Since the Edelman company began tracking trust with its Trust Barometer, never has the world seen such an “implosion of trust.” In 2017, two-thirds of countries fell into “distruster” territory with trust levels of below 50 percent. Governments are now distrusted by investors in 75 percent of countries, and the same is the case for business in 46 percent.
« Ce n’est pas parce que cela fonctionne au Brésil que cela fonctionnera au Burundi. » C’est vrai. Et ça semble évident. Pourtant, ce genre de critique continue d’être matraquée aux chercheurs, qui pratiquent des évaluations d’impact aux quatre coins du monde. Les institutions varient. Les niveaux d’éducation varient. Les cultures varient. Ainsi, un programme qui a réussi à autonomiser les filles en Ouganda, ne marchera pas forcément en Tanzanie.
In recent years, growing evidence supports the value of cash transfers. Research demonstrates that cash transfers lead to productive investments (in Kenya, Tanzania, and Zambia), that they improve human capital investments for children (in Burkina Faso, Tanzania, Lesotho, Zambia, and Malawi), and that they don’t get spent on alcohol (all over the world).
At the same time, the vast majority of governments invest large sums in training programs, whether business training for entrepreneurs or vocational training for youth, with the goal of helping to increase incomes and opportunities.
L’information diffusée par les médias sur l’épidémie d’Ebola en Afrique de l’Ouest attire souvent l’attention sur les enfants orphelins. Reportage après reportage, des histoires déchirantes (a) nous parviennent d’enfants qui ont perdu leurs parents à cause du virus Ebola et qui sont parfois même rejetés par leur communauté. Ces enfants méritent notre attention, car chacun sait que la perte d’un parent est lourde de conséquences à court et à long terme. Des travaux empiriques menés au Kenya (a), en Afrique du Sud (a), en Tanzanie (a) et dans l’ensemble du continent font apparaître que les résultats scolaires des enfants devenus orphelins se détériorent rapidement. Certaines observations en Tanzanie montrent que ces impacts négatifs sur l’éducation et la santé continuent de se faire sentir jusqu’à l’âge adulte.
Much of the media coverage of children during West Africa’s Ebola epidemic has been focused on orphans. Repeatedly, we have read heartbreaking stories of children who have lost parents to the disease and even been rejected by their communities. These children deserve our attention: We know that losing a parent has both short-term and long-term impacts. Evidence from Kenya, South Africa, Tanzania, and across Africa demonstrates significant reductions in educational outcomes for orphans in the short run. Evidence from Tanzania shows that adverse education and health effects persist into adulthood.
Tanzania has undoubtedly performed well over the past decade, with growth that has averaged approximately 7% per year, thanks to the emergence of a few strategic areas such as communication, finance, construction, and transport. However, this remarkable performance may not be enough to provide a sufficient number of decent or productive jobs to a fast-growing population that will double in the next 15 years. With a current workforce of about 20 million workers and an unemployment rate of only 2%, the challenge for Tanzanians clearly does not lie with securing a job. Rather, it is to secure a job with decent earnings.
Is bigger always better? Economists have long debated what size firms are more likely to drive business expansion and job creation. In industrial countries like the United States, small (young) firms contribute up to two-thirds of all net job creation and account for a predominant share of innovation. (Source: McKinsey, Restarting the US small-business growth engine, November 2012). In developing countries, evidence from Ethiopia, Ghana and Madagascar shows that the vast majority of small operators remain small, and so are unlikely to create many decent jobs over time [Source: World Bank, Youth Employment, 2014]. By contrast, ‘big’ enterprises are seen as the best providers of employment opportunities and new technologies.
The difference in role and performance of small firms in developing and industrial countries reflects to a large extent their owners’ characteristics. In the US, small firm owners are generally more educated and wealthier than the average worker, while the opposite is true in most developing countries. This point was emphasized by E. Duflo and A. Banerjee in their famous book ‘Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty’ (Penguin, 2011). Most business owners in developing countries are considered to be ‘reluctant’ entrepreneurs; essentially unskilled workers that are pushed into entrepreneurship for lack of other feasible options for employment.
This is also very much a reality in Tanzania where small business owners have few skills and limited financial and physical assets. Of the three million non-farm businesses operating in the country, almost 90% of business owners are confined in self-employment. Only 3% of business owners possess post-secondary level education. As a result, their businesses are generally small, informal, unspecialized, young and unproductive. They also tend to be extremely fragile with high exit rates, and operate sporadically during the year. Put simply, most small businesses are not well equipped to expand and become competitive.
The expansion of household surveys in Africa can now show us the number of poor people in most countries in the region. This data is a powerful tool for understanding the challenges of poverty reduction. Due to the costs and complexity of these surveys, the data usually does not show us estimates of poverty at “local” levels. That is, they provide limited sub-national poverty estimates.
For example, maybe we can measure district or regional poverty in Malawi and Tanzania from the surveys, but what is more challenging is estimating poverty across areas within the districts or regions (known as “traditional authorities” in Malawi and “wards” in Tanzania).
To address this shortfall, several years ago a research team from the World Bank developed a technique for combining household surveys with population census data, and poverty maps were born. Poverty maps can be used to help governments and development partners not only monitor progress, but also plan how resources are allocated. These maps depend on having access to census data that is somewhat close in time to the household survey data. But what if there is no recent census (they are usually done every 10 years) or the census data cannot be obtained? (I will resist naming and shaming any specific country): we are left with no map. Can we fill in the knowledge gaps in our maps?
- Burkina Faso
- Cabo Verde
- Central African Republic
- Congo, Democratic Republic of
- Congo, Republic of
- Equatorial Guinea
- Gambia, The
- Sao Tome and Principe
- Sierra Leone
- South Africa
- South Sudan
- Cote d'Ivoire
- King Baudouin African Development Prize
Travelling across Africa these days you are likely to run into increasing numbers of mining, oil, and gas industry personnel engaged in exploration, drilling, and extraction across the continent. Although commodity prices are moderating, the discoveries being made in Africa offer the real prospect of significant revenue to many cash-poor, aid-dependent governments in the decade ahead. If you care about development, the question is whether these revenues will catalyze broad economic development and whether they will benefit the poor in Africa.