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I will participate to a conference at the University of Geneva on “The informal economy, vulnerabilities and employment”.

I’m not sure if I’m equipped for this weather…


I PAID A BRIBE is a new Kenyan website where citizens can report when they are forced to pay “kitu kidogo” (“a little something” aka “bribes” in Kiswahili) as well as stories when they refused to pay officials.

The website is still under construction, though there are already some interesting analytics.

The website is full of stories of how corruption affects the daily life of Kenyans. Contributors tell three type of stories: “I Paid a Bribe”, telling the usual stories of corruption. “I didn’t pay a bribe”, reporting when they refused to pay bribes and the reactions of officials. And finally “I didn’t have to pay a bribe”, telling stories of well functioning offices and officials.

In my experience, as a European living in Kenya, I know that corruption is all around me but I’ve never experienced it personally, so I’ve never really grasped the details of how bribery occurs, how officials ask for money and which kinds of offices are most likely to ask for the infamous kitu kidogo. If the website develops as I hope, it will become a very valuable account of corruption in Kenya as well as a tool against one of the biggest obstacles to development in the country.

h/t Evan Lieberman

There is an interesting new paper by Johanna D’Hernoncourt and Pierre-Guillaume Méon (ungated older version here) investigating the relation between trust and the size of the shadow economy. From the abstract:

This paper reports a negative relationship between the size of the shadow economy and generalized trust, in a sample of countries, both developed and developing. That relationship is robust to controlling for a large set of economic, policy, and institutional variables, to changing the estimate of the shadow economy and the estimation period, and to controlling for endogeneity. It is independent from trust in institutions and from income inequality, and is mainly present in the sample of developing countries. Those findings suggest that the tax compliance effect of trust dominates its role as a substitute for the formal legal system.

The idea is that countries with a higher level of generalized trust have smaller shadow economies. The measure of trust is taken from the World Values Survey and it measures the number of people in each country who answer “yes” to the question “Generally speaking, would you say that most people can be trusted or that you need to be very careful when dealing with people?”.

Johanna D’Hernoncourta and Pierre-Guillaume Méon

I think that this is a very interesting piece of research, though it overlooks the inner dynamics of the informal economy. As legal systems are weak and property rights are not enforced by formal institutions, informal operators must rely on trust in all their transactions. In social capital theory, this is called a “club good”, meaning that trust is very strong within a group but small towards the general public (read this paper for a much better explanation).

We are seeing this everyday in our research in Kariobangi. One of the most common problems for entrepreneurs is that costumers cannot pay on time. Though, rarely entrepreneurs decide to cut the relationship with the insolvent clients, because this might reduce future business. Trust within groups, be they other entrepreneurs in local markets, informal associations or ethnic networks is very high because there is no alternative.

It would be very interesting to calculate a proxy for “social capital as a club good” in the World Value Survey and regress that against the size of the shadow economy. That would make a very interesting paper.

We have mentioned before that the Kenyan economy has a major current account deficit (i.e. imports are much higher than exports) and that this imbalance is one of the structural causes for the recent depreciation of the Kenyan Shilling.

Let’s take a deeper look at the Kenyan import and export markets. What does Kenya import and who are the largest importers? And where does Kenya export its goods?

Here I am reporting the most recent data available from the Kenya Bureau of Statistics, the so-called monthly leading economic indicators, which highlight interesting new dynamics on the period July 2010-July 2011. Let’s look first at the graph above on Kenyan import market.

In the period from July 2010 and July 2011, the United Arab Emirates were the major exporters to Kenya. This is a clear indicator of the huge oil bill that Kenya is paying today. China is in the second place and India is third, followed by South Africa and Japan.

Arguably, the most interesting new dynamic is that India is overtaking China as the second largest trading partner. If we consider only the first 7 months of 2011 up to August India has already overtaken China. This highlights interesting new dynamics between Kenya and the Asian emerging powers.

The graph below instead shows the imports by economic category. We see that industrial supplies have the lion’s share, followed by fuel and capital equipment.

Now, let’s look at exports. Kenya exports mostly to the regional East African market (Uganda, Tanzania and Rwanda) as well as to the UK, Netherlands (read cut-flowers) and the US. I didn’t know that Pakistan was an important export market for Kenyan tea.

And below are the exports by category. I am using the same categories used by the KNBS, although it would be interesting to have more precise details about the export of specific commodities (tea, coffee, cut-flowers, etc). I’ll look into that in one of the future posts. It is interesting to see that industrial supplies are a very important export market.

More info on imports and exports:

Everything you wanted to know about Kenyan imports and exports in 2012

Kenya Import policy (and other interesting facts)

The least efficient port on the planet


After last week’s post on microfinance vs credit cooperatives we want to talk more about the “socio-financial landscape” in urban economies in Kenya. The fieldwork we are doing in Kariobangi is telling us some interesting stories.

First, we are realizing that the term “unbanked” depicts a completely wrong image of what’s happening in local economies: most entrepreneurs in Kariobangi, both informal and semi-formal, have one or more bank accounts. This might be the particular case of Kenya where the financial sector has deepened in the low-income population. Furthermore, banks must find their market segments in complex preexisting financial structures: in addition to bank accounts, entrepreneurs use a variety of other (mostly unconventional) financial instruments. In a certain way, the term “hyper-banked” seems more appropriate than “unbanked”.

So what are the “financial portfolios” of MSEs?

Starting from the informal side of the spectrum, the most common socio-financial instruments are the so-called ROSCAs (Rotating saving and credit associations) and ASCAs (Accumulating Savings and Credit Associations). ROSCAs are also known as “mery-go-round”: members of the groups meet regularly and contribute a certain amount. Then the entire “pot” (or lump-sum) of money collected goes to one member at each meeting on a rotating basis. ASCAs work on a similar way, but the money collected is given as a loan, not a lump-sum, to the members who apply for it, who have to pay it back to the group with interest over an agreed period. At the end of the year, all the money collected by the group plus interests on loans is divided among the group members.

Other common group types are the so-called saving clubs, where members simply keep their savings for future use; the investment clubs, where the money is used for investment in business, property or stock markets. Then there are the welfare associations, which operate as informal insurance companies. Moneys collected by groups are used only for emergencies, such as hospitalizations or funerals.

On the more formal side of the spectrum, there are the institutions that everybody knows: banks, microfinance institutions (MFIs) and credit cooperatives (SACCOs). We are noticing a growing hostility towards MFIs because of the high interest rates and the “harassment” of debtors when they are late with the repayments. Though, many businesses said that MFIs were very important for the growth of their business, but they can’t afford to borrow repeatedly over time. Some businesses also secured loans from banks such as Equity Bank and Co-operative Bank. Though, it is only a minority of businesses.

Since it launched in 2007, the service has garnered 15.1 million customers. At peak times, there are 200 transactions every second and the equivalent to 20 per cent of the country’s GDP washes through the system.

But replicating Safaricom’s success has long proved beyond reach. Since the UK’s aid agency gave a £1m grant in 2006 to try to facilitate microfinance payments, which led to the birth of the service, none of the other 120 or so copycat mobile money platforms have performed as well. Only the Philippines comes close, with about 3m customers, while Tanzania may yet overcome a sluggish start.

Check out the full article from the BeyondBrics (FT) here.

In a variant on the Kenyan model, the Indian mobile money will have to partner with a bank, meaning customers might even make interest from the money they store. In Kenya, 12-15bn shillings are stored on M-PESA systems at any one time, but Safaricom is not allowed to make a profit with the interest and neither is the customer. Instead the earnings go into a charitable M-PESA foundation. Any attempt to change this is likely to spook banks, which have in the past attempted to close down M-PESA.

In Kariobangi whave noticed that MPESA is bringing new habits and “rules of the game” in local markets and it is used by virtually 100% of market operators. However, let’s not overestimate its impact: cash is still the king, by far.

The problem is that transferring money with MPESA and withdrawing small sums from the agents requires the payments of a fee, which becomes burdensome in markets where there is a huge number of very small transactions. This, combined with the lack of interest on savings, makes MPESA a rather expensive (though handy) financial product.

For a very interesting analysis of the use of MPESA check out the recent work of Guy Stuart and Monique Cohen “Cash in, Cash out Kenya: The Role of MPESA in the lives of low income people” (PDF). They recorded over 18000 transactions with financial diaries and showed that not only cash is still king in local economies (over 94% of total transactions), but that MPESA is valuable especially for the urban-rural remittances: the “Send money home” strategy, where MPESA is an alternative to physically taking an envelope by bus over long distances.

Tomorrow is the great day when we will be back in the field. Over the past few weeks, a new assistant has joined the team (welcome Ignatius!) and the questionnaire has received a nice haircut, from 18 to 14 pages. The main challenge was to give a “haircut” to our questionnaire,  not an amputation, and I believe we succeeded. If you happen to pass by Kariobangi around 10am, come say hello in Landmark Plaza, we’ll just have finished our initial training session.

We have done a lot of brainstorming during this break and I have received feedback from many colleagues around the world. A few interesting points have emerged on the “joys and sorrows” of doing surveys – in Kenya as compared to other countries, and using surveys as compared to other research methods.

First, our experience confirms that Kenya (and Kenyans) are particularly research-friendly. Many colleagues were impressed that we could handle an extensive questionnaire without paying the respondents. Let’s be clear: more than once we have been turned down by respondents and several times people received us with suspicion. But that was mostly our own fault.

Thanks to an interesting discussion with the market chairman in Kariobangi, we realized that showing up with a questionnaire in our hands was a disastrous way of approaching people and that “being introduced properly” was crucial for increasing both the response rate and the quality of answers. Once we learned the proper manners, we noticed a much higher willingness to participate to the survey and interest about the results.

Though, “being introduced” to entrepreneurs (aka a partial “snowballing technique“) reduces the representativeness of the sample, which is no longer “purely random“. Unfortunately, in our own fieldwork, we saw a tradeoff between the “quality of the answers” (arguably higher with snowballing) and the “quality of the sample” (arguably higher if random). We chose to maximize the quality of responses, though at a price.

There is also another finding: we noticed that respondents rarely answer “I don’t know” to any questions -although they actually do not know the answers. We tried to understand whether we are posing the questions in the wrong way or whether this is related to culture or something else. On the “plus side”, this means that we have a very low number of missing values -the greatest headache in econometric studies. On the minus side, it might imply inaccurate data -a complete disaster- especially because it adds up to the infamous recall bias typical of recall questionnaires.  Quality control of the data collection and research process will be key. But this topic deserves its own post.

View of the manufacturing cluster in Kariobangi, Nairobi (left side of the road)

Many of the future posts will focus on businesses operating in the Kariobangi Light Industries. This is a very interesting cluster that specializes on metalwork, woodwork and on building machinery of different kinds.

You can see from the photo that Kariobangi does not look like an usual industrial area. There are numerous (concrete) buildings with small industries on the ground floors and apartments in the floors above. Safety in the area is a problem. A few months ago a business dealing with chemicals got on fire at night time and 10 people living in the floors above were killed.

Several studies were conducted in the past in Kariobangi. The most recent one is by Sonobe, Akoten and Otsuka  “The growth process of informal enterprises in Sub-Saharan Africa: a case study of a metalworking cluster in Nairobi” (ungated version). This is how they introduce the areas:

Our study site is called Kariobangi Light Industries since the local government designated it to be an area for artisans in 1989. Its development dates from the early 1980s, when the workers of formal-sector factories lost jobs as a consequence of the implementation of the Structural Adjustment Program (SAP) and began to establish garages and workshops along the main road. They cleared the bushes to construct roads inside the area. The current population of enterprises is about 300, of which half are related to metalworking. They call themselves Jua Kali in Swahili, meaning informal sector artisans. This cluster is informal and may be categorized as what Altenburg and Meyer-Stamer (1999) call a ‘‘survival cluster of micro and small-scale enterprises,’’ which produce generally low-quality products and sell them primarily to domestic markets.

The article provides lots of details about growth processes and constraints in the cluster and it is definitely the main empirical study done in this area. Though, after spending several weeks in the field,  I do not agree entirely with their description, especially the last part. First, because although there is no official census, the population of enterprises in the Light Industries seems larger than the 300 estimated in their article. But this is probably just a matter of delimitations of the cluster and fact that many businesses are quite hidden.

Second, the definition of  Kariobangi as a ‘‘survival cluster of micro and small-scale enterprises’’ does not reflect the local perception of Kariobangi. Although most businesses operate at a micro and small level, Kariobangi is technologically more advanced than most informal clusters in Kenya and produces goods that require a higher level of skills.

Third, many products coming from Kariobangi are not of low-quality. There are tons of restaurants and small dining places that buy their machinery in Kariobangi. Many agricultural enterprises come to Kariobangi to buy their technology as well. Although the quality of this machinery is low for western standards, it seems to satisfy the needs of local markets and it is difficult to produce with the scarce means available.

If we fail to identify the differences between clusters in local markets, from informal to semiformal and from survival to those with a growth potential, then we have little chances to design appropriate policies for private sector development. Kariobangi Light industries is not a survival cluster. On the contrary, many of the firms operating here are at the higher end of the local MSE sector.

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