Despite a sustained period of falling unemployment pre-pandemic, many workers across the G20 have been displaced from middle income employment into insecure, low income, poor-quality work. Compounded by the impact of COVID-19, this paucity of “good jobs” has both economic and societal impacts and contributes to distrust in institutions and governments. Policymakers should urgently focus on: agreeing on a measure of job quality; understanding the benefits of better aligning human workers with the value they can deliver; and guiding labor market transformation, as economies across the G20 stabilize post-COVID-19.
Challenge
The world is experiencing unprecedented challenges as nations continue to combat the COVID-19 virus and navigate its health, economic, and societal impacts. The World Bank predicts the global economy will shrink by 5.2% this year, potentially “plunging the world into the deepest economic recession since the Second World War” (World Bank 2020) and creating significant challenges to the availability of good jobs now and in the future. As G20 members act extensively to support all stakeholders (including workers, employers, and educators) they must collectively encourage the design and protection of good jobs.
Defining good jobs
While there is no agreed upon definition of a good job, this brief defines the term as work that is safe, paid fairly, reasonably secure and motivating, and leverages the human skills of the worker, thus delivering higher levels of productivity (Sethi and Stubbings 2019). Good jobs also provide opportunities to build skills for future employability. Economic value is more often generated when organizations place workers in jobs that call for the skills that humans excel in, while utilizing machines and technology to do the rest (Kayser et al. 2017). Good jobs are not limited to a particular industry, geography or demographic—the dimensions of good work are relevant for developed and developing economies, skilled and unskilled labor, and all types of employment (full time, part time, gig, informal).
There is a clear opportunity to create an international consensus on the metrics that should be used to measure job quality (Warhurst, Wright and Lyonette 2017). Those that exist today tend to focus on income and benefits alone. The Organisation for Economic Co-operation and Development’s (OECD) framework to measure job quality across countries has three dimensions: earnings quality, labor market security, and the quality of the working environment (2016a). Work by Cornell Law School to develop a Job Quality Index for the private sector in the US defines job quality as “the weekly dollar-income a job generates for an employee. Payment, after all, is a primary reason why people work” (Alpert et al. 2019, 3). Although accurate, it is by no means the whole story. A study by the Lumina Foundation, Bill & Melinda Gates Foundation, Omidyar Network and Gallup asked 6,600 workers what they value in a job; only 40% described themselves as being in good jobs (2019).
The reduction in good jobs before COVID-19
Despite a pre-pandemic sustained period of falling unemployment levels across G20 members—with a drop of 0.4 percentage points from its peak in 2009 to a low of 5.1% in 20181—workers increasingly ended up in insecure, low-wage employment (Goos and Manning 2003).
Many workers were displaced from middle-income, secure work (ILO 2018b) as organizations sought competitiveness through efficiency, cost cutting and new operating models: their tasks have been routinized and automated, or reconfigured (Das and Hilgenstock 2018). PwC UK research shows that 30% of jobs across OECD countries are at high risk of automation (enabled by technology availability) by the mid-2030s (PwC 2018).
Driven by a lack of time and/or opportunity to find a good job fit or to acquire new skills, displaced workers were forced to accept lower-skilled and lower-paying, often precarious, jobs, putting downward pressure on wages in the low-wage sector (ILO 2018b). Analysis on the US private sector shows that 63% of all jobs created since 1990 have been low wage, low hours work. Furthermore, four in 10 EU workers surveyed felt trapped in low-quality jobs or contingent work and that their skills are underutilized (Cedefop 2018).
At the same time, the increasing automation and robotization of routine tasks has driven demand for highly-skilled workers. This has led to a hollowing out of the workforce with a decline in reasonably secure, fairly paid work.
Twin impacts of COVID-19 and automation
Developments in technology, competition, and the desire to drive down costs and increase workforce productivity, have powered automation in the workplace to date. Now, the impact of the COVID-19 pandemic and the related global downturn are further accelerating automation and displacement of workers (Smith et al. 2020). According to the most recent numbers released by the International Labour Organization (ILO), there was a 14% decline in global working hours in the second quarter of 2020, which is equivalent to roughly 400 million full-time jobs (2020a). By comparison, the 2008-9 global financial crisis increased global unemployment by 22 million (2020b).
OECD research shows that routine-intensive work is more susceptible to economic shocks which serve to accelerate labor market transformation (2016b). As demonstrated in Figure 1, large-scale rises in unemployment can superficially equate to rises in some job quality measures with fewer low-paid workers included. However, subsequent rounds of middle income worker displacement create further polarization and can drive low-income wages even more.
Historically, displaced workers have suffered large and persistent earnings losses over time (Davis and von Wachter 2011). The Obama report on AI and jobs saw that 10 or more years after their displacement, worker earnings remained depressed by 10% or more relative to their previous wages (2016). One study found that the skills mismatch that arises when workers’ human skills are underutilized at a new job is a key mechanism for the earnings losses of displaced workers (Nedelkoska, Neffke and Wiederhold 2015).
Job displacement can also have a negative effect on worker wellbeing and mental health. Low and/or unpredictable earnings and hours contribute to insecurity and uncertainty for long term planning and, in turn, to a high cognitive load for workers (Sheehy-Skeffington and Rea 2017). In addition, low-income jobs are less likely to provide displaced workers comparable levels of employee benefits; in some cases, such as in the informal sector, benefits are not offered at all (Lumina Foundation et al. 2019).
As the platform/gig economy expands at exponential rates, policymakers in the Global South have a unique opportunity to translate the aggregation of gig workers through digital platforms into a more formalized labor market, with opportunities for both revenue collection and higher quality employment (Gregory and Galperin 2019). In the gig economy, algorithmic controls used by online labor platforms offer workers high levels of flexibility and autonomy, and contribute to the formalization of work in these economies (Wood et al. 2019). But these same controls can also result in social isolation from working unsocial hours, overwork, sleep deprivation, and exhaustion (in addition to low pay and limited or no access to formal social protection mechanisms). Many of these traits are also common in other types of poor quality work.
Polarized labor markets caused by the hollowing out of middle-income workers has led to greater income disparity and rising distrust in institutions and governments. Income inequality has become a strong predictor of trust in developed markets and, pre-pandemic, government was the least trusted institution. The 2020 Edelman Trust Barometer showed that around 57% of respondents described their government as only serving the interest of “the few” as opposed to serving the “interests of everyone” (Edelman 2020).
A lack of good jobs has an economic (GDP) impact, reduces government tax and social security collections, and increases social safety net costs (OECD 2014).
Proposal
Why job quality, and our ability to measure it, is important
Job quality matters because the better alignment of human skills leads to higher levels of worker productivity. The economist David Autor’s “O ring principle” argues that, as machines take on more tasks, the advantage of workers who supply problem-solving skills, adaptability, and creativity is amplified. Automating one part of a task does not make the part played by humans less important; in fact, human work becomes more important because the success of the automated part depends on the task that is performed by a human (Autor 2015).
Workers employed in good jobs also tend to be more fulfilled and therefore more productive (OECD 2017). A study into the link between productivity and happiness at work found that individuals who felt happier were 12% more productive than the control group (Sgroi 2015). In studies by the Queens School of Business and Gallup, disengaged workers had 37% higher absenteeism, 49% more accidents, and 60% more errors and defects (Seppälä and Cameron 2015). But without a consistent measure of job quality, it is difficult to assess and therefore access this potential productivity boost.
The development of transferable skills also enhances future employability for workers in good jobs by making the workforce more adaptable. Adaptable workers will be better equipped to withstand cyclical changes and future economic shocks due to their ability to flex across different business sectors and apply these skills in new settings. This can minimize structural long-term unemployment.
Delivering more good jobs has the potential to:
- Boost economies: Rising wage levels—when enabled by higher productivity—create an uplift in the economy through increased spending power of workers (ILO 2016; L20 Argentina 2018). Whether or not wage-push inflation is created, growth in the economy would follow.
- Boost government finances: Higher earning levels and increasing inclusion in the formal economy can boost tax and social security collections and lower the costs of social safety nets (Madrick 2012).
- Bolster trust in the government: All the above plus reduced wage inequality may halt or reverse declining trust in governments and institutions.
As communities, business sectors, and economies look to “build back better” from the COVID-19 pandemic, the opportunity to shift to a more resilient, sustainable, and inclusive model must be seized (Bakker and Elkington 2020).
As stated in the G20 Communiqué following a virtual meeting of financial ministers and central bank governors on April 15, “no efforts are to be spared, both individually and collectively, to protect lives… and safeguard people’s jobs and income” (2020, 1). As nations and economies begin to re-open and jobs start to return, G20 members should take care to generate good rather than bad jobs.
Societal pressures to protect workers are pushing organizations to act fairly. At a national level, policy adjustments, such as minimum wage, maximum working hours legislation or workers’ rights that discourage creation of precarious or exploitative work, can incentivize innovation and transformation. They can also support the labor market’s adjustment to protect workers and help make sure that growth is broadly shared (ILO 2015).
Furthermore, G20 nations with aging and youthful populations alike should aim to act swiftly and with a vested interest in generating good jobs. On the one hand, countries with an aging workforce (e.g., Japan) are seeing older workers remain in the workforce longer, but limited investments have been made to reskill this segment of the workforce, although they hold jobs that are typically at high risk of automation (OECD 2018). Displaced older workers (particularly those lacking updated skills) are less likely to obtain good jobs, which can cause further strain on economic and social resources.
On the other hand, countries with a large youth population are experiencing increasing levels of youth unemployment (e.g., South Africa, India) (United Nations 2019). Meanwhile, high extreme working poverty rates are prevalent among young workers in sub-Saharan Africa and the Arab States, where the poverty rate sharply increased by 12 percentage points between 1999 and 2019. Young individuals in these economies look to ameliorate their economic situation by accepting low-skilled, precarious work, that lacks legal and social protection and offers limited opportunities for skill development (ILO 2020c). This poor quality of employment is likely to have negative effects on the individual in the long-term and stalls economic growth at the national level.
The ultimate societal aim should be to drive out bad jobs (i.e., jobs which are harmful, exploitative, precarious, or demotivating) without driving out jobs altogether, and encourage the creation of good jobs, which better align human skills to the value chain and drive workforce productivity.
This transformation brings real benefits to organizations and society alike, and can help accelerate post-pandemic economic recovery. Businesses can benefit from sustainable workforce productivity and competitiveness, whilst society can benefit from better use of resources (Sheehy-Skeffington and Rea 2017). Investment in upskilling (to lift people out of low-value, unfulfilling work that is able to be automated and into work that requires problem-solving, creativity, and adaptability; the work humans are better equipped for) is as important as investment in technology if we are to create good jobs and drive productivity, innovation and rebuild growth. This requires incentives and more detailed workforce management reporting that identifies the effective use of humans in work.
Policy Actions
This proposal is for three interrelated policy actions focused on delivering economic value and driving increased societal cohesion through a focus on the identification, recognition, and creation of good jobs. The first policy action is centered on the foundational work needed to establish international consensus around the definition (and drivers) of good jobs. Once this is achieved, subsequent actions to measure job quality, promote awareness, and guide labor market transformation across G20 nations can be taken.
Policy action 1: Establish a G20 working group to identify the underlying drivers and trends in the provision of good jobs and implement an agreed measure of job quality across industries, member nations, and subnational areas.
The G20 should establish a working group (across the T20, B20, L20 and Y20) to identify drivers and trends in job quality at an industry, national, and subnational level. Bringing together policy makers with economists, technologists, labor unions, businesses, and youth across the G20, this working group should:
- collectively determine a set of indicators that measure quality of employment across all G20 members at an industry, national and subnational level.
- develop a globally consistent framework to measure the controllable factors that drive job quality, including: job wage levels, contract hours, job or contract security, and job resilience to automation. This should form the basis for consistent national and subnational measurement and reporting to inform policy decisions.
- make recommendations for corporate level public reporting on job quality and controllable driving factors within an organization. It will be important to build on progress already made across the business sector in the public reporting arena. The working group may look to collaborate with other organizations to harness their experience and align on the realization of the Sustainable Development Goals (SDGs).
Policy action 2: Build awareness of the dual economic and societal value of good jobs stemming from better-aligning human workers with the value they can create (alongside technology) in a value chain.
The G20 should seek to build increased awareness of the benefits to the economy and to society of good jobs. This can be achieved by the foundation of a G20 research institution with a mandate to:
- identify the economic and societal advantages and disadvantages derived from adopting policies that drive better job quality in an interconnected global economy;
- build broad awareness across G20 members (including policy makers, institutions corporates and citizens) around the benefits that stem from a better alignment of human skills and attributes in a value chain;
- use a systems thinking approach to help determine how individual factors interplay and identify potential unintended consequences for industries, countries, regions and cities (Curtatone and Esposito 2014; Kayser et al. 2017);
- publish its findings in a widely accessible and easily understandable way; and
- provide research capabilities at the subnational level in order for communities to better understand and manage their individual challenges in increasingly complex and interdependent environments.
Policy action 3: Act to guide labor market transformation across the G20 to make better use of resources and drive out poorly aligned use of human skills and attributes.
Policy action 3a
The G20 should act collectively to identify factors that can shape labor market transformation across one interconnected global labor market and in turn drive both productivity and job quality at industry, national and subnational levels. This will require:
- extending the mandate of the G20-led global working group formed in response to Policy action 1 (or the formation of a parallel working group across T2, B20, L20 and Y20) to work with businesses, labor unions, job aggregators/platform recruitment industry and research bodies to understand the levers for, and widely communicate the benefits from labor market transformation. The working group will:
- establish a common framework for research to understand the dynamics and projections of labor markets and skills mismatches across all geographies, societal layers (including the community level), and industries, and continuously validate the long-term outlook. Specifically, this would include the development of big data analytics solutions to assess the complex labor market dynamics. The G20 should ensure that its analytics capability is commonly accessible for local communities to develop customized solutions and share best practices;
- encourage broad transparency of the types of skills and jobs that each economy (including subnational economies) is most likely to need in the medium and longer term. This clarity will allow workers and students to make better choices around building their skills and managing their careers;
- identify the success of policy levers in guiding labor market transformation and the provision of good jobs including minimum wage legislation, maximum working hours policies, and policy actions which discourage the creation of precarious work;
- identify the drivers and policy actions that mitigate the transfer of work to the informal economy. Here, the working group may look to reinforce existing policy recommendations put forth by Abrieu et al. (2019) to (a) identify the specific drivers of informal employment in each labor market and (b) extend social protection mechanisms for workers in non-standard employment, with a particular focus on vulnerable populations (e.g., women in the platform economy in the global south); and
- identify the economic and societal advantages and disadvantages derived from adopting policies to support displaced workers as they transition to new roles, including substantiating the impact on government finances and better job quality as part of an interconnected global economy.
Policy action 3b
The G20 should act consistently to deliver improved job quality across all members. This will require:
- the agreement and publication of a G20 “Roadmap for Good Jobs” statement that signals the intent of all G20 members to act, in order to:
- create transparent and implementable plans to monitor and improve the ratio of good jobs at both a national and subnational level;
- implement policies to rapidly increase the percentage of workers within the formal economy whose earnings meet or exceed a living wage and are able to expect fair workers’ rights and job security;
- restructure education curricula and skills development funding in light of changing skills needs and longer working lives. Efforts in this area can build upon existing recommendations from Park (2018), Grainger and Bandura (2019) and others that call for policy makers’ support in incentivizing businesses and the education sector (including vocational training) to align with high-growth skill needs;
- incentivize and encourage individual citizens to invest in their own skills and education, whether employed or unemployed;
- invest in targeted reskilling initiatives working with businesses, unions, industries and subnational and national government bodies. Luxembourg’s Digital Skills Bridge provides one example of how stakeholders can align funding and outcomes successfully;
- identify and publish a set of workforce management goals across G20 nations that organizations will be recognized for achieving. These would include: reskilling workers, wellbeing, and fair pay practices along with leading management practices that measurably improve work performance and worker inclusion; and
- explore the viability of establishing minimum working rights across all G20 members, building from the successful practices in a number of G20 member states. These should attempt to guard against retrograde people management practices and working conditions such as unfair penalties and workplace practices that undermine human dignity in an interconnected global market and can align directly with Sustainable Development Goals 8 (Decent work and economic growth) and 10 (Reduced Inequalities), but recognizing that currently, minimum working rights are different in advanced and developing countries.
The same G20-led working group established in policy action #1 and #3a could also be responsible for drawing up the “Roadmap for Good Jobs” and working across member states to generate consensus.
Disclaimer
This policy brief was developed and written by the authors and has undergone a peer review process. The views and opinions expressed in this policy brief are those of the authors and do not necessarily reflect the official policy or position of the authors’ organizations or the T20 Secretariat.
References
Abrieu, Ramiro, Martin Rapetti, Urvashi Aneja, and Krish Chetty. 2019. “How to Promote
Worker Wellbeing in the Platform Economy in the Global South.” G20 Insights.
Last updated June 14, 2019. https://www.g20-insights.org/policy_briefs/how-to-promote-worker-wellbeing-in-the-platform-economy-in-the-global-south.
Alpert, Daniel, Jeffrey Ferry, Robert C. Hockett, and Amir Khaleghi. 2019. “The U.S.
Private Sector Job Quality Index.” Cornell Legal Studies Research Paper No. 20-33.
https://dx.doi.org/10.2139/ssrn.3566575.
Autor, David H. 2015. “Why Are There Still So Many Jobs? The History and Future of
Workplace Automation.” Journal of Economic Perspectives, 29, no. 3: 3–30. Available
at: https://economics.mit.edu/files/11563.
Bakker, Peter and John Elkington. 2020. “To Build Back Better, We Must Reinvent
Capitalism. Here’s How.” World Economic Forum, blog post, July 13, 2020. https://www.weforum.org/covid-action-platform/articles/to-build-back-better-we-must-reinvent-capitalism-heres-how.
Cedefop. 2018. Insights Into Skill Shortages and Skill Mismatch: Learning From Cedefop’s
European Skills and Jobs Survey. Cedefop Reference Series, No. 106. Luxembourg:
Publications Office of the European Union. https://doi.org/10.2801/645011.
Cornell-JQI-RIWI. 2020. “The U.S. Private Sector Job Quality Index (JQI).” Job Quality
Index Website, August 4, 2020. Accessed August 21, 2020. https://www.jobqualityindex.com.
Curtatone, Joseph A. and Mark Esposito. 2014. “A Systems-Thinking Approach to Public
Policy Eschews Linear Model For More Holistic Understanding of Decision-Making.”
London School of Economics blog, September 25, 2014. https://blogs.lse.ac.uk/impactofsocialsciences/2014/09/25/systems-thinking-approach-to-public-policy.
Das, Mitali and Benjamin Hilgenstock. 2018. “The Exposure to Routinization: Labor
Market Implications for Developed and Developing Economies.” International Monetary
Fund Working Paper No. 18/135. https://www.imf.org/en/Publications/WP/Issues/2018/06/13/The-Exposure-to-Routinization-Labor-Market-Implications-for-Developed-and-Developing-45989.
Davis, Steven J. and Till von Wachter. 2011. “Recessions and the Costs of Job Loss.”
Brookings Papers on Economic Activity. Last updated November 23 2011. https://www.econ.ucla.edu/tvwachter/papers/Recessions_and_the_Costs_of_Job_Loss_23_November_2011.pdf.
Edelman. 2020. “2020 Edelman Trust Barometer.” Edelman webpage. Last updated
January 19, 2020. https://www.edelman.com/trustbarometer.
Executive Office of the President. 2016. “Artificial Intelligence, Automation and the
Economy.” Obama White House Archives. Last updated December 2019. https://obamawhitehouse.archives.gov/sites/whitehouse.gov/files/documents/Artificial-Intelligence-Automation-Economy.PDF.
G20. 2020. “Communiqué: G20 Finance Ministers and Central Bank Governors Meeting.”
G20 website, Virtual Meeting. Accessed July 23, 2020. https://g20.org/en/media/Documents/G20_FMCBG_Communiqu%C3%A9_EN%20(2).pdf.
Goos, Maarten and Alan Manning. 2003. “In the UK: Lousy and Lovely Jobs: The Rising
Polarization of Work in Britain.” London: Centre for Economic Performance.
Grainger, Paul and Romina Bandura. 2019. “Rethinking Pathways to Employment:
Technical and Vocational Training for a Digital Age.” G20 Insights, G20 Japan. Last
updated June 14, 2019. https://www.g20-insights.org/policy_briefs/rethinking-pathways-to-employment-technical-and-vocational-training-for-the-digital-age-2.
ILO. 2015. Labour Protection in a Transforming World of Work. At International Labour
Conference, 104th Session, 2015. Geneva: International Labour Office.
ILO. 2016. Global Wage Report 2016/17: Wage Inequality in the Workplace. Geneva:
International Labor Organization.
ILO. 2018a. “G20 Facts and Figures.” International Labour Organization webpage.
Last updated 2018. https://www.ilo.org/global/about-the-ilo/how-the-ilo-works/multilateral-system/g20/WCMS_565183/lang–en/index.htm.
ILO. 2018b. “The Impact of Technology on Quality and Quantity of Jobs.” In 2nd Meeting
of the Global Commission on the Future of Work, February 15-17, 2018. ILO website,
Issue brief. https://www.ilo.org/wcmsp5/groups/public/—dgreports/—cabinet/documents/publication/wcms_618168.pdf.
ILO. 2020a. “COVID-19 and World of Work: Impacts and Responses.” International
Labour Organization Monitor, PDF. Last updated March 18, 2020. https://www.ilo.org/wcmsp5/groups/public/—dgreports/—dcomm/documents/briefingnote/wcms_738753.pdf.
ILO. 2020b. “As Jobs Crisis Deepens, ILO Warns of Uncertain and Incomplete Labour
Market Recovery.” International Labour Office, article. Last updated June 30, 2020.
https://www.ilo.org/global/about-the-ilo/newsroom/news/WCMS_749398/lang–en/index.htm.
ILO. 2020c. Global Employment Trends for Youth 2020: Technology and the Future of
Jobs. Geneva: International Labour Office, 2020.
Kayser, Harald, Michael Ey, Peter Gerdemann, Sinem Kuz, Joachim Müller, Frank
Navrade, Nina Pannewick, et al. 2017. “Accelerating Labour Market Transformation.”
G20 Insights, Policy Brief. Last updated June 26, 2017. https://www.g20-insights.org/policy_briefs/accelerating-labour-market-transformation.
L20 Argentina. 2018. “Economic and Social Policy Brief: The Case For Wage Led
Growth.” International Trade Union Confederation website, Executive Summary. Accessed
March 29, 2020. https://www.ituc-csi.org/IMG/pdf/l20_-_2018_argentina.
Lumina Foundation, Bill & Melinda Gates Foundation, Omidyar Network, and Gallup.
2019. “Not Just a Job: New Evidence on the Quality of Work in the United States.”
Gallup website, Report. Accessed August 21, 2020. https://www.gallup.com/education/267590/great-jobs-lumina-gates-omidyar-gallup-quality-report-2019.aspx.
Madrick, Jeff. 2012. “The Case for Wage-Led Growth.” New America Foundation
website, Economic Growth Program Policy Paper. Roosevelt Institute and Schwartz
Center for Economic Policy Analysis, June 2012. https://static.newamerica.org/attachments/4251-the-case-for-wage-led-growth/Madrick_Jeff_NAF_The_Case_For_Wage_Led_Growth_June_2012_1.9cb208c479f246a7bc98934262481645.pdf.
Nedelkoska, Ljubica, Franke Neffke and Simon Wiederhold. 2015. “Skill Mismatch
and the Costs of Job Displacement.” Accessed August 21, 2020. https://hdl.voced.edu.au/10707/349166.
OECD. 2014. “Focus on Inequality and Growth.” OECD website, PDF. Last updated
December 2014. https://www.oecd.org/els/soc/Focus-Inequality-and-Growth-2014.pdf.
OECD. 2016a. “How Good is Your Job? Measuring and Assessing Job Quality.” OECD
website, PDF. Last updated February 2016. https://www.oecd.org/sdd/labour-stats/Job-quality-OECD.pdf.
OECD. 2016b. “Routine Jobs, Employment, and Technological Innovation in Global
Value Chains.” Directorate for Science, Technology, and Innovation Policy Note, February
2016. https://www.oecd.org/sti/ind/GVC-Jobs-Routine-Content-Occupations.pdf.
OECD. 2017. OECD Guidelines on Measuring the Quality of the Working Environment.
Paris: OECD Publishing. https://dx.doi.org/10.1787/9789264278240-en.
OECD. 2018. Working Better with Age: Japan, Ageing and Employment Policies. Paris:
OECD. https://doi.org/10.1787/9789264201996-en.
Park, Cyn-Young Park. 2019. “Lifelong Learning and Education Policies to Capture
Digital Gains.” G20 Insights G20 Japan. Last updated June 14, 2019. https://www.g20-insights.org/policy_briefs/lifelong-learning-and-education-policies-to-capture-digital-gains.
PwC. 2018. “How Will Automation Impact Jobs?” PwC UK webpage. Accessed August
21, 2020. https://www.pwc.co.uk/services/economics-policy/,insights/the-impact-of-automation-on-jobs.html.
Randolph, Gregory and Hernan Galperin. 2019. “New Opportunities in the Platform
Economy: On-ramps to Formalization in the Global South.” G20 2019 Japan, PDF. Last
updated March 18, 2019. https://www.global-solutions-initiative.org/wp-content/uploads/g20-insights-uploads/2019/05/t20-japan-tf7-13-new-opportunities-in-the-platform-economy.pdf.
Seppälä, Emma and Kim Cameron. 2015. “Proof That Positive Work Cultures Are
More Productive.” Harvard Business Review, article, December 1, 2015. https://hbr.org/2015/12/proof-that-positive-work-cultures-are-more-productive.
Sethi, Bhushan and Carol Stubbings. 2019. “Good Work.” Strategy+Business blog, February
18, 2019. https://www.strategy-business.com/feature/Good-Work?gko=89684.
Sgroi, Daniel. 2015. “Happiness and Productivity: Understanding the Happy-Productive
Worker.” Social Market Foundation website, Global Perspectives Series:
Paper 4. Last updated October 2015. https://www.smf.co.uk/wp-content/uploads/2015/10/Social-Market-Foundation-Publication-Briefing-CAGE-4-Are-happy-workers-more-productive-281015.pdf.
Sheehy-Skeffington, Jennifer, and Jessica Rea. 2017. “How Poverty Affects People’s
Decision Making Processes.” Joseph Rowntree Foundation report, Last updated
February 2017. https://www.lse.ac.uk/business-and-consultancy/consulting/assets/documents/how-poverty-affects-peoples-decision-making-processes.pdf.
Smith, David, Sabah Meddings, Sam Chambers, and John Collingridge. 2020. “Unemployment
To Double As Coronavirus Ravages Economy.” The Times article, March
29, 2020. https://www.thetimes.co.uk/article/unemployment-to-double-as-coronavirus-ravages-economy-g8ljhgjdj.
United Nations. 2019. “Global Issues: Youth Employment Remains a Policy Challenge.”
World Economic Situation and Prospects, April 1, 2019. United Nations website,
briefing. un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/wesp_mb125.pdf.
Warhurst, Chris, Sally Wright and Clare Lyonette. 2017. “Understanding and Measuring
Job Quality.” CIPD research report, November 2017. https://www.cipd.co.uk/Images/understanding-and-measuring-job-quality-3_tcm18-33193.pdf.
Wood, Alex J., Mark Graham, Vili Lehdonvirta, and Isis Hjorth. 2019. “Good Gig, Bad
Gig: Autonomy and Algorithmic Control in the Global Gig Economy.” Work, Employment
and Society, 33, no.1: 56–75. https://doi.org/10.1177/0950017018785616.
World Bank. 2020, June 8. “COVID-19 to Plunge Global Economy Into Worst Recession
Since World War II.” World Bank website, Press Release. Accessed July 22, 2020.
https://www.worldbank.org/en/news/press-release/2020/06/08/covid-19-to-plungeglobal-economy-into-worst-recession-since-world-war-ii.