How Data Can Beat Poverty

May 14, 2018|Desola Ososami

According to the World Bank, approximately 50% of the Nigerian population lives in poverty.

Understanding the poor is a hard enough task in any country, but Nigeria further complicates it with our large, ethnically and regionally fragmented population. This makes it hard to design or implement one-size-fits-all policies. For instance, a national minimum wage is likely to have a smaller impact on poverty rates in Jigawa state, where 3 in 5 labour force participants are under or unemployed.

On top of the complicated landscape, we don't even know how many Nigerians there are. The truth is, we need to understand our population to guide poverty tackling policies. And data can take us a step forward. 


Data and Understanding The Poor

The standard definition of poverty is based on one’s income – to live on less than $1.90 a day. Therefore, the seemingly obvious way to monitor poverty is through measuring income and material standards of living. This way of quantifying poverty guided (or misguided) Nigeria’s poverty alleviation policies in the era of the infamous Structural Adjustment Programme of the 80s.

However, attributes of poverty span much wider than income. We can’t understand the poor by only considering their earnings. Factors such as actual consumption, health and education determine the quality of life and have the power to break poverty cycles. In all instances, we need detailed and varied forms of data on the impacts these factors have on poverty. 

Unfortunately, Nigeria has been known to be notoriously bad at data collection, especially on matters to do with poverty. For example, the SURE-P campaign of Jonathan’s administration struggled to monitor the progress of its maternity healthcare initiative.

In fact, 80% of observations were reported as missing. To make matters worse, data was collected via varying methods at different health centres, leading to incomparable statistics. This meant the policy was not able to quantify its impact and we cannot say how effective this ₦440 billion policy was. This type of careless approach to data collection makes it hard for Nigeria to tackle its detrimental poverty problem. 


The Proof is in the Pudding

It is easy to assume that people are poor only because they have no money and hence cash transfers should be an effective solution. However, data has proven that the solutions we think should work aren't always successful.

For example, a study of six microfinance Institutions around the world found that they did not have a transformative impact on poverty rates in any of their respective regions. Alarmingly, many were burdened by debt from microcredit to the extent that there was a staggering increase in India's suicide rates caused by the inability to pay back money from microfinance. This was only brought to light because data was collected from Randomised Control Trials to monitor the results of the microfinance Initiatives.

These results fundamentally adjusted the way microfinance institutions are structured; there is now a heavy emphasis on having low-interest rates. Without data, we cannot test and trial policies that common sense may deem effective.


Data Collection - Difficult but Mandatory

As paramount as data is in understanding the poor, it has its flaws. The poor quality of data collection in Nigeria cannot be solely attributed to people not recognising data’s importance. A major contributing factor is the difficulty of collecting good quality data anywhere in the world.

Besides the well-known issues such as survey bias, there is an even bigger problem where the poor have little or no access to technology. Systems such as Big Data and the Cloud that are widely used in more developed countries allow for one to analyse a whole demographic without the costly task of distributing a survey. In Nigeria, we do not have that luxury of mass cohesive data collection, especially amongst the most deprived areas of the country.

Nevertheless, poverty tackling policies are simply a game of cat and mouse without the guidance of good quality data collection. Collecting or at least using historical examples of success stories will go some way in tackling policy in Nigeria. With our vast population, we also have the potential to use much bigger samples than anywhere else on the African continent and provide results that can be extrapolated to other poverty issues in Africa. Its high time we led by example in tackling what is arguably the continent's biggest problem. 


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