Kinship-ties and entrepreneurship in Western Africa

Transcription

1 Kinship-ties and entrepreneurship in Western Africa (work in progress) Michael Grimm International Institute of Social Studies, Erasmus University Rotterdam, The Hague, The Netherlands Flore Gubert DIAL-IRD, Paris, France Ousman Koriko AFRISTAT, Bamako, Mali Jann Lay German Institute of Global and Areas Studies (GIGA), Hamburg and University of Göttingen, Germany Christophe J. Nordman IRD, DIAL, Paris, France Funding by the Austrian, German, Norwegian, and Korean Government through the Multi Donor Trust Fund Project: Labor Markets, Job Creation, and Economic Growth, Scaling up Research, Capacity Building, and Action on the Ground is gratefully acknowledged.

2 Ici en Afrique, quand tu n as pas ta famille à côté, il faut savoir que tu vas souffrir. (Rasmané, 45 ans, tailleur, Ouagadougou, 2009). En Afrique, tu ne dis même pas à ta femme quand tu as de l argent. (Thérèse, 42 ans, comptable, Ouagadougou, 2010) 2

3 Motivation Research project on entrepreneurship in Sub-Saharan Africa (SSA): Starting point: Lack of knowledge on causes of informal sector heterogeneity and implied inefficiencies in particular in SSA. Research objectives of project: Identification of constraints that lead to these inefficiencies? Identification of types of entrepreneurs that have the potential to grow and for which these constraints are binding? Identification of policies to remove these constraints? 3

4 Motivation Often heard hypothesis: Poverty traps, i.e. the existence of low returns for low levels of capital (non-convex production technologies) in conjunction with imperfect capital markets (Banerjee and Newman, JPE, 1993). Empirical evidence: McKenzie and Woodruff (EDCC, 2006), Mexico, cross-section: High returns (15% per month) for low levels of capital (<$200) Moderate returns (3%) for high levels of capital (>$1000) Although credit market constraints are binding for many, no evidence for poverty traps (although non-convexities may arise at higher levels of capital) McKenzie and Woodruff (WBER, 2008), Mexico, randomized experiment (cash transfer) 20-30% per month for capital <$900 But low re-investment rate 4

5 Motivation De Mel, McKenzie and Woodruff (QJE, 2008), Sri Lanka, randomized cash transfer also high returns at low levels of capital (>5% per month) and no evidence for non-convexities Again surprisingly low re-investment rates Grimm, Krüger and Lay (2010), on West Africa, using the same cross-sectional dataset as the present study, find similar evidence: very high marginal returns for low levels of capital (<$150), absence of substantial entry barriers low re-investment rates Following this evidence, the question is what prevents small and microentrepreneurs to re-invest their profits and to develop their business? 5

6 Motivation Possible reasons: Entrepreneurs are risk averse and have time-inconsistent preferences. They are recurrently hit by shocks that require liquidity to cope. The lack of savings institutions or at least the lack of knowledge about their functioning. Entrepreneurs face problems to save due to high family / kin-ship demands and/or their incentives to save are low because they anticipate that a large part of the benefits will have to be shared with others ( dark side of social capital ) 6

7 Motivation Duflo, Kremer and Robinson (2009) show that Kenyan farmers forgo highly profitable investments in fertilizer Impatience would be partly rooted in the difficulty of protecting savings from consumption demands. Di Falco and Bulte (2009) find some evidence that kinship size is associated with higher budget shares for non-sharable goods. They also find evidence that compulsory sharing leads to free riding and attenuates incentives for self-protection against shocks (Di Falco and Bulte, 2010). Baland, Guirkinger and Mali (2007) find that some people take up credits even without liquidity constraint just to signal to their kin that they are unable to provide financial assistance. Beegle, De Weerdt and Dercon (2008) show, for Tanzania, that migrating out of agriculture and out of the village has a strong effect on consumption growth (rising in distance). However, social constraints prevent some villagers from taking advantage of such opportunities. 7

8 Motivation However, literature emphasizes of course also positive effects of family and kin-ship ties (e.g. La Ferrara, 2007): Access to markets Informal insurance Informal credit Support for prospective migrants These are similar benefits than those associated with the broader concept of social capital (Fafchamps, 1996, 2001, 2002, Minten and Fafchamps, 1999 and Banerjee and Munshi, 2004). Main difference between family / kin-ship ties and the ties of a generic set of individuals who interact: Kin membership is exogenous Kin membership cannot be freely changed 8

9 In this paper... We provide some ideas on how family and kinship ties may constrain potentially successful entrepreneurs to develop their business. We conduct an explorative analysis of data covering entrepreneurs in West-Africa. Is the descriptive evidence consistent with ideas above? 9

10 Outline Theoretical framework Data Empirical Analysis Conclusion 10

11 Theoretical framework Framework inspired by Hoff and Sen s poverty trap model (2006): If a kin member achieves economic success in the modern sector, he is invariably besieged with demands by his less successful kin to help them out by remitting money, finding urban jobs for them, letting them stay in his city home, and so on. The need to meet such demands can adversely affect the incentives of kin members in the modern sector or to sever his kin ties presumably at a substantial psychological cost. If the kin group foresees that it will lose some of its most productive members [ ] it may take collective action ex ante to erect exit barriers. The kin system becomes a poverty trap. 11

12 Theoretical framework Model inspired by agricultural household models. Urban households combine consumer and firm. Utility function: Max U = U(X, l) Cash income constraint: p (X - Q)+ R + wl h + rk h X : consumption of market goods l : leisure R : transfers paid to other households + p v V p F(L, K, V ) + w L m + S L h : hired labour, K h : rented capital, V: intermediate goods Q : Production of the informal unit Neo-classical production technology Q = F(L, K, V, Z h ) Z h : exogenous household characteristics 12

13 Theoretical framework Transfers R to other households are assumed to be a share of the firm s value added, VA (turnover minus the costs for intermediate inputs), i.e. transfers are treated like a tax on VA R = s VA, with 0 s 1 with VA = p F(L,K,V,Z h ) - p v V Assumptions that these transfers are imposed by social norms, failing to deliver them, implies prohibitive social sanctions. 13

14 Theoretical framework In the most general case, the share s (the tax rate or solidarity tax ) depends on egalitarian norms prevailing in the entrepreneur s kin, N, on the size of the kin, T, and on the costs to observe the entrepreneur s profits, C, Thus: s = f (N, T, C)

15 Theoretical framework First order conditions imply that factor use in household business declines with tax : Q (1 s ) = L Q (1 s ) = K w p r p Households allocate less labour and capital to production the higher the tax rate s We will thus test the following hypotheses: For two different households 1 and 2, facing s 1 and s 2, where s 1 > s 2, we expect L 1 < L 2, K 1 < K 2 and VA 1 < VA 2. 15

16 Data Set of surveys (Enquêtes 1-2-3) gathered in seven economic WAEMU capitals in the early 2000s. Cross-sections survey is a multi-layer survey organised in three phases and specially designed to study the informal sector Phase 1 is a representative labour force survey Phase 2 is a survey which interviews a sub-sample of informal production units identified in Phase 1 Phase 3 is a household expenditure survey (again sub-sample) 16

17 Data Consistent with the theoretical framework, we consider firms at the household level, i.e. several firms within the same household are aggregated to one single firm. We focus on firms by internal migrants, i.e. migrants from the country side or secondary towns to the economic capital (and observed in the capital) (N = 2369). 17

18 Sample Mean S.D. Owner characteristics Male (=1) Age No diploma Primary completed Some secondary Other post primary Ethnic group Ethnic group Ethnic group Household characteristics Household size Only informal firm Public wage earner Private formal wage earner Other combination Half of all entrepreneurs are men, 72% do not have any diploma, 18% have completed primary school and only 10% have a diploma from a general or vocational secondary school or higher. About 79% of all entrepreneurs live in households that only run one or several informal firms. Only 19.8% live in households that have in addition at least one wage worker in the public sector or in the formal private sector 18

19 Sample Firm characteristics Age of firm Clothing Other manufact./food Construction Wholesale/retail Petty trading Hotels and restaurants Repair services Transport Other services The largest sector is petty trading. The smallest sectors are transport and repair services, which are both rather capital intensive. Firm characteristics Ann. VA in intl.$ PPP Monthly hours owner Total monthly hours Total staff incl. owner Hired paid staff No phys. capital (=1) P.Cap. in intl. $ PPP Physical cap. lowest 33% middle 33% highest 33% No. of firms per hh

20 Determinants of potential solidarity tax The share of the population from the same ethnic group in the neighbourhood. The share of the population from the same area of origin (district) in the neighbourhood. The higher these shares the higher the potential pressure for redistribution. Alternatively, a higher concentration of the own-kin group may also mean more support for own entrepreneurial activities... The geographical distance to the area of origin. A longer distance makes it more difficult and costly to observe the entrepreneur s activities and productivity and hence redistributive pressure is supposed to decline with distance. Number of years passed since migration to the city. Family and kinship ties may erode with time, an out of sight, out of mind effect These proxies imply to distinguish family / kinship ties linked to the village and those linked to the local context (city). 20

21 Determinants of potential solidarity tax Mean S.D. Share same ethnic group Share same origin Distance to origin (km) Time since migration (years) N

22 Determinants of potential solidarity tax Pairwise correlation with transfers ln Transfers ln Transfers Net given received transfer Share same ethnic group 0.158* (0.001) (0.247) (0.370) Share same origin * (0.116) (0.456) (0.086) Ln distance to origin * * (0.002) (0.049) (0.352) Years since migration * * (0.139) (0.002) (0.014) N 580 Note: * significant at 10%. Significance level in parentheses. The share of people in the neighbourhood belonging to the same ethnic group is significantly positively correlated with given transfers. The share of people coming from the same area of origin is positively correlated with net transfers, i.e. given minus received transfers. Distance to the area of origin is statistically negatively correlated with given and received 22 transfers, consistent with the hypothesis that distance dilutes family ties.

23 Empirical analysis 1. We show that inter-household transfers are correlated with value added of firms and that the propensity to transfer out of profits is higher than to transfer out of earnings from (informal) dependent wage work. 2. We explore the relationship between the intensity of family and kinship ties and factor use physical capital, total hours of labour employed, owner s total hours of labour employed controlling for other observable factors that may determine such ties and factor use. 3. We present robustness / further issues 23

24 (1) Regressing transfers on value added and earnings Ln value added 0.175*** (1) (2) (3) (4) OLS Tobit OLS Tobit (0.065) (0.097) Ln total household income The OLS 0.334** 0.499* model (1) suggests that (0.146) (0.261) Share of income from dep. inf. work an increase of *** ** value added (0.831) (1.483) by 1% leads to Share of inc. from dep. formal work an increase in given transfers (0.754) (1.108) by 0.18%. R-squared N Controls: Gender and age of owner/manager, Household size, Ethnicity, Country effects, Activity portfolio of household ((1) + (2).) In models (3) and (4), the propensity to transfer out of household income is again positive, and the negative coefficients associated with the share of informal earnings suggest that the higher the share of informal earnings in total earnings the less is transferred, as our theoretical model predicts. 24

25 (2) Regressing Family / kinship ties on use of labour hours (1) (2) (3) (4) Ln total labour hours Ln total hours owner Years since Years since migration migration 15 All 15 All Share same ethnic group 0.281** 0.248*** 0.217** (0.132) (0.096) (0.097) (0.072) Share same origin 1.340** 1.356*** 0.781* 0.643* (0.532) (0.444) (0.428) (0.361) Ln distance to origin 0.087*** 0.057** 0.048* 0.032* (0.033) (0.024) (0.026) (0.019) Years since migration 0.012* 0.005** (0.006) (0.002) (0.005) (0.002) Ln physical capital 0.176*** 0.169*** 0.069*** 0.059*** (0.019) (0.013) (0.014) (0.010) Family and kinship ties tied to the city are associated with positive effects whereas family and kinship ties tight to the village are associated with negative effects. R-squared N Controls: Gender, age and education of owner/manager, Activity portfolio of household, Ethnicity, Age of firm, Sector effects, Country effects. 25

26 (3) Regressing Family / kinship ties on use of capital (1) (2) (3) (4) Years since Years since migration 5 migration 15 OLS Tobit OLS Tobit Share same ethnic group (0.549) (0.581) (0.347) (0.359) Share same origin (3.105) (3.085) (1.972) (1.803) Ln distance to origin 0.263* 0.316* (0.152) (0.161) (0.089) (0.098) Years since migration ** 0.036** (0.067) (0.083) (0.016) (0.017) R-squared N Controls: Gender, age and education of owner/manager, Activity portfolio of household, Ethnicity, Age of firm, Country effects. Positive coefficient of the distance variable consistent with the idea that redistributive pressure and the related adverse incentive effects get diluted with distance. The further away 26 an entrepreneur is from the family, the higher the investment in the production activity.

27 Problems High ability entrepreneurs may select themselves into neighbourhoods with a large share of people of the same ethnic group and area of origin. High ability entrepreneurs are those who are brave enough to move further away from their village / or are in a better position to find business opportunities even if far away. 27

28 Robustness High ability entrepreneurs may tend to move further away. However, all migrants in sample took the step to move to the capital, thus this is a quite homogenous group (you are not more brave if you move 200km instead 100km once you have decided to move to the capital: relationship between distance and ability is likely to be non-linear). We re-estimated equations for various sub-samples that are limited to entrepreneurs that migrated at least a certain distance away from their area of origin, and found a robust coefficient associated to distance... Coefficient of ln distance Hours of labour used Minimum distance to be included in sample

29 Robustness Coefficient of ln distance 1.8 Physical capital used Minimum distance to be included in sample

30 Additional Result: Number of firms and transfers Various reasons why households may set up several firms: This is an optimal portfolio choice in the presence of activities with different expected returns and associated risks. Firms may belong to different household members that do not necessarily pool their resources. Finally, splitting activities may serve as a strategy to avoid taxes from the extended family (easier to hide several smaller firms than one large enterprise) and to satisfy job demands in unproductive peripheral firms (Camilleri, 1996). 30

31 Regressing the number of firms on transfers given OLS Ln value added 0.110*** Single firm (0.041) (Ref.) Two firms * (0.217) More than two firms (0.493) R-squared N 1194 Controls: Gender and age of owner/manager, Household size, Ethnicity, Country effects, Activity portfolio of household. (Here all firms, migrants and non-migrants.) The results are consistent with the idea that splitting up enterprises is an effective way to reduce transfers to other households. It would also explain why we find so many small firms, many of them highly productive: benefits are rather invested in new firms rather than in existing ones. 31

32 Conclusion We find that the intensity of local family/kin networks within the city is positively correlated with factor use and value added. We find negative effects associated with social networks tied to the village of origin. We provide some evidence that splitting-up enterprises is a successful strategy to save on transfers to other households. Tax seems indeed to be higher on informal profits than on earnings from informal labour outside the household. Easier to hide? 32

33 Conclusion We still need to address potential endogeneity problems (location choice) and explore heterogeneity across countries. The exact nature of underlying mechanisms needs further analysis. Exploration of other potential channels: Baker (2004) assumes for instance, that forced solidarity may also hinder technology adoption, because kin group tends to overestimate returns of such investment and to underestimate implied risks. Policy? Values may change, inter-household transfers decline and negative incentives disappear if formal support mechanisms become more important (in particular insurance). 33

34 Additional results Value added, physical capital and labour (production functions) (1) (2) (3) (4) Years since Years since migration 1 15 All migration 1 15 Ln total labour hours 0.582*** 0.572*** (0.050) (0.043) Ln labour hours owner 0.349*** 0.376*** All (0.058) (0.046) Ln physical capital 0.110*** 0.116*** 0.161*** 0.188*** (0.025) (0.018) (0.025) (0.017) R-squared N Controls: Gender, age and education of owner/manager, Activity portfolio of household, Ethnicity, Age of firm, Sector and Country effects. 34