Among anticompetitive practices, abuse of dominance is more widespread worldwide across multiple sectors of the digital economy

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7.4 238 Since 1990, the global trade in data-driven services has grown exponentially and now constitutes half of trade in services

7.5 239 Three distinct approaches to handling cross-border data flows 7.6 248 East Asian countries are losing a

substantial volume of tax revenue by failing to apply current VAT rules to digital services

8.1 268 Data governance and data management, working seamlessly together in support of the social contract

8.2 270 Functions of data governance 8.3 273 No low-income and few lower-

middle-income countries have a separate data governance entity;

most embed them in another government institution

8.4 276 The lower the country income level, the fewer are the countries with data protection authorities

8.5 276 More than half of countries across all income groups have antitrust authorities

8.6 277 Only about one-quarter of low- income countries have cybersecurity agencies

8.7 281 Features of well-functioning institutions for effective data governance

S8.2.1 300 Using a diverse set of open science and citizen science tools and technologies in the Amazon basin 9.1 305 What happens in an integrated

national data system?

9.2 309 A data maturity model for a hypothetical national data system 9.3 310 Steps to integrating the public sector

into the national data system 9.4 313 Steps to integrating civil society into

the national data system

9.5 315 Steps to integrating academia into the national data system

9.6 317 Steps to integrating the private sector into the national data system 9.7 320 Steps to integrating international

and regional organizations into the national data system and collaborating across borders

Maps

O.1 5 Use of aggregated cellphone records to track mobility week by week during COVID-19 lockdowns in The Gambia, March–May 2020 O.2 7 Highly refined data pinpointed

areas of Nigeria that needed better sanitation

O.3 9 Combining satellite imagery with household survey data increases the resolution of the poverty map of Tanzania

O.4 12 Data infrastructure is not yet widespread across all parts of the world

1.1 27 John Snow’s innovative mapping of the cholera epidemic in London in 1854 revolutionized tracing of the disease

B1.4.1 37 Use of repurposed data to study COVID-19: Published articles, by country

2.1 57 Reducing poverty: Mapping pockets of poverty in Croatia allowed better targeting of antipoverty funds 2.2 59 Improving public safety: The use of

citizen-collected data in Bogotá led to greater safety around bike paths B4.1.1 122 Mapping the home location of

smartphone users in Jakarta, 2020 B4.2.1 127 Uses of repurposed data to study

COVID-19: Published articles, by country

4.1 132 Private intent data can provide unique and comparable information not collected by national governments, such as the number of adults who lack a formal financial account 4.2 133 Agricultural extension services

can be tailored to the slower, older broadband internet accessible to many small-scale farmers

S4.1.1 151 Large gaps remain in global reporting on basic weather data

S4.2.1 153 By combining police reports and crowdsourced data, researchers were able to identify the 5 percent of roads where half of the crashes occur in Nairobi

5.1 169 The global fiber-optic cable submarine network reaches all corners of the world, but data infrastructure is unevenly developed 7.1 241 Uptake of regulatory models to

cross-border data flows

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Tables

1.1 28 Examples of data types based on original intent and collection methods

2.1 63 Assessment of the openness of data, by country income group

2.2 64 Data dissemination practices and openness, by country income group 4.1 142 Selected research gaps to be

addressed to advance the use of private intent data for development 5.1 177 Recommendations for data

infrastructure improvements sequenced according to a maturity model

6.1 207 Certain elements of the regulatory framework are much better developed than others, but performance is generally low

6.2 209 Recommendations organized according to a maturity model based on data safeguards and enablers 7.1 241 Policy bases for regulating

cross-border personal data 7.2 244 Key provisions on digital trade in

recent trade agreements

8.1 268 Data management decisions along the data life cycle

8.2 272 Candidate institutions and actors to perform or inform data governance functions

8.3 278 Snapshot of common data intermediary structures

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Data governance is the subject of intense debate in advanced economies and increasingly among large emerging markets. And yet many complex policy questions remain unan- swered. In response, World Development Report 2021: Data for Better Lives surveys the emerging landscape and provides policy makers with a framework for thinking through the issues, opportunities, and trade-offs. One thing is clear: the perspective of lower-income countries has so far been largely absent from these global debates and urgently needs to be heard.

Data are a double-edged sword. On the one hand, they offer tremendous potential to create value by improving programs and policies, driving economies, and empowering citizens. On the other hand, data accumulation can lead to a concentration of economic and political power, rais- ing the possibility that data may be misused in ways that harm citizens. Data are a resource that can be used and reused repeatedly to create more and more value, but there is a problem—the more data are reused, the higher is the risk of abuse.

It is hard to imagine a more dramatic example of these opportunities and tensions than the COVID-19 pandemic. Countries around the world have moved swiftly to repurpose mobile phone records to monitor the spread of the virus. But at the same time they have struggled to balance this benefit against privacy concerns and the risk of misuse.

Beyond pandemic times, the statistical capacity to produce and effectively use core economic and social data is limited. Many poor countries are unable to accurately track public finances, report on external debt, or monitor their development goals. Without such data, the ability to hold governments accountable and track progress withers.

Data governance arrangements to facilitate greater use of data while safeguarding against misuse remain in their infancy. The legal and regulatory frameworks for data are inadequate in lower-income countries, which all too often have gaps in critical safeguards as well as shortages of data-sharing measures. There, the data systems and infrastructure that enable interoperability and allow data to flow to more users are incomplete; less than 20 percent of low- and middle- income countries have modern data infrastructure such as colocation data centers and direct access to cloud computing facilities. Even where nascent data systems and governance frameworks exist, a lack of institutions with the requisite administrative capacity, decision-making autonomy, and financial resources holds back their effective implementation and enforcement.

To address these concerns, World Development Report 2021 calls for a new social contract for data—one that enables the use and reuse of data to create economic and social value, promotes equitable opportunities to benefit from data, and fosters citizens’ trust that they will not be harmed by misuse of the data they provide. However, in seeking such a social contract, lower- income countries are too often disadvantaged because they lack the infrastructure and skills to capture data and turn them into value; the scale and agency to participate equitably in global data markets and their governance; and the institutional and regulatory frameworks to create trust in data systems.

Forging a new social contract for data is a pressing domestic policy priority that will require strengthening national data systems and engaging all stakeholders at the national level. Because of the global scale of data, some of the most challenging aspects of the social contract also call for closer international cooperation to harmonize regulations and coordinate policies—bilaterally,

Foreword

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regionally, and globally. Critical areas for international engagement include reform of international taxation rights for data-driven businesses, World Trade Organization arrangements for trade in data-enabled services, regional collaboration on the development of data infrastructure, international harmonization of technical standards to support interoperability, and bilateral collaboration on law enforcement and antitrust regulation.

The World Bank stands ready to support its client countries on this important and challeng- ing agenda. The findings of this World Development Report will shape support for client countries by identifying where public and private sector investments are the most critical, defining a rich program for policy reform and technical assistance, and highlighting areas in which global initiatives can help to convene and facilitate cross-border cooperation.

Realizing the full value of data will depend on a substantial commitment and effort, and it will be difficult. But the cost of failure is a world of missed opportunities and greater inequities.

David R. Malpass President

The World Bank Group

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This year’s World Development Report (WDR) was prepared by a team led by directors Robert Cull, Vivien Foster, and Dean Jolliffe. Malarvizhi Veerappan served as report manager and as a mem- ber of the Report’s leadership. The core team was composed of Jaffar Al-Rikabi, Adele Moukheibir Barzelay, Miriam Bruhn, Rong Chen, Niccolò Comini, Craig Hammer, Talip Kilic, Jan Loeprick, Daniel G. Mahler, Michael Minges, Martin Molinuevo, Nancy Morrison, David Newhouse, Sara Nyman, Vincent Francis Ricciardi III, David Satola, Dorothe Singer, Philip Wollburg, and Bilal Zia, together with research analysts Kenneth Zaul Moreno Sermeno, Nikkie Pacheco, and Eliza- beth Salazar. Selome Missael Paulos provided the team with administrative support.

Davida Louise Connon, Hai-Anh H. Dang, Cem Dener, Samuel Paul Fraiberger, Lucas Kitzmüller, Aspasea Mckenna, and David Medine were members of the extended team. Rory Macmillan and Zia Mehrabi provided input as expert consultants. The Report was sponsored by the World Bank’s Development Economics Vice Presidency and was prepared in close partnership with the Infrastructure Vice Presidency. Overall guidance was provided by Carmen M. Reinhart, Chief Economist, and Aart Kraay, Deputy Chief Economist. The team is especially grateful for the support and guidance provided by Makhtar Diop, who was at that time Vice President, Infrastructure, and Haishan Fu, Director, Data Group. The team is also appreciative of the comments and suggestions from Mari E. Pangestu, Managing Director, Development Policy and Partnerships. In the early months of the Report’s preparation, Pinelopi Goldberg, then Chief Economist, provided guidance as well.

The team received suggestions from an advisory panel of high-level government officials, representatives of national statistical agencies and competition authorities, and private sector leaders: Ola Awad (President, Palestinian Central Bureau of Statistics), Dr. Long Chen (Director, Luohan Academy, representing Alibaba Group), Kersti Kaljulaid (President, Republic of Estonia), Francis W. Kariuki (Director-General, Competition Authority of Kenya), Zia Khan (Senior Vice President, Innovation, The Rockefeller Foundation), Ming Maa (President, Grab), Joyce Murray (Minister, Digital Government, Canada), Nandan Nilekani (Cofounder, Infosys, and architect of India’s Data Empowerment architecture), Regina Opondo (Community Director, Kounkuey Design Initiative), Haleema Saeed (Director General, International Relations, Palestinian Central Bureau of Statistics), Kecuk Suhariyanto (Chief Statistician, BPS Statistics Indo- nesia), David Tudor (Group General Counsel, Prosus Group), Rodger Voorhies (President, Global Growth and Opportunity Division, Bill & Melinda Gates Foundation), Sheila Warren (Head, Blockchain and Data Policy, World Economic Forum), and Biratu Yigezu (Director, CSA Ethiopia). The team also received guidance from a technical board of leading academics:

Emmanuelle Auriol (Research Faculty, University of Toulouse), Marshall Burke (Associate Professor, Stanford University), Luciano Floridi (Faculty, University of Oxford), Jan Kramer (Faculty and Chair, Internet and Telecommunications Business, University of Passau), Jacques Kremer (President, WorldWide Advisors, Inc.), Bruno Liebhaberg (Director General, Centre on Regulation in Europe), Fernando Perini (Senior Program Specialist, International Develop- ment Research Centre), John Pullinger (President, International Association for Official Statistics), Anna Scherbina (Associate Professor, Brandeis University), and Tommaso Valetti (Faculty, Imperial College London). The team valued their advice and found it very useful.

Acknowledgments

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Finally, Shaida Badiee, Oliver Chinganya, Johannes Jutting, Stephen MacFeely, Angela Me, and Claire Melamed provided specialized reviews of chapter 9. However, the views expressed in the Report do not necessarily reflect those of these advisers and reviewers.

The team would also like to thank the following Bank staff, who were members of the

“BrainsTrust,” for their guidance during preparation of the Report: Luis Alberto Andres, João Pedro Azevedo, Andrea Barone, Kathleen Beegle, Tania Begazo, Jerome Bezzina, Calogero Carletto, Andrew L. Dabalen, Vyjayanti Desai, Marianne Fay, Michael Ferrantino, Marelize Gorgens, Mary Hallward-Driemeier, Kimberly D. Johns, Tim Kelly, Saki Kumagai, Daniel Leder- man, William F. Maloney, Fredesvinda F. Montes Herraiz, James Neumann, Umar Serajuddin, Sharada Srinivasan, Davide Strusani, and Paolo Verme. Background and related research, along with dissemination, are being generously supported by the KDI School of Public Policy and Management (KDIS) Partnership Trust Fund, World Bank’s Knowledge for Change Program (KCP, a multidonor trust fund), and the United States Agency for International Development.

The team drew on the analysis, research, and literature reviews of researchers and specialists from across the world. In addition, the team would like to thank the following for feedback and helpful discussions: Susan Ariel Aaronson, Ali Abbas, Karina Acosta, Sonia Ahmand, Sabina Alkire, Noam Angrist, Belinda Archibong, Kaushik Basu, Vitoria Beard, Theresa Beltramo, Willem Buiter, Tsenguunjav Byambasuren, Anupam Chander, Anindya Chatterjee, Nancy Chau, Katie Clancy, Julie Crowley, Shanta Devarajan, Gary Fields, Avi Goldfarb, Zihan Hu, Yingyi Jin, Ravi Kanbur, Carlos Lopez, Bentley MacLeod, Chelsea Madryga, Jose Antonio Ocampo, Kevin O’Neil, Ariel Ortiz-Bobea, Brian Park, Michael Pisa, Maria Poli, Cristian Pop-Eleches, Christian Reimsbach Kounatze, Elettra Ronchi, Benjamin David Roseth, Phet Sayo, Harman Sing Dhodi, Jenna Slotin, Michael Stanger, Joseph Stiglitz, Aberash Tariku, Jim Tebrake, Jeni Tennison, Anh Phuock Thien Nguyen, Kathryn Toure, Miguel Urquiola, Eric Verhoogen, Stefaan G. Verhulst, Sonali Vyas, and Yue Wang.

The following World Bank colleagues provided insightful comments, feedback, collaboration, and support: Rabah Arezki, Audrey Ariss, Angela Armstrong, Aziz Atamanov, Natalia Baal, Prospere R. Backiny-Yetna, Kathleen Beegle, Abdoullahi Beidou, Moussa Blimpo, Hana Brixi, Niklas Buehren, Greta L. Bull, Maurizio Bussolo, Cesar Calderon, Yu Cao, Greg Chen, Louise Cord, Paul Andres Corral Rodas, Jose Cuesta, Conrad Daly, Richard Damania, Olivia D’Aoust, Francesca Daverio, Zelalem Yilma Debebe, Asli Demirgüç-Kunt, Francesca de Nicola, Tami Ann Dokken, Mark Dutz, Alison Evans, Pablo Fajnzylber, Deon P. Filmer, Juliane Fries, Isis Gaddis, Emilia Galiano, Roberta V. Gatti, Tina George, Alejandro Medina Giopp, Chorching Goh, Lesly Goh, Markus Goldstein, Tania Gomez, Aparajita Goyal, Caren Grown, Boutheina Guermazi, Afef Haddad, Daniel Halim, Stephane Hallegatte, Nagaraja Harshadeep, Kristen Himelein, Johannes G. Hoogeveen, Chyi-Yun Huang, Elisabeth Huybens, Roumeen Islam, Ergys Islamaj, Ann-Sofie Jespersen, Anna Kalashyan, Woubet Kassa, Faruk Khan, Young Eun Kim, Soo Min Ko, Florence Kondylis, Ayhan Kose, Holly Krambeck, Megumi Kubota, Christoph Lakner, Somik Lall, Adriana Legovini, Norman Loayza, Nancy Lozano Gracia, Morgan Sofia Lucey, Cathrine Machingauta, Andrew D. Mason, Aaditya Mattoo, Anna Metz, Frederic Meunier, Sveta Milusheva, Miriam Muller, Mamta Murthi, James Neumann, Rochelle Glenene O’Hagan, Sandie Okoro, Madalina Papahagi, Utz Johann Pape, Elizaveta Perova, Tobias Pfutze, Martin Raiser, Laura Ralston, Martin Rama, Pooja Rao, Vijayendra Rao, Sheila Reszapi, Mark Roberts, Denis Robitaille, Carlos Rodriguez-Castelan, Dan Oliver Rogger, Clelia Rontoyanni, Rosemary Rop, Karla Viviana Saavedra Betancourt, Arisha Salman, Tara Sarma, Marc Tobias Schiffbauer, Ethel Sennhauser, Gabriel Sensenbrenner, Fatima Shah, Parmesh Shah, Nurlina Shaharuddin, Siddharth Sharma, Brian William Stacy, Clara Stinshoff, Prachi Tadsare, Daria Taglioni, Jomo Tariku, Jeff Thindwa, Hans Timmer, Margaret Triyana, Tea Trumbic, Vladimir Tsirkunov, Andrew Whitby, Mark Williams, Quentin Wodon, Keong Min Yoon, and Albert G. Zeufack.

Nancy Morrison provided developmental guidance in drafting the Report, which was edited by Sabra Ledent and proofread by Gwenda Larsen and Catherine Farley. Robert Zim- mermann verified the Report’s extensive citations. Dania Kibbi, Base Three Studio, was the principal graphic designer. Special thanks go to Stephen Pazdan, who coordinated and oversaw

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production of the Report; Mark McClure, who provided assistance; and the World Bank’s Formal Publishing Program. The team would also like to thank Mary C. Fisk, who facilitated multiple translations of the overview and main messages; Patricia Katayama, who oversaw the overall publication process; and Deb Barker and Yaneisy Martinez, who managed the printing and electronic conversions of the Report and its many ancillary products. Naureen Aziz, Mark Felsen- thal, Chisako Fukuda, David Mariano, and Mikael Reventar developed the communications and engagement strategy. Monique Pelloux Patron provided the team with resource management support. The team would also like to thank Maria Alyanak, Marcelo Buitron, Gabriela Calderon Motta, Maria del Camino Hurtado, and Alejandra Ramon for their help with coordination.

Beyond Words studio designed and developed the WDR 2021 website (http://wdr2021.world bank.org) and data stories. The team comprised Kate Ashton, Rebecca Conroy, Jamie Gilman, Chris Hankins, Ceri Jones, Becca Muir, Richard Pullinger, Duncan Swain, and Lucy Swan. The illustrations for the website were created by Elisabetta Calabritto. Maarten Lambrechts and Adrianus Willem Tulp developed the website’s data stories. Emmanuel Cosmas Maliganya, Vidhya Nagarajan, Balaji Natarajan, Somu Sinthamani, Anushka Thewarapperuma, and Roula Yazigi contributed to website development and dissemination.

This Report draws on background papers prepared by Meaza Abraham, Rodrigo Barajas, Noelia Carreras, Anupam Chander, Sandeep Chandy, Yuan Fang, Martina Francesca Ferracane, Angelina Fisher (New York University), Dayoung Park, Sharada Srinivasan, Clara Stinshoff, Thomas Streinz (New York University), Erik van der Marel, Dereje Wolde, Isabel Yu, and the WDR team. Federico Cardenas Chacon, Nicolas Conserva, Lillyana Sophia Daza Jaller, Paris Gkartzonikasm, New Doe Kaledzi, Olga Kuzmina, Aliaksandra Tyhrytskaya, and Yasmin Zand provided support for the data collection and research required for the Global Data Regulation Survey prepared for this Report.

Contributors to the special-feature spotlights in the Report are Diana Jimena Arango, Anna-Maria Bogdanova, Martin Brocklehurst, Libby Hepburn, Stephen MacFeely, Angela Me, David Rogers, Sven Schade, Lea Shanley, Vladimir Tsirkunov, and Mariana Varese. The team would also like to thank the World Bank colleagues who helped organize and facilitate consultations and advised on translations: Jaffar Al-Rikabi, Adele Moukheibir Barzelay, Rong Chen, Candyce Da Cruz Rocha, Nicole El Hajj, Vivien Foster, and Jevgenijs Steinbuks.

The WDR team consulted policy makers, international organizations, civil society organizations, private sector companies, development partners, academics, research institutions, as well as the offices of the World Bank’s Executive Directors and Bank colleagues. This year’s World Development Report faced the additional challenge of the COVID-19 pandemic, which made it impossible to conduct the usual face-to-face consultation meetings. Nonetheless, the team was able to turn this into an advantage because virtual consultation events enabled much wider par- ticipation by hundreds of stakeholders. Due to travel restrictions, the team conducted consultations using a digital format and partner networks, thereby allowing more people with diverse backgrounds to participate. Some of the events focused on regional and targeted stakeholder consultations in multiple languages, allowing hard-to-reach organizations to join the discus- sion. Interactions with core contributing units to the World Development Report as part of ongo- ing debates in certain areas such as taxes leveraged wider consultations taking place on these related issues. Team members also drew heavily on their own experiences and interactions with the many data professionals, statisticians, data scientists, civil society organizations, and policy makers working in often difficult conditions to use data to achieve development outcomes.

The consultations were launched in October 2019 with a high-level roundtable—a side event of the World Bank’s annual meetings—and continued until October 2020. The team also conducted a series of bilateral consultations from April through June 2020 with the national statistical offices of Canada, Ethiopia, India, Indonesia, Mexico, the United Kingdom, and West Bank and Gaza. The team thanks the organizers of the many events that brought together a wide variety of stakeholders, including government officials, civil society organizations, academic institutions, the private sector, and international organizations. The organizers were Germany’s Federal Ministry for Economic Cooperation and Development

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(BMZ) and Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); Canada’s Inter- national Development Research Centre (IDRC), which organized consultations across Africa, Asia, and Latin America and the Caribbean in French, Spanish, and English; the Global Part- nership for Sustainable Development Data (GPSDD); the GW Elliott School of International Affairs; Columbia and Cornell Universities; the Mastercard Advocacy Center of Excellence;

A. T. Kearney’s Global Business Policy Council; the Fletcher School of Law and Diplomacy’s Institute for Business in the Global Context at Tufts University; Committee for the Coordina- tion of Statistical Activities (CCSA); United Nations World Data Forum (UNWDF); Organisation for Economic Co-operation and Development’s Development Assistance Committee (DAC);

Global Data Barometer; and the Open Gov Hub.

The team organized and held a dedicated consultation event for civil society members and several bilateral consultations with technology firms, platform-based businesses, internet exchange points, payment industries, and cybersecurity firms in the private sector. They included Alibaba, Amazon, CADE (Brazilian competition authority), De Novo, Facebook, Google, LinkedIn, Lori Systems (Kenya), Mastercard, Power2SME (India), and UA-IX (Ukranian Inter- net Exchange Point). The team also reached out for guidance on specific topics from experts based in institutions that included Aelex Legal (law firm, Abuja, Nigeria), Atlantic Council (think tank), DataPrivacy.Com.Br (São Paulo, Brazil), Georgetown University, Hamu and Com- pany (law firm, Lagos, Nigeria), Hogan Lovells (privacy and cybersecurity law firm), Hunton Andrews Kurth (global privacy and cybersecurity law firm), Interswitch (Lagos, Nigeria), New York University, Organisation for Economic Co-operation and Development, Oxford Internet Institute, Rockefeller Foundation, the United Nations Conference on Trade and Development (UNCTAD), the University of Southern California, and WilmerHale (data and cybersecurity law firm). Detailed information about all consultations and contributors can be found at https://

www.worldbank.org/en/publication/wdr2021/consultations.

The team is grateful as well to the many World Bank colleagues who provided written comments during the formal Bank-wide review process. Those comments proved to be invaluable at a crucial stage in the Report’s production.

The team apologizes to any individuals or organizations inadvertently omitted from this list and expresses its gratitude to all who contributed to this Report, including those whose names may not appear here. The team members would also like to thank their families for their support throughout the preparation of this Report.

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A4AI Alliance for Affordable Internet AI artificial intelligence

AIS automatic identification system APEC Asia-Pacific Economic Cooperation API application programming interface ARPU average revenue per user

ASEAN Association of Southeast Asian Nations ATAF African Tax Administration Forum ATI access to information

BEPS OECD/G20 Inclusive Framework on Base Erosion and Profit Shifting BRICS Brazil, Russian Federation, India, China, South Africa

B2B business to business B2C business to consumer B2G business to government CDR call detail record

CPTPP Comprehensive and Progressive Agreement for Trans-Pacific Partnership CSIRT Computer Security Incident Response Team

CSO civil society organization

DEPA Digital Economy Partnership Agreement DLT distributed ledger technology

DPA data protection authority DTA Digital Trade Agreement

EITI Extractive Industries Transparency Initiative

EU European Union

FAIR findability, accessibility, interoperability, and reuse FAO Food and Agriculture Organization

FCS fragile and conflict-affected situations FRAND fair, reasonable, and non-discriminatory GATS General Agreement on Trade in Services GDP gross domestic product

GDPR General Data Protection Regulation (EU)

GHG greenhouse gas

GIS geographic information system GNI gross national income

GPS global positioning system G2B government to business G2C government to consumer G2G government to government HAPS high-altitude platform station

ICT information and communication technology ILO International Labour Organization

IMF International Monetary Fund

Abbreviations

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IoT Internet of Things IP Internet Protocol

IPRs intellectual property rights IRB Institutional Review Board

ISO International Organization for Standardization ISP internet service provider

IT information technology

ITU International Telecommunication Union (UN) IUCN International Union for Conservation of Nature IXP internet exchange point

KIXP Kenya Internet Exchange Point LEO low Earth orbiting

LSMS Living Standards Measurement Study M&E monitoring and evaluation

ML machine learning

MLAT mutual legal assistance treaty MNE multinational enterprise MNO mobile network operator MPA Marine Protected Area

MSMEs micro, small, and medium enterprises NGO nongovernmental organization NIC news flow indices of corruption NPDR Non-Personal Data Regulation (EU)

NSDS National Strategies for the Development of Statistics NSO national statistical office

ODbL Open Database License

OECD Organisation for Economic Co-operation and Development OGP Open Government Partnership

ONS Office for National Statistics (UK)

PARIS21 Partnership in Statistics for Development in the 21st Century PIMS personal information management system

PPP public-private partnership PTA preferential trade agreement

RADD Radar Alerts for Detecting Deforestation SCC standard contractual clause

SDGs Sustainable Development Goals

SINTyS National Tax and Social Identification System (Argentina) SMEs small and medium enterprises

SPI Statistical Performance Indicators SSO standard setting organization TFP total factor productivity TVWS TV white space

UN United Nations

UNCITRAL United Nations Commission on International Trade Law UNDP United Nations Development Programme

UNEP United Nations Environment Programme UNICEF United Nations Children’s Fund

USITC United States International Trade Commission USMCA United States–Mexico–Canada Agreement USSD unstructured supplementary service data VAT value added tax

WFP World Food Programme

WHO World Health Organization

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OVERVIEW

You can have data without

information, but you cannot have information without data.

—Daniel Keys Moran, computer programmer and science fiction author

“

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D

ata, which are growing at an unprecedented rate, are becoming an integral part of the daily lives of most people everywhere. But how does that matter for the more than 700 million people living in extreme poverty? Is the explosion in the new types and uses of data improving their lives? Or will poor people and poor countries be left behind, creating a widening gap between those who reap the benefits of this new data-driven world and those who do not?

The innovations resulting from the creative new uses of data could prove to be one of the most life-changing events of this era for everyone. Like many general-purpose technologies such as the steam engine and electricity, the transformations emerging from the data revolution could touch all aspects of societies and economies. But such sweeping changes are not automatic. The productivity value of the steam engine and electricity was realized decades after they were first introduced. The delay occurred not because people did not recognize the importance of these innovations—sooner or later everyone did—

but because the new manufacturing systems needed for these innovations to realize their economic potential could not take shape overnight. Just as electricity itself did not result in economic development, data alone will not improve well-being. Data can improve social and economic outcomes, but only if they are used systematically in ways that create information that generates insights that improve lives.

This Report aims to answer two fundamental questions. First, how can data better advance development objectives? Second, what kind of data governance arrangements are needed to support the generation and use of data in a safe, ethical, and secure way while also delivering value equitably?

One important message of this Report is that simply gathering more data is not the answer. Sig- nificant data shortfalls, particularly in poor countries, do exist, but the aim of this Report is to shift the focus toward using data more effectively to improve development outcomes, particularly for poor people in poor countries.

Advancing development objectives through data

Part I of this Report develops a conceptual framework that links data to development through three institutional pathways (figure O.1). The middle pathway is the use of data by governments and international organizations to support evidence-based policy making and improved service delivery. The top pathway is the use of data by civil society to monitor the effects of government policies and by individuals to enable them to monitor and access public and commercial services. The bottom pathway is the use of data by private firms in the production process—

use that fuels their own growth as well as wider economic growth. One implication of the conceptual framework is that data alone cannot solve development problems: people (in society, governments, and firms) are the central actors transforming data into useful information that can improve livelihoods and lives.¹ Alongside capital, land, and labor, data are also an input to the development objectives that emerge along all three pathways. But, unlike capital, land, and labor, using data once does not diminish its value. Data that were initially collected with one intention can be reused for a completely different purpose (chapter 1).

O VE RVIEW

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Disseminating, exchanging, and

sharing data to enhance data reuse and repurposing

Because the potential of data to serve a productive use is essentially limitless, enabling the reuse and repurposing of data is critical if data are to lead to better lives. It is thus a central aspect of the conceptual framework. Figure O.1 uses two-way arrows to depict these flows. The two-way arrow between the private sector and government/international organizations indicates the reuse and repurposing of data originally collected for commercial purposes for public policy, and vice versa. Similarly, the two-way arrow between individuals/civil society/academia and government/international organizations indicates data being exchanged and reused by those parties. The final two-way arrows reflect the use of private sector data and data-driven applications by individuals/civil society/academia and the use of data and analysis generated by individuals/civil society/academia by firms. In practice, however, those holding data may be unwilling to exchange data. They may have concerns about data protection and security or the need to capture returns on investments in collecting data.

Or they may hope to gain market power from accu- mulating data to capture economies of scale or obtain any other kind of political or competitive advantage from hoarding them.

The phrase “sharing and reuse” is shorthand used in this Report for all the types of transactions and exchanges of data that permit reuse, from government open data initiatives for sharing data to market-based transactions for data involving private firms. In theory, defining clear economic property rights over data should enable data to be traded widely on markets.

But in practice, the extent of the data trade (beyond the market for advertising) has been limited by competing claims on ownership, tensions between the wide dissemination of data and incentives to accumulate more data for private commercial gain, and difficulties in assessing the quality and accuracy of data.

Each of the three pathways illustrated in figure O.1 shows how data can improve lives, but those same pathways create openings for data to be used in ways that harm people. Through the government pathway, data can be abused for political ends, such as politi- cally motivated surveillance or discrimination along lines of ethnicity, religion, race, gender, disability Figure O.1 How data can support development: A theory of change

Source: WDR 2021 team.

Note: Positive impacts are shown in green; negative impacts are shown in red.

Greater accountability Criminal activity, dark net

Development Political surveillance

Increased business opportunities Data

production and collection

Greater transparency

More data on individuals

Production process in firms

Reuse

Reuse Individuals Civil society

Academia Data analytics and

processing

Government International organizations

Private sector

Better policy making and service delivery

Market concentration Widening inequality Discrimination

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status, or sexual orientation. In the pathway running through individuals, there is the potential for cyber- criminals to inflict considerable harm by stealing and manipulating sensitive information. The “dark net” is a vast parallel network of hidden websites that provides an underground digital platform for a wide array of criminal activities, facilitating illegal trade in drugs, counterfeit currency, stolen goods, credit card numbers, forged papers, firearms, and human organs.

Similarly, through the private sector pathway, examples of harmful use include, among other things, the exploitation of information about consumer prefer- ences and behavior to engage in aggressive or manip- ulative marketing techniques based on microtarget- ing of persuasive messages or to apply algorithms that facilitate collusion among market players.² Unlocking data for the public good and safeguarding against misuses:

Some COVID-19 examples

Many countries have used data to control the COVID-19 pandemic. This use includes tracking peo ple’s locations to better understand mobility pat- terns during lockdowns or to aid in disease contact tracing. Using call detail records (CDRs) from March through May 2020 aggregated to mask individual- level data, policy makers in The Gambia were able to review maps showing the movement of people across administrative boundaries (map O.1). These maps helped them understand the extent to which lockdowns were succeeding in reducing movement

and allowed them to identify the factors linked to lockdown compliance and noncompliance and plan accordingly. Meanwhile, the government of Israel approved emergency regulations in March 2020 to allow the individual-level data collected from cellphones to be used to track people and then, through contact tracing, to curtail the spread of COVID-19.

CDRs were not created to aid public policy making or to allow the government to track the movements of individuals, but they are an example of data being reused and repurposed (flowing in the vertical chan- nels in figure O.1 ). In Israel, these data were being collected before the pandemic, but they could be accessed only for national security purposes.³

These early efforts at repurposing CDRs to track infected individuals seemed to have a positive effect.

In The Gambia, the maps helped reveal that the lockdown disproportionally affected poorer districts, indicating a need for relief and recovery efforts to tar- get these areas. In Israel, analysis of the cellular data suggested their use led to identification of more than one-third of all of the country’s coronavirus cases in the early weeks of the pandemic (more than 5,500 of the 16,200 people who had contracted the disease), possibly contributing to Israel’s exceptionally low ini- tial rates of coronavirus infections and deaths.

This new use of CDR data to track large parts of the population of Israel sparked debate and pushback over concerns about the potential misuse of the data by government. In Israel, many lawmakers raised privacy concerns, and the Supreme Court eventually Map O.1 Use of aggregated cellphone records to track mobility week by week during COVID-19 lockdowns in The Gambia, March–May 2020

Source: Knippenberg and Meyer 2020. Data at http://bit.do/WDR2021-Map-O_1.

Note: Blue shades indicate outflow of people; green shades indicate inflow of people. A nationwide lockdown was imposed on March 22, 2020. Data were gathered using call detail records.

Brikama

Kanifing Mansa Konko

Kerewan Georgetown

Basse Santa Su

Brikama

BANJUL

International boundaries District boundaries

IBRD 45xxx | MARCH 2021

Week 3: March 15–21

Week 6: April 5–11

Week 12: May 17–23

Week 4: March 22–28

Week 7: April 12–18

Week 10: May 3–9

Week 5: March 29–April 4

Week 8: April 19–25

Week 11: May 10–16

Week 13: May 24–30 Week 9: April 26–May 2

% change in population flows 0 4 8 12 16 20 40 60+

-4 -8 -12 -16 -20 -40 -60

National capital District capitals

IBRD GAM45640 | MARCH 2021

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halted the program. The Court ruled in late April 2020 that the government must legislate the use of cellphone tracking and that “a suitable alternative, com- patible with the principles of privacy, must be found.”⁴ Many of the themes of this Report are illustrated in this example. The sharing and reuse of private sector CDR data with public authorities created social value by supporting the control of COVID-19 infections, thereby saving lives. At the same time, this transfer of data raised fundamental concerns about trust, with citizens concerned that their CDR data could then be repurposed by government officials for other unin- tended and potentially harmful purposes beyond pub- lic health. Issues of equity were also at stake. Whereas in a high-income country like Israel smartphone penetration was 93 percent, in a low-income country like The Gambia smartphone penetration was only 75 percent. In each case, that minority of the population lacking a smartphone was unable to generate CDR data and would not necessarily benefit directly from the public health protection afforded by contact tracing.

These examples also illustrate a key conundrum.

The potential benefits that people realize in the form of improved policies and service delivery may increase rapidly as more data, especially personal data, are shared and reused—but the risks of data being misused increase as well. These potential benefits depend on data being disseminated or exchanged between parties. But parties must trust the systems,

regulations, and institutions that underlie the security of such exchanges to willingly engage in them.

How can people trust that their data will be protected and that they will share in the value that data can produce? The mounting nature of such concerns suggests the need for a new social contract around data—that is, an agreement among all participants in the process of creating, reusing, and sharing data that fosters trust that they will not be harmed from exchanging data and that part of the value created by data will accrue equitably (figure O.2). The idea that societies engage in these sort of agreements, or social contracts, has existed for centuries, often linked to the writing of philosophers such as Thomas Hobbes, John Locke, and Jean-Jacques Rousseau.

Legal systems, and governance more generally, can be viewed as instruments for establishing, facilitating, and enforcing social contracts. Persuading parties to abide by the rules of a social contract is not an easy task and will hinge on ensuring that the benefits from using data are shared in an equitable way—that is, everyone has something to gain. In this process, lower-income countries are too often disadvantaged, lacking, as they often do, the infrastructure and skills to capture data and turn them into value; the institutional and regulatory frameworks to create trust in data systems; and the scale and agency to participate equitably in global data markets and their governance.

With data reshaping our lives, our societies, and the world more generally, social contracts for data are needed both nationally and internationally, especially because of the cross-border nature of data transactions and flows. Spotlight 8.1 extends this idea of a social contract to the international realm, calling for a global consensus to ensure that data are safeguarded as a global public good and as a resource to achieve equitable and sustainable development.

The untapped potential of data; the evolving legal, regulatory, and governance frameworks for data generation, use, and reuse; the importance of country context (history, culture, governance, and political economy) in shaping appropriate frameworks; the role of technical capabilities for making the most of data safely; and the need for trust and more equitable sharing of the value of data—all these are the themes at the core of this World Development Report.

Part I of the Report begins by describing in more detail the potential development impact of data col- lected for public purposes—public intent data (chapter 2); data collected by the private sector as part of rou- tine business processes—private intent data (chapter 3);

and the synergies that arise from the joint use of different types of data (chapter 4). This distinction between public intent and private intent data is used

Source: WDR 2021 team.

Figure O.2 A social contract for data founded on value, trust, and equity

The full value of data materializes when systems enable

the use and reuse of data for different purposes.

SOCIAL THE CONTRACT

VALUE

A trust environment is created when the rights and interests that

all stakeholders have in data are safeguarded.

TRUST

All share equitably in the benefits of data when investments and

regulations create a level playing field.

155 Part II: Aligning data governance with the social contract

1 Overview

21 Part I: Advancing development objectives through data

Contents

155 Part II: Aligning data governance with the social contract

301 Part III: Moving toward an integrated national data system

Boxes

Figures

Maps

Tables

Foreword

Acknowledgments

Abbreviations

OVERVIEW

You can have data without

information, but you cannot have information without data.

“

D

Advancing development objectives through data

O VE RVIEW

SOCIAL THE CONTRACT

VALUE

TRUST

EQUITY