Lying with statistics finally catches up

Nigeria became the largest economy in Africa. Kenya too will catapult into middle income status and as fourth largest economy in sub-Saharan Africa.

Most developing countries have not been capturing all the statistics that matter when it comes to economic growth.

Now they are undergoing a statistical review that in most cases will show the correct picture of economic growth, reflecting the true size of the economies across Africa.

A statistical review in Nigeria raised its gross domestic product (GDP) by close to 90 per cent to $519 billion (Sh44 trillion), making the country the largest economy in Africa.

Kenya’s review will put its GDP at $50 billion (Sh4.3 trillion) and $55 billion (Sh4.7 trillion) using the 2009 statistics as a base.
Analysts still think Kenya’s GDP will be even higher because 2009 was a drought year that may not give a clear base for Kenya’s economic growth.


Statistics especially from the chaotic micro and small enterprises is not often captured. In some countries, they do not even bother to gather the data. Most available data are simply voodoo estimates using antiquated predictive models.

Up until 2009 census exercise, Kenyans put Kibra population at one million but the actual census established that the sprawling shanty had less than 300,000 inhabitants.

In most countries, census data is real time, dynamic and factual owing to technologies that can help capture data to the last minute, but in Africa we still use out of date methodologies to gather the data.

With mobile penetration approaching 90 per cent, it is possible to get daily census data from every village aggregated at county level for verification.

Indeed, we can create an anonymised national register that can help our security agencies improve on national security while at the same time providing key statistical information for national development.

The statistical reviews may help to solidify the need for open data. Open data is not just a tool for transparency, but another way of data verification.

For example, when the Central Bureau of Statistics detected abnormal population growth in the North Eastern Province during the 2009, it rejected the data to the chagrin of the local people who argued that their population growth rate was higher because they married more than two women.

In reality, some foreigners had hoped to become Kenyans by default and such an eventuality can be destabilising. With open data, those charged with the responsibilities of gathering data will be on their toes knowing that the public has access and can verify it when necessary.

Clean and consistent data has many benefits. It opens up more foreign direct investment and greater borrowing capacity from not just the Bretton Woods institutions, but other international lenders.

Local lending will become easier to manage. Insurance companies, banks and other organisations will minimise losses since they will get to know their customers better in the face of existing jungle of information.

Planning as well at allocation of resources will be more responsive to citizen demands.

More importantly, the pride that comes with the fact that we shall no longer be considered a beggar nation will create the much needed confidence to trigger other benefits such as innovative capacity through research and development.

I say this because Africa has never quite come to terms with past colonial abuses.

This innately causes what psychologists will call a sense of lack of control which often affect people who are the victims of physical, emotional, or sexual abuse, or of discrimination on the grounds of religion, culture, race, sex, or sexual orientation.

To overcome such a problem, African countries must attain a respectable middle income status just like Asia’s newly industrialised countries.

This cannot happen if we do not have the discipline to make decisions based on data whose validity and reliability can be verified. No country or organisation will survive in the days to come without relying on big data analytics.

As it is often said in the information and communications technology sphere “garbage in garbage out” which refers to the fact that computers, since they operate by logical processes, will unquestioningly process unintended, even nonsensical, input data (“garbage in”) and produce undesired, often nonsensical, output (“garbage out”).

With valid data and the ability to analyse it, the impossible is possible.

Dr Ndemo is a senior lecturer, University of Nairobi and a former permanent secretary, Ministry of Information and Communication.