Data has emerged as a powerful tool for driving sustainable development and achieving the 2030 Agenda. Recent years have seen a marked increase in advocacy and action
around data-driven approaches for advancing the Sustainable Development Goals, and in November 2022, Prime Minister Modi announced that the principle of data for development (D4D) would be central to India’s G20 presidency. The data landscape across the G20, however, remains highly uneven, with some countries being able to effectively harness D4D, while others experience significant challenges in doing so. This article explores the implications of bridging data gaps and divides between the Global North and the Global South, as well as within countries, outlining strategic actions that G20 member states could jointly undertake to promote D4D.
The G20’s data landscape
The data landscape within the G20 presents a complex picture, with significant variations
in the quality and availability of and access to data. While some G20 countries have robust data ecosystems and well-established statistical systems, others lag behind with respect to their data collection and analysis capacities. This results in a wide range of gaps
, including the absence of disaggregated development data, and the invisibility of data pertaining to marginalised communities, and could also create skewed representations of on-ground challenges that hinder the formulation of responsive policies and interventions. The G20 Data Gaps Initiative Phase 3 (DGI-3), for instance, has identified
four broad areas in which the G20 should prioritise the closure of information gaps: climate change; household distributional information; fintech and financial inclusion; and data from private sources, as well as administrative data.
Table 1: Statistical products targeted under the G20 DGI-3
Source: G20 Data Gaps Initiative 3: Workplan, March 2023
|Climate Change-Related Data Gaps
|Greenhouse gas (GHG) emission accounts and national carbon footprints
|Annual air emissions accounts (for GHGs) by industry and estimates of national carbon footprints by demand category
|Annual energy accounts that record the supply and use of energy from natural inputs, energy products, energy residuals and other residual flows
|Carbon footprints of foreign direct investment
|CO2 emissions per unit of output of foreign-controlled multinational enterprises and domestic-controlled enterprises by industry
|Climate finance (green debt and equity securities financing)
|Statistics on green debt securities and listed shares by sector of issuer and holder
|Forward-Looking physical and transition risk indicators
|Forward-looking physical and transition risk indicators related to populations, assets, output/production, firm profitability, and wealth
|Climate-Impacting Government Subsidies
|Annual estimates of government subsidies by type of subsidy
|Climate Change Mitigation and Adaptation Expenditures
|Annual estimates of current and capital expenditures on climate mitigation and adaptation activities by sector
|Household Distributional Information Data Gaps
|Distribution of household income, wealth, consumption and savings
|Annual estimates of household income, consumption, saving and wealth by quintile or decile
|Digitalization and Financial Innovation and Inclusion
|Estimates of fintech credit aggregates and linkages of fintech credit entities with the financial and non-financial sectors
|Estimates of the stock and flow of digital money by type
|Fintech-enabled financial inclusion
|Annual estimates of fintech-enabled financial inclusion and access by type of access and sector
Required investments, resources, and capacities
Strategic investments in data collection, reporting and analysis systems, particularly in countries with limited technical capacity, are a prerequisite for the success of D4D programmes. As such, G20 member states, particularly low- and middle-income countries (LMICs), need to identify areas where additional resources and technical support are required, and how weaknesses in the monitoring and evaluation of D4D initiatives and evidence-based interventions might be addressed. Corrective measures, including the smart allocation of resources to strengthen D4D ecosystems, could significantly improve prospects
for socio-economic growth and betterment. LMICs must also seek to bridge domestic digital divide
s by improving access to data infrastructures. This entails a chain of activities beginning with the enhancement of broadband connectivity, the establishment of data centres, and the creation of digital platforms, particularly in underserved areas, that could empower communities. LMICs may also need to invest in data literacy and technical skilling programmes to nurture a “data culture” from the ground up while remaining cognisant of the risks of adverse digital incorporation
that could in fact exacerbate existing divides. The sensitisation and training of policymakers is yet another space in which targeted programmes and investments could make an impact.
G20 member states, particularly low- and middle-income countries (LMICs), need to identify areas where additional resources and technical support are required, and how weaknesses in the monitoring and evaluation of D4D initiatives and evidence-based interventions might be addressed.
Strengthening data ecosystems
To bridge the data divides within the G20, and promote equitable access to and use of D4D, member states could undertake the following actions:
- Boosting data collection efforts: G20 countries must support internal capacity development related to data collection, focusing on areas with conspicuous data gaps and marginalised populations. Within their sovereign space, countries can foster partnerships between sub-national governments, civil society, and private sector entities to strengthen and expand data collection networks. There is a particular need to train stakeholders to disaggregate and anonymised the data collected, so that the possible needs of the data subjects can be clearly identified on the one hand, and their identities remain secure and confidential on the other.
- Establishing inter-country data partnerships: Data partnerships need to be established between countries with advanced data capabilities and those that have traditionally experienced D4D-related challenges. New South-South and North-South cooperation models must be devised to exchange knowledge and promote collaboration. Mentorship programmes, technical assistance, and funding support will all prove to be crucial for strengthening D4D capacities.
- Upgrading data infrastructures and embracing emerging and disruptive technologies: Allocating resources to upgrade data infrastructure—including facilities for data storage, processing and analysis—ought to be yet another key focus area for Global South economies. While the G20 accounts for a significant share of global data production, consumption and storage with over 69 percent of the global data servers and cloud centres located in the G20 countries, most of these are presently concentrated in the US , China, Japan, United Kingdom (UK), Germany, and Australia. The use of emerging and disruptive technologies (EDTs) such as Artificial Intelligence (AI) and machine learning could help generate greenfield datasets, and produce new actionable insights by deploying data analytics. To support the application of EDTs, entire innovation ecosystems should be evolved further, including the incubation of startups, the incentivisation of entrepreneurship, and the formation of tech-oriented public-private partnerships.
Using Data to Advance the 2030 Agenda: Recommendations for the G20” by the authors has been published by Think20 India.>
- Creating mechanisms to facilitate data sharing: Establishing mechanisms for sharing data between G20 countries would improve access to D4D. There is a marked need to promote the use of open data, and to build open-access repositories through which development datasets can be made publicly available. Concomitantly, the interoperability of electronic systems must be strengthened so as to ensure the potentially seamless integration and utilisation of data across platforms. National statistical and D4D institutions across the G20 should come together to lead efforts on enhancing data quality, comparability, and standardisation. Finally, and perhaps most importantly, comprehensive data privacy and security frameworks must be put in place to ensure confidentiality and build trust, while also creating the groundwork for harmonized standards, approaches and protocols that allow specific types of development data to be shared across borders.
Anirban Sarma is a Senior Fellow at Observer Research Foundation
Debosmita Sarkar is a Junior Fellow with the Centre for New Economic Diplomacy at the Observer Research Foundation
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