Basic income

Book Review: The Equality Effect: Improving Life for Everyone by Danny Dorling

Published by Anonymous (not verified) on Fri, 02/06/2017 - 8:42pm in

In The Equality Effect: Improving Life for Everyone, Danny Dorling delivers evidence that more equal countries enjoy better outcomes, with their populations being happier, healthier and more creative, producing less waste and committing fewer crimes. This optimistic book is a pleasure to read, writes Natasha Codiroli Mcmaster, and encourages us to see greater equality – and its social benefits – as being within our reach. 

If you are interested in this book, you may also like to watch a video or listen to a podcast of Danny Dorling’s recent LSE lecture, ‘The Equality Effect: Improving Life for Everyone’, recorded on 18 May 2017. 

The Equality Effect: Improving Life for Everyone. Danny Dorling. New Internationalist. 2017.

Find this book: amazon-logo

In The Equality Effect: Improving Life for Everyone, Danny Dorling takes a renewed look at the growing evidence that has amassed on the stark and clear differences between equal and unequal societies in the ten years since Kate Pickett and Richard Wilkinson published the groundbreaking book, The Spirit Level: Why More Equal Societies Almost Always Do Better. Levels of equality within countries are associated with a startling range of outcomes. In more equal countries, people are happier, more numerate, produce less waste and commit fewer crimes. The list goes on, and with complimentary illustrations by Ella Furness, Dorling outlines the supporting data in a clear and engaging way. The book is optimistic about the future but does not shy away from a critique of policies and practices within unequal countries.

The impacts of inequality are explored across three main areas, including impacts on children’s health, education and wellbeing; differences in environmental harm; and impacts on population and housing. Each chapter includes a number of scatter graphs measuring income equality within countries against one of the many outcomes explored. Whilst these charts are not fully convincing when taken alone, together the consistency of associations is difficult to ignore. In all cases presented, income equality is associated with positive social outcomes.

One key example involves the skills of individuals within countries. Numeracy in young adults is highest in countries with smaller differences between the incomes of the top and bottom 10 per cent of people. In the US and UK – both relatively unequal but also relatively wealthy countries – maths ability is far lower than many more equal but poorer countries. In Japan and Scandinavian countries, which have a more equal income distribution, mathematics ability is relatively high. Numeracy skills, along with other forms of knowledge, are extremely important not only for day-to-day functions but also for individuals to have a greater understanding of the way the world works and to make better decisions in a democracy. On the societal level, the acquisition of skills allows the country to perform better economically, and allows for more innovation within sectors.

Image Credit: Ella Furness (provided by New Internationalist)

Equality is also associated with environmental behaviour. In the Netherlands, over half of the population cycle or walk to work. In the US, where the income ratio is over double that of the Netherlands, less than ten per cent do. Meat, water and petrol consumption are also particularly high in the most unequal countries. The countries with the highest ecological footprints include the US and Singapore, both with an income ratio (between the top and bottom deciles) of over 15. Japan and New Zealand have the lowest ecological footprints and income ratios below 10.

Key issues around data availability and its interpretation across countries are another important theme highlighted throughout the book. Many countries have different measures of the same underlying construct, and these can even change within countries over time. One clear example of this is the measurement of crime. There is a clear association between the levels of inequality within a country and crime rates. However, what is classified as a crime, or the number of people who report certain crimes, can vary widely across countries. For example, in Finland, income differentials are relatively low, but crime is extremely high compared to other countries. This could reflect more crime overall, but is likely to be at least partly explained by the fact in Finland all speeding offences are recorded as crimes. In many countries (including the UK) the majority of speeding offences are classed as ‘non-notifiable’, and not included in national statistics.

The Equality Effect offers an optimistic view of the future. Whilst stark inequalities are observed globally, overall the majority of countries are becoming more, rather than less, equal. It is difficult to see these shifts in part due to the negative bias in media reporting. The fact that we perceive inequality as being worse than before makes high pay differentials more likely to be reported, and thus to seem more likely overall. Therefore, when inequalities decrease, the focus of debate is not on this but on inequality itself. More equal societies also rarely leave much of a mark on history. Dorling points out that the pyramids in Egypt and many other great temples could only be made through the enslavement of others.

The fact that this increase in equality is not occurring at the same rate across countries, as well as the high inequality in wealthy countries including the US and the UK, allows us to see the negative impacts of inequality most clearly. If we were all moving towards equality at the same speed, it would be more difficult to attribute subsequent positive outcomes to this, and easier to argue that the increasing wealth of the few would eventually trickle down to the many. Whilst previously popular, this latter argument has been notably absent from political discourse even in the relatively unequal UK. Dorling argues that this represents a change in thinking about inequality, which will ultimately lead to better societies.

Dorling focuses on the changing rhetoric around basic income as an example of the fact that globally we are becoming more open to the idea of more equal societies, but also as an important next step in achieving equality. A basic income would allow everyone a base salary whether they are in work or not. Basic income is understandably argued to be unfair – why should some people get money for nothing whilst others work hard? In practice, however, no one gains if there are people living in poverty. The majority of people who do not work are unable to do so or are temporarily unemployed. A basic income would allow people to take up training, or to follow their passions rather than just take a job to survive. And with automation making many menial jobs redundant, the best way to harness human workforce in the future will likely be through greater creativity and innovation.

A recent survey of public sentiment towards basic income across EU countries suggests that around 31 per cent people would be in favour of the introduction of basic income immediately, and a further 48 per cent would be in favour following successful trials. In the UK we have the groundwork for a basic income for those people who cannot work: however, this has been eroded in recent years through successive cuts to benefits. Basic income has recently been trialed in India with evidence of positive impacts on a range of outcomes including health, nutrition and labour market participation, and in Finland with some preliminary indication of positive impacts on mental health. There are further plans to runs trials in Canada, Kenya, Uganda, the Netherlands, the US and Scotland.

I was left with some questions about the dynamics of different types of equality. The focus is on income inequality across all groups. Whilst issues of gender, racial and other types of inequality are touched upon, it would be interesting to compare levels of these types of inequality with levels of income equality overall. For example, are gender disparities always smaller in more equal countries? And if there are examples where this is not the case, why would this be? This may be a welcome focus of further academic study.

The Equality Effect was a pleasure to read, and because the book covers research from such a broad range of disciplines, I would recommend it to anyone interested in in/equality or quantitative research more generally. The take home message of the book is that whilst it may take some time, greater equality is within our reach, and it is within our power to accelerate this process.

Natasha Codiroli Mcmaster is a PhD student based at the Institute of Education, UCL. Her research focuses on inequalities in education, and her most recent research considered disparities in students’ subject choices. She has also worked as an analyst at the Department for Work and Pensions on projects aimed at understanding the drivers and consequences of disadvantage.

Note: This review gives the views of the author, and not the position of the LSE Review of Books blog, or of the London School of Economics. 

ARTICLE: Jason Hickel on Why Basic Income is a Birthright

Published by Anonymous (not verified) on Sun, 16/04/2017 - 4:30pm in

In a recent article for The Guardian, Jason Hickel writes that “a basic income could defeat the scarcity mindset, instil a sense of solidarity and even ease the anxieties that gave us Brexit and Trump.” Hickel argues that a basic income is not just a privilege, nor just a nice idea – instead, basic income is a birthright. Hickel begins

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The False Promise of Universal Basic Income

Published by Anonymous (not verified) on Mon, 10/04/2017 - 11:00pm in

Long dismissed as utopian, proposals for a universal basic income are now gaining traction on both the right and the left. But UBI’s supporters on the left should proceed with caution.

Continue Reading…

The Automation Grift: Robots Are Hiding From The Data But Not From The Pundits –Part 1

Published by Anonymous (not verified) on Wed, 05/04/2017 - 8:09am in

It’s conventional wisdom among pundits that automation will cause mass unemployment in the near future, fundamentally changing work and the social relations that underpin it. But the data that should support these predictions do not. Part 1 of this article contrasts this extreme rhetoric and the data that should support the inevitable robot apocalypse, and finds that these predictions are likely motivated by politics or outlandish assessments of technology, not data. Part 2 assesses the technology behind these predictions, and follows a thread from the mid-20th century onwards. Subsequent parts will examine the political economy of automation in both general and specific ways, and will also discuss what the future should look like — with or without the robots.

Illustration: Heske van Doornen

The Automation Grift: The Robots Are Hiding From The Data But Not From The Pundits – Part 1

By Kevin Cashman

The Rhetoric

Few things are more breathlessly written about than automation and how it will affect society. In the mainstream discourse, technology writers, policy wonks, public relations hacks, self-stylized “futurists,” and others peddle their predictions and policy prescriptions, as if they are letting the rest of us in on a secret rather than following in a long history of over-enthusiastic predictions and misplaced priorities. Others view automation as a panacea for social problems. Either way, mass unemployment is usually at the center of this narrative and how workers, especially poorer workers, will become outmoded in the age of robots. In the waning days of the Obama administration, the White House joined the frenzy, publishing a report warning about the dangers automation posed to workers as well as the benefits of technology.

This report cited (and further legitimized) a 2013 report that boldly claimed that 47 percent of occupations were at risk from automation in the next two decades. Since its release, this study has been cited close to 900 times. Other predictions are just as bold. One is that the entire trucking industry will be automated in the next ten or so years. “Visionaries” like Bill Gates, Stephen Hawking, and Elon Musk use their stardom to add to the fears of these claims — and push for policies that don’t make much sense, like taxing robot workers or creating a basic income that is an excuse to eviscerate our other social programs and do other bad things. Still others blame automation for causing past problems, like the loss of manufacturing jobs in the U.S., when they are easily explained by political decisions, not economic realities.

With all this interest and all these forecasts, you’d think there would be evidence that automation is affecting the economy in a significant way. Indeed, economists have determined a measure for “automation”: productivity growth. As productivity growth expresses the relationship between inputs (e.g. robots, people, machines) and outputs (i.e. goods and services), it should be a decent and measurable proxy for automation. More automation and robots would result in greater outputs for fewer inputs, which would show up clearly in the data. This is because replacing humans with robots only makes economic sense if it saves money or increases output. In both of these scenarios, productivity would increase.

The Data

So what do the data points say? They show that productivity growth on an economy-wide scale has been very low for the past ten or so years, at a rate that is a bit over 1 percent annually. (In fact, multifactor productivity — productivity of all combined inputs — decreased 0.2 percent in 2016, the first decline since 2009.) The previous ten years — the mid-1990s to mid-2000s — was a period of moderate productivity growth, or just over 3 percent annual productivity growth. From the mid-1970s to mid-1990s, there was another period of slow growth. And before that, there was a sustained period of moderate growth post war until the mid-1970s: the so-called “Golden Age” of prosperity. These data points do not support the assertion that automation is happening on a large scale.

It is important to note that productivity growth and automation are constantly happening, and that automation can affect small industries or occupations in big ways. It can also replace individual tasks but not entire jobs themselves; for example, you may order your food on a computer at a restaurant rather than talk to a waiter, who would still deliver your food. These things may not show up in the data because they do not represent fundamental changes to the entire economy. In other words, automation on a small scale is not evidence that automation will cause a sea change in how work is done: it is normal.

Other macroeconomic indicators support the low rate of productivity growth seen today. The labor market has still not recovered to pre-recession levels, levels which were depressed compared to the highs of the late 1990s and early 2000s. Growth in wages and employment costs have also been relatively low. Since these indicate that there is still considerable slack in the labor market (i.e. in general it is easy to fill open positions, and there are many more applicants than open positions) there is less pressure to automate. After all, why would businesses en masse invest in automation on a significant scale if they can find desperate workers willing to be paid minimum wage?

History also provides useful data points. Technological change and its effects on the labor market have been consistently overstated in the past, which is acknowledged by even mainstream economists. If anything, this is evidence that automation is good for the economy because it creates jobs, in net, and it creates new sectors of the economy. It also can increase living standards by, for example, shortening work weeks or improving conditions of work (and together with organized labor, this happened in the “Golden Age,” which is how it got its moniker).

Supporters of the robots-are-taking-all-of-our-jobs myth usually ignore this evidence. They’ll say that productivity growth cannot take into account the changes that are happening and that automation will have catastrophic effects on the labor market either way. While there are legitimate debates to be had on how to measure automation, the reality is that despite all the spilled ink, the robot boosters do not have history or the data on their side. It is only their analysis of the technology that supports their assertions. They think that there is something extraordinary about the technological change that is happening now and it will be transformative, in contrast to the slow and steady automation that occurred in the past, where benefits were realized over a long horizon.

Part 2 will assess the technology behind these predictions.

About the Author
Kevin Cashman lives in Washington, DC, and researches issues related to domestic and international policy at the Center for Economic and Policy Research. Follow him on Twitter: @kevinmcashman.

The post The Automation Grift: Robots Are Hiding From The Data But Not From The Pundits –Part 1 appeared first on The Minskys.

BitNation: Recent Advances in Cryptocurrency See Basic Income Tested

Published by Anonymous (not verified) on Thu, 30/03/2017 - 5:30pm in


News, Basic income

Johan Nygren, a basic income activist, is currently exploring if basic income can be implemented using cryptocurrency. Cryptocurrency are digital currencies whose value and number of units are regulated by encryption techniques, outside of any central banking system. A cryptocurrency-based basic income will be funded with taxes grown within a peer-to-peer (P2P) network. P2P is an architecture for building computer

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Brian Eno on basic income

Published by Matthew Davidson on Mon, 24/10/2016 - 5:00pm in

From an item in this weeks reading (transcription provided by the author of the item):

"I often get asked to come and talk at art schools, and I rarely get asked back, because the first thing I always say is, ‘I’m here to persuade you not to have a job.’ … My first message to people is: try not to get to a job. That doesn’t mean try not to do anything. It means try to leave yourself in a position where you do the things you want to do with your time, and where you take maximal advantage of whatever your possibilities are. The obstacle is that most people aren’t in a position to do that. I want to do anything to work to a future where everybody’s in a position to do that. … [T]he concept [of basic income] is the closest thing I’ve heard to achieving the kind of future that I would like to live in."