Life before the web was neatly compartmentalized. Research was produced by researchers who wrote articles for academic journals; news was written up by professional journalists who wrote for newspapers and talked on news broadcasts on the TV and the radio; policy was made by politicians and policymakers behind closed doors in smoke-filled ministries in capital cities; and entertainment was crafted by professionals and delivered in theaters, cinemas and on the TV.
With just four years to the target date of 2015, progress on the health-related Millennium Development Goals (MDGs) has been slow. Measuring progress has been hampered by the lack of quality and timely data; this is especially true when measuring progress toward goals that rely on civil registration for their information, such as Goal 4 on reducing child mortality. Available data in the new edition of World Development Indicators show that of the 144 countries for which data are available, more than 100 countries remain off-track to reach the MDG 4 by 2015.
It’s 1988. I’ve just started my career as a statistician in the British Civil Service. One of my first tasks: find data to compare the major aid donors of the world: how much they give, and the size of their economies.
But twenty three years ago there isn’t a computer on every desk. There is no internet, no World Wide Web. So no email, no instant messages, no Google. Communication is by letter (in quintuplicate, I should add), fax, phone – and more than an occasional telex. And getting hold of some data means spending a few happy hours in the statistical annex of the departmental library, digging out the latest statistical publications.
Rising food prices have once again grabbed everyone’s attention. Prices for some basic foods are nearing the 2008 food crisis levels. In the post ‘Soaring Food Crisis’, Paul Krugman analyzes the data from USDA World supply and demand estimates, and blames the current price spikes on global harvest failures. However, the main question still remains unanswered – is another food crisis afoot? Answers to this and some other concerns are addressed in the latest World Bank Flash and also in the World Food Program’s ‘Rising Food Prices: 10 Questions Answered’ piece.
Should 16 year old Africans vote? Why not… Africa has the youngest and fastest growing population in the world…where more than 20% are between the ages of 15- 24, argues Calestous Juma in an insightful post on the Guardian’s Poverty Matters blog. Speaking of Africa, in an interesting post, ‘Do informed citizens hold governments accountable? It depends…’ (Governance for Development blog), Stuti Khemani from the World Bank’s Research Group examines the impact of radio access on government accountability in Benin.
Major funders of public health research – the World Bank included – have today issued a joint statement to champion the wider sharing of data to achieve better public health worldwide.
|Mother and boy being attended to by Health Education nurse. Sri Lanka. Photo © Dominic Sansoni / World Bank|
This is a great step forward: advances in public health throughout the decades, perhaps like no other discipline, have been underpinned by careful research based on data. An early and celebrated example is the epidemiologist John Snow’s study of the relationship between the water supply and cholera outbreaks in central London in 1854, which used public data to establish the link between contaminated water and the disease. More recently, the mapping of the human genome was completed by a global collaborative effort based on the sharing of effort and data.
In many fields and in many countries, sharing of data is fast becoming normal practice (www.data.gov). An environment where data are open, freely available and easily accessible to all can provide tremendous benefits for development. At the World Bank we opened our databases last April. And there are great examples of agencies starting to routinely provide access to their datasets, which were previously closely guarded, such as data collected through household surveys.
New Year’s resolutions are always of the lofty – but often short-lived kind. I will go to the gym more often, lose more weight, or volunteer more often than I do now. One resolution made by a number of us in the Research Group of the Bank – and elsewhere, has been to find a way to get more people excited about investing in data collection and analysis on trade. I recognize this is not the most glamorous of topics at any time of the year – but nonetheless a resolution as important as any made each year for decades as the calendar turns another page.
Here is why 2011 is different and resolutions made can be kept, however, and why data and research should be high on anyone’s development and trade agenda.
There were a number of high level dialogues in 2010 and 2011 related to global finance, trade, and development issues. These included the High Level Summit on the MDG’s in September 2010 and the G20 Summit in Seoul in November 2010. These events provided important opportunities -- in the post-crisis environment – to inform priorities going forward on aid effectiveness and trade. The President of the Bank, Mr. Zoellick, outlined in October 2010 -- in a very high profile speech at Georgetown University – a new vision of development economics which included new ways of looking at and advancing research tied to make aid more effective and inclusive.
The volume of public domestic debt issued in developing countries has grown substantially in recent years, but consistent data on the domestic debt of developing countries have not been generally available until now. As part of the Open Data Initiative, the World Bank is launching an online, quarterly, Public Sector Debt database developed in partnership with the IMF, which will allow researchers and policymakers to explore questions about debt management in a comprehensive manner. The database promotes consistency and comparability across countries by standardizing the treatment of public sector debt, valuation methods, and debt instruments, and by identifying, where possible, the debt of central, state, and local governments as well as extra-budgetary agencies and funds.
As December 4th approaches, I’m getting excited for the International Open Data Hackathon and even more excited to see World Bank challenges and data featured in an event that will span 50 cities (and counting ) over 6 continents. It’s thrilling to consider what hackers and users working together might mash-up and what role we (as data providers) can play in giving people access to clean and interoperable data sets for their using. Let a thousand flowers bloom.
Having recently traveled in India and after meeting development folks of various stripes from economists in Delhi to social entrepreneurs in Hyderabad to geeks in Bangalore , I’m struck again by how important local data remains. It’s one thing to talk about global economic trends and macro indicators but quite another to understand what’s happening in one Indian state, say Andra Pradesh, compared to its neighbors. Imagine a citizen group comparing rainfall data between states, at the district level, compared to crop yields over two decades. That’s when things get interesting and potentially useful to users.
In today’s data-saturated, highly visual and networked world, statistics are used by policymakers, researchers and journalists for just about everything. However, a veritable mix of government officials, economists and statisticians work – often against overwhelming odds - to produce data sets that are, paradoxically, often taken for granted, but also used as gospel in policy discussions.
Earlier this week, the World Bank celebrated the first ‘World Statistics Day,’ where the successes, challenges and future directions for collecting and analyzing economic development-related data were discussed.
The statistics discipline in the economic development field has seen some breakthroughs in the recent past.
Princeton University's Angus Deaton, a panelist at the event, pointed to the 2005 round of the largest international data collection exercise in the world, called the International Comparison Program, which collects internationally comparable price levels. This data set is critical for comparing living standards between countries.