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What does “urban” mean?

Chandan Deuskar's picture
Follow the author on Twitter: @cd_planner
 

 
This aerial view of Hanoi, Vietnam, clearly shows areas of decreasing density between the city and the countryside, making it hard to define the limits of the "urban" area.
Anyone reading this blog is likely to have heard the statistic that ‘over half of the world’s population now lives in urban areas’. This has been the standard opening line of reports and presentations about urbanization since this milestone was supposedly reached in 2008. But what does it really mean?

In everyday usage, terms related to human settlements have vague, shifting meanings. What one person might describe as a small ‘city’ might be a ‘town’ or ‘village’ for someone else; one person’s ‘megacity’ might be a cluster of cities from a different perspective. Similarly, we can usually identify areas that are clearly within a city and others that are outside it, but there is usually a peri-urban area of intermediate density that usually lies between the two, making it hard to define a clear city limit. Formal administrative boundaries may have historic or political meaning, but are rarely aligned with the physical or economic extents of the urban area.

What exactly is a city? It depends who you ask

It turns out there is no standard international definition of an ‘urban’ area or ‘urban’ population. Each country has its own definition, and collects data accordingly. The statistic that 50% of the world’s population is urban is arrived at simply by adding up these incomparable, and sometimes conflicting, definitions.
 

Is a Data Revolution under way, and if so, who will benefit?

Duncan Green's picture

RicardoFuentesNieva croppedGuest post from the beach big Data Festival in Cartagena, Colombia, by Oxfam’s Head of Research and paid up member of the numerati, Ricardo Fuentes-Nieva (@rivefuentes)

A spectre is haunting the hallways of the international bureaucracy and national statistical offices – the spectre of the data revolution.  Now, that might suggest a contradiction in terms or the butt of a joke – it’s hard to imagine a platoon of bespectacled statisticians with laptops and GIS devices toppling governments. But something important is indeed happening – let me try and convince you.

A new research report by ODI  “Data Revolution – Finding The Missing Million”  (launched yesterday in Cartagena during a Data Festival) tries to make sense of the coming data revolution, and what it means for international development. According to the authors: The data revolution is “an explosion in the volume of data, the speed with which data are produced, the number of producers of data, the dissemination of data, and the range of things on which there are data, coming from new technologies such as mobile phones and the internet of things and from other sources, such as qualitative data, citizen-generated data and perceptions data.”

For the numerically minded (I proudly include myself in this group) this is a rather welcome transformation. Data, data everywhere – but then why haven’t we, number geeks, solved all of the world’s problems yet?
 

Please Steal these Killer Facts: A Crib Sheet for Advocacy on Aid, Development, Inequality, etc.

Duncan Green's picture

Regular FP2P readers will be (heartily sick of) used to me banging on about the importance of ‘killer facts‘ in NGO advocacy and general communications. Recently, I was asked to work with some of our finest policy wonks to put together some crib sheets for Oxfam’s big cheeses, who are more than happy for me to spread the love to you lot. So here are some highlights from 8 pages of KFs, with sources (full document here: Killer fact collection, June 2014).

The Need to Improve Administrative Data

Suvojit Chattopadhyay's picture
While we debate poverty estimates and methodologies, the humble administrative data continues to be ignored
 
A key aspect of good governance is the generation and use of data—good quality data, produced through reliable means that can inform policy-making and implementation. The importance of official data need not be underlined—state and national-level poverty statistics are fodder for academic as well as political debates. We know that this is mainly because the headline figures reflect the achievements of the governments in power.

However, in the same universe, administrative data is often ignored. Administrative data is the data collected primarily for (or as part of) implementation of specific interventions or functions. Within the government, this may refer to data as varied as that of birth and death registries; cooking gas cylinders issued; teachers’ attendance or mid-day meals served. It is easy to see how such administrative data can be used in monitoring implementation—better data can help identify and plug leakages; ensure better targeting and delivery; and maintain a high quality of service delivery, among others. In fact, the quality of data is both a contributing factor as well as outcome of the quality of governance. Better data, made public in easily digestible formats can also enable citizens to hold governments to account.

Are We Measuring the Right Things? The Latest Multidimensional Poverty Index is Launched Today – What do You Think?

Duncan Green's picture

I’m definitely not a stats geek, but every now and then, I get caught up in some of the nerdy excitement generated by measuring the state of the world. Take today’s launch (in London, but webstreamed) of a new ‘Global Multidimensional Poverty Index 2014’ for example – it’s fascinating.

This is the fourth MPI (the first came out in 2010), and is again produced by the Oxford Poverty and Human Development Initiative (OPHI), led by Sabina Alkire, a definite uber-geek on all things poverty related. The MPI brings together 10 indicators, with equal weighting for education, health and living standards (see table). If you tick a third or more of the boxes, you are counted as poor.

Media (R)evolutions: Internet Live Stats

Roxanne Bauer's picture

New developments and curiosities from a changing global media landscape: People, Spaces, Deliberation brings trends and events to your attention that illustrate that tomorrow's media environment will look very different from today's, and will have little resemblance to yesterday's.

Internet Live Stats is a counting clock that tracks live statistics on information technology, including Internet users in the world, emails sent today, Google searches today, smartphones sold today, and how much electricity is used today for the Internet.  The website is part of the Real Time Statistics Project  that also includes Worldometers and 7 Billion World.

Toing and Froing in Freetown

Mark Roland Thomas's picture



Countries coming out of crises undergo rapid structural changes, including migration and big economic shifts. This can complicate the measurement of their progress, sometimes in unexpected ways, as we found out recently in Sierra Leone.

DIY: Measuring Global, Regional Poverty Using PovcalNet, the Online Computational Tool behind the World Bank’s Poverty Statistics

Shaohua Chen's picture

World Bank Group President Jim Yong Kim recently announced ambitious goals to end poverty and boost shared prosperity, with a target to reduce the percentage of absolute poor – those living on or less than $1.25 a day (in 2005 PPP) – to 3 percent by 2030. The Bank, he said, will also focus on expanding opportunities for those living at the bottom 40 percent of the income or consumption distribution in each country.

How do we manage revisions to GDP?

Soong Sup Lee's picture

Gross Domestic Product (GDP) estimates are some of the most heavily requested and used data published on data.worldbank.org.  And as many users notice, the estimates are sometimes revised, occasionally  resulting in large changes from previously published values. Why do revisions happen, what information do we publish about those revisions, and where do you find it?

What do existing household surveys tell us about gender? It depends which sector you ask

Julie Babinard's picture

A very good panel discussion this week on Gender Equality Data and Tools at the Bank reminded me of the research we did in transport on household surveys with my friend and a World Bank colleague, Kinnon Scott. In retrospect, this work should be better advertised as it touches upon many of the points that were raised on the importance of gender-relevant data for policy. The three main questions that follow permeate t


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