Over the past weeks, speculation over the country's economic growth rate has been more pronounced than usual. Some economists have suggested that the rate of increase in value-added tax collections, or an increase in the number of workers registered on the Unemployment Insurance Fund (UIF) database, are good indicators of economic growth.
Statistics SA calculates gross domestic product (GDP) using both production and income approaches. The production approach derives GDP at market prices by deducting intermediate consumption expenditure (uses) at purchasers' prices from total output at basic prices after making provision for taxes and subsidies on products as well as trade and transport margins.
The income approach entails summing all the components of value added - compensation of employees and gross operating surplus after making provision for taxes and subsidies on products.
The SA Reserve Bank is responsible for compiling the expenditure approach to estimate the GDP. This entails the summation of the components of final demand - household consumption expenditure, general government consumption expenditure, fixed capital formation, change in the value of inventories and exports, and subtracting imports.
GDP estimations are data intensive and overreliance on one source to assess economic growth (UIF registrations, for example) might result in conclusions that cannot be sustained. Generally speaking, the more detailed and frequent the data, the higher the quality of the estimates.
However, in some cases the detail required for estimations is not immediately available. To some extent, this is compensated for through benchmarking, a process where data sets with different characteristics are combined to benefit from the strengths of each series.
In this way, infrequent data sets provide the basis for the development of benchmarked level estimates of the GDP.
The various data sets used are often designed to serve different purposes and report on different aspects of the economy. Benchmarking enables development of an integrated, coherent set of statistics that will inform users on the dynamics of the economy.
Stats SA uses the input-output framework for the derivation of the benchmark estimates of GDP. This allows for the comparison and confrontation of all relevant data sets in a comprehensive and systematic manner.
It combines the results from all three different approaches to GDP compilation (production, income and expenditure). The framework is embodied within the sets of supply and use tables. These tables provided the nominal estimates of GDP for the relevant years on a detailed industry and commodity level.
As a statistical tool, these tables provide a co-ordinating framework for checking the consistency of economic statistics on flows of goods and services obtained from different statistical sources.
Quarterly GDP estimates are seasonally adjusted. This is a means of removing the estimated effects of normal seasonal variation from the estimates so that the effects of other influences can be more clearly recognised.
The estimates of value added by each industry are classified according to the fifth edition of the Standard Industrial Classification of all Economic Activities (SIC). A range of data sources are integrated in order to estimate the value added in each of the nine main SIC categories: agriculture, forestry and fishing (SIC 1); mining and quarrying (SIC 2); manufacturing (SIC 3); electricity, gas and water (SIC 4); construction (SIC 5); wholesale, retail, motor trade and accommodation (SIC 6); transport, storage and communication (SIC 7); financial intermediation, property and business services (SIC 8); and general government and personal services (SIC 9).
Economic performance in each of these areas is measured using a number of different sources of information. In SIC 2, for example, information is supplied by the Chamber of Mines and the department of minerals and energy. This is integrated with monthly data on production and sales for the various sectors of the mining industry.
For SIC 5, benchmark year estimates are extrapolated according to the trend in gross domestic fixed investment of residential and non-residential buildings, and construction works as compiled by the Reserve Bank.
Distribution keys are developed from building statistics and information obtained on the sale of building materials. Information is gathered on trends in gross domestic fixed investment of residential and non-residential buildings, and construction works. Finally, data on monthly statistics regarding building plans passed and approved are integrated.
The sources used for evaluation of growth in each of the industrial sectors are considerable. Reliance on a single source of information can be an important control factor against which changes in GDP are assessed.
However, it would be unusual for a single stand-alone data set to be used as a reliable indicator of economic measurement. Official GDP statistics for the third quarter of the year will be published late this month. These will provide answers to many of the questions raised in speculation over economic growth.
Pali Lehohla is South Africa's statistician-general and head of Statistics SA. For more information on Stats SA and its statistical outputs, visit www.statssa.gov.za or contact user services on (012) 310 8600.