Measuring development

The search for a response to the anxiety engendered by scarcity is not a new quest for either human beings or economists… The debates on the optimal allocation of resources are not new. What has changed is the distance that separates us from the wall and the speed at which we are leading the global economy right into it: shorter and faster than ever before in human history.

Already in 1972, the Club of Rome published its conclusions: “The limits of growth”. In 1987, the Brundtland Commission Report established this definition which has become famous: “Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.”

Once the limits of our planet have been pinpointed and the inability of GDP to take into account the depletion of natural resources, the loss of biodiversity, pollution, and wellbeing, the need for an alternative measurement of the progress of societies becomes clearly apparent. 

“The welfare of a nation can scarcely be inferred from a measurement of national income”, Simon Kuznets, 1934

These recent years have witnessed what is now called the “data deluge”. With global household surveys, the increase in the provision of perception data and barometers, Big Data, etc., the digital revolution has generated a tsunami of data. There is an increasing amount of information, even if its quality is sometimes questioned. The problem will stem less and less from the scarcity of information and more and more from its abundance.
The problem of measuring the progress of societies is now less a statistical problem, but indeed a conceptual and philosophical challenge. As Joseph Stiglitz points out, you only achieve what you manage to measure.

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If we look back, we see that GDP became institutionalized as a universal measurement of wellbeing after the Second World War, when the emergency was for reconstruction. GDP and wellbeing thus increased concomitantly, elevating this “historical coincidence” to the rank of causality, during which time GDP growth involved an improvement in wellbeing. Consequently, GDP growth has, almost by chance, become an objective to be achieved, the quantified perspective of a better life. This relationship is, however, not always observed…
Since the end of the "Thirty Glorious Years" (the years of reconstruction following the Second World War), we have gradually become aware of the fact that GDP growth is not always synonymous with poverty reduction, does not necessarily produce work or decent living conditions, and is not synonymous with social cohesion or a better life.

While the limits of GDP are well documented, they have not managed to refute the success of this indicator, which is observed and commented on a daily basis. Yet the challenges of today are not those of the post-war period. Mass consumption has revolutionized the organization of work, social relations and global trade. The perception of scarcity has changed, especially when former poor countries have become giants… with huge needs…

Today, even the richest countries anticipate an increase in the scarcity of natural resources. The perception of scarcity, which used to stem from difficulties of extracting, producing and trading in a context of a belief in the eternal abundance of resources, has changed. At the same time, as the GDP of most nations / several parts of the world has increased, human progress has appeared to be less and less correlated with it. The UNDP Human Development Report (2010) highlights an increasing decorellation between the monetary and non-monetary aspects of the Human Development Indicator (HDI). Greater wealth is no longer necessarily synonymous with better health, education or satisfaction. The context has changed, but not the hegemony of GDP as a standard measurement of wellbeing.

However, things are changing and certain initiatives seek to call into question the standard measurement. Bhutan was the first to adopt an alternative measurement of development. Gross National Happiness was conceptualized back in 1972 and permanently adopted by the Kingdom in 2008. In addition to monetary income, it includes environmental sustainability, health, education and subjective wellbeing. Following the Sen-Stiglitz-Fitoussi Commission, the OECD launched the “Better Life Index” initiative, which presents a scoreboard on the progress made by societies, including subjective wellbeing, the balance between work and leisure, the environment, security, etc. But there is effectively no consensus over what could be a measurement of the progress of societies and how to measure it. 

“Stat4dev” Program

This research program aims to question the existing measurements and conduct further research on alternative development indicators. A specific focus will be placed on the appropriation of this research and its operationalization at AFD, and the provision of innovative tools to promote the use of the most relevant indicators in the formulation of our strategies for operations. It comprises 4 main areas:


1. Measurement of human development

The most successful attempt at calling into question the predominant paradigm, i.e. at reconsidering what human progress could be and the way to measure it, is the Human Development approach established by Mahbub ul Haq and the United Nations Development Programme.

UNDP’s response, which is also rooted in a universalist perspective, has intended to be clear and coherent over the past 20 years: “Progress resides in the diversification and broadening of the range of choices and capacities of individuals.”

The research conducted at AFD fits in with this context and concerns the capabilities and measurements of human development in the framework of support for preparatory research for the UNDP Human Development Reports.

  • 2013 program: Vulnerability and human development
  • 2014 program: Work and human development

2. Big data and development

For about ten years now, there has been an improvement in the availability of socioeconomic statistics in developing countries, in particular under the impetus of multilateral donors and the Millennium Development Goals. However, the quality of the data produced is often called into question. In both the South and North, the need for a more regular and rapid updating of data has become apparent in a context of increasing economic and political instability. Indeed, both policymakers and donors often base their actions on data reflecting economic, political or social situations which date back much earlier.

The world has recently become aware of the existence of considerable flows of digital data passing through telecommunications networks (mobile telephony, Internet) for energy distribution, means of payment (credit cards, mobile telephony), geolocation or satellite imagery. It is the emergence of what is generally called Big Data.

The private sector has clearly understood the stakes of this new segment of the digital revolution. Investment has exploded in this sector in recent years. Social media, Internet access providers, mobile telephony providers, banks, etc., already store considerable amounts of data. In addition to their economic value, these data can potentially be used to more effectively direct development policies. Private companies are already working on anonymizing and making available the data that is collected.

In 2013, Orange made an unprecedented amount of data available to researchers, making Data for Development (D4D) the largest research initiative to date on Big Data for development. The D4D challenge has gathered 90 research institutes (MIT, IBM, University of Louvain, etc.) and received the support of the UN (Global Pulse), World Economic Forum, and GSMA (International Association of GSM Mobile Telephone Operators).
Research conducted on this theme at AFD: An alternative measurement of poverty in Côte d’Ivoire based on the data mentioned above (Orange D4D), as well as specific surveys. This research work aims to develop an alternative measurement of poverty in Côte d’Ivoire. By comparing mobile phone data from households (number and length of calls, geolocation, mobility, payments made) with socioeconomic data (2013 Demographic Health Survey and specific surveys), it will be possible to analyze the links that exist between poverty and the use of mobile services. This process of comparison with traditional poverty measurement tools will make it possible to identify the specific biases of these Big Data, and determine whether this can produce a valid and robust poverty indicator.

3. Measure social cohesion

Social relations are one of the key elements of wellbeing. The research conducted in the field of subjective wellbeing and cognitive psychology has highlighted a number of results which show that the “happiness” or rather the “satisfaction” of individuals greatly depends on family ties, friendships and social interactions. According to Amartya Sen’s capability approach, integration within a social network has both an intrinsic interest (as a source of immediate satisfaction) and instrumental interest (as a vector for increasing capabilities). Despite certain attempts, there is still no consensus on its measurement, nor on its potential impact on the relationship between income growth and development.

Research conducted at AFD: Measurement of social cohesion, weight of inequalities, social protection, social movements.

It involves exploring the empirical and theoretical link between the quality of the social network of a community (slum, city, region, country…) and wealth distribution within this community. It entails filling a theoretical gap in orthodox economics, which postulates that market goods and services have an intrinsic value that is independent from the externalities they have in terms of social relations, and that wealth distribution does not affect the effectiveness of market transactions.

This research will provide criteria to assess the relevance of public policies in emerging countries, in the light of the contributions that the projects in question make to improving social cohesion. Establishing such indicators will make it possible to refine the definition of AFD’s position in its dialogue with authorities and donors, by considering social cohesion not so much as a social capital to support growth but as a development objective. 

4. Data literacy and data visualization

What do we really know about the international statistics provided by the World Bank, IMF, etc. What do they hide? Can we assess their quality?

How to represent income distribution and trends? How to put these trends into perspective? How to facilitate access to data? How to share information? Which tools do we have and how to implement them in order to improve decision-making?

Data visualization is a relatively recent field, at the intersection between design, IT and statistics. With the opening up of access to data (most are now free and accessible online), the development of Big Data and the increasing involvement of actors such as IBM, Google…. these information technologies have developed enormously. The OECD, World Bank, UNDP and think tanks have all invested in these tools and now use them as a major driver for their communication.

Projects currently being developed:

  • Country dashboards:  
  • Research: “African statistics, where do we stand?” With Vanessa Jacquelin, AFR

Activities and publications

Last update in December 2015

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