76 billion dollars. That’s what it would cost to implement basic income in Canada according to a new report released by the Parliamentary Budget Office (PBO).
The report comes just days after Ontario began testing its own basic income pilot study in Hamilton, Brantford, Brant County, Lindsay and Thunder Bay. As part of the study, 4000 Ontarians will receive unconditional cash transfers of up to $2500 per month for the next three years. The new report estimates how much it would cost to roll out the program nationwide.
Importantly, the policy under consideration would not be an universal basic income, and would only be available to low-income individuals between the ages of 18 and 64. Roughly 1 in 5 Canadians (7.5 million people) would qualify for benefits. The plan would guarantee a minimum annual income of $16,989 for singles, and $24,027 for couples (those with a disability could receive an additional $500 per month).
The report also assumes that the guaranteed basic income (GBI) would replace $33 billion in federal spending already in place to help low-income people, thus bringing the net cost of implementing the program down significantly to $43 billion.
The report has drawn both praise and criticism from both sides of the debate. Opponents of the idea (including Conservative MP Pierre Poilievre, who requested the PBO study) cite the high cost of the program, arguing that the plan would add an additional 13 percent to the current federal budget.
Supporters argue that the report actually underestimates the value of a minimum income by not taking into account potential savings in other areas of the economy. Elaine Power, a professor in public health at Queen’s University, notes that a basic income could save the government up to $28 billion in healthcare costs directly attributable to poverty. Andrew Coyne, a columnist at the National Post, also suggests that local governments would likely share the cost burden, which could knock an additional $20 billion off the federal price tag.
Currently, there are no plans to implement a nationwide guaranteed basic income in Canada. However, the report marks the first attempt by the federal government to estimate what such a program might cost. In order to further assess the viability of basic income in Canada, all eyes will surely be on the Ontario pilot study in the years to come.
More information at:
André Coelho, “ONTARIO, CANADA: Applications for basic income pilot project reach residents at Thunder Bay and Hamilton“, Basic Income News, 29th June 2017
André Coelho, “CANADA: Quebec is implementing a means-tested benefit, not a basic income”, Basic Income News, 24th January 2018
Rob Rainer, “A basic income for working-age adults is within fiscal reach“, 19th April 2018
As many as 375 million people may have to switch jobs as a result of automation by 2030. This is according to a new report published by the McKinsey Global Institute (MGI), a private sector think tank and the business and economics research arm of McKinsey & Company.
According to MGI researchers, “the transitions will be very challenging – matching or even exceeding the scale of shifts of agriculture and manufacturing we have seen in the past.” Such dramatic shifts in the global labor market will demand proportionately dramatic responses from governments, businesses, and individuals. Specifically, the MGI report emphasizes the importance of providing transition and income support to workers.
The report, entitled “Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation”, builds on previous MGI research suggesting that 50% of global work activities could theoretically be automated by modifying existing technologies. While only 5% of jobs are at risk of disappearing entirely, 6 in 10 of jobs have 30% of constituent work activities that could be automated. According to MGI researchers, the question is not whether or not automation will alter the nature of work, but how long it will take.
Their analysis model potential net employment changes over 12 years for more than 800 occupations in 46 countries, focusing particularly on China, Germany, India, Japan, Mexico, and the USA. The report also accounts for several factors that could affect the pace of automation including technological and financial feasibility, demographic changes to labor markets, wage dynamics, regulatory responses, and social acceptance.
The report finds that 75 million to 375 million workers, or 3 – 14% of the global workforce, may be displaced by automation by 2030. These effects will be particularly felt in high income countries. In the most extreme scenario, 32% of American workers (166 million people), 33% of German workers (59 million people), and 46% of Japanese workers (37 million people) will be forced out of their jobs by 2030.
However, there may not be any shortage of new jobs available. MGI’s researchers note that new jobs will need to be created to care for aging societies, raise energy efficiency, address challenges posed by climate change, provide goods and services to the growing global middle class, and build new infrastructure.
Automation itself may also have the potential to create at least as many jobs as it destroys. Historically, transformative technological advancements have often led to significant jobs growth across industries.
The real challenge will be to ensure a smooth and stable transition between jobs. According to MGI research, automation is likely to disproportionately affect workers over 40, and sustained investments in retraining programs will be necessary to prepare midcareer workers for new employment opportunities. The report notes that this will require “an initiative on the scale of the Marshall Plan…involving collaboration between the public and private sectors.”
The MGI researchers also emphasize the need for increased financial support during transitions. Workers will need unemployment insurance to compensate for lost wages, as well as supplemental income to offset wage depressions typical in transitioning economies. A universal basic income (UBI) may be capable of satisfying both needs.
The report points to completed UBI trials in Canada and India, which showed no significant reduction in work hours and demonstrated increases in quality of life, healthcare, parental leave, entrepreneurialism, education, and female empowerment. The report also references ongoing and planned UBI experiments in the United States, Uganda, Kenya, Spain, the United Kingdom, and the Netherlands as programs to watch in the years to come.
The worldwide spread of automation may be inevitable, but according to researchers at the McKinsey Global Institute, the demise of human labor is not. Whether or not we can respond effectively to the needs of a changing economy will depend largely on our ability to ensure a secure and stable transition for displaced workers.
More information at:
James Manyika, Susan Lund, Michael Chui, Jacques Bughin, Jonathan Woetzel, Parul Batra, Ryan Ko, and Saurabh Sanghvi, “What the future of work will mean for jobs, skills, and wages”, McKinsey Global Institute, November 2017
In the three years since its initial publication, Rutger Bregman’s Utopia for Realists has helped spur a global conversation on universal basic income (UBI). The book has become an international bestseller, garnering praise from intellectual heavyweights and propelling its author to the TED stage this past April. However, Stephen Davies, education director at the Institute for Economic Affairs (IEA), remains skeptical of many of the young Dutch journalist’s ideas. He makes his case in the most recent edition of the Journal of Economic Affairs.
“Rutger Bregman’s book is both interesting and irritating,” declares Davies in the opening line of his review. To clarify, he quickly notes that it is interesting “not so much because of its particular content…but because it gives us an insight into what may turn out to be a development of both intellectual and political importance” (p. 442). Such an off hand rejection of a book advocating basic income from the education director of a think tank advocating free market capitalism may be unsurprising to some, but Davies’ response is actually not as inevitable as it may seem. Historically, UBI has found supporters on both sides of the political divide.
Davies distinguishes between two types of arguments Bregman makes for basic income. The first considers UBI to be a pragmatic solution to the shortcomings of the current social welfare system. The second considers it to be a necessary means of radically transforming the existing social order. While Davies may be more sympathetic to the second line of reasoning, he spends most of his time critiquing the first.
Steven Davies. Credit to: The London School of Economics and Political Science
In Utopia, Bregman draws on a wealth of research to highlight deficiencies in the means-tested benefit programs that constitute the welfare states of most developed societies. He notes that many of these programs create negative incentives, keeping beneficiaries locked in a poverty trap. Even worse, financial instability can result in a scarcity mindset, making it even harder for poor people to make responsible financial decisions. According to Bregman, unconditional cash transfer programs (UCTs) have proven to be the most successful remedy to this vicious cycle of poverty and dependence. In support of this view, Bregman offers additional in-depth analyses of related programs, including Richard Nixon’s Family Assistance Plan, negative income taxes, and the Speenhamland system.
Davies acknowledges the implications of this body of research. He writes, “Much of the evidence presented by Bregman is indeed very striking and should encourage us simply to trust people more and have greater confidence in their judgment and their knowledge” (p. 447). However, he is far more hesitant to interpret these results as evidence for universal basic income.
Davies notes that many of the policies Bregman touches on are in fact means-tested in one way or another, and may therefore be more analogous to standard welfare programs than basic income. Additionally, Davies argues that many of the UCT programs discussed in Utopia for Realists have not been around long enough to show lasting impacts, and he calls for more research to determine the specific amounts at which UCTs can begin to induce behavioral change. Yet, even more worrisome for Davies is the “bold assumption that there is no meaningful distinction between single lump-sum payments and continuing income stream” (p. 448). He notes that while individual cash transfers may bring sudden and liberating benefits, similar effects of ongoing basic income payments may become muted over time.
According to Davies, all of this “reveals confusion over what a UBI is thought of as being – is it a way of establishing a floor or minimum that is guaranteed to all or is it a redistributive mechanism designed to narrow income differentials?” (p. 449). This confusion motivates Davies’ second critique of Bregman’s argument for universal basic income as a response to the widening global wealth gap. While basic income programs may go a long way in ensuring no one lives in a state of absolute poverty, Davies writes that “it is not clear how a UBI by itself will do anything to reduce relative poverty or inequality” (p. 449). In fact, he notes it may even make the problem of inequality worse if UBI programs seek to replace other means-tested benefits.
However, while Davies takes issue with many of Bregman’s pragmatic arguments, he seems much more sympathetic to the idealistic aspects of his account. As automation increases and “bullshit jobs” proliferate, Davies grants Bregman his assumption that UBI could become a useful tool to decouple meaningful activity from paid work. He writes, “This is clearly the vision that truly inspires Bregman, the utopia of his book’s title, and he would have done better to stick to this rather than muddy the waters by conflating it with more limited and pragmatic discussions of a guaranteed income in a society where wage labor is still widespread and predominant” (p. 456).
While he may be unmoved by Utopia for Realists, Davies clearly recognizes the significance of the political and intellectual movements it represents. The book’s international success seems to reflect a growing anxiety about stagnation of big ideas in the face of an increasingly unsatisfying status quo. Davies concludes, “What we are starting to see is an attempt to work out what a non-capitalist or, more accurately, a post-capitalist political economy would look like” (p. 457).
Davies review appears in the most recent edition of the Journal for Economic Affairs.
Recently, there has been a great deal of attention paid to the changing nature of work. From rising automation to the ever-expanding gig economy, the effects of shifting labor landscapes are being felt by governments, businesses, and workers around the world. A new report from Deloitte, a global consulting firm, in partnership with the Human Resources Professionals Association, wades into this discussion with an analysis of the Canadian workforce. In addition, the report offers an array of potential public policy responses to address disruptive trends in the labor market including a shorter workweek, flexible education pathways, and a basic income.
In the report, authors Stephen Harrington, Jeff Moir, and J. Scott Allinson provide analysis based on interviews with 50 leading experts, as well as a review of the relevant literature. The authors argue that Canada is on the verge of an “Intelligence Revolution” that will be shaped by three dominant trends: machine learning, increasing computing power, and automation. These “waves of disruptive change” are already being felt in the Canadian economy, and their effects will become increasingly significant over the next decade.
Specifically, the report identifies two overarching themes that have already begun to impact labor markets. First, as work becomes more decentralized, workers are increasingly finding themselves in temporary or contingent jobs. These “contingent workers” bring their skills to specific projects or tasks, moving on when the task is completed, and work for multiple companies simultaneously. These arrangements form the basis of the gig economy. Second, the researchers argue that automation is opening up new opportunities for collaborative work between machines and humans. While automation can cause job displacement in the short term, the researchers contend that new job opportunities will continue to arise as productivity increases.
However, the report also notes that individuals and institutions seem ill-prepared to adapt to the rapidly increasing pace of change. In Canada, the number of contingent workers has grown from 4.8 million in 1997 to 6.1 million in 2015. Today, approximately 1/3 of Canadian jobs are for contingent workers. However, temporary positions still pay 30% less on average than permanent positions, and private sector pension plans only cover 24% of the Canadian workforce. At the same time, while 41% of organizations have “fully implemented or made significant progress in adopting cognitive and AI technologies”, only 17% of business leaders report feeling ready to manage a workforce of robots, AI, or humans working side-by-side (p. 17).
In response, the report’s research team offers several suggestions. Eight job archetypes of the future are presented, and individuals are advised to develop “future-proof” human-centered skills in judgment, leadership, decision making, social awareness, systems thinking, and creativity. The report also recommends integrated partnerships between businesses and educational institutions to enable workers to meet the needs of a changing labor market.
However, the researchers also note that efforts by individuals and businesses alone will not be sufficient for Canada to “emerge as a winner in the Intelligence Revolution.” To this end, policy reforms must be adopted to reflect both the challenges and opportunities of a 21st century economy. Among these recommendations are a shorter workweek, increased consumption taxes, decreased income taxes, unemployment insurance, and a renewed commitment to immigration. Additionally, basic income is offered as a means to address rising automation. The researchers suggest that basic income may ease the strains of job displacement, provide support for individuals engaged in volunteer or social enterprises, and encourage entrepreneurial risk-taking.
You can read the report in full here.
In recent years, basic income has found support across the political spectrum. While some have justified it as a human rights issue, others believe it to be necessary in the fight against poverty and rising inequality. According to many supporters, these are sufficient justifications in their own right. However, many basic income proponents also cite the growing threat of automation to employment. Put simply, as robots become smarter and cheaper, more and more workers will find themselves out of a job, and basic income programs will be required to offset rising unemployment and job displacement. This view is particularly popular in Silicon Valley and has been championed by the likes of Elon Musk, Richard Branson, and Mark Zuckerberg. However, a new report from Pearson, an education publishing company, challenges this line of reasoning.
Pearson’s analysis, with help from researchers at Nesta and the Oxford Martin School, diverges from previous reports on automation (Frey & Osborne, 2013; Arntz et. Al, 2016; McKinsey, 2017; Richard Berriman, 2017) in two key respects. While previous studies have tended to focus exclusively on the potentially destructive effects of automation, Pearson’s report also incorporates the potential for growth in jobs and skills that may be complemented by automation. The study also considers how automation may interact with seven specific global trends to affect supply and demand in the labor market over the next decade: (1) environmental sustainability, (2) urbanization, (3) increasing inequality, (4) political uncertainty, (5) technological change, (6) globalization, and (7) demographic change.
Pearson’s report relies on a combination of expert testimony and, perhaps fittingly, machine-learning. Two panels of artificial intelligence experts in the United States and United Kingdom were asked to rate the future prospects of thirty occupations in the context of the seven global trends identified by the researchers, and to report on how certain they were in their predictions. This information was then fed into machine-learning algorithms, along with data from the U.S. Department of Labor, to generate predictions for more than 1,000 occupations in the United States and United Kingdom.
Using this model, the researchers at Pearson reached the following six conclusions:
- 20% of the workforce are in occupations that will shrink.
This figure is smaller than previous high-end estimates of 47% (Frey & Osborne, 2013), but also larger than more conservative estimates of 9% (Arntz et. Al, 2016). In line with previous findings, Pearson reports that routine, physical or manual abilities will become less valuable over time. However, Pearson also notes that certain sectors typically considered doomed by automation such as agriculture, trades, and construction, may actually show pockets of job growth where new skills are required to complement new technologies. So, it can be said that there cannot be a complete elimination of people in the workforce. Instead, building skill sets to work alongside automated machines could be the way to go. For example, with large industries adopting newer technologies and automation to improve the production process, an automation parts supplier could be the need of the hour, as there will always be a requirement for people who have the necessary knowledge to handle new machines and implement efficient functionalities.
- 10% of the workforce are in occupations that will grow.
Specifically, the researchers argue that jobs involving judgment and decision making, teaching, active learning, interpersonal skills, complex problem-solving, originality, fluency of ideas, and systems thinking will all grow in value. Jobs in high demand will include teachers and education professionals, sports and fitness workers, caregivers, managers, hospitality workers, legal professionals, and engineers. Occupations in the public sector, as well as those resistant to globalization, emerge as particularly resilient. Further, jobs in the construction sector and those that involve outdoor manual work could also need constant manpower, as we see companies such as Crane Renovation Group reaching out to potential workforce to increase hiring and provide consistent jobs. Pearson also points out that jobs and skills that will become more valuable are not specifically confined to any one particular income bracket or skill level.
- 70% of the workforce are in occupations where their future is uncertain.
- So-called “21st century” skills will experience higher demand.
- Both knowledge and skills will be required for the future economy.
- Occupations can be re-designed to pair uniquely human skills with technology.
A global leader in education publishing itself, Pearson argues for sweeping reforms to education systems so that they may adapt faster to the changing needs of labor markets, and begin offering more flexible pathways to employment including credentials and microdegrees. Pearson also advises business leaders to start thinking of ways to redesign roles to balance technological and human resources. Finally, the researchers encourage individuals to develop skills that are “uniquely human” and commit to becoming lifelong learners.
However, the report is not without limitations and the researchers note the large degree of uncertainty baked into any analysis of job creation, which is notoriously more difficult to predict than job destruction. Critics have also argued that Pearson greatly underestimates the difficulty of implementing public and private reforms in the context of the political and social turbulence accompanying severe job displacement.
Nevertheless, despite these limitations and the challenges that lie ahead, Pearson’s researchers remain optimistic about the future of work. They summarize their findings rather succinctly: “The bottom line of our research, we can all stop agonizing about machines taking our jobs.”
You can download the full report here, or visit the microsite.