Effect of Terror Attacks on Tourism in Kenya
July 23, 2014 — 15:13

Author: Vincent Agan  Category: #DataScience  Comments: 0

The role of the Tourism sector in Kenya’s economy can never be overstated: Contributes 14 per cent of Kenya’s GDP, employs 12 per cent of the work force and it is Kenya’s largest foreign exchange earner after Tea and Coffee.

It is therefore fundamental that the government plays its part to aid in growth of the sector and fully exploit its potential by undertaking infrastructure development; encouraging private sector investment in tourism-related facilities like accommodation and restaurants; and minimizing security threats.

There is no denying that the recent wave of terror attacks in the country have been an obtrusive stain in the government’s security efforts (existing or not), but just how bad an effect have they had on Kenya’s third biggest foreign exchange earner?

Tourism Arrivals and  Terror Attacks in Kenya

Source: ICTA and KNBS

Comparing tourist arrivals and terror attack numbers over the last 3 years with the years divided in quarters makes for interesting viewing. The tourist arrivals number should ideally be growing steadily but that has not been the case. The terror-attack wave from the fourth quarter of 2011 does not help at all as the numbers really start to plummet.

The security situation needs to improve drastically to save the sector from short-term and long-term damage because, as it is, Kenya’s tourism sector continues to ail: one travel advisory after the other.

Funding for Higher education in Kenya.
July 21, 2014 — 11:26

Author: linet  Category: #DataScience  Comments: 0

Is Funding for Higher Education, keeping up with the enrollment trends?

The Higher Educations Loans Board was established in 1995 with a critical mandate to disburse loans, bursaries and scholarship to Kenyan students pursing higher education in recognized institutions. The board gives loans to students at affordable rates, which are repayable once they secure an income.

In the last few years the number of students enrolled in Kenyan universities – public and private – has increased from 177,618 in 2010/11 to 324,560 in 2013/14 and significant increase of 82%. The student numbers have grown faster in public universities at 98% in the same period compared to 27% in private universities as shown in the chart below.

Public-private uni

 

Source: Kenya Economic Survey 2014 –KNBS

The next step is to analyze the resources that are allocated to fund education in Kenya as well as help students’ access the loans provided by HELB.

The funding for public universities in Kenya comes in two main streams; first, universities get money that is collected as fees from students who learn in these institutions. Secondly, they also get transfers from the Ministry of Education to top up the revenues generated as fees in the institutions. One thing to note is that over the past few years the total budgetary allocations per capita (total university expenditure per student) has been declining showing a case of increasing number of students in public universities that is not commensurate with the money funding their education as shown in the chart below.

university budget

Source: Kenya Economic Survey,2014 and the Budget Expenditure Estimates

The next area of analysis is to see if the funds available to HELB will ensure the increased number of students still have access to loans and scholarships. Data between 2010/11 to 2012/13 shows an increase in per capita allocations to HELB as shown in the next table. However, there is a drop in 2013/14 which could be explained by the 53% increase in the number of students but only a 7.8% increase in the expenditure to universities for that year.

Helb per capita

 

Kenya still has a very low transition rates between secondary schools into tertiary institutions. It is expected that the Government together with private sector players will continues to push for higher intakes over the foreseeable future. However, this could be a challenge to the institutions if the resources available to keep the students in school is deficient.

 

 

 

 

 

 

 

A working nation but is it saving for a rainy day?
July 16, 2014 — 7:57

Author: john  Category: #DataScience  Comments: 0

Kenya is a country that has a high age dependency ratio as an aging population is dependent on their working children and relatives to support them. This is in addition to other dependents who are of working age but are not engaged in any income generating activities and are dependent on the same providers. This has led to a debate on Kenyans planning for life after retirement which means saving for retirement benefits when still in active employment. However, majority of employed Kenyans are actually in the informal sector and do not have regular incomes which makes periodic savings a challenge. According to the Economic survey 2014, 88% of people employed in Kenya are in the informal sector. In addition the proportion of informal jobs created every year is over 80% and increasing in size compared to formal sector jobs.

In the light of these developments the government has been pushing to get more people in the informal sector to take up health covers and start saving for their retirement. The recommendation to register more people under the National Health Insurance Fund (NHIF) and the National Social Security Fund (NSSF) has also been complemented by some private companies who have developed some products to tap into this huge market.

So how has the enrolment into NHIF and NSSf played put so far?

According to the National Health Insurance Fund the number of  people in the formal sector registered under NHIF rose from 1.8 million in 2008/09 to 2.7 million in 2012/13,a 49% increase in the 5 years as shown in the chart below.

Formal sector members

In the same period the number of NHIF members from the informal sector increased from just over 376,000 to 1.1 million. A 196% increase over 5 years. This is quite an impressive increase over the period. However the share of members from the informal sector in relation to the total NHIF membership was still under 30% in 2012/13 despite making up 88% of the workforce. This is an indication of the scale of need for health insurance in Kenya.

NSSF

 

The chart below shows the share of people registered with NSSF that are employed. Over the last five years that number has been varying between 29%-32% and it does not seem to be rising. While we don’t have data on the numbers brought in by the Pension ya Mbao scheme. Available data shows a stagnation in pension plans uptake.

registered nssf

What does this mean? Only a third of the employed (Formal and Informal Sectors) have some sort of pension benefits to look forward to and this could be an indication that the dependency rates in Kenya could remain high if we incorporate the large proportion of the unemployed and the old.

 

Visa Requirement For Kenyans Visiting COMESA Member States
June 25, 2014 — 11:47

Author: Vincent Agan  Category: #DataScience  Comments: 0

World Cup 2014: Can Africa Defy History?
June 18, 2014 — 11:35

Author: Vincent Agan  Category: #DataScience  Comments: 0

So the 2014 FIFA World Cup is here.

Maradona’s “hand of God” goal, Roberto Baggio’s penalty miss against Brazil, Bergkamp’s wonder goal against Argentina, Zidane’s sending-off against Italy; Every football fan has their own most memorable World Cup moment.

For African teams though, the World Cup has been a forgettable outing. Apart from 1990 when Cameroon, led by the hip-shaking Roger Milla, took the world by storm and probably in 1982 when Algeria looked destined for greatness but were undone by a disturbing case of match-fixing between West Germany and Austria, the rest have been disappointments.

In the 2014 edition, Algeria, Cameroon, Cote d’Ivoire, Ghana and Nigeria will be flying the African flag. With all five African participants having played at least once as of today, the African record reads: Played 5, Won 1, Drew 1 and Lost 3.

Cote d’Ivoire were the only winners beating Japan with Nigeria drawing against Iran and Ghana, Cameroon and Algeria loosing to USA, Mexico and Belgium respectively. Not the best of starts and if these early results are anything to go by, Africa is treading the far too familiar path of failure at the global showpiece.

A tribute to the late Carey Eaton, CEO One Africa Media
June 12, 2014 — 12:20

Author: linet  Category: #DataScience  Comments: 0

DataScience LTD lost a friend, the man that gave us our first shot and believed in our work.

The world has lost a change maker, a man that worked hard to grow everything and everyone.

Carey, because you believed in us, others have and will continue to.

Rest in peace.careyThe DataScience Team.

Word Cloud: Kenya’s Budget Statement 2013/2014
June 11, 2014 — 8:51

Author: Vincent Agan  Category: #DataScience  Comments: 0

Kenyans, institutions and private sector players will all be watching keenly tomorrow as Cabinet Secretary for the National Treasury Henry Rotich reads the budget statement for the fiscal year 2014/2015, especially with it coming in the wake of recent Anglo Leasing payments and other national debates including the wage bill and how to contain recurrent expenditure.


Here is a Word Cloud of last year’s budget statement, the first under President Uhuru, to get us all in the mood. I have to say, though, that it does not analyze the statement; it just emphasizes the frequency of words used and not necessarily their importance.

Kenya Budget 2013-14 Word Cloud

Where Did The Children Go?
June 5, 2014 — 14:05

Author: Vincent Agan  Category: #DataScience  Comments: 0

It recently occurred to me that I seldom hear children playing around my neighborhood – at least not as much as they do back at my parents’ place. Considering my parents’ environment is more rural than where I live, I tried to see if rural areas have more children than urban areas.



Urban areas have a lower average child population of 36.5% compared to rural areas which have 46.1%. It could be because of a number of reasons ranging from individuals leaving their families behind while relocating to urban areas to seek employment; to rural-based parents having more children than their urban-based counterparts; the list is endless.

Looking at size of households in rural and urban areas in Kenya, Rural households are generally larger – with 66% of rural households having 4-7 members – compared to urban households which have 46% of households with 4-7 members.




To delve further into the counties, Mandera, West Pokot, Wajir, Tana River and Samburu Counties have a child population of more than 50%. Incidentally, these are among the poorest counties in Kenya.
Looking at the other extreme, Nairobi, Kiambu and Mombasa have the lowest child population in Kenya at just over 30% and are among the least poor in Kenya.

The English say the soul is healed by being with children, fair enough but what if it makes us poorer and therefore unable to provide for them as well as we would want to?

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

Author: Vincent Agan  Category: #DataScience  Comments: 0

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?


Repercussions

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

Author: Vincent Agan  Category: #DataScience  Comments: 0

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.