Anglo-Leasing Payments and Kenya’s Debt-GDP Ratio
May 29, 2014 — 12:11

To quote the Government statement on settlement of Anglo Leasing debts, The Government’s decision to settle the judgment debts is premised on – Protecting Kenya’s economy on account of rising interest rates occasioned by domestic borrowing due to constrained access to international borrowing; Protecting Kenya’s reputation as a country that meets its contractual obligations and adheres to the rule of law; Protecting Kenya’s assets abroad; and maintaining and improving Kenya’s credit rating currently at B+.

If the statement is anything to go by, it was necessary to make the payments to Anglo-Leasing so as to maintain and improve Kenya’s credit rating in light of the proposed issuance of Eurobond to finance the Fiscal Year 2013/2014 budget.

To explain it , a Eurobond is a bond denominated in a currency other than the issuer’s home country. They are mainly issued by governments, corporations, and international organizations.

Kenya is set to follow Rwanda, Nigeria and Ghana – African countries who issued bonds in 2013 – in doing so and, according to the Central Bank of Kenya, the proceeds from the $1.5 bn Eurobond issue will significantly raise the level of foreign reserves with the exchange rate of the shilling expected to come under pressure to appreciate in the coming months. The Kenyan shilling has been on a downward spiral against other currency, recently falling to just under KES 88 – a 28 month low. Using this USD-KES exchange rate, the amount to be borrowed will be around KES 132 billion.

So it all amounts to doing away with KES 1.4 bn to get KES 132 bn. Worth it?


An increase in government debt raises the Debt-GDP ratio. Looking at @Ramah_Nyang’s Twitter time line from 27th May, 2014, this will raise Kenya’s Debt-GDP ratio to the 53%-55% range.


Comparing Kenya with a few selected countries worldwide makes for some interesting viewing.

But the expected GDP re-basing for later this year should raise the GDP figure and thus lower the Kenyan ratio by some percentage points.

Diversification and GDP per Capita: Related?
May 22, 2014 — 11:17

GDP is loosely defined as a country’s total economic output for each year. It constitutes consumer spending, government spending, spending by businesses and net exports which is export revenue less cost of imports.

Focusing on export revenue – income from sale of commodities to other countries on the world market – does diversity matter? Is it prudent for countries to diversify production in their efforts to bolster economic growth or should they focus and narrow down on what they can produce best?

Diversification is achieved by boosting non-traditional sectors; expanding range of exported commodities; and engaging with new economic and development partners. Simplifying this and focusing on the range and variety of exported commodities as our only metric, A more diversified economy would be one in which the revenue from highest export revenue earner makes up a lesser proportion of total export revenue. For example, South Africa, where the highest revenue earner (Gold) constitutes 14% of total export revenue, would be deemed more diverse than say Zambia where the highest revenue earner (Copper) constitutes 77% of total export revenue.

I have therefore compared GDP per capita- as it is often considered an indicator of a country’s standard of living – against proportion of total export revenue as a percentage for a number of African countries.

GDP per capita against highest ERE

As is apparent from the countries plotted, diversification has not translated to better living conditions as such. Spreading the risk amongst many commodities has its advantages in situations like a drastic fall in price of certain commodities in the international market, granted, but maybe just getting the most out of a few commodities by, say, value addition could be the key to more revenue rather than just diversification.

Is this fair on Aisha?
May 14, 2014 — 10:09

“They grow up so fast these days”, cliché, I know, but that was my thought when I spoke to Aisha the other day.

She told me she is now in standard eight, the last year of primary school in Kenya. That means she is penciled to sit for her Kenya Certificate of Primary Education examinations at the end of 2014. I could not believe what I was hearing as she bragged about having an examinations index number; I used to babysit her the other day. Heck, she could not even pronounce my name right, it seems to me,  a few months ago! But there she was seemingly chuffed, a thirteen year old girl preparing for a national exam along with hundreds of thousands of other boys and girls. I have qualms about exposing children to so much pressure at that age but that is a story for another day.

Different challenges, different environments, different circumstances but same blanket exam conducted in less than a week to determine whether they can join high school; and if they are “good” enough to join high school, which type of high school? Is it fair on them?

So, taking the 2013 results, for instance: Was the performance a measure of real ability and effort or was it affected by income levels across the country? Should more financially endowed households be able to support their children more with resources to study and be able to prepare better for such an exam as opposed to lesser financially endowed households?

To try and find out, I plotted the KCPE mean score for every county against its poverty level using data from KNBS/ SID inequality report, 2013 on a scatter plot. The higher the poverty level the lesser the average income in the county. To get a rough idea of the disparity within the counties Nairobi, the lowest in Kenya, has a poverty level of 22% while Turkana’s is at 88%; a difference of 66%!

KCPE mean score against poverty level

KCPE mean score 2013 against Poverty level



Notice the relation? As the poverty level increases, the KCPE mean score generally tends to reduce. Calculating the Pearson’s R (correlation coefficient) for the relationship gives an answer of -0.50, not a perfect but a fairly high degree of negative correlation, still.

But then, some will say we have free primary education where the government abolished fees so as to give every thirteen-year-old-out there a fighting chance by undertaking to provide the resources needed. Fair enough, but are these resources allocated equitably?

To provide childhood education, one the most important resources needed is enough well trained teachers so as to have smaller class sizes. In fact, studies have shown that the smaller the class, the more effective the teacher can be. How about we look at class sizes at county level then?

Using data from the Ministry of Planning, National Development and vision 2030, I did another scatter plot this time with the KCPE mean score for every county against its figure for number of pupils per teacher where a bigger figure means a larger class per teacher. Disparities exist here as well because a County like Elgeyo Marakwet, second ranked county using the KCPE performance has a Number of pupils per teacher ratio of 33 while the last ranked county, Mandera, has a figure of 88!

KCPE mean score against Number of pupils per teacher

County 2013 KCPE mean score against Number of pupils per teacher - Kenya

Notice the relation again? As the figure for the number of pupils per teacher increases, the KCPE mean score generally tends to reduce.  Calculating the Pearson’s R (correlation coefficient) for the relationship gives an answer of -0.47, a fairly high degree of negative correlation as well.

Of course, these are only 2013 numbers. We could get a better idea after looking at numbers over time but for Aisha’s  - and every other standard eight pupil out there’s – sake, I hope they don’t imply the same.


The Economy: Comparing Kenya With Africa
May 8, 2014 — 10:01

After Nigeria followed Ghana by re-basing the country’s GDP the other day, and the subsequent effect in making the numbers look good, the research team at DataScience got curious: How do the numbers in other African countries look? Which sectors contribute to their GDP? And how does Kenya come up against other African countries?



Kenya has the largest economy among the members of East Africa Community in terms of GDP accounting for 40 percent of the region’s GDP, followed by Tanzania at 28 percent, Uganda at 21 percent, Rwanda at 8 percent, and lastly Burundi at 3 percent.



According to the CIA World Fact Book, services sector contributes to 53 percent of Kenya’s GDP, agriculture makes up 29 percent while industry produces 17 percent.  A comparison with global growth giants China and Malaysia and then to Sub-Saharan African neighbors (can we refer to them as peers?) Uganda, Nigeria and South Africa corroborates the importance of the industrial sector to economic growth.



The Industrial sector in Kenya constitutes of manufacturing, building and construction, mining and quarrying. Manufacturing takes the lion’s share with 70 per cent of the industrial sector contribution to GDP, going with data from the Kenya National Bureau of Statistics. As highlighted in the vision 2030, manufacturing and industrial sector as a whole is one of the key drivers for sustained economic growth, probably because of its limitless yet untapped potential to contribute to employment and GDP growth.


Connected Kenya 2014 – Breaking The Barriers.
April 28, 2014 — 14:07

A week ago, The Kenya ICT Authority held the annual Connected Kenya event in Kwale County, at the Diani Beach which is part of the Msambweni division.

The event, as always was attended by high profile delegates and a whole lot was discussed. There are 3 main events that caught my attention for obvious reasons as noted below:

The Women in ICT fireside Chat.

As always, no matter what ICT event you go to, there will always be the question of, where are the women in technology?! From a previous blog, it is very clear to see why there are very few women in a lot of professional fields but this event provided a great opportunity to discuss what can be done to actually increase the number of women in technology.

  • Upbringing – to encourage more young girls into technology or any other STEM profession for that matter, there needs to be a champion in their life. It could be parents or just the environment.
  • A more practical education system – It is very obvious to hear people complain about the fact that the education system is not providing any valuable insights for professionals. Well, unfortunately, there are girls who do not even have access to any of the training at all.
  • Mentorship – The only way we can have more women in leadership is, if we have more women in leadership – Dr. Wanjiru Kamau
  • De-Mystifying STEM – my father once told me that the reason why a lot of people fail mathematics is that too many people have over complicated the idea of doing well in mathematics that young kids think that you must be very special to pass mathematics. This definitely needs to change if we are to encourage any young girls into technology.

Information System Security Session.

This was an interesting session for obvious reasons. Just looking at how much information we have put out there about ourselves and how big a data shadow we have created, the speakers in this session sought to remind us of the dangers. Think about all the receipts you put in your garbage, the posts on your social media interactions and just how much information individuals have left unsecured!

Of  great interest, was that this session came in jut days after the heartb-leed cyber attack came to life and just how Kenya has a great number, a higher percentage of malware infected PCs compared to global averages. In this wake of online and mobile banking, we have gotten into the habit of only going t places with free internet including coffee shops and offices without the clear assurance of the security of the internet connections. “Caution, surf at your own risk – By Management”

Kenyans have gotten into a clear habit of ‘torrenting’ free/pirated software from the web, very often without any security assurance of the safety of their devices or networks. We have seen government and corporate websites being hacked, making the issue of vulnerability real. with stolen credit cards going for about $10, we surely want to be safer online.

Reinventing government planning through analysis of past and present trends.

The government of Kenya launched the Kenya Open Data Initiative in 2011, an initiative that is aimed at not only releasing data to the public freely and openly but so that the government itself would be able to use the data for analysing for resource allocation and planning.

This session was particularly important for the identification of exiting solutions and trends and simply seeing how far the various government entities are in sharing data or even making use of them. Key in this session was just how important data sharing is. At the beginning, the moderator carried out a short ice breaker that had people exchange business cards and have you question if you will ever use those cards or not. Data is no different! We can be overloaded with masses of data from the government and other agencies but at the end of the day the main question is, is this data important/useful or would we rather have an option to select what might be important?

And in unison with the theme of the event, closing the day was a valuable lesson from the ICT minister for Rwanda, Nsengimana Jean who shared the 5 key pillars for Smart Africa – Policy, E – Government, Broadband, Sustainable Development, and putting the private sector first.

Important to note too was that the Kenya National ICT Master Plan that will guide the ICT industry in Kenya was launched, check it out HERE, as I shall and let us see what this has for us!

Doing Business with Nyeri County.
April 24, 2014 — 9:03

With one of our Clients, The Daily Nation, we have partnered to release this monthly pullout on the Daily Nation Newspaper that is focused on enticing investors to the various counties due to each county’s unique business opportunity.

In this month’s article, we focus on Nyeri County, the demographics, the production, the consumption and much more.

This is part of the work that we do in aggregating and mapping data at county level, we have more than what a 1 page article can cover and are excited for how much innovation we have been able to bring in with this but be sure to get a copy of the daily.

Click on the image to expand and see the numbers in details, space constraints :-)




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

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

“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

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

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.