Statistical indicators, compiled both by transnational agencies such as the UN and by national statistical agencies, provide the basis for comparison between countries.
The UN's millennium development goals (MDGs) involve a particularly important example of this sort of measurement, where progress towards time-bound targets is monitored through a set of statistical indicators.
Reducing by half the proportion of people without sustainable access to safe drinking water, and achieving significant improvement in the lives of at least 100 million slum dwellers by 2020.
Progress towards each goal is monitored through a statistical indicator usually based on one or two data variables, such as child mortality or enrolment at schools by gender. Other indicators, especially when countries are compared, are usually more complex in construction and can involve a number of data sources combined in various ways to construct an index that ranks countries in a type of league table.
One of the best known of these is the UN Development Programme's annual human development index (HDI). Development has often been measured in terms of economic or material wellbeing only, as reported through gross domestic product (GDP) per capita. The HDI was designed to go beyond this narrow measurement. It is based on three measurements: life expectancy, education and GDP.
The HDI makes it possible to rank countries according to progress in development. It enables policy makers, investors, social scientists and others to evaluate each county in relation to others, using a single number (the index). Constructed from three separate and fairly simple statistics, it is easy to understand. Therein lies its strength.
There are, however, weaknesses in its construction, primarily because it is based on only three components, which have been chosen arbitrarily from a wide range of available data sources.
The complexity of measurement and transnational comparison through the construction of indicators was evident at the recent steering committee of the Partnership in Statistics for Development in the 21st Century (Paris21) consortium, which I am privileged to co-chair.
One of the discussions at last week's meeting in Paris centred on measurement and monitoring of government performance. This has become a subject of increasing public debate, especially in the developing world and low-income countries. How, the Paris21 steering committee pondered, can one best measure government performance and compare between countries What information should be used in constructing indicators enabling legitimate comparison These questions are not easily or quickly answered?
Assessment of the strengths and weaknesses of the HDI provides some direction. Data sources and components must be justifiable according to sound and transparent criteria. Comparability between countries is essential if credible indicators are to be constructed.
A wise and experienced statistician of international standing recently suggested to me that this problem necessitated a choice: either select very few components and risk misrepresenting the social reality, or select a greater number and risk awkward or clumsy reporting. Discussions in last week's Paris21 steering committee meeting suggest that, at least for developing and low income countries, the risk of inadequate or incorrect measurement is far greater than the difficulty of managing and communicating inelegant and awkward indicators.
Finally, the absence of adequate data poses a risk of even greater proportion than misrepresentation or clumsy communication. Without data of appropriate quality, all measurement will be of dubious value.
Pali Lehohla is South Africa's statistician-general and head of Statistics SA. For more information on Stats SA's products and services, visit www.statssa.gov.