Transforming policy, changing lives with statistics and knowledge

statistics forumOECD Statistics Directorate

For over a decade now, the OECD has been spearheading work on well-being measurement and policy, in line with its mission of promoting “Better Policies for Better Lives”. Many individuals and organisations around the world have also been part of a global call for better measures and policies for progress “beyond GDP”. The OECD Forums on Statistics, Knowledge and Policy have been important drivers of this agenda, providing a space for all kinds of practitioners to take stock of experiences, to learn from best practices, and to gain inspiration for further change.

Gradually, this work has led to a paradigm shift, one that puts people at the centre of public policies and collective action. In the process, the key question has evolved from “How do we measure progress?” to “How do we best put those measures into practice for policies aimed at improving lives?” At the 4th World Forum on Statistics, Knowledge and Policy in New Delhi in 2012, OECD Secretary-General put it like this: “We want to transform our notion of well-being from an implicit to an explicit goal that can be assessed across the whole spectrum of government policies, business strategies and individuals’ decisions.”

The 5th OECD World Forum, “Transforming Policy, Changing Lives”, will provide an opportunity to reflect and debate on actually achieving a people-centred, planet-sensitive agenda. It will also be an occasion to showcase concrete examples of the impact of policies, frameworks and institutions that are using new well-being measures around the world, and will explore how this accumulated experience can contribute to country-level action in the pursuit of a new set of universal Sustainable Development Goals (SDGs) that are now being discussed in the UN setting.

The Forum will take place in Guadalajara, Mexico, and we would like to encourage all people with an interest in well-being and sustainability to take part. It will bring together hundreds of experts from various backgrounds including government, international organisations, official statistical offices, civil society, business, and academia, to present successful practices and address a number of topics relevant to the SDG agenda.

This is the first time the OECD World Forum will be held in Latin America, an ideal choice for an event primarily focused on policy innovation and transformation, given the immense change the region has seen in recent decades. It will be co-organised with the Mexican National Statistical Institute (INEGI), which has played a vital role in the development of new measures of well-being.

In addition to the main programme, the Forum will also include an Exhibition space with the opportunity for NGO’s, governments, international organisations, researchers and the private sector to showcase their work. There may also be the possibility for selected projects from the Exhibition to be presented at special sessions during the Forum.

Useful links

You can view the preliminary agenda and other information at the Forum website: www.oecd-5wf.mx

Participation in the Forum is by invitation only and at your expense. You can request an invitation by writing to [email protected], giving your name, email address, title/role, and organisation, along with 200 words explaining why you are interested in attending the Forum.

Win a paid trip to Guadalajara to attend the 5th OECD World Forum by entering the Wikiprogress Data Viz competition. Deadline is 24 August.

The road to better data

Paris21 road mapToday’s post is by Johannes Jütting, Manager of the Partnership in Statistics for Development in the 21st Century (PARIS21), which promotes the better use and production of statistics in developing countries. PARIS21’s new report, A Road Map for a Country-led Data Revolution, sets out a detailed programme to ensure developing countries can monitor the Sustainable Development Goals and benefit from technological and other innovations in data collection and dissemination.

Tradition tells us that more than 3,000 years ago, Moses went to the top of Mount Sinai and came back down with 10 commandments. When the world’s presidents and prime ministers go to the top of the Sustainable Development Goals (SDGs) mountain in New York late this summer they will come down with not 10 commandments but 169. Too many?

Some people certainly think so. “Stupid development goals,” The Economist said recently. It argued that the 17 SDGs and roughly 169 targets should “honour Moses and be pruned to ten goals”. Others disagree. In a report for the Overseas Development Institute, May Miller-Dawkins, warned of the dangers of letting practicality “blunt ambition”. She backed SDGs with “high ambition”.

The debate over the “right” number of goals and targets is interesting, important even. But it misses a key point: No matter how many goals and targets are finally agreed, if we can’t measure their real impact on people’s lives, on our societies and on the environment, then they risk becoming irrelevant.

Unfortunately, we already know that many developing countries have problems compiling even basic social and economic statistics, never mind the complex web of data that will be needed to monitor the SDGs. A few examples: In 2013, about 35% of all live births were not officially registered worldwide, rising to two-thirds in developing countries. In Africa, just seven countries have data on their total number of landholders and women landholders, and none have data from before 2004. Last but not least, fast-changing economies and associated measurement challenges mean we are not sure today if we have worldwide a billion people living in extreme poverty, half a billion or more than a billion.

Why does this matter? Without adequate data, we cannot identify the problems that planning and policymaking need to address. We also cannot judge if governments and others are meeting their commitments. As a report from the Centre for Global Development notes, “Data […] serve as a ‘currency’ for accountability among and within governments, citizens, and civil society at large, and they can be used to hold development agencies accountable.”

So data matters. Despite this, blank spaces persist in the statistics of many developing countries. And they persist even at a time when the world is experiencing a “data revolution” – a rising deluge of data matched by ever-increasing demand for data.

Despite the challenges, we are optimistic that all countries, including the poorer ones, can make quick, dramatic progress in meeting their data challenges. Firstly, there is not only a growing awareness of the problems countries are facing but also a growing willingness to do something about it. Statistical offices in almost 40 developing countries have signed up to our Data Declaration, in which they state that “the time is now to bring the data revolution to everyone, everywhere”.

Second, new technologies are already helping to revolutionise the world of data. PARIS21’s Innovations Inventory has compiled hundreds of ways in which technology is making it easier and less costly to collect data and providing new sources of data, like “big data”. Examples abound, from NGO to private sector initiatives. As part of its Data for Development (D4D) challenge, Orange Senegal opened up its mobile-phone call-log data for researchers to generate insights into health, transportation, demographics, income inequality, and more. Another truly “Big Idea” comes from Restless Development, a youth-led development agency that equips young people with knowledge, skills, and platforms necessary to effectively interpret data in order to mobilise citizens to take action.

Third, we are optimistic because we want to build on what is already there – existing national statistical systems. Clearly, many are far from ready to join the data revolution; a colleague recalls visiting one national statistical office that couldn’t pay its power bill and had to negotiate with a neighbour to string an extension cord from his home to the office. That may be an extreme example, but other challenges – including technology gaps, shortages of trained staff, weak data dissemination and poor relations with users – are all too common. Nevertheless, national statistical agencies are the only entities with the expertise and legal frameworks to play the lead role in collecting, processing and disseminating data. It is on them that the data revolution for development for sustainable development must be built.

Of course, our Road Map for a Country-led Data Revolution is only a start. Much else needs to happen. This includes designing pilot projects, finding better ways to integrate new sources of data in existing national systems and – unsurprisingly – finding extra funding. But here again we are optimistic. We don’t accept that the cost of monitoring the SDGs will be “crippling”. With our colleagues in the UN Sustainable Development Solutions Network, we have calculated that additional donor funding of $200 million a year, matched by a similar rise in domestic funding, would enable the 77 IDA countries (“The World Bank’s Fund for the Poorest”) to successfully monitor their progress the SDGs – yes, even the proposed 17 goals and 169 targets!

We don’t yet know if that will turn out to be the final number of SDG “commandments”. But here’s something we do know – developed and developing countries are on the cusp of a huge and dramatic change in how they collect and disseminate. True, unlike Moses, we don’t live in a time of miracles. But with the aid of a clear road map, strong political will and “miraculous” technologies, we really are much closer to the promised land of better data than we realise.

Useful links

Informing a Data Revolution – PARIS21

Watch the launch of A Road Map for a Country-led Data Revolution at the Cartagena Data Festival on Monday 20 April from 1700 hours UTC (noon in Cartagena, 1pm in New York, 6pm in London, 7pm in Paris, 2am in Tokyo).

Do we really have a good picture of women’s well-being?

BLI InitiativeToday’s post is from the OECD Statistics Directorate

Lack of data limits the ability to measure women’s conditions in an accurate and comprehensive way, and to make informed decisions about how women and girls fare. The post-2015 development agenda will translate into an increased demand for gender statistics that are regularly produced and provide solid and objective evidence. However, there are many data gaps in national and international monitoring of gender inequality, particularly in less-traditional areas of official statistics. Countries face many challenges in mainstreaming the gender dimension into data production, analysis and dissemination.

To address this, the OECD is working with the United Nations and the World Bank through the Evidence and Data for Gender Equality (EDGE) Initiative to build national capacity to produce and disseminate gender statistics and create standards for data collection. We are also contributing to improving access to gender statistics through our Gender Data Portal, which gathers information on various topics of relevance to the post-2015 development agenda, including education, employment, entrepreneurship, unpaid work.

In terms of the metrics themselves, gender parity is not sufficient for measuring gender equality. Indicators that measure the quality of change are also necessary. For example, women may have similar rates of paid employment as men but this does not mean that they are paid the same or that they have the same opportunities for career advancement. Across OECD countries, women working full-time earn on average 16% less than men, although there is substantial variation amongst countries. Moreover, wage penalties increase as women get older and have children. Among women of child-bearing age who work full-time, those with children earn 22% less than men and 7% less than childless women. Conventional statistics do not measure the security of jobs either, which is particularly important since women’s paid employment is often more vulnerable than men’s, especially in developing countries. The OECD’s work on job quality may shed new light on the working conditions that women face around the world.

Women do not stop working when they leave their offices. At home, women still bear the brunt of unpaid work, such as child-rearing and household tasks. Across the OECD, women spend twice as much time as men on household chores and parenting. In other words, if women and men were to share unpaid tasks equally, women would gain 5 hours of free time per week. There are large variations from country to country: an average Italian woman spends 22 hours (or almost 3 full-time workdays) more than her partner on unpaid work per week, while this gap averages 5 hours in the Nordic countries.

When both paid and unpaid work are combined, the gender gap in working hours narrows, but it’s still the women who put in the longest hours. However, this kind of work is too often under-recorded or undervalued. Time-use data and statistics on time spent on domestic chores and caring are available only in around a third of countries of the world. An even smaller number of countries “value” this unpaid work through satellite accounts for household production. The OECD is contributing to fill this gap through its Time-Use Database, which gathers detailed information on how total time per day is spent in different activities in OECD countries and selected emerging economies.

Time spent in unpaid work and leisure

Minutes per day

Unpaid work and leisure
Click to see full size

Another important issue is the fact that data is simply not being collected for certain areas. Not because it is not possible, but because it has not been thought of or because power imbalances between men and women in institutions shape data collection priorities.

A good example is gender-based violence. The absence of an indicator on violence against women (VAW) in the MDG framework due to lack of data was a ‘missed opportunity’. Only half the countries in the world currently produce official statistics on violence against women. And yet both the extent of such violence and costs of this form of discrimination call for action. Worldwide, 35% of all women report having experienced physical and/or sexual violence from their intimate partner or others in their lifetime. In the OECD area, one in four women reports having been a victim of such forms of violence at least once in her life. We expect great improvements in the cross-country comparability of data on VAW after the recent release of the Guidelines on Collecting Data on VAW by the UN Statistics Division. But we should also explore other data sources, such as records from shelters, hotlines, hospitals, the press or Internet searches. The OECD is currently undertaking research on the determinants of violence against women and on the costs of such violence to women.

Finally, a significant challenge relates to the need to measure gender equality and women’s rights for different demographic and social groups. Lifecycle analyses suggest that women and girls face constraints that can be age-specific or may be specific to different socio-economic groups. Disaggregated statistics along these lines should be promoted to assess how gender interacts with other ‘disadvantages’ or characteristics.

Useful links

OECD data on gender equality

Work-life balance in the OECD Better Life Index

Wikigender

Closing the Gender Gap: Act Now

Find, compare and share OECD data

Sunday Post
Data suggest they’re not Greek

Scottish newspaper The Sunday Post (“A thoroughly decent read”) built its fortune on a mixture of gratitude for heart-warming behaviour; outrage at things that should or should not be happening in this day and age; cartoon strips featuring happy families; editorials that denounced absolute disgraces; and reader services that catered to two main groups. First, clueless shoppers in Kirkcaldy, asking for: “A Kirkcaldy stockist of men’s coats, please.” (“Wright’s Coats on High Street should have what you’re looking for, Mr. B”) And people who spent their time starting fights: “To settle an argument, which has the bigger population, Kirkcaldy or Tokyo?” (“Tokyo, but it’s hard to find a reasonably-priced coat”.)

Thanks to the Internet, finding a shop that sells coats is now a lot easier than it used to be, but it’s an absolute disgrace that in this day and age the same still isn’t true for information on other subjects that are nearly as important to many people, such as GDP or employment. So thank goodness for the new OECD Data Portal. Its 500+ free databases provide quick, easy access to information on all the topics, for OECD and a number of non-OECD countries too. The data are divided into twelve themes (agriculture, education, innovation and technology, and so on).

When you click on the catalogue, the default listing is by relevance. The most intriguing, for me anyway, was the second dataset: Energy prices in national currency per toe. But I was disappointed to discover it’s nothing to do with your frostbitten tootsies dropping off because you can’t afford heating. It turns out that “toe” here means “tonnes of oil equivalent”. It’s a standardised measure used by energy economists based on the energy released by burning a tonne of crude oil – 11.63 MWh in these tables. The toe is a practical way to compare prices and consumption, given the large variations in types of energies used even within a single country.

Take Greece for instance. On Saturday, a BBC reporter described how the smell of wood smoke was now characteristic of Athens since so many people couldn’t afford central heating anymore. A toe of electricity costs Greek households 1895 euros, more than France (1693), but less than Germany (3395). Average household disposable income in 2012 (last year for which comparable data are available) was the equivalent of $33,406 in Germany, $30,811 in France and $19,224 in Greece. Despite the crisis, France and Germany have seen rises in average income, but it’s fallen in Greece ($23,682 in 2008).

The OECD Data Portal has a useful feature called “pinboard” that allows you to collect a number of different data sets and present them together. To stick with Greece, here are a few of the things voters are asking the new Syriza-led government to change:

You can also compare groups of countries for the 518 indicators provided and share your results via the pinboard in various formats. Here for instance is a map giving the share of corporate tax in total tax, showing that it’s much lower in rance than in the US for isntance.

Useful links

OECD work on Greece

For effective development, listen, learn and measure more than GDP

Click to go to the conference website

Our final post from the Annual Bank Conference on Development Economics (ABCDE) is from Jon Lomoy, Director of the OECD Development Co-operation Directorate

Hal Varian, Google’s chief economist, famously remarked recently that being a statistician would be the sexiest profession of the 21st century. After hearing discussions at this week’s Annual Bank Conference on Development Economics, I think he may be on to something. The conference has confirmed my view that good data is an essential ingredient for development. I’m not just talking about how data has illuminated many of the excellent conference papers and debates. I’m also talking about how data helps governments design and measure better policies for better lives.

So how should governments measure whether lives are indeed getting better? In a 2009 report commissioned by the French Presidency, Joseph Stiglitz, Amartya Sen and Jean-Paul Fitoussi showed that the data used to measure success have a major influence on what societies strive to achieve – if we measure only GDP, we will strive only for growth.

But after focusing on growth for a long time, we now know that we need to look at a much more nuanced picture of societal progress – it takes more than income to make lives better. What about better health? What about a cleaner environment? These issues are important to people, and we need to start measuring them better and more prominently.  In this context, I am looking forward to seeing the outcomes of the OECD’s new Better Life Initiative, which allows individuals to build a personal index using their own better life indicators.

The question of what constitutes effective development and how it should be measured is also sure to figure prominently at the Fourth High-Level Forum on Aid Effectiveness in Busan, Korea (29 November – 1 December 2011). While all countries might agree that reduced infant mortality and higher literacy rates constitute “development”, I am sure that many other priorities will differ from country to country. Discussing these priorities and deciding how to measure them will be crucial, and will rely on solid data. 

Organisations such as the OECD and the World Bank, with their vast experience in producing and using good data, can certainly support such discussions. However, what we have learnt at this week’s ABCDE is that we also need to become much better at listening to our partner countries’ needs and learning how they see development. Now you may or may not view that idea as sexy, but I hope you agree that it is extremely important.

Useful links:

World Bank’s open data

Aid flows

OECD International Development Statistics online

Paris21 Statistics for development

World statistics day

Today, on 20.10.2010, more than 100 statistical organizations celebrate World Statistics Day at the initiative of the UN.

OECD statisticians and economists will discuss the contribution of statistics to the mission of OECD: “better policies for better lives“, with a focus on green growth, innovation, societydevelopment and progress. The talk is scheduled today at noon Paris time, and it can be seen live  at http://interwebcast.oecd.org/ (and it will be archived there afterwards).

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A football field the size of Belgium

Did you know that if you spread all your skin evenly over a flat surface you’d die? Fifty percent of our readers thought I was going to say it would cover an area the size of Belgium. (The other one’s gone to look for a knife, since you ask.) What is it about this “highly improbable” country that’s made it the standard international measurement for death and destruction, as in “an area of rain forest the size of Belgium has disappeared”?

You’d think that given its popularity, the measure would be standardised, with 1 Bm = 1000 millibelges, but in fact the  correct subdivision is football fields. These are used for a range of difficult measurements such as the length of oil tankers at sea, but really come into their own when scientists need a particularly precise metric for the size of sophisticated equipment like the UK’s Diamond Light Source Synchrotron.

So, how many football fields are there in a Belgium? I’ve no idea. And I haven’t a clue how big Belgium is. Even in Brussels, I’m sure few people could tell you the size of the place. Yet you see this “statistic” practically nobody could define used worldwide. Does that matter? Probably not. In fact it can be quite useful.

As Belgian writer Paul de Man said, metaphors are much more tenacious than facts. Belgium is a country most people have heard of, even if they couldn’t locate it on a map, and anything that’s as big as a country must be really big. Likewise, most of us are exhausted by the time we run the length of a football field, so it must be really long.    

The (average) statistician is now apoplectic. Comparing this kind of garbage to real statistics just because they both claim to measure something is like comparing coal to diamonds just because they’re both made of that stuff they’re both made of. They’ve got a point. A striking image is fine to draw attention to something, but for practical purposes, you need precise, comparable data. The OECD has over 200 statisticians supplying its 200 committees and working groups with over 200 indicators on all areas of government action.

To celebrate World Statistics Day, why not take a look at our statistics portal on the OECD iLibrary? You’ll find the expected and the unexpected: data economic growth of course, but even which OECD country has the tallest population. I still couldn’t find the area of Belgium though.

Useful links

OECD Statistics Directorate