- ^ Such as World Bank Development Report (2016) Digital Dividends; Mary Hallward-Driemeier, Gaurav Nayyar (2017) Trouble in the Making? The Future of Manufacturing Led Development, World Bank
- ^ http://drodrik.scholar.harvard.edu/files/dani-rodrik/files/premature_deindustrialization_revised2.pdf
- ^ Pathways for Prosperity Commission, Oxford (2018a), Charting Pathways for Inclusive Growth: From Paralysis to Preparation; World Bank Development Report (2019), The Changing Nature of Work; Hernan Galperin, Andrea Alarcon (eds) (2018) The Future of Work in the Global South, International Development Research Centre (IDRC) | Centre de recherches pour le développement international (CRDI); Karishma Banga and Dirk Willem te Velde, 2018, Digitalisation and the Future of Manufacturing in Africa, SET Discussion Paper
- ^ For a discussion of the East Asian export-led manufacturing growth model, see Wade (1990), Amundsen (1989), Johnson (1982). For a review of the literature, see Kyle (2017).
- ^ Manufacturing’s unique properties as compared to the other major sectors of the economy, namely agriculture and services, have been empirically documented.
- ^ We borrow this categorization from Hallward-Driemeier and Nayyar (2017) Our Explainer: Why was manufacturing-led development so important and why is it at a juncture? describes adoption trends and effects of these technologies in further detail.
- ^ For example, Foxconn (Hon Hai Precision Industry), ranked 24 on Fortune Global 500 replaced 60,000 workers in one factory with robots. In 2012 Foxconn had 1.3m workers but this fell to 870,000 by 2016. See “Robots, not humans: official policy in China,” Jenny Chan, 1 November 2017, New Internationalist, https://newint.org/features/2017/11/01/industrial-robots-china See also “A new t-shirt sewing robot can make as many shirts per hour as 17 factory workers”, Marc Bain, 30 August 2017, Quartz, https://qz.com/1064679/a-new-t-shirt-sewing-robot-can-make-as-many-shirts-per-hour-as-17-factory-workers/ and “The Robots Are Coming for Garment Workers. That’s Good for the U.S., Bad for Poor”, Jon Emont, 16 February 2018, The Wall Street Journal, https://www.wsj.com/articles/the-robots-are-coming-for-garment-workers-thats-good-for-the-u-s-bad-for-poor-countries-1518797631
- ^ See Chapter 4 in Hallward-Driemeier and Nayyar (2017).
- ^ See UNCTAD TDR 2017 and Banga and te Velde (2018).
- ^ We infer this from the fact that less complex products, such as those common in light manufacturing, are produced by a greater number of countries than more complex products. See Hausmann and Hidalgo (2010).
- ^ See Jiajun Xu, Stephen Gelb, Jiewei Li and Zuoxiang Zhao, 2017, ‘Adjusting to Rising Costs in Chinese Light Manufacturing: What opportunities for developing countries?’
- ^ Felipe et. al. (2014).
- ^ Analysis based on Medium Fertility Variant Projections, 2015-2100. United Nations, World Population Prospects: The 2017 Revision.
- ^ Autor, David, David Dorn, and Gordon Hanson. (2016) ‘The China Shock: Learning from Labor-Market Adjustment to Large Changes in Trade.’ Annual Review of Economics 8: 205-240. For summary interview with Autor, see Zeeshan Aleem, 20 March 2017, Vox, ‘‘Another kick in the teeth’: a top economist on how trade with China helped elect Trump’
- ^ For an extensive review of the types of anxieties fuelling populism, and how the centre left can manage and allay these, see Martin Eiermann, 2018, ‘Confronting Populist Anxieties: How the Centre-Left Can Quell the Far-Right Surge’, a Tony Blair Institute for Global Change report
- ^ Autor and Dorn, 2013
- ^ See Karishma Banga and Dirk Willem te Velde, 2018, Digitalisation and the Future of Manufacturing in Africa, SET Discussion Paper, p.20
- ^ This is an example of how 4IR technologies may create opportunities in manufacturing that have typically been too complex for African countries to engage in, e.g. manufacturing of machines that are used in the manufacturing of final goods.
- ^ https://infomineo.com/additive-manufacturing-africa-middle-east/
- ^ AGRA, 2017, ‘Africa Agriculture Status Report 2017 The Business of Smallholder Agriculture in Sub Saharan Africa’ https://agra.org/wp-content/uploads/2017/09/Final-AASR-2017-Aug-28.pdf
- ^ World Development Report, 2019
- ^ Ibid
- ^ Ekkehard Ernst, Rossana Merola, Daniel Samaan 2018, ILO future of work research paper series: The economics of artificial intelligence: Implications for the future of work
- ^ For a literature review of the impact of ICTs on farm productivity, see Elvis Melia (2019) ‘The impact of ICTs on jobs in Africa: A literature review
- ^ Ibid
- ^ Bernard Hoekman (2017) ‘Trade in services: Opening markets to create opportunities’ a UNU-Wider Working Paper publication
- ^ Graham and Anwar (2018) Towards a fairer sharing economy, in Davidson et al., (eds) The Cambridge handbook of the law of the sharing economy, Cambridge University Press, Cambridge, pp.328-340
- ^ Siou Chew Kuek et al (2015) The Global Opportunity in Online Outsourcing
- ^ Both MTurk and Upwork offer opportunities for a range of skilled services. Upwork’s website for examples markets its scope of work available from its pool of workers as ‘Short-term tasks’; ‘Recurring Projects’; and ‘Full-time contract work’. See https://www.upwork.com/ and https://www.mturk.com/
- ^ See https://www.ft.com/content/dbe61434-1e41-11e9-b126-46fc3ad87c65 and https://andela.com/about/ for more on its model
- ^ Pathways for Prosperity Commission, Oxford (2018a),
- ^ Ibid
- ^ Graham and Anwar (2018) Towards a fairer sharing economy
- ^ Ibid
- ^ Ghani and O’Connell (2014).
- ^ For an overview of other opportunities, such as within horticulture as well as tourism, see John Page (2019) ‘How industries without smokestacks can address Africa’s youth employment crisis’, part of Brookings Foresight Africa 2019
- ^ Jack Daly and Gary Gereffi, 2017, Tourism global value chains and Africa
- ^ Aubrey Hruby, 2018, ‘Tab creative industries to boost Africa’s economic growth,’ Financial Times
- ^ Yuen Yuen Ang, 2016, How China Escaped the Poverty Trap, and Funke Osae-Brown, ‘Nollywood: No longer living in bondage’, NewAfrican, October 2018
- ^ Erick Oh, 2014, ‘Nigeria’s Film Industry: Nollywood looks to expand globally’, United States International Trade Commission (USITC)
- ^ Hruby, 2018
- ^ Industrial policy is a range of government measures, such as tariffs, subsidies or other incentives, infrastructure investment, etc, ‘aimed at improving the competitiveness and capabilities of domestic firms and promoting structural transformation’ (Unido, Unctad, 2011, ‘Economic Development In Africa Report 2011’ https://unctad.org/en/docs/aldcafrica2011_en.pdf). It is considered the means to address market failures by encouraging the growth of specific growth sectors, and is often ‘considered at the core of what development economists study’ (Dani Rodrik, 2008, ‘Industrial Policy: Don’t ask why, ask how,’ https://drodrik.scholar.harvard.edu/files/dani-rodrik/files/industrial-policy-dont-ask-why-ask-how.pdf). Traditionally, Industrial policy focused on manufacturing sectors but this model can be applied to any sector.
- ^ Whitfield et al. 2015: pg. 288.
- ^ Our report, ‘A New Deal for Big Tech: Next-Generation Regulation Fit for the Internet Age,’ Chris Yiu, 2018, explores how government must and can invest in education to prepare for the digital age, and our ‘Technology for the Many: A Public Policy Platform for a Better, Fairer Future’, Chris Yiu, 2018, offers policy advice for lifelong learning, with a call to fund the up-front costs of education or training for anyone that needs it, at any point in their life, with greater repayments from those who go on to earn the most. Both refer to the West, but are as essential and applicable to the Global South.
- ^ The ‘Last Mile’ in telecommunications and the internet industries refers to the final stretch of infrastructure that delivers telecoms services to end-users. In this context it refers to the last set of infrastructure investments necessary to connect those that still do not have access to reliable internet. Despite referring to distance, it does not necessarily mean laying traditional wire infrastructure such as the fibre optic cable to this group of people
- ^ With thanks to Sarah Hunter, Director of Public Policy for Google X, for her insights on the underpinning connectivity challenge.
- ^ We draw on Schlogl and Sumner (2018) for elements of this diagram but offer a different categorisation and take a broader view, to include how governments can use automation to promote structural transformation, productivity growth and greater social welfare.
- ^ We draw upon Andrews, Pritchett, and Woolcock, ‘Building State Capability’ and Kyle, ‘Perspectives on the Role of the State’ for these criteria.
- ^ YY Ang’s book, book How China Escaped the Poverty Trap, 2016 provides an excellent case study on Nollywood’s growth (see the Conclusion), and the broader lessons that can be gleaned for adaptive government.
- ^ Yuen Yuen Ang, How China Escaped the Poverty Trap, 2016.
- ^ Ibid.
- ^ Nearly always, alternative approaches in any given policy area are already being carried out, even if government has not formally authorized variation in the way a policy goal should be pursued. Part of government’s role then is to seek out cases where this deviance results in more-positive-than-usual outcomes.
- ^ Beegle et al., ‘Realizing the Full Potential of Social Safety Nets in Africa’, http://documents.worldbank.org/curated/en/657581531930611436/Realizing-the-Full-Potential-of-Social-Safety-Nets-in-Africa.
- ^ David Snowden, Cynefin framework, https://hbr.org/2007/11/a-leaders-framework-for-decision-making.
- ^ Many have pointed out the folly of over-emphasizing plans and control. The nineteenth-century German field marshal Helmuth Karl Bernhard Graf von Moltke advocated for the idea that ‘no plan survives contact with the enemy’, while former world heavyweight boxing champion Mike Tyson stated that ‘everyone has a plan until they get punched in the mouth’.
- ^ Patrick Collison interview, The Knowledge Project podcast, May 2, 2018, https://fs.blog/2018/05/patrick-collison/.
- ^ This is known as Goodhart’s law.
- ^ Here we adapt some of the principles of a ‘learning organization’, as pioneered by Peter Senge, but expand their scope to apply to the overall policymaking space. This space involves many different actors and organisations, which is why we use the term ‘learning ecosystem’.
- ^ Pritchett and de Weijer, ‘Fragile States: Stuck in a Capability Trap?’
- ^ This is akin to the aphorism ‘don’t put all your eggs in one basket’. Silicon Valley learned this lesson long ago, where we see investors building portfolios of investments in a range of companies across many different sectors. They are acutely aware that many of their investments will not pay back – a failure at the individual investment level. And whether an investment will succeed or fail is highly unpredictable (just as is the case for any given policy that government wants to implement). Hence, they pursue and evaluate their investments at the portfolio level, with the expectation that the investments that succeed will make up for those that do not (in financial terms). This is the same idea that underlies portfolio investing in the personal finance space.
- ^ Ang 2016, p.223
- ^ Ibid, p.79
- ^ ODI, Bastagli et al (2016) ‘Cash transfer: what does the evidence say? A rigorous review of programme impact and the role of design and implementation failures’; Haushofer and Shapiro (2016) ‘The short-term impact of unconditional cash transfers to the poor: experimental evidence from Kenya’
- ^ Most notably, Finland (see Economist, April 2018, ‘The lapsing of Finland’s universal basic income trial’) and private UBI experiments in the US (see WIRED, August 2018, ‘Y Combinator learns Basic Income is not so basic after all’)
- ^ As defined by the World Bank: extreme poverty for those living in low-income countries (much of Africa) at <$1.90 p/day, and the poverty line in lower-middle income countries (including some economies of Africa) at <$3.20 p/day). See http://blogs.worldbank.org/developmenttalk/richer-array-international-poverty-lines
- ^ Van Reenen (2018), https://voxdev.org/topic/firms-trade/management-and-wealth-nations.
- ^ See Pathways for Prosperity Commission’s publication ‘Digital lives: Meaningful Connections for the Next 3 Billion’, 2018
- ^ See https://loon.co/ and https://x.company/projects/fsoc/
- ^ See https://ifcextapps.ifc.org/IFCExt/pressroom/IFCPressRoom.nsf/0/F6A93BAEE6BB7569852581230072D7A2
- ^ See Pathways for Prosperity Commission’s ‘Digital lives’ 2018
- ^ https://ec.europa.eu/digital-single-market/en/better-access-consumers-and-business-online-goods
- ^ https://ec.europa.eu/digital-single-market/en/right-environment-digital-networks-and-services
- ^ See https://ec.europa.eu/digital-single-market/en/policies/shaping-digital-single-market
- ^ See https://twitter.com/iam_internet/status/1109068355942711299 and https://twitter.com/iam_internet/status/1109064957054853120
- ^ A startup company, privately held, which is valued at over $1 billion. See https://www.holoniq.com/edtech-unicorns
- ^ https://www.thetechedvocate.org/which-country-is-leading-the-edtech-movement/
- ^ Off the record conversations with investors and development finance institutions have indicated that the size of individual African markets are simply too small, and consequentially uncommercial, for private investors in frontier sectors such as EdTech, in stark contrast to India.
- ^ Ekkehard Ernst, Rossana Merola, Daniel Samaan, 2018, ‘The economics of artificial intelligence: Implications for the future of work’, ILO future of work: Research paper series
- ^ Thanks to Lant Pritchett for this useful framing.
- ^ This idea is described in depth in Clemens et al., ‘Migration is What You Make It: Seven Policy Decisions That Turned Challenges Into Opportunities’, 2018, https://www.cgdev.org/sites/default/files/migration-what-you-make-it-seven-policy-decisions-turned-challenges-opportunities.pdf and Michael Clemens and Lant Pritchett, ‘Temporary Work Visas: A Four-Way Win for the Middle Class, Low Skill Workers, Border Security, and Migrants’, 2013, https://www.cgdev.org/sites/default/files/time-bound-labor-access.pdf.
- ^ Ibid.; in the first six years of its program, New Zealand had an overstay rate of less than one percent.
- ^ Clemens provides a concrete example: if we consider a nursing school in Banjul, The Gambia, the EU and European employers could provide support to the school’s training of both nurse assistants to work in the EU and nurses to work in The Gambia. Migrants would thus obtain the precise set of skills they need to contribute effectively as nurse assistants in the EU. Importantly, the EU needs these nurse assistants, and would be able to get them more cheaply due to lower training costs in The Gambia. Meanwhile, The Gambia would end up with more nurses, which would motivate Gambian youth to maximize their education and skills because they may have concrete, quality job opportunities available when they enter the labour market. For more detail, see Clemens, ‘Cultivating a New Bargain on Migration: Three Recommendations for the Global Compact’, 2018, https://www.cgdev.org/blog/cultivating-new-bargain-migration-three-recommendations-global-compact.
- ^ Harvey Redgrave, 2018, ‘Balanced Migration: A Progressive Approach’
- ^ https://www.cgdev.org/blog/idea-counting-dollars-illicit-financial-flows-undermining-action-where-it-counts
- ^ https://www.cgdev.org/blog/proposed-sdg-indicator-illicit-financial-flows-risks-conflating-ordinary-business-dirty-money
- ^ High Level Panel on Illicit Financial Flows, UN Economic Commission for Africa https://www.uneca.org/iff
- ^ For an overview of recommendations from leading IFF experts, see https://www.cgdev.org/blog/what-advice-would-you-give-penny-mordaunt-combating-illicit-financial-flows. See also UK Gov on Unexplained Wealth Orders, https://www.gov.uk/government/publications/circular-0032018-criminal-finances-act-unexplained-wealth-orders/circular-0032018-unexplained-wealth-orders
- ^ For further review of this, see https://www.cgdev.org/blog/idea-counting-dollars-illicit-financial-flows-undermining-action-where-it-counts and https://www.cgdev.org/blog/proposed-sdg-indicator-illicit-financial-flows-risks-conflating-ordinary-business-dirty-money
- ^ https://institute.global/insight/renewing-centre/new-deal-big-tech
- ^ Our report suggests defining these tech superstars as ‘firms with more than 50 million monthly active users, annual revenues of more than $1 billion or a market capitalisation of more than $25 billion’, such as Google, Amazon and Facebook. See A New Deal for Big Tech: Next-Generation Regulation Fit for the Internet Age