Entrepreneurship Programs in Developing Countries: A ... - IYFLive.net

We find that business practice and labor market activity outcomes are more likely associatedwith positively significant impacts than labor income outcomes (omitted category) by 46.7 and 35.4percentage points respectively (column 1). For business performance and labor income, theimpacts seem to be less likely to be positively significant. This suggests that changing knowledgemay be easier than changing behavior and labor market outcomes at least for the short term. 24 Thisfinding may be different if the long term impacts were estimated as knowledge fades away andimpacts on labor market outcomes are materialized.The model in column 2 examines the probability of program success by intervention types. 25We classify programs into ‘Training only’, ‘Training + Counseling’, ‘Financing only’, ‘Financing +Counseling’ and ‘Financing + Training’ (omitted group). 26 Results show that differences acrossinterventions in the chances of success are not significant although the sign and magnitude suggeststhat training combined with counseling is more promising than others.A clear pattern emerges when comparing program estimates by population groups (column3). Program impacts estimated for youth and urban population are more likely to be positive andsignificant than estimates for the general population. To the contrary, programs targeted tomicrofinance clients are less likely to yield positive impacts. Differences in program results bygender, education, enterprise ownership and social assistance dependency are statisticallyinsignificant. It is worth clarifying that the model includes dummy variables for the populationgroup for which the effect has been estimated; it does not necessarily capture whether the programis targeted to that particular group. 27Compared to the case of having multiple agencies involved in the program delivery (omittedcategory), programs delivered solely by banks or microfinance institutions are less likely to beassociated with program success (columns 4). 28 NGOs are associated though weakly with betterperformance. This finding suggests that programs could work better when delivered by providerswhich have strong connection with the beneficiaries and are familiar with local contexts.24 End line surveys for our sample of impact evaluations take place, on average, 18 months after the completion of theprogram, and about three quarters of estimates are measured within two years.25 Note that we are using “program success” for having positively significant impacts at 10-percent level.26 See Appendix Table A3 for the distribution of estimates by type of interventions and outcomes of interest.27 For example the dummy variable “female” is equal to one either when the corresponding effect size has beenestimated for the subsample of female or, by definition, when the program is targeted to women.28 When multiple agencies are involved, it is usually the cases where government agencies working with NGOs andresearchers collaborating with government or NGOs.14