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The Politics of County Economies: Why Central Kenya MPs Are Wrong

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DAVID NDII pulls apart the old myth of Central Kenya’s economic dominance.

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The Politics of County Economies: Why Central Kenya MPs Are Wrong
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One of our problems is to decide how much priority we should give in investing in less developed provinces. To make the economy as a whole grow as fast as possible, development money should be invested where it will yield the largest increase in output. This approach will clearly favour the development of areas having abundant natural resources, good land and rainfall, transport and power facilities, and people receptive to and active in development.” – Sessional Paper No. 10 of 1965 on African Socialism and its Application to Planning in Kenya.

Can Central Kenya contribute 60 percent of Kenya’s GDP, as recently claimed, nay, asserted, by the region’s members of parliament? If 12 percent (old Central Province) or 20 percent (including Meru, Embu, Tharaka Nithi and Laikipia) percent of the work force is responsible for 60 percent of the economy, what does that say about the rest of the country. What would make Kikuyus or GEMA community four or five times more productive than other Kenyans?

The word “contribute” is a loaded one. It suggests that there is a common kitty called economy to which some people put in more than others. This is of course not the case. The economy is the sum total of the goods and services produced in the country. When Nyandarua grows potatoes that are consumed in Nairobi: which county has contributed more to the other’s economy? Neither—they have exchanged value, with each profiting from the other. The argument can also be a self defeating one. It justifies domestic import substitution. If we can champion “buy Kenya build Kenya”, why not “Buy Kilifi, build Kilifi”?

The word “contribute” is a loaded one. It suggests that there is a common kitty called ‘economy’ to which some people put in more than others.

The Central Kenya MPs are most likely to be under the impression that the region contributes more to the tax kitty. This is also a fallacy. The tax base and the economy do not overlap. Ideally they should but they do not. In an economy with our structure we have, a large informal sector and largely untaxed smallholder agriculture account for half the economy, the correlation between the economy and tax base is pretty low. The main sources of tax are profits, payroll taxes and consumption taxes (excise and VAT).

The Central Kenya MPs are most likely to be under the impression that the region contributes more to the tax kitty. This is also a fallacy.

The regions that contribute more to the tax base are those with larger corporatized economy. Though I do not have figures, I would expect the coastal counties to constitute a larger tax yield (revenue to GDP ratio) than central Kenya on account of high concentration of the corporatized economy— tourism, manufacturing, mining and logistics industry. The tourism establishments for example sell more highly taxed alcoholic beverages than consumed in central Kenya. They pay more VAT on food, and their employees pay PAYE which the presumably more productive and prosperous farmers of Central Kenya do not. If Central Kenya is so much more prosperous, the more pertinent political question would be whether it is paying its fair share of tax.

That cleared up, we can now turn to the question of county economies. Which counties have the strongest economies? The simple answer is we do not know. The Kenya National Bureau of Statistics (KNBS), the national statistics agency, only publishes national accounts for the whole economy. It is now publishing “County Statistical Abstracts” but these do not include GDP. Six years on, the counties have not found it worthwhile to measure the sizes of their economies even though this is part of their mandate, and it is not particularly difficult or expensive.

In response, I posted a graphic with two sets of figures of the relative size of county economies. One is an estimate of county GDPs computed by World Bank researchers, and published in a paper titled Bright Lights, Big Cities: Measuring national & sub-national economic growth from outer space in Africa, with an application to Kenya and Rwanda.

Which counties have the strongest economies? The simple answer is we do not know. The Kenya National Bureau of Statistics (KNBS) only publishes national accounts for the whole economy. It is now publishing “County Statistical Abstracts” but these do not include GDP. Six years on, the counties have not found it worthwhile to measure the sizes of their economies even though this is part of their mandate, and it is not particularly difficult or expensive.

This methodology is actually more technically sophisticated than it sounds. If one looks at a satellite image of earth taken at night, it becomes apparent that the night lights closely mirror the economic geography of the world. In fact, because the intensity of lights is captured accurately up to a square kilometre, they provide much more detailed geographical coverage than statisticians use to calculate national GDP. Moreover, night lights provide real time data while statistical samples can fall hopelessly out of date, as revealed by the latest rounds of “rebasing” which saw upward GDP revisions ranging from 13 percent in Uganda, 30 percent in Tanzania, to 90 percent in Nigeria. One only frowns at the night lights if they do not know what statisticians do in the kitchen. But as it turns out in fact that over time, the night lights estimate tracks the statistically estimated GDP growth quite well.

For the second series, I used household consumption expenditure shares from the most recent household budget survey data published by the KNBS, the Kenya Integrated Household Budget Survey (KIHBS 2015/16). This is the survey data that is used to measure poverty as well as to update the consumption basket used to calculate the rate of inflation. Household consumption expenditure is the largest component of GDP. Although the percentage is bound to vary from county to county, we have no reason to expect that to be very large. In general, survey data is more reliable than the methods used to estimate GDP, hence it provides a good check for the night lights data.

Another useful source of information is the relative size of a county’s workforce. In a fully integrated economy with free movement of labour and capital, the size of a region’s economy would be proportional to the labour force: if County A accounts for 5 percent of the workforce, then it should also account for 5 percent of GDP. This is because labour and capital will move to where the opportunities are until capital per worker, and in effect production per worker is the same across the whole economy.

Readers of this column may recall that I used this argument to respond to the urban legend, which still persists, that Nairobi accounts for 60 percent of GDP (people who make up numbers seem to like 60 percent). I argued that Nairobi’s GDP was at best between 15 and 20 percent of GDP. This was based on Nairobi accounting for 10 percent of the national labour force, and allowing for more capital than the national average. As we will see shortly, the estimate was overgenerous.

The conventional definition of labour force is population aged 15-64. Ideally, we should use actual participation rates because many young people between 15 – 24 are in full time education, and many older people also work full time, but this data is not readily available on a county by county basis. We will just have to assume that the youth and older people’s participation rates do not vary too much across counties. I use the data published in the Labour Force Survey Report 2015/16, which is part of the KIHBS 2015/16.

We want to see whether the three sources tell the same story. We call this research strategy i.e. cross-validating different data and methodologies, triangulation.

We are in luck. The three sources are remarkably consistent. The correlation between the night lights GDP and household expenditure is 70 percent, between the night lights GDP and labour force is 73 percent, and between household expenditure and labour force shares is 90 percent (see charts). The strong correlation between the night lights GDP and labour force shares tells us that the bright lights GDP is pretty good. We can conclude from these correlations that all these data are telling us the same story. What is the story?

Second, all three tell us that Nairobi has the largest economy as expected, but it is a far cry from 60 percent. The night lights GDP puts it at 12.7 percent, while the expenditure share puts it at 20 percent. But the labour force share weighs in close to the night lights GDP at 12 percent.

The counties with the largest economies according to the night lights GDP are Nairobi(12.5%), Kiambu (11.1) Nakuru (8.5%). Between them, they account for 32% of the GDP.

The household expenditure data have the same order, and their combined share is also about the same (31%) but Nairobi’s share is much bigger (19.8%) while Kiambu and Nakuru are closer at 5.6% and 5.2% respectively. Eight other counties have large economies between 3 and 4 percent of GDP (Nyeri Kilifi, Kajiado, Machakos, Kwale Mombasa and Meru). With the notable exceptions of Nyeri and Kwale, their expenditure shares are also in line with the GDP shares. However, when it comes to the GDP and labour force, Kiambu, Kwale, Nyeri and Nakuru have much larger shares of GDP than their share of the labour force. I will come back to this shortly.

Nairobi has the largest economy as expected, but it is a far cry from 60 percent. The night lights GDP puts it at 12.7 percent, while the expenditure share puts it at 20 percent.

At the other end of the scale, Isiolo, Lamu, and Samburu have the smallest economies accounting for 0.2 percent of the national GDP each, followed by Marsabit, Tharaka-Nithi and Elgeyo Marakwet at 0.4 percent, Nyamira and West Pokot follow at 0.6 percent and Baringo and Tana River, 0.7 percent each, complete the ten smallest county economies. There is very close correspondence between the between the GDP and household expenditure in the small counties.

It’s worth pointing out here that the size of the county’s economy has no bearing on the incomes and well being. Whereas Lamu, Isiolo and Samburu are the smallest counties, Lamu’s incidence of poverty (28.5) percent is well below the national average of 36 percent; both Isiolo (56 percent) and Samburu (75 percent) are much higher. In fact, in terms of incomes and poverty Lamu, the smallest economy compares favorably with Nakuru, the third largest. This should put to rest those who are wont to argue that small counties are not economically viable. The Seychelles (Pop. 100,000, less than Lamu’s 130,000) has an average income ten times Kenya’s.

What explains the large difference between Nairobi’s GDP and household expenditure share.   Why are Kiambu and Nakuru’s GDP estimates so much larger than their shares of the labour force. Are there plausible economic explanations, or is it flaws in the data?

For Nairobi, cost of living is a plausible and likely explanation, in particular housing costs which are much higher than elsewhere. According to a national housing survey conducted by KNBS a few years ago, housing costs for house-renting Nairobi households take 40 percent of expenditures, a third more than the next highest, Mombasa and Kiambu, at 30 percent. Rural house renting households spent an average of 13 percent. Although the report does not give the percentages, we do know that Nairobi has a much larger percentage of renting households than other counties. Overall, 70 percent of urban households are renters, while 90 percent of rural households are owners. You would not know it from listening to Nairobi’s navel-gazing middle class going on about home ownership and mortgage interest. In aggregate 70 percent of Kenyans live in their own homes, and a good percentage of urban renters own decent debt-free rural homes. Home ownership is not a national priority, but I digress.

The large divergence of GDP and labour force shares is perhaps the more economically meaningful and insightful one. The straightforward interpretation of this observation is that the GDP per worker in Kiambu and Nakuru is considerably higher than average. Is this plausible? In the Census of Industrial Production conducted in 2010, Kiambu had 206 factories, second to Nairobi with 1090, out of a national total of 2252 establishments. In effect, Kiambu accounts for close to a fifth of the factories outside Nairobi. This is not a surprise given that Thika and Ruiru are large industrial towns, but even in my rural home I can count least six fairly large factories within shouting distance (4 tea factories, a chicken processing plant, and a dairy processor) and thats not counting the Bata shoe and a couple of other factories in Limuru town.

Nakuru may not count as many factories, only 95, but it certainly has a lot of capital. The country’s entire geothermal electricity industry, the flower industry as well as a very significant hotel industry around Lake Naivasha—that is a fair amount of capital. This ratio seems to be capturing, as it should, the capital intensity of the counties’ economy. If this is indeed what these data are telling us, then it is worthwhile to pay more attention to them, because they are conveying important information about the structure and character of the economy.

In the Census of Industrial Production conducted in 2010, Kiambu had 206 factories, second to Nairobi with 1090, out of a national total of 2252 establishments. In effect, Kiambu accounts for close to a fifth of the factories outside Nairobi.

If capital was evenly distributed across the country, all the ratios would be clustered around around 1. The actual ones range from 0.4 to 2.3. Kiambu’s ratio is the highest at 2.3 followed by Kwale and Nyeri (2) and Nakuru (1.9). There are three more counties with a ratio of 1.5 or higher, that is GDP share is 50 percent more than labour force share, Kajiado, Laikipia and Murang’a. Interestingly, Nairobi is not one of them. In fact, Nairobi is in the middle of the pack with a share just 10 percent higher, alongside Tana River. At the other end of the scale we have Elgeyo Marakwet and Nyamira with a GDP share which is 40 percent of the labour force share, and 12 counties where it is 50 percent. Looking at this pattern, it is readily apparent that the counties at the top are generally wealthier, while those at the bottom are poorer. The wealthier counties have more capital.

We have what looks like credible estimates of county GDP shares, we have each county’s labour force, and we also have the conventional national GDP. With these we are able to compute GDP per worker for each county, which will give us an idea which counties have the strongest economies. Kiambu comes out on top with a 2016 GDP per worker of Sh. 673,000. This is telling us that people in Kiambu produced on average Ksh. 56.000 worth of goods and services per person per month. The ten strongest economies are Kiambu, Kwale, Nyeri, Nakuru, Kajiado, Laikipia, Muranga, Garissa, Kilifi and Machakos.

One of the striking findings is that the big city counties are not among the strongest economies.

Nairobi and Mombasa are about the same at 14th and 15th respectively with a GDP per capita of Sh. 300,000 and Kisumu is 16th with Sh. 263,000. Obviously Kisumu is both urban and rural – Kisumu City on its own would probably be comparable with Nairobi and Mombasa. Still, these data put some question marks on the widely held belief that big cities are the engines of economic growth. To be sure there could be other explanations. The cities, Nairobi in particular could have a larger share of young people in full time education and unemployed, but these are puzzles for curious students to write dissertations on.

One of the striking findings is that the big city counties are not among the strongest economies. Nairobi and Mombasa are about the same at 14th and 15th respectively with a GDP per capita of Sh. 300,000 and Kisumu is 16th with Sh. 263,000.

More significantly perhaps we also do not see an economically dominant region. Kwale’s economy compares favourably with Nyeri, both in absolute size and productivity. Kirinyaga sits next to Wajir in terms of productivity. Makueni is more productive than Nyandarua.

This is not to say that we’ve heard the last of central Kenya politicians’ ethnic chauvinism. As Bertrand Russell observed long ago, a man offered a fact that goes against his instincts will scrutinize it closely, and unless the evidence is overwhelming, refuse to believe it; but offered something which affords a reason for acting in accordance to his instincts, he will accept it even on the slightest evidence.

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David Ndii is a leading Kenyan economist and public intellectual.

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Why Opinion Polls May Not Always Predict Election Outcomes in Kenya

This is the second in a series of articles that will review and comment on surveys related to the August 2022 general election, providing analytical tools to enable the reader to assess their credibility and potential impact.

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Why Opinion Polls May Not Always Predict Election Outcomes in Kenya
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This is the second in a series of pieces I have been engaged by The Elephant to write on the place of surveys in the forthcoming election.  As I noted in my first piece, I do so as objectively as I can, although for the sake of transparency I again declare that I am currently engaged as a research analyst for one of the firms whose results I review here (Trends and Insights for Africa, or TIFA).

A handful of recent polls

Since my previous piece was published at the beginning of April, the results of three credible surveys were published through the middle of May: those released by the Radio Africa Group in The Star on 18 April, by Trends and Insights for Africa (TIFA) on 5 May, and by Infotrak (sponsored by the Nation Media Group) on 12-13 May. While the first two indicate that Deputy President William Ruto was leading former Prime Minister Raila Odinga in the presidential race by 5 and 7 per cent respectively, they differ somewhat in important details, even beyond their respective headlines. They are also at odds with the most recent of these three surveys: those of Infotrak which have the two in a dead heat at 42 per cent each. I will begin with a visual comparison of the figures from the first two polls.

Survey Firm Sample Size/No. of Counties Data Collection Dates  Ruto  Odinga Others Undecided/NR
Radio Africa/The Star 4,057 / 47 1-5 April 2022 46% 41% 1% 12%
TIFA Research 2,033 / 47 22-26 April 2022 39% 32% 1% 28%
Difference -7% -9% +2% +14%

 

The first point to make is that although the TIFA results gave Ruto a larger lead margin (7 per cent vs. 5 per cent), the difference may not be significant, given that it falls almost entirely within their respective margins of error of around +/-2 per cent. The main difference is a whopping 16 per cent variance in the proportion who failed/declined to answer the presidential choice question. Two obvious questions arising from this are: (1) what might explain this gap, and (2) can any “deeper” analysis of the data suggest the “leanings” of these “silent” respondents?

Regarding the first question, no clear answer is apparent. However, it may be relevant that the Radio Africa poll was conducted by sending text messages to the sample derived from their data-base of phone numbers, whereas TIFA’s was conducted through the more standard Computer-Assisted-Telephonic-Interview (CATI) method (i.e., through live phone calls), based on the (comparable) TIFA data-base. Still, why this would make respondents in the latter survey less willing to reveal their presidential preferences is unclear.

Another puzzling issue has to do with Radio Africa’s stated margin of error, which is given as +/ 4.5 per cent. Yet with a reported sample size of 4,497, based on some 22 million registered voters (a figure against which the data were reportedly weighted), the margin of error is actually only +/-1.5 per cent. Why would the “Star Team” who produced the story want to make their findings look less precise than they are? (I made two phone calls to journalists at The Star about this but neither was able to provide a definitive explanation.)

Further, while the article by The Star made reference to findings from two previous similar Radio Africa surveys – showing Ruto leading Odinga by a huge 29 per cent last July (i.e., 43-14 per cent), and Odinga taking the lead for the first time in March, by 4 per cent (i.e., 47-43 per cent)—no suggestion was offered as to what could account for Ruto’s regaining the lead he previously enjoyed.  Indeed, even when reporting the results in March, all The Star could offer was that “Poll ratings can go up and down so Radio Africa will continue to conduct its monthly opinion polls up to the August 9 elections.”  In any case, it remains to be seen whether the just concluded party nominations and running mate selections will further reshape the race.

Why would the “Star Team” who produced the story want to make their findings look less precise than they are?

In addition, while the text of the article reported some results by region (i.e., North Rift, South Rift, Central, Upper Eastern, Lower Eastern, Nyanza, Western and Coast), the kind of quite useful table of results that had been included in the mid-March story was absent, as were any explicit comparisons of results at this sub-national level, leaving such calculations up to its readers to make—assuming they had kept the March results for such a purpose: e.g., an increase in support for Ruto in North Rift (from 63 per cent in March to 69 per cent now) but basically no change in Central (57 per cent in both March and April). While such changes may help to explain the overall result—the re-establishment of Ruto’s lead – it would be useful if the respective margins of error for each of the regions was also noted so that such sub-national changes from one poll to another could be put in a clear statistical perspective. But the earlier point remains: could the “Star Team” have provided any explanation as to why Odinga’s rating in Nyanza fell by 11 per cent in a little over one month?

Yet another methodological point is important to make here. If Nyanza constitutes about 13 per cent of the total sample, that generates a margin of error of +/-6 per cent, which means Odinga’s actual proportion in March (shown in The Star’s table as 78 per cent) could have been anywhere in the range of 71-84 per cent, and in April (shown as 67 per cent) in the range of 61-73 per cent.  Note here that at the low end of the March figure and the high end of the April figure there is an overlap of 2 per cent, meaning that it is possible—though unlikely—that his “true” Nyanza figures did not change at all over this period.

Could the “Star Team” have provided any explanation as to why Odinga’s rating in Nyanza fell by 11 per cent in a little over one month?

Another point: according to the Market Survey Research Association (MSRA) Guidelines, its members should interview at least 1,500 respondents in any survey reporting national (presidential) voting intention results, and while there is no such minimum for any sub-national polls (county, parliamentary constituency, ward), the margin of error should be made clear. There is, of course, no such requirement for the Radio Africa survey since the regions for which results are reported are not electoral units, even were this news organization an MSRA member (which it is not).

Stop press—another poll is out!

As I was writing this piece, the results of another national survey were released, this one by Infotrak, commissioned by the Nation Media Group. Its headline findings may be compared with TIFA’s in the same way as the latter are compared with Radio Africa’s above:

Survey Firm Sample Size/No. of Counties Data Collection Dates  Ruto  Odinga Others Undecided/NR
TIFA Research 2,033 / 47 22-26 April 2022 39% 32% 1% 28%
Infotrak 2,400 / 47 8-9 May 2022 42% 42% 1% 15%
Difference +3% +10% 0% -13%

 

Before addressing the main contrasts in these results, several points regarding methodology should be made. As Macharia Gaitho, writing an accompanying piece for the Daily Nation, pointed out, “The dates the data was [sic] collected will always have a bearing on the outcome in a fluid political situation, but unless there were very major shifts and realignments in the intervening period, even a fortnight between two polls cannot account for such variations.” This assertion makes sense given the absence of any dramatic events relevant to the fortunes of the two main contenders during the period between the two polls—the departure of Governors Alfred Mutua and Amason Kingi from Azimio to Kenya Kwanza coming just after data collection for the Nation/Infotrak poll. And he went on to add: “Other factors which influence the outcome of an opinion poll are methodology and sampling.” Note that Gaitho had raised some of these same important issues in a Daily Nation piece he authored just before the August 2017 election which I responded to and published in the Nation a few days later, identifying issues that I felt he had not sufficiently addressed.

Leaving aside the semantic error that sampling and methodology are distinct (since sampling is an inherent aspect of methodology), the factors he cites are certainly relevant: sample size and distribution across the country.

Sample size in this case is not an issue, since despite Infotrak’s being slightly larger, the respective margins of error are nearly identical: +/-2 per cent vs. +/-2.17 per cent. Further, even though Infotrak’s question wording differs slightly from TIFA’s (“…who would you vote for…?” vs. “…who do you want Kenya’s next president to be?”), it can be assumed that much of the contrast between the two surveys is a consequence of sampling. Simply put: how each sample was distributed across the country, and what the achieved distribution (whether through the “pot luck” willingness of those selected to participate, or through post-data collection weighting—or some combination of both) is for each demographic variable that might be relevant to the issue at hand: presidential candidate preference.

Unfortunately, and in contrast to TIFA’s release, the Nation gives us no basis for comparing these two samples in demographic terms. That is, while TIFA included figures for gender, age groups, and education level (the latter required by the relevant law enacted in 2012)—as well as the proportion allocated to each of the nine “zones” for which results were reported—we have no such data from the Nation (whatever Infotrak may have provided).

Of course, for most political surveys in Kenya the most salient variable in assessing the representative accuracy of a sample is its ethnic distribution. Most survey firms collect data on the ethnic make-up of its sample but, as far as I know, no survey firm has ever published it nor does the relevant Act require it. Presumably, this is for reasons of “sensitivity”—a form of “self-censorship” that appears universally accepted. This is not to suggest that ethnicity explains “everything” about the achieved results, but it is critical when gauging whether samples are truly representative. For example, in TIFA’s survey, well over half—but nowhere near all—of Ruto’s and Odinga’s “home” ethnic groups (i.e., the Kalenjin and Luo) expressed support for their respective presidential candidates. Given this reality, it is impossible to judge the comparability of the two samples involved here without knowing what proportion of the total sample in each survey is comprised of the country’s main ethnic groups. Specifically, was there a “sufficient” number of Kalenjin in the Infotrak sample, and a “sufficient” number of Luo in TIFA’s (and Radio Africa’s)? Of course, such figures should reflect “correct” random sampling based on the geographical distribution of registered voters according to the IEBC, rather than any “search” for these ethnic proportions.

Of course, for most political surveys in Kenya the most salient variable in assessing the representative accuracy of a sample is its ethnic distribution.

It should also be recognized that whether using the eight pre-2010 Constitution provinces, or TIFA’s nine “zones”, none of them is mono-ethnic, with some of the more homogeneous—Central, Nyanza and Western—having less than 90 per cent of their dominant ethnic groups (Kikuyu, Luo and Luhya, respectively). TIFA’s data indicates Lower Eastern is the most ethnically homogenous “zone” although even here, Kalonzo Musyoka, the leading Kamba candidate, only polled at 15 per cent support.

Another problem arises when using survey results to predict election outcomes. While the presidential contest results of both surveys were generally presented by the media as reflecting actual 9 August ballot choices, in neither case was it reported whether all respondents were registered voters, and among those who claimed to be (assuming they were asked), how “certain” they were that they would actually vote on Election Day. Despite this, the main Nation newspaper article reporting the results refers to the survey’s respondents as “voters”. This raises the possibility that actual voter turnout (that is known to vary across the country in every election) will deviate from the samples of these three surveys, even if they all claim to have used the distribution of registered voters as their sampling “universe”.

Since this cannot be precisely known in advance even much closer to the election, it is misleading to use such survey results to suggest, let alone predict, actual outcomes, as the Daily Nation did in its front-page caption by stating that neither Ruto nor Odinga “has enough backing to cross the 50%+1 threshold to win”. (It may be assumed that those involved in producing these stories are also aware of the additional requirement of obtaining at least 25 per cent in at least 24 of the 47 counties.)

But there is an even more blatant flaw in this “run-off contest” statement: an actual voter who wishes his/her vote to count cannot be “undecided” or “refuse to answer” as one can in a survey interview, since voters must choose from actual ballot choices. In response to one of the several 2013 presidential election petitions, the Supreme Court ruled that spoiled ballots are removed from the count of “total votes cast”, so that the denominator of the calculation for each candidate is based on total valid votes cast, not the total number of people who walked into a polling station.

TIFA’s data indicates Lower Eastern is the most ethnically homogenous “zone” although even here, Kalonzo Musyoka, the leading Kamba candidate, only polled at 15 per cent support.

Based on this reality, for example, the Infotrak results imply that each of the main candidates “would get” 49 per cent, since only about 1,008 of the reported total sample of 2,400 respondents mentioned Odinga and Ruto, and this figure should be divided by roughly 2,040, which is the figure we are left with after subtracting those who said they were undecided or who refused to answer the question—about 360 respondents.

In other words, even if these top two candidates are nearly tied on 9 August, it would seem that a run-off contest would be unnecessary unless the combined figure of all the other presidential candidates  exceeds 2 or 3 per cent—a much more likely prospect should Kalonzo Musyoka insist on “going it alone”.

Another contrast between the Infotrak and TIFA polls is important to point out, as it, too, could help to explain their contrasting results.

In terms of the distribution their samples, TIFA uses nine ethno-political “zones” while Infotrak (like Radio Africa) continues to use the former eight provinces. As such, the only sub-national results that can be compared (since they are used by both firms) are: Nairobi, Coast, Western and Nyanza. The table below shows the figures for these four units (comparing the TIFA figure on the left with Infotrak’s on the right, and the difference in parentheses on the far right):

Nairobi
TIFA / Infotrak
Coast
TIFA / Infotrak
Nyanza
TIFA / Infotrak
Western
TIFA / Infotrak
Ruto 25% / 33% (+8%) 26% / 29% (+3%) 21% / 18% (-3%) 37% / 33% (-4%)
Odinga 40% / 51% (+11%) 36% / 55% (+19%) 56% / 72% (+16%) 29% / 48% (+19%)

Even setting aside the higher error margins for each of these regions, which range between about +/-6 and 7 per cent—and thus equal to 12 per cent and 14 per cent spreads, based on their respective sub-national sample sizes—these contrasts are remarkable, especially the larger figures for Odinga in the Infotrak survey. (Note that given the lower Infotrak figures for “undecided” and “no response”—10 per cent and 5 per cent, respectively, as compared to TIFA’s 16 per cent and 12 per cent—Infotrak’s overall figures for both candidates are higher, as is also the case in the comparison of Radio Africa’s figures with TIFA’s.)

While the contrasting figures for Nairobi are minimal, since the 8 per cent difference between Infotrak’s and TIFA’s figure for Ruto is only 3 per cent lower than the difference in Odinga’s numbers for the other three sub-national units (Coast, Nyanza and Western), Odinga’s “Infotrak advantage” is much higher: 16 per cent, 19 per cent, and 23 per cent, respectively.  As noted, while TIFA provides the proportions allocated in its sample to each of the nine zones for which it presents results, Infotrak—or at least the Daily Nation—does not. But assuming they were roughly similar—and, as indicated, even taking the higher error margins for each into account—Gaitho’s summary point stands: that such disparate results cannot be accounted for by a minor discrepancy in the dates of the two surveys, given that no major events occurred that might have caused any significant shifts in attitudes towards either of the two main presidential candidates.

In connection with such contrasts between Infotrak and other credible survey firms in Kenya, a little history may be useful. For example, in their last surveys before the contested 2007 election, The Steadman Group gave Odinga a 2 per cent advantage over Kibaki, while Infotrak gave him a 10 per cent lead. Just before the 2013 election, Infotrak “predicted” an outright win for Odinga, whereas Ipsos’ results indicated that neither candidate would achieve this in the first round.  A little earlier, an Infotrak survey conducted at the end of December 2012 and into the first few days of 2013 gave Odinga a 12 per cent advantage over Uhuru Kenyatta (51 per cent to 39 per cent), whereas an Ipsos poll conducted only about two weeks later gave the former only a 6 per cent advantage (46 per cent to 40 per cent). Similarly, in their final surveys before the 2017 election late July, Infotrak had Odinga and Kenyatta in a virtual tie (47 per cent vs. 46 per cent) —on which basis it suggested that no one would win on the first round—whereas Ipsos gave Kenyatta a clear outright win: 52 per cent vs. 48 per cent, excluding those who claimed to be undecided or who declined to reveal their preference (which when included, generated a 47 per cent vs. 43 per cent advantage for Kenyatta), although leaving room for some minor deviation from these figures based on differential voter turnout across the country. In fact, Ipsos offered four possible voter turnout scenarios, none of which put Odinga closer than 4 per cent behind Kenyatta.

Of course, given the disputed nature of the official results in all three of these elections, it is impossible to know which survey firm’s results were closer to “the truth”. But they do reveal a clear pattern: that Infotrak has consistently given more positive results to Odinga than any of the other reputable survey firms in the country.  I should stress, however, that this “track record” should not be the sole basis for dismissing Infotrak’s current figures, but it does underscore Gaitho’s point that whenever there are differences in survey firms’ results that go beyond the stated margins of error, additional scrutiny is warranted—preferably to a degree that goes beyond what the Nation Media Group offered its readers/viewers on this occasion. Of course, given the fact that they sponsored the survey, such rigorous scrutiny might have been considered “inappropriate” at best.

On the other hand, it should also be recalled that in the polls conducted just before the August, 2010 constitutional referendum, Infotrak produced results that were slightly more accurate than those of Synovate—and there were no claims of any “rigging” in response to the official results.

In any event, the promise of continued polling by at least these three firms—Infotrak, TIFA and Radio Africa—should not only provide Kenyans with an evolving picture of the possible electoral fortunes of particular candidates and political parties/coalitions (as well as identifying the issues motivating voters at both the national and sub-national levels), but also invite them to more thoroughly scrutinize the performance of these firms and of any others that may appear and attain any serious media coverage. This is so even if the announcement of deputy presidential running-mates will make the next set of polls non-comparable with those examined here.

Of course, given the disputed nature of the official results in all three of these elections, it is impossible to know which survey firm’s results were closer to “the truth”.

The most useful data, however, would be the actual results announced by IEBC about which no credibility doubts are raised, so that only differential voter turnout would have to be taken into account in assessing the performance of the pollsters in their final survey rounds.

A concluding comparison: in the recent, second round run-off French presidential election, the final national poll had President Emmanuel Macron defeating Marine Le Pen by 56 per cent to 44 per cent, and the official (uncontested) results gave him a 58.5 per cent to 41.5 per cent victory (just within the poll’s margin of error). Given that, so far at least, there is no evidence that Kenyans lie any more than French people do when answering survey questions, let us hope that Kenyan survey firms can both individually and collectively achieve such accuracy.

Post-script

Just after completing this piece, on May 18 TIFA released the results of another CATI survey it had conducted the day before, comprised of 1,719 respondents. This came in the immediate wake of two days of drama: first, on 15 May, the announcement by Kenya Kwanza Alliance’s presidential candidate, DP William Ruto, of his coalition’s deputy president running mate, Mathira Member of Parliament Rigathi Gachagua, and on the following day, the announcement by Azimio la Umoja’s Raila Odinga of former member of parliament and cabinet minister Martha Karua as his running mate.

The most useful data, however, would be the actual results announced by IEBC about which no credibility doubts are raised.

The two main questions it sought to answer were: (1) How many Kenyans were aware of each of these running mates? (2) What were their presidential voting intentions?

For whatever reasons, it emerged than far more people were aware of Karua’s selection than of Gachagua’s (85 per cent vs. 59 per cent), a pattern which was replicated among those who expressed the intention to vote for Odinga or Ruto, respectively (90 per cent vs. 69 per cent). By contrast, awareness of Kalonzo Musyoka’s choice of running mate, Andrew Sunkuli, was far lower among both the general public and among those (few) who reported an intention to vote for Musyoka (21 per cent and 38 per cent, respectively).

But as expected, it was the results of the second issue that attracted most attention, which gave Odinga a modest but measurable lead over Ruto: 39 per cent to 35 per cent.  The central question these figures raised was whether Odinga’s jump into the lead, beyond the tie that Infotrak had reported just one week earlier, was to any degree a consequence of the identification of these two running mates, a question that will be addressed in the next piece in this series, by which time it is hoped at least one additional poll would have been conducted so as to confirm whether TIFA’s most recent figures do indeed represent a major shift in the presidential electoral terrain.

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Tigray is Africa’s Ukraine: We Must Build Pan-African Solidarity

A genocide is taking place in Tigray. Why is there no mobilization of African civil society organizations, non-governmental bodies, religious institutions, and individuals in support of Tigrayan refugees?

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Tigray is Africa’s Ukraine: We Must Build Pan-African Solidarity
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Two months after the Russian invasion of Ukraine, more than  5 million Ukrainians fleeing the war have crossed the borders into other European countries. While this is largely a testament to the massive scale of the attack by Russian forces that has forced millions of Ukrainians to flee their homes in all directions, it also has a lot to do with the warm welcome and sympathy extended to these refugees by European nations.

Europeans both individually and collectively stood in solidarity with and committed to supporting Ukrainian refugees in all ways. Member states of the European Union established reception centres and facilitated the right to travel, stay, and work for all Ukrainians within days of the war starting. Families across Europe (and in the United Kingdom) volunteered to host Ukrainian families, organizations raised funds, individuals donated basic necessities, and many even travelled to borders to personally welcome Ukrainian refugees.

While this “gold standard” welcome by European countries—who are generally accused of being hostile to other (particularly black and brown) refugees—has been the subject of heated discussion, a question that is yet to be thoroughly addressed is why such solidarity is not seen in other parts of the world. More particularly, using the experiences of refugees from the Tigray war as a case study, we would like to ask why the multiple conflicts ravaging the African continent fail to inspire such a response by African countries.

The Tigray war, characterized as the world’s deadliest war, has been ongoing for seventeen months. Thus far, more than 500,000 people are reported to have died. Terrible atrocities amounting to war crimes and crimes against humanity, including scores of massacres, weaponized sexual violence, and a total humanitarian blockade have all contributed to creating conditions aptly described by the Director-General of the World Health Organization (WHO) as “hell”.  Despite the length and brutality of this conflict, however, the number of Tigrayans who have managed to escape into neighbouring African countries is relatively minuscule.

As far as we are able to establish, about 70,000 Tigrayans crossed into Sudan during the first few days of the war. We can add to these the thousands of Tigrayans who worked and lived in Djibouti before the war and the few hundreds that managed to flee to Kenya following the ethnic profiling and mass arrests they faced in Ethiopia. It is possible to argue that the number of refugees from Tigray has remained low mainly because the borders have been blocked by the Ethiopian regime and its allies. This draconian blockade has indeed been used as a tool of war by Prime Minister Abiy Ahmed to completely cut off Tigray from the rest of the world in order to hide atrocities and control the narrative. It is also believed to have the approval of key members of the international community seeking to mitigate the impact of the war on the broader Horn of Africa region and its potential contribution to the migration crisis in Europe.

Even so, taking into account the precarious situation of the millions of Tigrayans in the region itself and in the rest of Ethiopia along with well-known patterns of illicit migration from conflict areas, it is reasonable to wonder if the low number of Tigrayan refugees is due to the receptiveness—or lack thereof—of neighbouring countries as well as the blockade. With this in mind let’s look more closely at some policies and practices in the region that can be perceived as obvious deterrents to those seeking refuge.

Political and diplomatic support given by African countries to the regime in Addis Ababa 

The Tigray war is happening in the host country of the African Union (AU) and the second-most populous country on the continent. However, this conflict has not been included as an agenda item in any of the meetings of the AU heads of states that have been convened since its onset in November 2020. The only significant statement that was made regarding this conflict by the Chairperson of the AU, Moussa Faki Mahamat, was one that endorsed the war. Since this early statement, the AU has assiduously ignored the overwhelming evidence of the gruesome atrocities and violations of human rights and humanitarian laws perpetrated during this conflict. Nor has the AU acknowledged the direct involvement of Eritrea and Somalia—both members of the AU—who deployed troops into Tigray and have been credibly accused of committing grave atrocities.

Diplomatically, African countries have given cover to the Ethiopian regime in all multilateral forums including the United Nations Security Council (UNSC). The passionate and well-received speech by Kenya’s ambassador to the UN, Martin Kimani, in opposition to Russia’s war of aggression against Ukraine, makes one wonder why the same passion is absent for crises nearer home, including Tigray. Sadly, however, not only do the so-called A3 countries on the UNSC continue to frustrate action against the Ethiopian regime, African countries have voted against measures to establish investigative mechanisms into the atrocities committed in Tigray. Even more disappointingly, on the 31st of March, Kenya voted in support of a bill introduced by the Ethiopian regime to halt funding for the International Commission of Human Rights Experts set up to investigate the crimes and human rights abuses that took place in Tigray.

The AU has assiduously ignored the overwhelming evidence of the gruesome atrocities and violations of human rights and humanitarian laws perpetrated during this conflict.

These actions indicate that the AU and its member states have either failed to recognize the gravity of the human rights and humanitarian violations in Tigray or are unwilling to address violations by other member states, however grave, as a matter of policy.

Forced Repatriation to Ethiopia

This policy and the attendant practices in turn mean that Tigrayans or other minorities seeking refuge from state-sanctioned violence in the region are denied official welcome and feel insecure even when they are sheltered there as refugees under UN protection. Tigrayan refugees in the region are under continuous threat from Ethiopian and Eritrean intelligence and security officials that are fully capable of crossing borders to harm or forcibly repatriate them. Just to look a bit more closely at the experience of Tigrayan refugees in the region, in Sudan, senior Ethiopian officials and supporters of the regime have on several occasions threatened to forcefully repatriate Tigrayan refugees from the Sudanese refugee camps that are under the auspices of the United Nations High Commissioner for Refugees (UNHCR).

In Djibouti, the threat of forced repatriation was realized when several Tigrayans, who had committed no known crime, were apprehended and returned to Ethiopia. This clear breach of the principle of non-refoulement has excited no response from other African governments or African Civil Society Organizations (CSOs). 

Tigrayans also live in fear of forced repatriation even in the relatively more friendly Kenya. The December 2021 abduction of Tigrayan businessman Samson Teklemichael in Nairobi in broad daylight is a prominent example of the insecurity of Tigrayan refugees in Kenya. In addition, personal accounts from Kenya suggest that newly arriving refugees can fall victim to immoral actors demanding large sums of money to facilitate registration. Tigrayans who have been unable to obtain proper documentation for this and other reasons risk being thrown in jail. The lucky few that are registered are coerced to relocate to remote and inhospitable camps. As a result of this, and due to the increased insecurity created by the presence of Ethiopian and Eritrean intelligence officers operating in Nairobi, Tigrayans in Kenya are increasingly opting to remain hidden. This means that the actual number of Tigrayan refugees in Kenya is unknown.

The December 2021 abduction of Tigrayan businessman Samson Teklemichael in Nairobi in broad daylight is a prominent example of the insecurity of Tigrayan refugees in Kenya.

It also bears noting that in response to the war in Tigray, the Kenyan government tightened its borders with Ethiopia, essentially closing the only avenue open for Tigrayans fleeing conflict and ethnic-based persecution by land. Moreover, Tigrayan refugees who have been stopped at Kenyan border controls in Moyale have at different times been apprehended and returned by agents of the Ethiopian regime.

Harsh conditions facing Tigrayan refugees

Sudan hosts the largest number of documented Tigrayan refugees. An estimated 70,000 Tigrayans fled to Sudan to escape the brutal invasion and occupation of Western Tigray. While these people were welcomed with extraordinary kindness by the people of Eastern Sudan, the refugee camps to which they were relegated are located in remote and inhospitable regions with almost no basic infrastructure. As a result, international organizations have been unable to provide adequate support and Tigrayan refugees have fallen victim to extreme weather and fires.

Similarly, Tigrayans remaining in Djibouti are kept in remote camps under unbearable conditions, facing maltreatment and abuses such as rape and sexual violence including by security forces. The whereabouts of the thousands of refugees who escaped from abuses and starvation at Holhol, one of Djibouti’s remote refugee camps where over 1,000 Tigrayans remain, are unknown.

The disinterest of African media and society

Arguably, the above realities describe the failings of African governments in terms of welcoming and protecting refugees fleeing conflict. But what of other sections of African society? Why are there no responses akin to the mobilization of European civil society organizations, non-governmental bodies, religious institutions, and individuals to support Ukrainian refugees? Even taking into full account economic limitations likely to affect responses to such crises, this could potentially speak to a larger failure in terms of building pan-African solidarity, not just as a political concept but as a grassroots reality. In the specific case of the Tigray war, this is further reflected and augmented by the minimal coverage of the war in African media outlets relative, for example, to the extensive daily coverage given to the Ukraine war. Moreover, African intellectuals and intercontinental forums have shown little to no interest to address an ongoing genocide that is quickly paralleling the worst examples of mass atrocities on the continent thus far.

What can we learn from the European Response to the Ukraine crisis?

In many ways, the European response to the Ukraine crisis has been unprecedented and arguably sets a new standard for welcoming refugees from all regions including Europe itself. In the African context, the Tigrayan experience of policies and practices that endanger and harm the most vulnerable seeking safety reveals an urgent need to take these lessons on board.  With this in mind, we can tentatively outline the following suggestions.

First, we as Africans should find mechanisms for building pan-African solidarity amongst citizens that are not contingent upon the will of our governments. This can only be achieved if African media, civil society organisations, thought leaders, and other influencers commit to prioritizing what is happening on the continent. In this interconnected and highly digital age, it is no longer acceptable that an African anywhere on the continent does not know about what is happening in Tigray as much as, or more than, they know about what is occurring in Ukraine.

We as Africans should find mechanisms of building pan-African solidarity amongst citizens that are not contingent upon the will of our governments.

Second, African citizens should protest policies and practices by African governments that favour state-sanctioned violence and support regimes over vulnerable communities. We all, as Africans, are prone to fall victim to state violence and violations of human rights in our countries and this necessitates pan-African reflection on human rights for all, indigenous communities as well as refugees and migrants.

Third, refugees and migrants are rarely a burden on the host countries and communities. Those fleeing the Tigray war, for example, are generally highly educated and carry unique skills that could contribute to societies wherever they land. Harnessing these resources on the continent should be a priority. Moreover, refugees enrich host communities and facilitate regional and continental integration which the AU and its member states continue to discuss, but never materialize.

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UK-Rwanda Refugee Deal: A Stain on President Kagame

Rwanda’s proposed refugee deal with Britain is another strike against President Paul Kagame’s claim that he is an authentic and fearless pan-Africanist who advocates for the less fortunate.

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UK-Rwanda Refugee Deal: A Stain on President Kagame
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In mid-April 2022, Rwanda and Britain unveiled a pilot scheme in which the latter will ship off asylum seekers who arrive in Britain “illegally” to the former for the whopping sum of £120 million. Although full details of the deal remain sketchy, it is believed that it will target mainly young male refugees who apply for political asylum in Britain. Anyone who entered the UK illegally since January 1, 2022, is liable to be transferred. Each migrant sent to Rwanda is expected to cost British taxpayers between £20,000 to £30,000. This will cover accommodation before departure, a seat on a chartered plane and their first three months of accommodation in Rwanda. Their asylum application will be processed in Rwanda and if they are successful, they will have the right to remain in Rwanda. Those whose applications fail will be deported from Rwanda to countries where they have a right to live. The plan is contingent on the passage of the Nationality and Borders Bill currently before the British Parliament. Britain is planning to send the first set of asylum seekers in May 2022, but this is highly unlikely as human rights groups will almost likely challenge this deal in court and, as a result, delay the implementation.

Rwanda’s Foreign Minister, Vincent Biruta, and Britain’s Home Secretary, Priti Patel, present the initiative as a remedy to what they deem a malfunctioning refugee and asylum system, “(T)he global asylum system is broken. Around the world, it is collapsing under the strain of real humanitarian crises, and because people traffickers exploit the current system for their own gain… This can’t go on. We need innovative solutions to put a stop to this deadly trade.” In a jointly written editorial for the UK’s Times newspaper, they portray the agreement as a humanitarian measure that would disrupt the business model of organized criminal gangs and deter migrants from putting their lives at risk.

Back in Rwanda, the pro-Kagame newspaper, The New Times of Rwanda, highlighted Rwanda’s experience in hosting refugees: “Rwanda is home to nearly 130,000 refugees from around the region.” The New Times claims that “… even those who arrived in Rwanda as refugees fleeing violence have since been integrated in the community and enjoy access to education, healthcare and financial services. This friendly policy toward refugees and migrants is in part linked to the country’s history.” It concludes by noting that “Kigali’s decision to extend a helping hand to migrants and asylum seekers in the UK who’re unable to secure residence there is very much in keeping with this longstanding policy on migrants and moral obligation to provide protection to anyone in need of safety. It is, therefore, shocking that this act of generosity has come under severe attack by some people, including sections of the media.”

Reaction in the UK has been mostly negative, ranging from the Anglican ChurchAmnesty International. A broad range of 150 organizations, including Liberty and the Refugee Council, sent an open letter to Prime Minister Boris Johnson and his Home Secretary (the UK immigration minister).  Even some MPs from Johnson’s ruling Conservative party condemned the deal. Dozens of Home Office staff have criticized the policy and are threatening to strike because of it.

Deals of this kind between Britain and Rwanda are not new. Britain tried to enter a similar agreement with Ghana and Kenya, but both rejected it, fearing a backlash from citizens. Rwanda has done similar deals before. Israel offshored several thousands of asylum-seekers, many of them Eritreans and Sudanese, to Rwanda and Uganda between 2014 and 2017. A public outcry forced Israel to abandon the scheme when evidence emerged that most of them ended up in the hands of people smugglers and were subjected to slavery when traveling back to Europe. Under a deal funded by the European Union, Rwanda has taken in evacuees from Libya. Denmark has a similar agreement with Rwanda, but it has not yet been implemented.

In 2016, Australia signed a similar deal with Nauru, a tiny island country northeast of Australia. In May 2016, Australia held 1,193 people on Nauru at the cost of $45,347 a month per person – about $1,460 a day or $534,000 a year. That same year, the EU signed a deal with Turkey under which Turkey agreed to take back “irregular migrants,” mainly from Syria, Afghanistan, Iraq, in exchange for reduced visa restrictions for Turkish citizens, €6 billion in aid to Turkey, update the EU’s customs union with Turkey, and re-energize stalled talks regarding Turkey’s accession to the European Union.

If these failed deals did not deter Britain, Rwanda’s human rights record should have. Even Kagame’s supporters concede that his human rights record is deplorable. At the 37th session of the Universal Periodic Review (a regular, formal review of the human rights records of all 193 UN Member States), Britain recommended that Rwanda “conduct transparent, credible and independent investigations into allegations of extrajudicial killings, enforced disappearances and torture, and bring perpetrators to justice.” A Rwandan refugee in London told The Guardian that, “Rwanda is a good country for image, but not for freedom of speech…Those who oppose Kagame end up in prison. The Rwandan government use[s] torture and violence against their opponents.”

The deal between Rwanda and Britain also contravenes international law. The principle of non-refoulement “… prohibits States from transferring or removing individuals from their jurisdiction or effective control when there are substantial grounds for believing that the person would be at risk of irreparable harm upon return, including persecution, torture, ill-treatment or other serious human rights violations.” The United Nations High Commissioner for Refugees (UNHCR) notes that Britain has a duty under international law to ensure that those seeking asylum are protected. UNHCR remains firmly opposed to arrangements that seek to transfer refugees and asylum seekers to third countries in the absence of sufficient safeguards and standards. Such arrangements simply shift asylum responsibilities, evade international obligations, and are contrary to the letter and spirit of the Refugee Convention . . . [P]eople fleeing war, conflict and persecution deserve compassion and empathy. They should not be traded like commodities and transferred abroad for processing.

Rwanda is the single most densely populated state in Africa, with more than 1,000 people per square mile. It already has its fair share of refugees from neighboring countries. (Biruta told the Financial Times last month: “This program [the deal with Britain] will be dedicated to asylum seekers who are already in the UK … we’d prefer not to receive people from neighboring countries, immediate neighbors like DRC, like Burundi, Uganda or Tanzania.”

Although it has done well economically compared to many other African countries, it remains a poor nation that needs to prioritize addressing its internal economic issues rather than allowing Britain to dump its refugees on them. It is unlikely that the economic benefits of this deal will help get the average Rwandan out of poverty. If Rwanda needs more refugees, it needs to look no further than its neighbors. Many of those who will end up in Rwanda will likely be genuine refugees who would have a right to remain in Britain and white supremacists in the UK do not want them there because they do not have the right skin color.

With this deal, Johnson and Patel are pandering to the racists simply to get more votes. If this deal was in place in 1972, when Idi Amin deported Ugandans of Asian descent to the UK, Patel’s family might likely have been shipped off to Rwanda. For his part, Kagame is pandering for influence and money from Western nations. It undermines his claim that he is an authentic and fearless pan-Africanist who advocates for the less fortunate. What happened to speaking the truth to Western powers? Let us hope a judge in the UK stops this terrible deal.

This post is from a partnership between Africa Is a Country and The Elephant. We will be publishing a series of posts from their site once a week.

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