In the first of a new series focusing on data and statistics, the OECD’s Matthias Rumpf looks at how much public servants are paid in some OECD countries.
Few issues are more likely to provoke a row than the pay of public servants – overpaid and underworked or selfless heroes who could be earning more in the private sector? We can’t settle that debate here, but, using data from Government at a Glance 2013, we can at least give you some sense of how public sector pay compares across some OECD countries.
The most basic approach is simply to look at annual compensation in USD – in other words, salaries paid in local currencies converted into US dollars and then adjusted for purchasing power parity, a statistical technique used to compare the cost of living in different countries.
That’s useful, but it doesn’t show how public servants’ pay compares to that of other workers in their own countries. To do that, we can look at their pay relative to all tertiary educated – in other words, people with a college or university degree. That measure is especially useful for comparing the pay of senior public servants, who typically are graduates. In OECD countries, the most senior managers in the public service earn 3.4 times more than the average graduate, suggesting that such careers are an attractive option for graduates.
One last comparison: public service pay relative to GDP per capita. “GDP per capita” is calculated by dividing the size of a country’s population into its GDP, and it gives a sense of how prosperous people feel in each country. It’s probably especially useful in making comparisons of pay for junior staffers, such as secretaries. In Poland and the Netherlands, their pay levels are well above GDP per capita but in the Slovak Republic and Estonia they’re well below.
OECD work on public employment and management
Government at a Glance 2013 (OECD, 2013)
Public Sector Compensation in Times of Austerity (OECD, 2012)
In the second of two postings, we look at the impact of artificial intelligence on our societies and economies.
Back when Amazon mostly sold books, it hired writers and editors to come up with helpful reviews and recommendations. The aim was to create the atmosphere of a friendly local bookshop. But the writers and editors didn’t last. They were replaced by Amabot, an algorithm that picked up on users’ browsing and buying history.
Amabot’s buying recommendations were – and are – often eerily accurate, but even some of Amazon’s own people didn’t much like the software robot. As Steve Coll writes, one anonymous staffer even vented his spleen in a newspaper ad: “Thanks for nothing, you jury-rigged rust bucket. The gorgeous messiness of flesh and blood will prevail!”
Will it? Just over a decade since that ad appeared, the rust buckets are becoming more powerful by the day. Even sober commentators like the Financial Times’ Martin Wolf speak of the dawn of a “second machine age,” one in which machines “will replace and multiply our intelligence.” And how about flesh and blood – i.e. you and me? To return to Martin Wolf’s theme, it depends on whether your intelligence is about to be multiplied or replaced.
Wolf’s theme is explored in greater depth in Average is Over by the influential economist Tyler Cowen, who argues that only a fairly small number of workers – perhaps 10 to 15% in the U.S. – will have the sort of skills that can be complemented, or multiplied, by computers. As a metaphor for the carbon-silicon partnerships that will succeed in the high-tech economy, he uses “freestyle chess,” where players are allowed to augment their skills with computers. For example, while a computer might need to scroll through all the possible moves in a chess game before making a decision, a human partner could use intuition and insight to spot an opening and then instruct the computer to focus on pursuing that opportunity. In this case, the combination of human and computer is stronger than either human or computer alone.
But what about everyone else? Well, if you can’t add value to the computer you may be at increasing risk of simply being replaced by it. According to estimates by Carl Frey and Michael Osborne, 47% of jobs in an advanced economy like the U.S. are at risk from computerization, adding to the long list of jobs that have already been lost to technology. As Bill Gates warned recently, “Technology over time will reduce demand for jobs, particularly at the lower end of skill set. … I don’t think people have that in their mental model.” But the technology revolution won’t just affect people working in low-skill, highly routinized occupations. As Tom Meltzer notes, it will also increasingly threaten the jobs of lawyers, architects and doctors (even writers won’t be immune).
Of course, these fears may be overstated. Technology has repeatedly replaced jobs in the past – think of hand-weavers and phone operators – but people still found something new to do. Still, even if we don’t head into an era of mass unemployment, there seems little doubt that the second machine age will drive an even bigger wedge into the division of economic spoils, deepening still further the trend of rising income inequality in the coming decades.
According to a recent OECD paper, earnings inequalities in countries that are today regarded as relatively egalitarian, such as Italy, Sweden and Norway, will by 2060 match levels currently found in the U.S. Most of the gap in earnings will be concentrated between high and middle-income earners.
How can societies respond? The Dutch economist Jan Tinbergen ascribed much of the widening in income gaps to a “race between education and technology”. When education levels are rising relative to improvements in technology, the gap narrows; when they’re falling, it widens. That’s why so much policy discussion in this area, including the OECD paper, emphasises education investment, especially building strong foundations in children’s early years.
But with technology now racing so far ahead of education, societies will clearly need to consider other options. These could include, perhaps, even deeper income redistribution than we see today, effectively subsidising people to work less.
That’s not such a new idea: As long ago as the 1930s, the economist J.M. Keynes foresaw a time when economic wealth and automation allowed people to work a 15-hour week. More recently, Google’s Larry Page revived the idea in an interview with The Guardian: “In Page’s view robots and machines should be able to provide a ‘time of abundance’ where everyone’s basic needs could be met relatively easily.” How would you spend all that spare time? No doubt Amabot could recommend a few good reads to fill the long hours.
Divided We Stand – Why Inequality Keeps Rising (OECD, 2011)
In the first of two postings, we look at the impact of artificial intelligence on our societies and economies.
How do you feel about robots? Do you look forward to one day lying by the pool sipping a piña colada mixed by your beaming electronic buddy? Or do you expect to die cowering in your hovel as an army of metal men batter down the door?
Wherever you stand, it’s hard to feel completely indifferent about robots. That’s no accident: Today, robots are real – think of the Roomba vacuum cleaner – but for most of human history they were figments of our imagination. Long before the word “robot” was coined by the Czech writer Karel Čapek in the 1920s, humans told tales of artificial life – from the Golem of Jewish culture to Frankenstein’s monster. By serving up an image of a creature that was like us, but not one of us, these fictions reflected, in part, on what it means to be human.
In the 20th century, this fictional role switched, and the robot became increasingly a “way of exploring human feelings about technology,” according to The Economist’s Oliver Morton. By and large, those explorations have gone in one of two directions – either towards a utopia where robots serve humanity or a dystopia where they steal our jobs.
Over the coming years, we’re likely to need to think even more about these questions as robots – and artificial intelligence more generally – move out of the pages of fiction and into our lives. This past year has bought a wave of evidence that this is happening much faster than we might have expected.
When Japan’s Prime Minister Shinzō Abe visited OECD Week back in May, he referred to robots and robotics several times in his speech as he pledged to “create a ‘new Industrial Revolution’ through the use of robots”. Japan is not alone: In July, a British agency unveiled a robotics strategy targeted at helping the UK to “win a much bigger share of a potential £70bn global robotics market by 2025,” according to the Financial Times.
Business, too, shows growing signs of interest. In recent months Google has bought eight robotics companies, while a couple of years ago Amazon bought robot-maker Kiva Systems for an eye-popping $750 million. Even China, which built an economic miracle in part on cheap human labour, is turning to robots. Officials in Guangzhou, a manufacturing hub in the south of the country, report that demand for factory robots is rising by 30% a year, the China Daily reports.
Why all the interest? To a large extent it reflects the fact that the cost of physical “robots” and software “bots” is falling rapidly while their capacity is soaring. As Richard Waters notes in the FT, three key factors are helping to bring this about.
First, the cost of computing power is falling relentlessly, fulfilling Gordon Moore’s long-ago prediction of a doubling in such power every two years. Second, digital data is becoming increasingly abundant, allowing the development of ever more subtle pattern-recognition software. Humans are highly skilled in pattern recognition – it’s why we’re so good at chess and at spotting minute differences human faces. Computers are still playing catch up, but the gap is narrowing – they can already beat us at chess. And, third it’s becoming ever-easier for us poor humans to communicate and interact with complex software systems – if you’re one of those lucky people with an accent that Siri actually understands, you’ll know all about this.
Indeed, the role that smartphones are playing in driving robot technology is notable. “Most of the components in smartphones are [the] same ones you need in robots—sensors, cameras, batteries, processors,” according to Dmitry Grishin, who runs a fund that invests in robotics. “The biggest difference between now and 20 years ago is that the components have become cheap.”
Of course, no technology can thrive unless it meets a need. And, here again, it looks as if the robot’s moment has come. The success of gadgets like robot cleaners, drones and robot cow-milkers (yes, really) is likely to drive demand for more. But other factors, such as our ageing societies, are also playing a role. The European Union’s Silver project is investigating the use of robots to support old people living independently, while in Japan, one of the best-known robots is Paro, a cuddly seal for the elderly and the ill.
So, whether we like it or not, the robots really are coming. A good thing or not? We’ll return to that question soon.
OECD work on science, technology and innovation
Today’s post is from Gyan Chandra Acharya, United Nations Under-Secretary-General and High Representative for the Least Developed Countries, Landlocked Developing Countries and Small Island Developing States. This is one in a series of ‘In my view’ pieces written by prominent authors on issues covered in the Development Co-operation Report 2014: Mobilising resources for sustainable development.
The UN classifies as “least developed countries” those nations that are the bottom of the development ladder from all perspectives. The category was created in recognition of the deep-seated structural constraints these countries face, resulting in low per-capita income, weak human capital and high economic vulnerability. Without help, they are unable to adequately address their development challenges, irrespective of the efforts they may make. Moreover, they are the most exposed to economic shocks and degradation of natural capital, including through climate change. Their need for enhanced and targeted support from the international community is obvious.
Of the 48 least-developed countries, 34 are in Africa, 13 in the Asia-Pacific region, and one, Haiti, in Latin America and the Caribbean. Together they are home to about 900 million people, with a relatively high share of young people among their populations. Over the past decade, the least developed countries have made progress in many of the areas targeted by the Millennium Development Goals (MDGs): they have reduced child and maternal mortality, increased enrolment in primary education, and improved gender equality and women’s empowerment. Yet they still have a very long way to go, and around 50% of their population remain poor.
These countries hold great potential and are rich in human and natural resources – two inseparable characteristics for their people, who live close to nature. A holistic focus on improving health and education, building productive capacity and protecting natural capital would greatly contribute to transforming their economies, enabling them to leapfrog to green economies with relatively few trade-offs.
The least developed countries are and will continue to be — at least in the short and medium term — among the countries most dependant on ODA. This source of development finance constitutes more than 50% of their inflows and public finances and except in the mineral-rich countries, foreign direct investment in these countries is minimal. While they have been gradually widening their domestic resource base through tax reforms, on average across the least developed countries the ratio of government revenues to GDP stands at about 13% and gross domestic savings reach only 15% of GDP. Yet the investment required for poverty eradication and sustainable development is at least 25-30% of GDP over a long period of time.
In my view — which is also shared by the least developed countries — much of this shortfall must be filled by ODA. From both a moral standpoint, and in the interest of the long-term wellbeing of the global community, those that are in danger of slipping should be given foremost priority. It is urgent that the level, quality and focus of ODA to the least developed countries be scaled up and consolidated. Channelling 50% of total ODA to the least developed countries will be an important step in that direction. At the same time, ODA can have a strong leveraging impact on other sources of development finance (Chapter 11).
In this day and age it is unacceptable that so many remain below the poverty line in the least developed countries. We have the means to help them. We need to summon the necessary collective will to do so. The alternative is continued deprivation for a large number of people, which also represents a threat to global peace, security and environmental sustainability.
Cedric de Coning’s article yesterday, “Can the New Deal Live Up To Its Promise to Significantly Shift Agency to the Local?” reminds us that the New Deal is meant to be a “game changer” in the way countries and organisations undertake development cooperation in fragile states. The New Deal calls for national ownership over the development process, involving “country solutions” to the challenges of peacebuilding and statebuilding. However, in fragile states, national ownership cannot be taken for granted. It needs to be built up, and this may require significant time and resources. It is not just about what countries and organisations do, but also how they go about doing it. The process counts.
As de Coning points out, a government – particularly one with weak and fragmented institutions – needs time to mobilise the required expertise to undertake many of the initiatives called for by the New Deal, like conducting fragility assessments, setting clear national priorities, and forging relevant indicators to measure progress against them. Through such initiatives, the government may be better able to not only “own” the development process, but also to make it more inclusive of local stakeholders, e.g. civil society, traditional leaders, local businesses, etc.
National ownership is predicated on such an inclusive process. Yet, it is also a complex undertaking that requires a minimum level of institutional capacity and resources. This is where international partners can help. To do so, they need to avoid the temptation to substitute local partners in favour of speeding up – or having undue influence over – the process on the ground. For example, the real value of a fragility assessment is not only to have a report for feeding into policy making and programme design. It is also about stimulating an on-going dialogue at several levels in a war-torn society, particularly as a way to help reset state-society relations.
De Coning rightly notes that the New Deal should not be seen as a blueprint involving a rigid sequencing of steps with each one being a “one-off exercise”. Rather, it describes a dynamic, iterative peacebuilding and statebuilding process in which a widening range of stakeholders have the opportunity to participate. Dialogue, participation and inclusiveness lie at the heart of the New Deal, given that “transitions” and “post-conflict reconstruction” are essentially a renegotiation of the social, political and even economic order in a country. This is no mean feat since it will inexorably affect a complex web of existing obligations, interests and agendas. There are bound to be “winners” and “losers”.
In fragile states, local politics can be volatile and international engagement may entail high risks. But the risk of non-engagement may be even higher. Therefore, international partners should be prepared for possible setbacks but find new ways to continue their engagement regardless. For donors, this requires political sensitivity, programme flexibility, and openness to striking up new partnerships. This may require some major reforms of donor policies and practices, including institutional incentives, for adapting programming and financing operations to the need for strengthening, and increasing the use of, country systems and forging new partnerships.
Compacts can help governments, donors, civil society and other partners to agree on core priorities and set up new partnerships. They can promote political dialogue, new partnerships, and pooling resources in a broader effort to build national ownership and ensure mutual accountability for taking forward agreed priorities.
In September 2013, donors pledged $2.7 billion in support of the Somali Compact. While not perfect, the Compact is a good start to a long conversation among national stakeholders (e.g. the government, regional authorities, civil society, and local businesses) on how they can best work together on shared goals such as a functioning federal state, and how international partners can best support their efforts in this direction. As Coning states, however, the Compact could be periodically reviewed and revised. This would require further dialogue and participation of local stakeholders. If fragility assessments are designed and managed as an on-going process, they can contribute significantly to the review and revision of the Somali Compact. Multi-level political dialogue among national stakeholders, and with international partners, is also necessary to improve the focus of the Compact over time. While this may involve some hard choices, it can also strengthen national ownership over it, and contribute to the renegotiation of the social and political order over time in Somalia. This is a tall order, but a necessary one.