Measuring GDP In Africa

Many of the issues with financial data in Africa stem from the reduced degree of resources open to national statistics offices, which has resulted in inadequate quality macroeconomic data. Most African countries also use out-of-date nationwide income accounting specifications rendering international comparisons between their economies and the developed world of little value.

African countries generally fail to adequately record the size of the informal economy which estimates suggest could take into account between 21.9% and 62.7% of GDP in the countries over the continent. This paper analyses the accuracy and provision of recognized national income accounting data across 54 African countries. The primary factor impacting on the grade of national income statistics across Africa is the capability of national statistical offices and the resources designed for them to check out the best international practice to ensure comparability with other parts of the world. This is a worldwide problem, but it is specially serious across Africa because of the relatively higher proportion of the world’s poorer countries that are located in the continent.

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“…in most African states the database for aggregating methods of income and development are vulnerable. The problem is more serious than the shortcomings that can arise from individual national statistics offices feeding inaccurate data into the public domain. There’s also serious discrepancies in the info on African economies released in international economic databases. Even though the economic data made by national statistical offices are released regularly serious distortions arise from the use of outdated base years. This biases estimations of the relative size of economies and the speed at which they are growing in real conditions.

The time elapsed between current estimations of GDP and the bottom year employed to assess the structure of the overall economy is of crucial importance to the accuracy of national income data. According to Jerven (2013) failures to regularly update a base calendar year in which the structure and comparative prices of the economy are monitored can lead to serious bias in the estimation of GDP. The methodology used is crude and consists of applying around constant cumulative annual rate of development to the years between the last reported foundation 12 months and 2014 on top of the fundamental rate of real development.

The longer the period between 2014 and the last bottom year and the higher the assumed cumulative growth rate, the higher the uplift that would be expected from reading. First the decision of a base-year data series to apply on a country by country basis, an activity made difficult given the inconsistencies between the WDI, the IMF, and the UN.

Inconsistent Base Year Data: The available data on the most recent base years for African countries are inconsistent. The three main international resources are the World Bank’s World Development Institute (WDI), the IMF, and the UN. Alternative sources will be the base year documented by each country’s national statistical offices, but often these are not reported. There are considerable variations in the reported base year between all of these sources, which are specially worrying when there are discrepancies between reputable international bodies like the WDI, and the IMF.