GDP Re-basing: What does it mean?
April 11, 2014 — 10:08

Author: Vincent Agan  Category: #DataScience  Comments: 0

Nigeria recently made headlines with news of its move to re-base its GDP and in the process topple South Africa as Africa’s biggest economy and move to within reach of the world’s top 20 economies.

With the updated figures, Nigeria’s estimated GDP in 2013 has been put at an incredible $510 billion, almost doubling the previous year’s figure of $263 billion according to Nigeria’s National Bureau of Statistics!

So what is GDP?

According to Investopedia, GDP (acronym for Gross Domestic Product) is the monetary value of all the finished goods and services produced within a country’s borders in a specific time period, mostly a year. It includes all of private and public consumption, government outlays, investments and exports less imports that occur within a defined territory.

It provides an indication of the economic health of a country by measuring its productivity although its accuracy and the failure to take into account the underground economy has raised doubts of how true a picture of the economy it portrays, especially in sub-Saharan Africa.

And as Morten Jerven, author of Poor Numbers: How We Are Misled by African Development Statistics and What to Do about It, wrote, one of the most urgent challenges in African economic development is to devise a strategy for improving statistical capacity.

And re-basing?

As we might imagine, economies vary in size over time as new products and services are developed; new sectors emerge; new technologies grow; and consumer tastes and preferences change. In light of that, GDP is measured relative to figures in earlier years, a base year to be more precise. So this base year needs to be continuously changed to reflect changes in an economy.

So re-basing is, basically, the process of replacing an old base year to compile volume measures of GDP with a new and more recent base year or price structure. Huh?

In Nigeria’s case, for instance, the re-basing altered Nigeria’s base year from 1990 to 2008. Consequently, the number of measurable industries has risen to 46 from 33 and greater weighting has been given to sectors such as telecommunications and financial services as a result of the re-calculation.

But the process does not change what is already there, it only reflects the current situation better, and as Yemi Kale, head of the Nigeria’s National Bureau of Statistics, puts it, “It’s just about measuring better and more accurately”.

More African countries are set to follow suit as a more up-to-date and higher income status would enable more borrowing from international institutions and could very well be the catalyst for increased direct investments in sectors such as Telecoms and Banking.

For example, Kenya, with plans to shift base year from 2001 to 2009 later this year, is estimated to confirm her status as the 4th largest economy in sub-Saharan Africa behind Nigeria, South Africa and Angola after updating her GDP figures.

But is it all good for Nigeria?

The tax revenue to GDP ratio is a metric that checks the percentage of GDP that is tax revenue collected by government. It is generally higher in developed countries like Sweden which has 54% and lower in poor economies. Before the re-basing, Nigeria’s ratio was about 20% but drops to a lowly 12% according to Nigeria’s National Bureau of Statistics after as the rise in GDP increases the value of the denominator at a higher rate compared to the numerator.

As mentioned earlier, it does not change the situation on the ground as Nigeria’s poverty rate still stands at a whopping 61% according to data from the World Bank: A figure which dwarfs other African economies.

Also, if we were to use the law of large numbers’ connotation in a financial context, a bigger economy makes achieving growth harder and therefore a slower growth rate as opposed to a smaller economy. This means not so eye-friendly growth numbers for Nigeria in the immediate future.

Makes sense? No? That is probably why they leave it for the economists!

Poverty, Population And A Possible Way Forward
April 4, 2014 — 5:19

Author: Vincent Agan  Category: #DataScience  Comments: 0

“Poverty is the worst form of violence,” said Mahatma Gandhi.


And it seems humanity does concur because the Millennium Development Goals (MDGs) constitute, among other targets, reducing by half the number of people living in extreme poverty by 2015. The ultimate aim, however, is to attack the root causes of poverty using a multipronged approach.


It is no secret that poverty rate is intertwined with population dynamics like population growth rates, distribution, age structure etc. Low income is one of the most important metrics of poverty and therefore having fewer dependents (children and older people) in relation to a larger healthy and working age population would enable a country to realize economic savings and high investments, which could, in turn, spur economic growth and reduce poverty.


Taking Kenya, for instance, there has been a continuous rise of the number of people falling into the poverty bracket from 2007 to 2012 in the country.



This puts the national poverty level at just about 47%. It is not to say though that this is uniform throughout the country, as the severity of poverty varies from one county to another: Some counties such as Kitui, Marsabit, Mandera, Samburu, Tana River, Turkana and West Pokot, for instance, have poverty levels above 70 per cent whereas some like Kajiado, Kiambu, Nairobi, Meru and Kirinyaga have sub 30 per cent levels!



Counties with high poverty levels in Kenya tend to be in harshly dry weather conditions with low population densities. The cost of providing services in these areas has been argued to be more expensive and have therefore suffered neglect over the years.  Devolution, and more specifically, an equalization fund has been set up and will be used to finance development programs in the counties considered marginalized with the sole aim of reducing regional disparities among counties. While it is a welcome step, if the government is truly committed to the realization of MDGs and elimination of poverty by the year 2030 as per the Kenya Vision 2030, you do get the feeling that more needs to be done, though.


Also, more educated women tend to bear fewer children as opposed to less educated women. This means a lower fertility rate in a more educated society, a more controlled population growth rate and a lower poverty rate. So in a nutshell, more investment in education to empower the population and better health care, not only for family planning but for a healthy working class population, would go a long way in attaining these targets.



Effects Of Corruption On Governance And Investment In Kenya
March 28, 2014 — 13:53

Author: Vincent Agan  Category: #DataScience  Comments: 0

Corruption is, essentially, moral perversion; a deviation from an ideal; that habit or set of habits that are illegitimate, immoral, or incompatible with ethical standards of a people.  Greek philosopher Aristotle is credited as having first used the word Corrupt.

Various forms of corruption exist but the insistence on bribery in both definitions places it as the most common form of corruption in governance and business. In Kenya, for instance, it is hardly considered an oddity but rather the norm to be asked for a bribe or be offered some form of bribe.  From the traffic police who demand bribes to let offenders off the hook; to government offices that charge an extra fee commonly known as chai to offer public services; to public school administrators who demand bribes to admit students; the list is endless and cuts across a variety of sectors with varying degrees.


Transparency International, in 2012, listed prevalence of bribery in Kenya at a staggering 29.5%; this is essentially a measure of the likelihood of bribery demand in a country.  Although lower than Tanzania and Uganda at 39.1% and 40.7%, respectively, it is still a high figure compared to Rwanda’s 2.5%, the least bribery-prone country in the region.


Corruption derails governance which consequently impacts negatively on the Global Competitive Index ranking of a country. For instance, according to the 2012 Ibrahim Index of African Governance, Kenya performed abysmally in the area of government effectiveness, scoring 35%, below the 50% average score. Rwanda on the other hand with a less bribery prevalence figure sat pretty among the best in the continent in the category.


Kenya’s Global Competitiveness Index ranking fell from position 102 in 2011 to 106 in 2012 compared to Rwanda’s improvement from position 70 to 63 within the same period, according to the World Economic Forum (2012) figures. Note the correlation between the prevalence of bribery scores and competitiveness ranking in the two countries.



Corruption touches on business as well as it raises transaction costs and creates uncertainties to prospective investors as doubts emerge over a number of business enablers among them the enforcement of contracts. In fact, for two years running in 2012 and 2013, corruption emerged as the most problematic factor for doing business in Kenya.



Other factors such as inflation, access to financing, taxation and crime fluctuate in their severity within the two-year period but corruption retains top spot all through as the most problematic factor for doing business in Kenya. Time to wake up and act?


It is going to take more than just plastering every wall with the phrase “This is a corruption-free zone” to rid our society of its Achilles’ heel. When A. P. J. Abdul Kalam highlighted the mother, father and teacher as the three key societal members who can make a difference for a country to be corruption free and become a nation of beautiful minds, perhaps he envisaged the change to such a society as more of an evolution rather than a revolution with the family as the basic unit of society at the forefront of the transformation and supported by the teacher, society’s nurturer of young minds.

Why the Access to Information Act alone won’t work for Open Data.
March 23, 2014 — 20:19

Author: linet  Category: #DataScience  Comments: 0

The Freedom of Information bill that was first introduced in Kenya and has been in debate since 2006 has still not seen the light of day in legislation. The bill was later renamed to the ‘Access to Information bill’, due to uncertainty on what ‘Freedom of Information’ really means.

Having read the entire proposed bill and its partner in crime, the proposed Data Protection Bill (proposed as a measure to protect information that should not be made public), I am convinced that just the simple act of enacting these bills into legislation will not save Open Data…

Inadequacies within the bill.

The proposed bills still do not make it very easy for citizens (or anyone within legislation) to access government information freely and any easier. From requiring that data seekers write a request letter and give up to 15 days response time to the affected institution introduces delays in this otherwise forward looking idea. There is more like data seekers having to take care of the cost of accessing the information in printing or transaction charges etc.

Data Hogging Culture.

We still don’t have a sharing culture be it in government, civil society or private sector. Everyone still has the  data hugging syndrome that is coupled with “this belongs to me, even if I am not using it right now” culture. For Open Data to work seamlessly, with or without legislation, the people, who are the carriers of this data need to change their outlook towards data sharing.


With the existence of the Official Secrecy Act, government officials will always find a reason to downplay openness and sharing of information about government processes and activities. The simple idea of the availability of this act preceding any other that allows for people to access and question government processes will for a while frustrate the access to information efforts.

Revenue Collection.

As much as we go around throwing the idea that all government statistics are collected primarily with tax payer money, the National Bureau of Statistics is required by law to make revenues out of the statistics that are collected.

All of the sales are in hard copy books that range in price between  KES 1000 and 1500. There have been arguments about the possibilities of making this sales online in softcopy… but we all know what happens to ebook businesses once someone has a copy.

Most of the hard copy data is available at the KNBS library but there is the small KES 50 for daily access, now this is cheaper and gives more access to more data but still, this can be done in a better way.


This little issue of lack of efficient digitization within government will forever slow down the efforts of access to information. Notice that I said slow down and not stop. There are very many government institutions that still can only give you info in hard copies or that only have hard copies hence putting these online becomes a hard task.

There needs to be a clear strategy for government digitization and this was part of the recommendations (that were not included in the bill as is) because without digitization of government records, no matter how open the data is, it will only be available to those with physical presence vantage.


Cancer, the uprise of a killer disease!
March 15, 2014 — 10:36

Author: linet  Category: #DataScience  Comments: 0

Cancer is quickly becoming a household name when you talk about health in Kenya. We have gone from hearing about it in the news to coming face to face with the disease in our daily lives.

The statistics below show some of the important numbers about cancer and its care, numbers that are very scary per capita and increase rates.

The good news is, there are many cancer survivious and if detected early, there is a lot of hope and a great possibility that one can be treated. So please, let us get checked!

All the statistics are based on a great blog by the Kenya Network of Cancer Organizations that contains all the links to the literature.

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Why There Are Very Few Women In The Workforce.
March 13, 2014 — 6:33

Author: linet  Category: #DataScience  Comments: 0


Being in the technology space, I am always confronted with the question of, “Why are there very few women in technology?” In my college class of Computer Science, out of 44 of us that were admitted, only 8 were women. An interesting thing to note on this is that at the end of the 4th year, during our graduation, out of the 27 graduands, 8 were women! None of the girls dropped out.

As I have grown to interact with more professionals, I have been constantly faced by the same question in different fields; in media, in medicine, in politics, in law, you name it. The only place there seems to be no shortage of women is in the home. Having let Sheryl Sandberg drum her ideologies of Lean In to my head, and looking at how many women really need to lean in, these question got to me, why are there very few women in the workforce?

I watched a Robert Reich document called Inequality For All and being a data nerd this was interesting. The documentary showed that in America, one of the most progressive countries in the world, Women started getting into the workforce in the 1800 to 1850 and although in very small numbers, there were very many great contributions by women in innovation, politics and technology. The feminist movement started in the 1960 and during the turn of the economy when the cost of living was going very high but the family income (mostly to the men) remained the same, women joined the workforce in masses to be able to complement income from their husbands. It is also around this time of 1980 that Dolly Parton released the song 9 to 5.  This started a culture of working women. A lot of women in America still have the option of go to work or stay at home until the kids are able to go to school.

In Africa, however, our mothers have always been working. The African labor force did not become very formal until mostly after independence but following the history very carefully, women have not always stayed at home to wait for the men to bring home food (although some do). Women were working along side the men during colonialism, as the men fought, the women gathered food. After colonialism, as the men were seeking formal jobs, the women were helping make their clothes etc. There was not a real option of stay at home and take care of the family, most of us were really raised by the village and our age mates as the mothers went out to the fields to till and grow/harvest food. All the mothers I know of, from my childhood to now, have always been working (although in informal sectors) and if not, not by choice.

Maybe we need to document and/or formalize some of the sectors that women in Africa work in or redefine what the formal sector is..(beyond having to wear a suit to work..) 80 percent of Kenya’s jobs and 60 percent of income are in the agricultural sector and women hold up to 60 percent of these. Historically, women have always been in the agricultural sector and men have been in the mechanical, engineering, policy and technology fields. So, mathematically, the number of women in these STEM sector is expected to be low, just as the number of women in agriculture is expected to be high.

Men have been working as engineers for a very long time, the women just joined in recently. There has been a culture around the world that anything that looks complicated – a computer, a printing machine, a car, a cooker, a mobile phone etc must be operated by a man. With the feminist revolution that had women drive cars, make their own living and take care of themselves, we have seen an increase in the number of women joining the formal workforce that is rumored to pay better. Although it be that women started off as secretaries and nurses, at the entry point, we must appreciate that there was a time when offices were filled with just men, there still are.

An unlikely headline the other day was that for the first time in history, women outnumbered men in Berkley’s Introduction to computer science class. I am almost certain this is the first in many parts of the world and in my class where women were 1/6 of the class’s population, there really is hope. This shows that once there is an entry point, the future is most certain set to change.

Please don’t get me wrong, I am not a big fan of “what a man can do a woman can do it even better” phrase that we use to push our way in, what I am saying is, historically, since the formation of the “formal sector” we must appreciate that a lot of the things were run by the men and moving forward, the question should stop being why there are very few women in the professional workforce to how can we bring in more women to the professional workforce. History already beat us to the why and that really cannot be changed.

Hell, in the movie Jobs, 2013 (a documentary of Steve Jobs), the biggest role played by a woman was that of his mother who always brought him food and encouraged him! Well, there is also his ex- girlfriend.

How to save Turkana, conversations with my Father.
March 3, 2014 — 6:41

Author: linet  Category: #DataScience  Comments: 1

Those of us who follow my undoings know that I am very close to my dad and that we like to spend time talking about all sorts of intelligent crazy things. This weekend, we had such pleasure to spend some time together and we spent it looking at the situation in the country, politics, health, leadership, counties etc.
Of the more interesting conversations was Turkana county, whether the media is portraying a real image of what is happening or not, the famine, floods and its leadership. Of importance, is the list below of a brainstorm that we had on how people in Turkana (and other parts of the country) can be saved from all the hardship they are going through.

Food for work

The Turkana county has been endowed with many valuable resources and top among those are oil and water. The local communities should be given employment in return for food. Now, don’t look at this surprised thinking how will the poor malnourished weak people manage to work! If given sufficient and continuous food, you and I know that they will gain strength capacity to work, I mean, don’t we all? #motivation

More Information on the County

One of the things that is ailing the county is the lack of information. We have seen mixed pictures of people in Turkana living in green well cultivated areas as others are still in the depth of suffering. There should be more information collected and made public about which areas of Turkana are really suffering, which ones have great capacity and which ones have resources that can be tapped to contribute to the entire county. As should other regions of the country.

A better focus for NGO work

Growing up, i read a tale about young boys who were tasked with ensuring that rats did not invade the family maize granaries. Every evening, these boys are said to have gone to the granaries with clubs to kill the rats but when they got there, they only killed the big rats and spared the young ones “for next time” they said.

The NGO sector (not the whole entire sector) but in a lot of the work that i have seen and talked to people about has become a business. The sector is failing in coming up with sustainable solutions for those suffering but have instead turned and become like the boys at the granaries. They are providing just enough food, just enough water to ensure survival until next time. This keeps development work relevant.

There are very few NGOs working in poverty afflicted regions that have focused on sustainable solutions for the locals. finding ways that will ensure that the locals are not dependent on them for eternity. Projects in Agriculture and trade.

Increase water points

The people in the Northern parts of Kenya have for a long time been known as patralists. Now, from my primary school education, pastralists are always moving from one point to another in search of water and pasture for the animals. To ensure sustained development, there should be more bore holes dug to supply water that would limit the movement of the herders, provide water for irrigation and ensure the availability of labor to focus on other economic activities in the county. This is not rocket science!

An added point to this is that it will allow the communities with deep cultural believes in animal raring realize that they do not have to abandon their animals, but that they can do both animals and plants.


We have all been put under the illusion that agriculture can only be done in areas that have predictable rainfall. On the contrary, there are some crops that do well in dry seasons and that probably only need a few days of rainfall. Sorghum is one such plant. This can be easily used both as a food crop and as a cash crop to the breweries for beer manufacturing. If enough research is done, I am sure there is gonna be a longer list of such plants.

Another option to farming is going back to the old days of barter trade. People in Turkana can grow drought resistant crops that can be exchanged for other items in other communities, or even the government and manufacturers.

These, people, are some of the things that we think if implemented, could see a more prosperous northern region of Kenya because:

“No matter where you are from, your dreams are valid” – Lupita Nyong’o.

Busia County Demographics Check.
February 24, 2014 — 9:29

Author: linet  Category: #DataScience  Comments: 0

Busia County is located in the Western part of Kenya, and its boundaries mark the Kenya/Uganda boarders. It goes without saying that Busia county stands in a good position for cross country trade and economic activities.

The Governor of Busia County is Sospeter Odeke Ojaamong (ODM).


According to KNBS’ census 2009, Busia had a total population of 743,946 with a male to female ratio of 1:1.1

This post aims at mapping out a few social demographic facts about the county, in relation to the population.

Access To Education:

Busia Education

Source: County Score Card.

People With Disability In The County:

Marital Status:


County Age Groups:

Flower Farming in Kenya.
February 16, 2014 — 20:50

Author: linet  Category: #DataScience  Comments: 0

Happy valentines day to you! Ok, happy post valentines day. As the world marked this annual event of flower sharing, the #dataScience team was busy looking into the flower farming business in Kenya.

Kenya’s economy largely relies on the agriculture sector which contributes:

Kenya’s GDP stands at 37.23 billion US dollars. Of this, horticulture as one of the top foreign exchange earners for the country generates approximately US$ 1 billion annually.

The amount in tons of Cut Flower Exports have seen a great increase over the years:

While the main areas where flower farming are around Lake Naivasha, Mt. Kenya, Nairobi, Thika, Kiambu, Athi River, Kajiado, Kitale, Nakuru, Kericho, Nyandarua, Trans Nzoia, Uasin Gichu and Eastern Kenya; the main export markets for the flower industry in Kenya are in Europe, including Holland, United Kingdom, Germany, France, and Switzerland; with new growing destinations for flower demands including Japan, Russia and USA.

The main flower types grown for export in the floriculture industry include:

The flower industry has been a great source of employment to the local people in the areas the cultivation takes place but also to people with different expertise from other regions within the country and internationally.

It is estimated that there are over 90,000 employees (directly or indirectly) in the flower farm industry and about 500,000 other people who depend on the industry.

Why Governments Shun The Open Data Movement…
February 7, 2014 — 6:31

Author: linet  Category: #DataScience  Comments: 0

The government of Kenya launched its Open Data Initiative in 2011, making it the 2nd country in Africa to launch an Open Data movement in Africa after the Morocco government. in 2012, Tunisia followed, and most recently, Nigeria also launched its Open Data Initiative – These are all government led initiatives.

The World Bank was a pioneer in opening up data and the African Development Bank followed on shortly after with its Open Data for Africa portal (another very rich data source!). More governments in the global northern countries (the west) have released data portal than African countries have and carrying the reputation that Africans generally like to follow what the “west” is doing, got me thinking about why more African countries are not releasing their data portals.

Having attended Open Data conferences both in Africa and in Europe and America, I noticed a big difference in the way the Open Data message is communicated to these groups that i can group to two – Africa and the “West.”

In the “West”, the open data message has been branded as that of development, citizen access and business development. Governments are encouraged to release train route data and time so that developers can make apps that allow better access to schedules. In Finland, there is an app that shows you when traffic builds up and when it slows down (working economies). There are very many examples to this like in the US where open data on gangs and arrests has been used to inform citizens on safe neighborhoods, corners and times. There was one project where open data allowed planners see the neighborhoods that did not have water supply which turned out to predominantly be black neighborhoods. You get the point. Now which government does not want its people to be served better?

In Africa on the other hand, Open data has become the “Let us fight corruption” project. Don’t get me wrong. While i am definitely of the opinion that open data can help do this, I feel that this is the wrong approach to getting the project running. As human beings, our first reaction under attack is to guard ourselves. People that work in government are no different. As soon as the only message we take out there about the benefits of open data is that it helps fight corruption, the corrupt government officials (who more often are top ranked) will definitely resist the implementation of the project.

My advice to open data evangelists is to choose a different approach when requesting governments to open up data, let us focus on the bigger picture of the benefits of open data. The citizens for example and how better their lives will be when they access the data, the planners and how resources will be better allocated, the entrepreneurs and how the GDP will be improved etc. While corruption is case that can be solved, a focus on corruption alone will only get open data into the trouble of resistance.