When I was a young child in rural Lesotho, my elders often warned me to be careful of barking dogs. This was not, as you might expect, because barking dogs could become dangerous, could attack or even savage children in the fields and villages. It was because of the importance of interpreting what the barking of dogs signified.
This explanation was usually accompanied by a story. Dogs in the fields often slept among the haystacks to keep warm. When they barked, some villagers immediately assumed that there were thieves in their midst, attempting to steal cattle. Others assumed the dogs were barking at cattle moving between the haystacks.
A third group suspected that the dogs were barking because their warm environment was threatened by some intrusion - cattle or people or even other dogs.
What does this have to do with statistics The bark of a dog is an indicator. It stands for some event or occurrence that cannot be immediately established with certainty - perhaps the arrival of cattle rustlers, or maybe a threat to the warmth of the protective haystack?
Statistics also make use of indicators. The best-known are regular short-term indicators of economic change and performance: the monthly consumer price index, for example, which provides various indicators of consumer inflation (headline or official inflation, inflation excluding mortgage costs, food inflation, inflation in the rural areas); or the monthly suite of indicators for trade in the wholesale, retail and motor sectors; or indicators of monthly production and sales in the mining and manufacturing sectors.
Typically, these indicators are derived from a single data set. Longer-term indicators are often constructed from a number of data sources. These may be based on a time series for the same data area, as with agricultural production by year over five years, or changes in access to piped water in each fiveyear period between 1991 and 2001.
Alternatively, the indicator can be derived from integration of a number of different data sources. The best-known example is quarterly and annual estimation of changes in gross domestic product (GDP), which relies on a wide range of social and economic statistics. These include Statistics SA's monthly surveys on mining, manufacturing, electricity, motor vehicle sales, and retail and wholesale trade sales. Other sources, such as the economic activity survey, the quarterly financial statistics, government accounts and building statistics, are integrated to construct the central indicator of economic growth - GDP.
The construction of indicators of a more social or developmental nature involves particularly complex and contested statistical methodologies. These aim to measure progress and development in the living conditions of individuals, households, social groups and countries.
Poverty measurement is especially important, given the commitment of programmes such as the millennium development goals and South Africa's programme of action to set measurable and attainable targets in reducing poverty. However, the very measurement of poverty is controversial. It is often quantified in relation to the income and expenditure of an individual, household or group of people.
Other approaches to poverty measurement take into account the "social wage", which can include state provision of subsidies and services at reduced or no cost. The approach to poverty measurement inevitably influences the way poverty indicators are constructed.
The development of statistical indicators is not confined to separate countries. The "internationalisation" of statistical practice increasingly allows for comparisons between countries. This is a central element in the monitoring of social and economic progress across the globe.
There are a range of other transnational indicators, which aim to compare and rank countries according to different criteria. One of the most prominent is the UN Development Programme's annual human development index (HDI).
Development Report for 2006, which was released last week. This report, which has been published every year since 1990, presents indicators of human development that go beyond the material wellbeing measured through GDP.
According to the report, the HDI "provides a composite measure of three dimensions of human development: living a long and healthy life (measured by life expectancy), being educated (measured by adult literacy and enrolment at the primary, secondary and tertiary level) and having a decent standard of living (measured by purchasing power parity income)".
Indicators used - life expectancy, education and income for the HDI - involve a choice by those constructing any index. They alert us that something is happening in the areas measured by the indicators chosen. But as with barking dogs, others factors have to be applied to establish what it is that is happening. These include the introduction of context (Where are the dogs Are the cattle moving around Is it cold); additional information (Have there been thieves in the fields recently); and interpretation (Does the barking sound similar to previous incidents of attempted theft, or more like the time when a neighbour's dog tried to get into the hay?
The UN report is quick to acknowledge that the HDI is not a comprehensive measure of human development and excludes many important indicators. In this sense, it shows considerable sensitivity to the lesson of the barking dogs.
Pali Lehohla is South Africa's statistician-general and head of Statistics South Africa. For more information on Stats SA products and services, visit www.statssa.gov.