Drivers of Entrepreneurship and Post-Entry Performance of Newborn Firms in Developing Countries - Working Paper

Quatraro and Vivarelli offer us a review of the latest research in "Drivers of Entrepreneurship and Post-Entry Performance of Newborn Firms in Developing Countries", that I believe bring some interesting questions around livelihoods and local economic development and also tags along nicely to my previous post on "Non-Farm Enterprises"

Abstract:     

"The aim of this paper is to provide an updated survey of the "state of the art" in entrepreneurial studies with a particular focus on developing countries (DCs). In particular, the concept of "entrepreneurship" is critically discussed, followed by a discussion of the institutional, macroeconomic, and microeconomic conditions that affect the entry of new firms and the post-entry performance of newborn firms. The reviewed literature bears some policy implications for the support of the creation new firms, such as the targeting of policy measures to prospective entrepreneurs who possess high education levels, long previous job experience, and innovative skills. Specifically, for DCs, tailored subsidies and support should be coupled with framework and infrastructural policies that are able to improve the business environment such that new ventures can start and grow."

Findings of relevance for programming are:
- Minimum Efficient Scale (Size matters). Risk of failure dramatically drops once it gets to its MES. Programming could be built around benchmarks like MES that allow for reallocation of resources towards more at risk business, instead of a fixed/same across the board timeline. This would also imply that each business may have a different growth objective/requirement (and not just slightly above break even) depending on the sector.
- Previous experience in the sector. While this may seem an obvious, sometimes selection criteria for interventions are based on needs rather than chances of success. Programme design has to be clear on what is aiming for (temporary relief or longer term livelihood) and act accordingly. 
- Financial. Credit constrains may have been overplayed as an obstacle to enterprise survival and maybe the focus should be more on savings rather than borrowing. Microfinance user may actually using it in that manner, as some studies have shown negative returns (they may actually be losing money) but positive savings (they save money in comparison with the previous situation). There is an increasing shift towards savings but the rethoric still remains around credit constrains.
- Education is a mixed bag. Higher level education reduces the chances of starting up, probably because the first preference is salaried labour (and seeking to avoid defensive entrepreneurship) that education gives access to. On the other hand, education is a high predictor of business growth and survival. It is interesting to note that there is a "threshold effect" depending on context/location, were there is a minimum level of education that leads to faster growth. Being able to identify that level for the target area may help in yielding better results. Then again we encounter the issue of selection criteria and programming priorities.
- Unemployment is negatively correlated with enterprise survival. Previous unemployment increases the risk of failure and tends to be linked to lower economic outcomes and job creation. Much programming is built around entrepreneurship for unemployed youth, wouldn't it be better to have a two staged/tiered system where unemployed would initially be waged labour (and gaining sector experience at the same time) before start-up is considered?
- Minorities. I am troubled with their recommendation of specific support to entrepreneurial minorities. While this may make sense from an economic point of view (building on an existing strength), the political and social risks of such actions can be large. Business minorities have been violently targeted even in recent times, and a policy that singles them out in a sector they may already have a comparative advantage will only fuel negative perceptions.

   

Non-Farm Enterprises in Rural Africa: New Empirical Evidence - Working Paper

Probably the biggest takeaway from Nagler and Naude's "Non-Farm Enterprises in Rural Africa: New Empirical Evidence" is the recognition that 'Africa is not a country', or as they put it: Heterogeneity. They compare data from six countries and data diverges significantly as dynamics are tied to local context, not only at national level but also at sub-national. Nevertheless, the issue of non-farm enterprises remains key in many African (and other) countries, and this paper highlights it quite well.

 

Abstract:     

"Although non-farm enterprises are ubiquitous in rural Sub-Saharan Africa, little is yet known about them. The motivation for households to operate enterprises, how productive they are, and why they exit the market are neglected questions. Drawing on the Living Standards Measurement Study -- Integrated Surveys on Agriculture and using discrete choice, selection model and panel data estimators, this paper provide answers using data from Ethiopia, Niger, Nigeria, Malawi, Tanzania, and Uganda. The necessity to cope following shocks, seasonality in agriculture, and household size can push rural households into operating a non-farm enterprise. Households are also pulled into entrepreneurship to exploit opportunities. Access to credit and markets, household wealth, and the education and age of the household head are positively associated with the likelihood of operating an enterprise. The characteristics are also associated with the type of business activity a household operates. Rural and female-headed enterprises and enterprises with young enterprise owners are less productive than urban and male-owned enterprises and enterprises with older owners. Shocks have a negative association with enterprise operation and productivity and a large share of rural enterprises does not operate continuously over a year. Enterprises cease operations because of low profits, a lack of finance, or the effects of idiosyncratic shocks. Overall the findings are indicative that rural enterprises are "small businesses in a big continent" where large distances, rural isolation, low population density, and farming risks limit productivity and growth."

Some points to note from the study:

- entrepreneurship have had a very urban focus, and when it comes to the rural areas the focus is on agriculture. The study show the importance of non-farm enterprises in smothing shocks and providing additional income

- Most livelihoods and entrepreneurship interventions focus on the individual. However,
in this context, enterprises are a household activity (both in decision making and operation), specially taking into account distribution of labor according to seasonality (planting and harvest), number of available workers and household tasks (and gender-based allocations).

- Response to shocks (drought, price, conflict) is a major reason for enterprise creation, however not all shocks have the same effect on the choice of sector. Many differences are country specific (different responses to the same kind of shock). Moreover, productivity of enterprises born out of necessity (shock response) is lower than those out of choice. This may help us rethink the programming 'mix' regarding both prevention and response to crisis.

- In some cases, education was positively correlated with entrepreneurship, probably due to the fact that educated individual do not have a comparative advantage in a rural setting where waged employment is limited and therefore reallocate into self-employment. The role of education (or the kind of) in rural settings have to be thought further.

- Each non-farm sector has its own profile. The variables studied (education, number of adults in the household, age and credit access) have different effect depending on the sector: agribusiness, sales, trade, restaurant, professional services, etc...

- Distance to population centers. Highlighting the importance of rural secondary towns and cities, as enterprises located up to 10 km from a population center are the most productive (on average urban enterprises are more productive than rural). Productivity drops significantly when they are more than 50 km away. Large gains in poverty reduction have actually been linked to secondary cities rather than major cities or capitals.

-Youth. Younger households are not only less productive but also less probable to engage in non-farm entrepreneurship in comparison with middle age groups. To note this is talking about household heads, and not necessarily individual engagement in activity.

- Seasonality and enterprise life. Agriculture remains the key driver in many rural settings and non-farm enterprises adapt to that cycle. Enterprises, in many cases, appear/grow and disappear /decrease according to the planting and harvesting needs, and not necessarily seen as permanent activities

- Exit reasons. The most self-reported reasons of enterprise termination are low profitability, lack of finance, unreliable supplies, as well as the impact of  death or illness in
the family (specially in settings with limited insurance or social protection)

While this paper provides and overview might be good for getting ideas where to look further, we would be better off going into country specific studies when it comes to programming and policy recommendations/development.

Ethnic Divisions and Production in Firms - Kenya Working Paper

As practitioners of development and peacebuilding, we usually develop a rule of thumb: "ethnic divisions as a predictor of ...." conflict, lack of trust, implementation inefficiencies, mis-allocation of resources, corruption, [put your own experience/pet theory here]. On the other hand we tend to be very aspirational/principled about diversity and how everybody should be included. Hjort's paper "Ethnic Divisions and Production in Firms",in a way, addresses this issue from a business management/productivity in Kenya standpoint.

Abstract

"A body of literature suggests that ethnic heterogeneity limits economic growth. This paper

provides microeconometric evidence on the direct effect of ethnic divisions on productivity. In team production at a plant in Kenya, an upstream worker supplies and distributes flowers to two downstream workers who assemble them into bunches. The plant uses an essentially random rotation process to assign workers to positions, leading to three types of teams: (a) ethnically homogeneous teams, and teams in which (b) one or (c) both downstream workers belong to a tribe in rivalry with the upstream worker's tribe. I find strong evidence that upstream workers undersupply non-coethnic downstream workers (vertical discrimination) and shift flowers from non-coethnic to coethnic downstream workers (horizontal discrimination), at the cost of lower own pay and total output. A period of ethnic conflict following Kenya's 2007 election led to a sharp increase in discrimination. In response, the plant began paying the two downstream workers for their combined output (team pay). This led to a modest output reduction in (a) and (c) teams (as predicted by standard incentive models) but an increase in output in (b) teams, and overall. Workers' behavior before conflict, during conflict, and under team pay is predicted by a model of taste-based discrimination. My findings suggest that inter-ethnic rivalries lower allocative efficiency in the private sector, that the economic costs of ethnic diversity vary with the political environment, and that in high-cost environments firms are forced to adopt "second best" policies to limit discrimination distortions."

Overall, ethnic divisions do reduce productivity both before and during active conflict through discrimination (as measured by output, not by perceptions or declared attitudes). Team design/task allocation does have a impact on the level of decreased productivity in comparison with a fully homogeneous team. Active conflict (in this case the 2007-08 election violence in Kenya) increases the discrimination (although we could have guessed that) but also the discrimination continues afterwards (a certain level of persistence). The firm's "solution" is to switch from individual productivity pay to group pay, a "second-best" option in terms of productivity in comparison to full segregation; but probably a good idea in terms of context, perception and business sustainability.

Implications for our work? Principled diversity without a good institutional design can have very inefficient outcomes (as we have seen, power sharing can be also a predictor of violence). In cases where we are working with divided ethnicities, special attention is required on the incentives to discriminate or not (i.e. group gains vs individual, payment on results rather than functions, etc..). This not only applies to the 'beneficiaries', but may also need to have a hard look inside our own operations and teams; as we tend to operate with HR manuals and processes that have a high personal responsibility component (in the study, the shop managers were not even aware of the extent of productivity differences!)

The author is careful to note that ethnic division, in this case, is a political construct, where an Bantu group (Luhya) alligns with a Nilotic group (Luo), in opposition to another Bantu group (Kikuyu).

HT to Chris Blattman