1. World Bank Group, 2018. The State of Social Safety Nets 2018, Table 3.26. Available at: www.openknowledge.worldbank.org/bitstream/handle/10986/29115/9781464812545.pdf?sequence=5&isAllowed=y
2. We define extreme poverty as measured using the 2011 PPP$1.90 extreme poverty line. Purchasing power parity (PPP) prices are the rate at which a country’s currency would have to be converted into that of another country to buy the same amount of goods and services in each country. PPPs are constructed by comparing the cost of a common basket of goods in different countries. Where subsequent figures in the report are in PPP these are denominated as $. Other denominations are referenced with a currency abbreviation, eg US$.
3. Brookings (Kharas H., McArthur J. and Rasmussen K.), 2018. Counting who gets left behind: Current trends and gaps on the Sustainable Development Goals. Available at: www.brookings.edu/blog/future-development/2018/07/13/counting-who-gets-left-behind-current-trends-and-gaps-on-the-sustainable-development-goals
4. The term ‘developing countries’ in this chapter and elsewhere in the report is used to refer to countries in the ‘DAC list of ODA recipients’, available at: www.oecd.org/dac/financing-sustainable-development/development-finance-standards/DAC_List_ODA_Recipients2014to2017_flows_En.pdf
5. SDG target 1.1: “By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a day.” The World Bank has been deemed responsible for tracking this indicator. It has since updated the extreme poverty line to $1.90 a day (2011 PPP). This line was developed by averaging the national poverty lines of several low income countries, adjusted for PPP. The World Bank’s PovcalNet has estimates of the extreme poverty headcounts adjusted by PPP.
6. SDG target 10.1: “By 2030, progressively achieve and sustain income growth of the bottom 40 per cent of the population at a rate higher than the national average.”
7. International Monetary Fund, 2017. World Economic and Financial Surveys. Fiscal Monitor: Tackling Inequality.
8. Poverty is defined and measured in different ways. The World Bank’s definition of extreme poverty is based on the median national poverty lines among a set of low income countries. These poverty lines themselves are based on income or consumption thresholds that were sometimes based on the caloric needs of people. The Multidimensional Poverty Index is weighted based on living conditions, health and education. BRAC’s concept of ‘ultra-poor’ draws on dimensions including access to markets and social stigma. We are most interested in the question: regardless of how poverty is defined, are people seeing improvements?
9. DI calculations based on Ravallion M., Jolliffe D., Margitic J., 2018, Social Protection and Economic Development: Are the Poorest Being Lifted-Up or Left-Behind? NBER Working Paper 24665.
10. Our emphasis.
11. World Bank Group, 2018 (see note 1), Table 3.26.
12. See note 1.
13. See note 1, Figures 3.1 and 3.2.
14. See note 1, Figure 3.3.
15. See note 1.
16. The purpose of ODA as defined by the OECD DAC, which was established in 1960, is to promote the “economic development and welfare” of developing countries.
17. The considerable debate on the extent to which inequality is or is not inimical to growth continues. But the weight of opinion in key global institutions such as the International Monetary Fund and OECD is that “excessive inequality can erode social cohesion, lead to policy polarization and ultimately lower economic growth”. International Monetary Fund, 2017 (see note 7). See also G20 Leaders’ Summit, 2017, Fostering inclusive growth: IMF Staff Paper. 7 and 8 July 2017, Hamburg, Germany, available at: www.imf.org/external/np/g20/pdf/2017/062617.pdf: “High and persistent inequality can have significant negative implications for both longer-term growth and macroeconomic stability”.
18. See note 9.
19. Carr-Hill R., 2013. ‘Missing Millions and measuring Development Progress.’ World Development 46:30–44.
20. Sanchez C. and Munoz-Boudet A.M., 2018. No, 70% of the world’s poor aren’t women but that doesn’t mean poverty isn’t sexist. World Bank blog, 8 March 2018.
21. Somalia Directorate of National Statistics, 2018. Poverty Profile: First Comprehensive Snapshot of Welfare Conditions (5 October 2018), available at: www.dns.org.so
22. The vast majority (98%) of the reduction of global poverty was from China between 1981 and 2005. See Chen S. and Ravallion M., 2008. The developing world is poorer than we thought, but no less successful in the fight against poverty. World Bank. Available at: https://elibrary.worldbank.org/doi/abs/10.1596/1813-9450-4703
23. Development Initiatives, 2013. Investments to End Poverty. Available at: www.devinit.org/post/investments-to-end-poverty/
24. The 2013 projections used a model based on different scenarios with a two-percentage-point margin of error on each side of a baseline consumption projection, in line with differences observed between past forecasts and actual outcomes. The scenarios use different outlooks for inequality based on the shares of national consumption among the poorest 40% of people and the richest 10%. The analysis sees these shares moving up or down by 0.25 percentage points annually. For the forecasts included in Figure 1.4, a more parsimonious model was used. A distribution-neutral growth pattern was assumed and the average growth rates from the IMF World Economic Outlook for the next five years were carried forward with plus or minus two percentage points to provide a range of estimates. The distribution-neutral approach provides lower poverty estimates but much of the differences between the forecasts made in 2013 and those today are due to faster-than-expected poverty reduction in recent years.
25. The progress in South Asia and India should not be taken for granted. The Multidimensional Poverty Index estimates that over half of all children in India are living in multidimensional poverty and there are more destitute people in India than in the whole of sub-Saharan Africa (Oxford Poverty & Human Development Initiative Multidimensional Poverty Index 2017, Briefing paper 47, page 13. Available at: www.ophi.org.uk/wp-content/uploads/B47_Global_MPI_2017.pdf
26. For more detail on the methodologies applied to identify countries at most risk of being left behind and analysis of their characteristics, see Development Initiatives 2018, Countries being left behind: tackling uneven progress to meet the SDGs. www.devinit.org/wp-content/uploads/2018/07/countries-being-left-behind_report.pdf
27. For example, Brookings, 2018. Leave no country behind: ending poverty in the toughest places, working paper. Available at www.brookings.edu/wp-content/uploads/2018/02/leave_no_country_behind_working_paper.pdf; Chandy L., 2017; World Poverty Clock, 2017; Manuel M., Desai H., Samman E. and Evans, M., 2018. Financing the end of extreme poverty. ODI. Available at: www.odi.org/publications/11187-financing-end-extreme-poverty
28. See Development Initiatives, 2018 (note 26) for more detailed assessment of the overlap of countries identified through different methodologies.
29. Alkire S. and Robles G., 2017. Global Multidimensional Poverty Index 2017. Available at: www.ophi.org.uk/wp-content/uploads/B47_Global_MPI_2017.pdf
30. The World Bank’s PovcalNet is the most influential tool for understanding poverty and wealth on a global level. Currently, it does not provide geographically disaggregated data by region. To better understand which regions are at risk of being left behind, we have used subnational region data from the Demographic and Health Surveys (DHS). These include estimates of wealth based on household assets. Following Wagstaff (2004) we have assumed that the percentile rankings of households by wealth index roughly compares with percentile rankings of households by income or consumption. This is a very crude proxy but gives a general sense of who is most likely to be left behind. We first looked at the latest DHS surveys conducted since 2005 (51 countries with household-level data). Two of these, Afghanistan and Cambodia, do not have data in PovcalNet and are excluded. Among the remaining countries, we took the extreme poverty rate (defined as $1.90 per person per capita in 2011 PPP) from PovcalNet at the national level and found the lowest wealth scores that add up to an equivalent percentage in the DHS surveys. We then can disaggregate the DHS surveys by survey region. Among the 51 countries, the latest available poverty rates from 2013 range from 0.2% for Jordan to 77.8% for Madagascar.
31. Brookings (Chandy, L.), 2017. No country left behind: the case for focusing greater attention on the world’s poorest countries uses this methodology at the national level, which we have replicated at subnational level.
32. World Bank Research Digest, Summer 2007, The Urbanization of Global Poverty page 1.http://siteresources.worldbank.org/DEC/Resources/84797-1154354760266/2807421-1183396414833/The_Urbanization_of_Global_Poverty.pdf: 24.6% in 2002 represented an increase over the 18.9% of global poverty attributed to urban areas in 1993.
33. Munoz-Boudet A.M., Buitrago P., Leroy de la Briere B. et al, 2018. Gender Differences in Poverty and Household Composition through the Life-Cycle: A Global Perspective. World Bank Policy Research Working Paper 8360, page 10.
34. Poverty and wealth calculations are typically defined at the household level, masking inequalities that may exist within households. However, the World Bank has shown that gender seems to have different impacts for the likelihood of living in extreme poverty along life cycle lines. See Munoz-Boudet A.M., Buitrago P., Leroy de la Briere B. et al, 2018 (note 33).
35. See, for instance, UN Economic and Social Council, 2017. Report of the United Kingdom of Great Britain and Northern Ireland on ageing-related statistics and age-disaggregated data. Available at: www.un.org/development/desa/ageing/wp-content/uploads/sites/24/2018/03/Report-of-the-United-Kingdom-of-Great-Britain-and-Northern-Ireland-on-ageing-related-statistics-and-age-disaggregated-data.pdf
36. See, for instance, Mitra S., 2017. Disability, Health and Human Development, Palgrave McMillan.
37. Detailed disaggregations of child mortalities by ethnicity and other dimensions can be found at the Save the Children’s Group-based Inequality Database (GRID). Available at: https://campaigns.savethechildren.net/grid
38. See: Munoz-Boudet A.M., Buitrago P., Leroy de la Briere B. et al, 2018 (note 33).
39. Transforming our world: the 2030 Agenda for Sustainable Development. Available at: https://sustainabledevelopment.un.org/post2015/transformingourworld
40. McArthur J.W. and Rasmussen K., 2018. Change of Pace: Accelerations and Advances During the Millennium Development Goal Era. Brookings Global Economy and Development Working Paper 97. Available at SSRN: https://ssrn.com/abstract=2941856.
41. McArthur J.W. and Rasmussen K., 2018 (note 40).
42. McArthur J.W. and Rasmussen K., 2018. (note 40).
43. The Guardian, 2005. ‘Brown calls for African Marshall Plan,’ 3 June 2005. Available at: www.theguardian.com/society/2005/jun/03/internationalaidanddevelopment.hearafrica05
44. IFFIm raises money by issuing bonds on the international capital markets. The financial strength of IFFIm to repay the bonds is based on legally binding agreements with donors for payments into IFFIm. This frontloads the funding but allows payback over 20 years. IFFIm delivers the funding to Gavi, which manages and invests the money.
45. Gavi. International Finance Facility for Immunisation evaluation. Available at: www.gavi.org/results/evaluations/iffim-evaluation
1. Poverty data exists for 124 of the 146 countries that receive ODA. In this group of 124, 35% of gross ODA goes to countries home to 75% of the people living on less than $1.90 per day. Also in this group of 124, 25% of gross ODA goes to countries home to 1% of the people living on less than $1.90 per day.
2. Hynes W. and Scott S, 2013. The Evolution of Official Development Assistance: Achievements, Criticisms and a Way Forward. OECD, Paris. Available at: http://dx.doi.org/10.1787/5k3v1dv3f024-en
3. UN, 1970. International Development Strategy for the Second United Nations Development Decade, 24 October 1970. Available at: www.un-documents.net/a25r2626.htm
4. UN Sustainable Development Knowledge Platform. France Voluntary National Review 2016. Available at: https://sustainabledevelopment.un.org/memberstates/france
5. En Marche, 2017. Le programme d’Emmanuel Macron. Available at: https://en-marche.fr/emmanuel-macron/le-programme
6. Pearson, 1969. Partners in Development: Report of the Commission on International Development.
7. This assumes that all donors that were DAC members in 1970 reached 0.7% by 1980 and donors that joined the DAC after 1970 reached 0.7% 10 years after joining.
8. Development Initiatives (DI), 2017. ODA modernisation: Background paper. Available at: www.devinit.org/wp-content/uploads/2017/09/Backgound-paper_ODA-modernisation.pdf
9. ‘Grant element’ is the standard way of measuring how concessional a loan is. It can be seen as the difference between the cost, in today’s prices, of the future repayments a borrower will have to make on the loan in question and the repayments the borrower would have had to make on a non-concessional loan. It is therefore the amount of money considered to have been ‘given away’ by the donor, hence ‘grant’ element. It is normally shown as a percentage of the value of the loan.
10. For a fuller treatment of this topic see DI, 2018. Accounting for ODA loans – the effect of the new rules. Available at: www.devinit.org/wp-content/uploads/2018/03/Accounting-for-ODA-loans-Feb-2018-briefing.pdf
11. DI, 2017. ODA modernisation – an update following the October 2017 HLM: Briefing paper. Available at: www.devinit.org/wp-content/uploads/2017/11/ODA-modernisation-an-update-following-the-October-2017-HLM.pdf
12. See note 11.
13. OECD, 2017. The ODA Coefficient for UN Peacekeeping Operations Explained. Available at: www.oecd.org/dac/financing-sustainable-development/development-finance-standards/ODA-Coefficient-for-UN-Peacekeeping-Operations.pdf
14. For 124 of the 146 countries that receive ODA, there is data on the number of people living on below $1.90 per day – the World Bank’s definition of living in extreme poverty. Our analysis of ODA to countries at different levels of poverty is, of necessity, limited to this group of 124 countries.
15. People in extreme poverty.
16. United Nations, www.un.org/development/desa/dpad/least-developed-country-category.html (accessed 1 October 2018)
17. ‘Adaptation-related ODA’ refers here to ODA reported to the OECD DAC CRS, marked as ‘principal’ or ‘significant’ to climate adaptation with the climate change adaptation Rio Marker. Totals here refer only to ODA from DAC donors and multilateral institutions. They include projects and their associated ODA scoring ‘principal’ and ‘significant’.
18. Quartile with the third greatest scores.
19. Quartile with the lowest scores.
20. Quartile with the greatest scores.
21. For a more compete list see www.oecd.org/dac/stats/type-aid.htm
22. Grants as debt relief are also excluded from analysis, which peaked around 2009–2011 for a number of countries.
23. Cordella T. and Ulku H. 2007. Grants vs. Loans, International Monetary Fund Staff Papers 54:1.
24. Odedokun, M. 2004. Bilateral and Multilateral Loans versus Grants: Issues and Evidence. The World Economy, 27.
25. Institute for Fiscal Studies, 2017. The changing landscape of UK aid. Available at: www.ifs.org.uk/uploads/publications/bns/BN204.pdf
26. The OECD data on channel of delivery tracks the aid to its first recipient. Apart from aid channelled via the public sector, most of these implementing agencies are international rather than local actors. Some of the aid funding channelled via international actors may be passed on to local organisations further down the value chain, but it is not possible to determine how much ODA eventually makes its way to local NGOs, for example.
27. Grand Bargain signatories, 2016. The Grand Bargain – A Shared Commitment to Better Serve People in Need. Available at: www.agendaforhumanity.org/initiatives/3861. The Grand Bargain is a set of 10 commitments agreed by donors and implementing agencies at the 2016 World Humanitarian Summit to deliver humanitarian assistance more effectively and efficiently.
28. DI, 2018. Global Humanitarian Assistance Report 2018. Available at: www.devinit.org/wp-content/uploads/2018/06/GHA-Report-2018.pdf, page 51
29. UN, 2015. Addis Ababa Action Agenda of the Third International Conference on Financing for Development. Available at: www.un.org/esa/ffd/wp-content/uploads/2015/08/AAAA_Outcome.pdf
30. UKAN and Bond, 2011. Country Ownership: the only way forward for development cooperation. Busan Partnership Documents, December 2011. Available at: www.bond.org.uk/data/files/publications/Country_Ownership.pdf
31. These figures should be taken as less concrete than other spending data due to the OECD finding significant inconsistencies between the way different donors calculated the amount of In-donor refugee costs that were eligible for reporting as ODA (see [anchor]Box 2.1 on measures being brought in to rectify this).
32. While a modality of aid delivery, general budget support is classed as a sector within OECD data. Given the substantial decline in such ODA it is highlighted here.
33. OECD, 2012. The Busan Partnership for Effective Development Cooperation agreement, July 2012. Available at: www.oecd.org/development/effectiveness/busanpartnership.htm
34. For example, OECD, 2010. Development Co-operation Report 2010. Available at: www.oecd-ilibrary.org/development/development-co-operation-report-2010_dcr-2010-en
35. Gross ODA minus humanitarian spending.
36. DI, 2016. Blended finance: Understanding its potential for Agenda 2030. Available at: www.devinit.org/post/blended-finance-understanding-its-potential
37. While there remains no agreed common definition of South–South cooperation, it is commonly understood as an exchange between developing countries and South–South cooperation actors see their contributions as quite different and unique compared with formal ODA.
38. Notably, data on expenditure from Saudi Arabia – a relatively large donor providing US$12.4 billion in 2014 and US$6.9 billion in 2015 – is not available in this year and may account for the apparent decrease in the 2016 total. Large proportions of Turkey’s expenditure are spent on humanitarian assistance, most of which is spent in Turkey on refugee hosting – see note 27.
1. A study by the Sustainable Development Solutions Network suggests that the SDGs are affordable and the challenge is mainly one of organisation and implementation: SDSN, 2015. Investment Needs to Achieve the Sustainable Development Goals. Available at: http://unsdsn.org/wp-content/uploads/2015/09/151112-SDG-Financing-Needs.pdf
2. Resources considered in this chapter include: Domestic public: non-grant government revenue. Domestic commercial: domestic credit to the private sector. Inflows: International official: ODA, development cooperation from other government providers, OOFs, export credits, official long-term debt. International commercial: FDI, commercial long-term debt, short-term debt, portfolio equity, private finance mobilised via blending. International private: remittances, private development assistance, international tourism receipts. Outflows: International official: ODA interest payments, ODA capital repayments, OOFs interest payments, OOFs capital repayments, official long-term debt interest payments, official long-term debt capital repayments, repayments on officially supported export credits. International commercial: FDI, outflows of profits on FDI, commercial long-term debt interest payments, commercial long-term debt capital repayments, short-term debt interest payments. International private: remittances, international tourism expenditures.
3. IMF, 2017. IMF Fiscal Monitor: Tackling Inequality. Available at: www.imf.org/en/Publications/FM/Issues/2017/10/05/fiscal-monitor-october-2017
4. Projections assume a constant government revenue-to-GDP ratio. Real GDP growth is available at the source until 2023; growth for 2024 to 2030 is set equal to 2023 at country level.
5. Manuel M., Desai H., Samman E. and Evans, M., 2018. Financing the end of extreme poverty. Overseas Development Institute (ODI) Report, available at: www.odi.org/publications/11187-financing-end-extreme-poverty
6. Inter-Agency Taskforce on Financing for Development (Chowla, P., Falcao, T.), 2016. Illicit Financial Flows: concepts and scope. Available at: www.un.org/esa/ffd/wp-content/uploads/2017/02/Illicit-financial-flows-conceptual-paper_FfDO-working-paper.pdf; Tax Justice Network (Picciotto, S.), 2018. Illicit financial flows and the tax haven and offshore secrecy system. Available at: www.taxjustice.net/2018/02/08/illicit-financial-flows-tax-haven-offshore-secrecy-system/; Center for Global Development (Forstater, M.), 2018. Illicit Financial Flows, Trade Misinvoicing, and Multinational Tax Avoidance: The Same or Different? Available at: www.cgdev.org/sites/default/files/illicit-financial-flows-trade-misinvoicing-and-multinational-tax-avoidance.pdf; Elcano Royal Institute (Cobham, A.), 2018. Target 2030: illicit financial flows. Available at: www.realinstitutoelcano.org/wps/portal/rielcano_en/contenido?WCM_GLOBAL_CONTEXT=/elcano/elcano_in/zonas_in/ari81-2018-cobham-target-2030-illicit-financial-flows
7. UNU-WIDER (Janský, P., Palanský, M.), 2017. Estimating the scale of profit shifting and tax revenue losses related to foreign direct investment. Available at: www.wider.unu.edu/publication/estimating-scale-profit-shifting-and-tax-revenue-losses-related-foreign-direct
8. See www.devinit.org/post/understanding-illicit-financing-flows-in-a-development-financing-context for further discussion on illicit financing flows.
9. IMF, 2018. Regional Economic Outlook, Sub-Saharan Africa: Domestic Revenue Mobilization and Private Investment. Available at: www.imf.org/en/Publications/REO/SSA/Issues/2018/04/30/sreo0518
10. UN, 2015. Addis Ababa Action Agenda of the Third International Conference on Financing for Development. Available at: www.un.org/esa/ffd/wp-content/uploads/2015/08/AAAA_Outcome.pdf (paragraphs 35 and 48)
11. Center for Strategic and International Studies, 2018. Blended Finance and Aligning Private Investment with Global Development. Available at: www.csis.org/analysis/blended-finance-and-aligning-private-investment-global-development; OECD, no date. Blended Finance. Available at: www.oecd.org/dac/financing-sustainable-development/development-finance-topics/blended-finance.htm; DI, 2018. Will blended finance lead to private sector growth in developing countries? Available at: www.devinit.org/post/will-blended-finance-lead-private-sector-growth-developing-countries/
12. For a more detailed discussion of various approaches donors can adopt to catalyse private sector resources in developing countries, including from the domestic private sector, see DI, 2018. The enabling environment for private sector development: donor spending and links to other catalytic uses of aid (pages 10–11). Available at: www.devinit.org/post/enabling-environment-private-sector-development/
13. Philippine Business for the Environment and UNDP, 2017. Transformational Business: Philippine Business Contributions to the United Nations Sustainable Development Goals. Available at: www.ph.undp.org/content/dam/philippines/docs/SDGs/Transformational%20Business%20-%20Philippine%20Business%20Contributions%20to%20the%20 UN%20SDGs.pdf
14. UN Conference on Trade and Development, 2017. World Investment Report 2017. Available at: http://unctad.org/en/PublicationsLibrary/wir2017_en.pdf
15. UNDP, 2018, forthcoming. Country innovations for integrated SDG financing.
16. Republic of Indonesia, 2017. Voluntary National Review Available at: https://sustainabledevelopment.un.org/content/documents/15705Indonesia.pdf (pages 70 and 71).
17. International tourism has a recognised, important role to play in achieving sustainable development outcomes (e.g. see SDGs 8, 12 and 14) and for many developing countries it represents an important source of foreign exchange income. Financing flows related to foreign visitors’ spending at the country level are included in the analysis to reflect a more comprehensive picture of the overall financing landscape in developing countries. For more detail, see Methodology online. Available at: www.devinit.org/post/investments-to-end-poverty-2018.
18. IMF, 2018. List of LIC DSAs for PRGT-Eligible Countries. Available at: www.imf.org/external/pubs/ft/dsa/dsalist.pdf
19. Department of Economic and Social Affairs, 2017. Global context for achieving the 2030 Agenda for Sustainable Development International financial flows and external debt. Development Issues No. 10. Available at: www.un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/dsp_policy_10.pdf
20. Since 2013 for aggregate commercial flows, and since 2012 for FDI specifically (source: DI based on UN Conference on Trade and Development and World Bank data).
21. Analysis on spending by philanthropic foundations uses data from the 2016-17 OECD Survey on Global Private Philanthropy for Development. For the purposes of this report an estimate for international private development assistance was calculated (as included in Figure 3.2) but it was not possible to create a historical series with available data. To assess trends in international private giving, data from this OECD survey was used – albeit this only includes foundations and the period 2013 to 2015. This data was also used to estimate spending by domestic foundations in developing countries; however, this is likely to be an underestimate of actual volumes given country coverage limitations.
22. Philanthropy Nigeria. Get To Know The Nigerian Philanthropic Sector. Available at: http://philanthropynigeria.org (accessed 18 August 2018).
23. In relation to public–private partnerships, critics have also pointed (among other things) to the lack of transparency and power imbalance between commercial actors and domestic governments when projects are initially negotiated. See for example: Inter-agency Task Force on Financing for Development, 2018. Financing for Development: Progress and Prospects 2018. Available at: https://developmentfinance.un.org/sites/developmentfinance.un.org/files/Report_ IATF_2018.pdf (p. 22).
24. Data on public–private partnerships relies on World Bank’s Private Participation in Infrastructure Database and refers to country-level total investments.
25. See, for example, OECD data on DFIs available here: https://public.tableau.com/views/NONODA_DFIs/DFIs_EN?:embed=y&:display_count=no?&:showVizHome=no#1
26. See, for example: data on amounts mobilised from the private sector for development published by the OECD. Available at: www.oecd.org/dac/financing-sustainable-development/development-finance-standards/mobilisation.htm; data on blended finance funds and facilities published by the OECD. Available at: www.oecd-ilibrary.org/development/making-blended-finance-work-for-the-sustainable-development-goals/methodology-for-surveys-on-blended-finance-funds-and-facilities_9789264288768-15-en; data published by the Association of European Development Finance Institutions (EDFI). Available at: www.edfi.eu; and the 2018 Joint Report by EDFI, IFC and other multinational development bank members of the IFI-DFI Working Group on Blended Concessional Finance for Private Sector Projects, which documents a shared methodology for quantifying amounts of funding mobilised from private investors. Available at: www.edfi.eu/wp/wp-content/uploads/2018/06/201806_Mobilization-of-Private-Finance_v2.pdf
27. FDI data used for this analysis is sourced from the fDi Markets Financial Times Ltd database, which allows for disaggregation of investments by destination country and industry. While health-related investments are included in the industry breakdown, education-related investments are not as education is considered a cross-cutting business activity. Therefore, the proportions of FDI related to human capital sectors reported here are likely to be an underestimation.
28. All data in this paragraph is sourced from the fDi Markets Financial Times Ltd database.
29. Business & Sustainable Development Commission, 2017. Better Business, Better World. Available at: http://report.businesscommission.org/uploads/BetterBiz-BetterWorld_170215_012417.pdf
30. GSMA, 2016. 2016 Mobile Industry Impact Report: Sustainable Development Goals: Executive Summary. Available at: www.gsma.com/betterfuture/wp-content/uploads/2016/11/UN_SDG_ExecSumm_v03_WEB_Singles.pdf
31. Danone. Danone Goals by 2030: Serving a food revolution by 2030. Available at: www.danone.com/about-danone/sustainable-value-creation/our-company-goals.html; http://iar2017.danone.com/performance-in-2017/our-contribution-to-the-uns-sustainable-development-goals/?L (accessed 18 August 2018).
32. UN Global Compact, 2018. Kofi Annan, 1938–2018: The visionary who launched the UN Global Compact and inspired the world’s largest corporate sustainability initiative. Available at: www.unglobalcompact.org
33. The B Team. Home page. Available at: www.bteam.org (accessed 18 August 2018).
34. Business Call to Action. About page. Available at: www.businesscalltoaction.org/business-call-action (accessed 18 August 2018).
35. In the words of the Business and Sustainable Development Commission: “The Commission represents a considerable combined corporate value and a wide range of geographies and sectors. But we are still, in the global scheme of things, a tiny handful of people armed only with a big idea”. Available at: http://report.businesscommission.org/uploads/BetterBiz-BetterWorld_170215_012417.pdf (p. 8).
36. DI. Spotlights on Uganda and Kenya. Available at: http://data.devinit.org/spotlight-on-uganda and http://data.devinit.org/spotlight-on-kenya (accessed 18 August 2018).
37. UNDP, 2017. Development Finance Assessment Snapshot Myanmar. Available at: www.asia-pacific.undp.org/content/dam/rbap/docs/dg/dev-effectiveness/RBAP-DG-2018-Development-Finance-Assessment-Snapshot-Myanmar.pdf
1. SDG target 16.10: Ensure public access to information and protect fundamental freedoms, in accordance with national legislation and international agreements.
2. UN High-Level Panel of Eminent Persons on the Post-2015 Development Agenda, 2013. A New Global Partnership: Eradicate Poverty and Transform Economies through Sustainable Development. Available at: https://sustainabledevelopment.un.org/index.php?page=view&type=400&nr=893&menu=1561
3. World Bank, 2017. World Development Report 2017: Governance and the Law.
4. MIT (Banerjee A., Hanna R., Kyle J., Olken B.A. and Sumarto S.), 2014. Information is Power: Identification Cards and Food Subsidy Programs in Indonesia. Available at: https://economics.mit.edu/files/9931
5. Brown S. and Neumann G., 2017. Paraguay’s transparency alchemists. How citizens are using open contracting to improve public spending, Open Contracting Partnership. Available at: https://medium.com/open-contracting-stories/paraguays-transparency-alchemists-623c8e3c538f122
6. In the Paraguay example, the education minister had to resign over a spending scandal concerning mismanagement of public resource in schools. This was triggered by a media and civil society campaign that uncovered inflated spending for a catering contract. The example demonstrates a confluence of factors in addition to high levels of availability of public information and open data in Paraguay, such as existing concerns over low levels of public education spending and education outcomes, a collapsing school structure, and strong pre-existing levels of youth mobilisation and other civil society actors (available at: https://medium.com/open-contracting-stories/paraguays-transparency-alchemists-623c8e3c538f). In Bogota, Colombia, the national procurement agency and the local education secretariat were able to bring significantly greater transparency and openness to the market for school supplies and services. This was driven by concerns over anti-competitive practices and inflated prices for key supplies. Reforms focused on moving to the use of structured market data and public information campaigns. They resulted in much expanded market participation by new suppliers. Key challenges to overcome in the process included strong resistance such as threats of legal challenges from established suppliers. Local stakeholders emphasise the critical role of political will in overcoming these barriers. Available at: https://medium.com/open-contracting-stories/the-deals-behind-the-meals-c4592e9466a2
7. DI, 2018. Supporting Grand Bargain signatories in meeting commitments to greater transparency. Progress Report 1. Available at: www.devinit.org/post/grand-bargain-progress-report-1
8. Publish What You Fund, 2018. Aid Transparency Index 2018. Available at: www.publishwhatyoufund.org/the-index/2018 (accessed 18 August 2018).
9. SDG target 12.6: Encourage companies, especially large and transnational companies, to adopt sustainable practices and to integrate sustainability information into their reporting cycle, see: https://sustainabledevelopment.un.org/sdg12
10. International Budget Partnership, Open Budget Survey, 2017. Available at: www.internationalbudget.org/open-budget-survey/open-budget-index-rankings/. Analysis includes countries shown on survey results.
11. World Bank. Statistical Capacity Indicator Dashboard. http://datatopics.worldbank.org/statisticalcapacity/SCIdashboard.aspx (accessed 18 August 2018).
12. Libya, Syria and Somalia
13. Considered here as having a score of 50 or lower in the World Bank’s Statistical Capacity Indicator. This accounts for roughly 18% of countries assessed.
14. Open Data Watch, 2018. The Open Data Inventory 2017 Annual Report. A Progress Report on Open Data. Available at: http://odin.opendatawatch.com/report/pressReport
15. Energy use statistics were the least reported data in the ODIN 2017 Annual Report: 120 out of 180 countries reported none of the indicators in this data category.
16. DI, based on Open Data Index (2017) https://index.okfn.org/dataset/ and Open Data Inventory (2017) www.odin.opendatawatch.com/. Colour shading of data categories is DI’s, based on Figure 11 of the Open Data Inventory (2017). Available at: http://odin.opendatawatch.com/. Categories used are 0–29% = light, 30–49% = medium, 50–100% = dark.
17. DI, 2017b. The P20 Initiative. Data to leave no one behind. Baseline Report. Available at: www.devinit.org/post/p20-initiative-data-to-leave-no-one-behind
18. See note 8.
19. Dennison L. and Rana P., 2017. Nepal’s emerging data revolution. DI (web blog), April 2017. Available at: www.devinit.org/post/insights-into-nepals-emerging-data-revolution
20. Syal R., and Campbell D., 2017. NHS data loss scandal deepens with further 162,000 files missing, The Guardian, 16 October 2017. Available at: www.theguardian.com/society/2017/oct/16/nhs-data-loss-scandal-deepens-with-162000-more-files-missing
21. Evenstad L., 2018. NHS data breach caused details of 150,000 patients to be shared, Computer Weekly, 3 July 2018. Available at: www.computerweekly.com/news/252444145/NHS-data-breach-caused-details-of-150000-patients-to-be-shared
22. International Committee of the Red Cross, 2017. Handbook on Data Protection in Humanitarian Action. Available at: www.icrc.org/en/publication/handbook-data-protection-humanitarian-action
23. Masaki T., Custer S., Eskenazi A., Stern A. and Latourell R., Decoding data use: How do leaders use data and use it to accelerate development?, AidData at the College of William & Mary, 2017. Available at: www.aiddata.org/publications/decoding-data-use
24. This is based on the responses of 1,769 of about 3,500 public, private and civil society leaders who participated in AidData’s Listening to Leaders Survey. Top categories for information use were Research and analysis (73.3%), Monitoring and evaluation (71.6%), Implementation (65.3%), Design (63.4%), Capacity building/technical assistance (62.4%), Advocacy and agenda-setting (61.2%) and External communications (42.9%).
25. Buvinic M., Furst-Nichols R. and Koolwal G., 2014. Mapping Gender Data Gaps, data2x. Available at: http://data2x.org/wp-content/uploads/2017/11/Data2X_MappingGenderDataGaps_FullReport.pdf
26. Allen C. and Geiser P., 2017. World Data Forum blog: Persons with disabilities must and can be counted in, International Disability Alliance and International Disability and Development Consortium, (web blog), 6 January 2017. Available at: www.internationaldisabilityalliance.org/blog/world-data-forum-blog-persons-disabilities-must-and-can-be-counted
27. At the time of writing, there were at least four separate, global SDG monitoring data platforms by UNSTATS (https://unstats-undesa.opendata.arcgis.com/), the World Bank (http://datatopics.worldbank.org/sdgatlas/), UNSDSN and Bertelsmann Stiftung (https://dashboards.sdgindex.org/#/) and Our World in Data (https://sdg-tracker.org/). While these represent primarily reuse of existing data, investment into essentially duplicative global efforts is in stark contrast to the limited resources available for data production and use relevant to the local level (and may in itself confuse global data users).
28. DI and the Asia Foundation (Pradhan K. and Zellmann C.), 2018, Aid data needs and use cases in Nepal. An initial assessment of selected user needs for data and information on aid flows and suggestions for action. Available at: www.devinit.org/post/aid-data-needs-use-cases-nepal
29. Sabiti B., 2015. Adventures in the Data Revolution: When the Data Tells no Story, DI, (web blog), 10 March 2015. Available at: https://digitalimpact.org/adventures-in-the-data-revolution-when-the-data-tells-no-story
30. Cf. DI’s case study on analysis of official Ugandan education resources and outcome data, which showed no significant relationship between these factors. When contrasted with local stakeholders’ theory of problems affecting the sector at local level, important alternative theories were developed, such as on the role of physical locations, provision of school lunches and other potential impact factors. Available at: https://digitalimpact.org/adventures-in-the-data-revolution-when-the-data-tells-no-story
31. OECD, 2017. Development Co-operation Report 2017. Data for Development. Available at: www.oecd-ilibrary.org/development/development-co-operation-report-2017/rethinking-donor-support-for-statistical-capacity-development_dcr-2017-9-en
32. See for example Toyama K., 2015. Geek Heresy. Available at: https://geekheresy.org/; World Bank, 2003. Information and Communication Technologies, Poverty and Development: Learning from Experience. Available at: http://documents.worldbank.org/curated/en/741291468779079516/Information-and-communication-technologies-poverty-and-development-learning-from-experience; and World Bank Group, 2016. World Development Report, 2016. When Does ICT-Enabled Citizen Voice Lead to Government Responsiveness? Available at: https://openknowledge.worldbank.org/handle/10986/23650
33. Brown G.W. and Horton P., 2018. Integrating evidence, politics and society: a methodology for the science-policy interface, Nature. Available at: www.nature.com/articles/s41599-018-0099-3
34. World Bank, 2017. Driving Performance from the Center. Malaysia’s Experience with PEMANDU. Available at: http://documents.worldbank.org/curated/en/318041492513503891/Driving-performance-from-the-center-Malaysia-s-experience-with-PEMANDU
35. Cassidy C. and Tsui J., 2017. Global evidence policy units: Department for Planning, Monitoring and Evaluation, South Africa, RTI International, Australian National University, Nossal Institute for Global Health and Overseas Development Institute (ODI). Available at: www.odi.org/publications/10829-global-evidence-policy-units-department-planning-monitoring-and-evaluation-south-africa
36. UNICEF, 2017. Data for Children Strategic Framework. Available at: https://data.unicef.org/resources/data-children-strategic-framework
37. Agrawal A., 2018. Brokering a Solution to Address Country-Level Challenges: The Africa Regional Data Cube, Global Partnership for Sustainable Development Data, (web blog) 21 March 2018. Available at: www.data4sdgs.org/news/brokering-solution-address-country-level-challenges-africa-regional-data-cube
38. This model is being promoted by OpenGovLab, and proposes that private sector data stewards lead the definition of appropriate sharing practices. Available at: http://datacollaboratives.org (accessed 18 August 2018).
39. The OPAL project involves, among others, the MIT Media Lab, Imperial College London, Orange, the World Economic Forum and Data-Pop Alliance. It has been piloted in Senegal and Colombia. Available at: www.opalproject.org (accessed 18 August 2018).
40. Open Institute, 2017. How Lanet Umoja Got Its Medical Centre, Open Institute. Available at: www.youtube.com/watch?time_ continue=48&v=4CPkzkbJBhQ
41. Global Integrity. Treasure Hunts. Available at: www.globalintegrity.org/treasure-hunts/ (accessed 25 July 2018).
42. Dennison L. and Theunissen T., 2017. Supporting Nepal in the sharing and use of (open) data for development. DI and The Asia Foundation, (web blog), 20 November 2017. Available at: www.devinit.org/post/supporting-nepal-sharing-use-open-data-development
43. See for example Open Contracting’s use case guide: www.open-contracting.org/2016/08/18/use-case-guide and Sunlight Foundation’s process for design of local open data initiatives: https://sunlightfoundation.com/policy/open-cities/tactical-data-engagement/equitable-neighborhoods-in-madison-wi
44. The Open Contracting Partnership is in the process of launching a Peer-Coaching and Mentorship programme: https://open-contracting-partnership.forms.fm/open-contracting-peer-coaching-and-mentorship-program/forms/5289 (accessed 1 August 2018) and Dutch NGO Hivos is implementing a €12.5 million programme to support use of open contracting data by civil society actors in Bolivia, Guatemala, Indonesia, Kenya, Malawi, Philippines and Tanzania (2016-2020). Available at: www.hivos.org/program/open-contracting/ (accessed 25 July 2018).
45. For example through the ODI-led Evidence-based Policy in Development Network programme 2005-2011. Available at: www.odi.org/projects/71-evidence-based-policy-development-network (accessed 25 July 2018) and the Building Capacity to Use Research Evidence (BCURE) programme from 2013–17. Available at: https://bcureglobal.wordpress.com/ (accessed 25 July 2018).
46. See for example recent grants to the London School for Economics on promoting sustainable economic growth through evidence-based research and policy (available at: www.lse.ac.uk/supporting-lse/your-gifts-in-action/2017-2018/gates) and ODI on building the technical capacity of policymakers to use financial inclusion data and evidence (available at: www.gatesfoundation.org/How-We-Work/Quick-Links/Grants-Database/Grants/2014/10/OPP1108961) among others.
47. A recent example is Hewlett Foundation’s call for proposals ‘African policy research institutions to advance government use of evidence’. Available at: https://hewlett.org/eipafrica/ (accessed 25 July 2018).
48. For example, New York City recently compelled ride-sharing platforms Uber and Lyft to share data for use in improvements to public transport. Available at: www.wired.com/story/new-york-city-cap-uber-lyft/
49. Pawelke A. and Tatevossian A.R., 2013. Data Philanthropy: Where Are We Now?, UN Global Pulse, 8 May 2013. Available at: www.unglobalpulse.org/data-philanthropy-where-are-we-now
50. GPSDD (Global Partnership for Sustainable Development Data), 2016. State of Development Data Funding. Available at: https://opendatawatch.com/the-state-of-development-data-2016
51. SDSN (Sustainable Development Solutions Network), 2015. Data for Development: A Needs Assessment for SDG Monitoring and Statistical Capacity Development. Available at: http://unsdsn.org/resources/publications/a-needs-assessment-for-sdg-monitoring-and-statistical-capacity-development
52. An updated estimate of costings based on a slightly revised methodology is expected to be published but was not available during the drafting of this report. See Open Data Watch, 2018. Development Data Funding 2018. Methodology for an Updated Cost Estimate. Available at: www.opendatawatch.com/knowledge-partnership/development-data-funding-2018/
53. See note 50.
54. PARIS21 (Partnership in Statistics for Development in the 21st Century), 2017. Partner Report on Support to Statistics. PRESS 2017. Available at: www.paris21.org/press2017
55. A Morton Jerven paper for the Copenhagen Consensus estimated the required investment for SDG data at US$254 billion.
56. Copenhagen Consensus Centre (Jerven M.), 2014. Benefits and Costs of the Data for Development Targets for the Post-2015 Development Agenda. Available at: www.copenhagenconsensus.com/publication/post-2015-consensus-data-development-assessment-jerven
57. Data for Development Festival, 2018. Panel Discussion: Making the Case: More and Better Financing for Data, 22 March 2018. Available at: https://livestream.com/accounts/4724843/events/8119584/videos/172180006
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5. See note 2.
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10. DI, 2018. Global Humanitarian Assistance Report 2018. Available at: www.devinit.org/post/global-humanitarian-assistance-report-2018
11. OECD, 2018. States of Fragility 2018. Available at: http://www.oecd.org/dac/states-of-fragility-2018-9789264302075-en.htm
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19. For more information on development effectiveness commitments see the Global Partnership for Effective Development Cooperation (home). Available at: http://effectivecooperation.org, and for the latest monitoring data see Global Partnership. About global partnership monitoring. Available at: http://effectivecooperation.org/monitoring-country-progress/what-is-global-partnership-monitoring (both accessed 12 September 2018).
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