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

4.2. Summary of Impacts of InterventionsTable 4 presents summary of the estimated impacts by outcome groups measured by significanceand effect size. 20 At 10 percent statistical significance, about 29 percent of the estimates arepositively significant while 68 percent is insignificant and 3 percent is negatively significant inlabor market activities. Compared to the significance of the Active Labor Market Programs(ALMPs) in OECD countries summarized in Card et al. (2010a), where 39 percent is positivelysignificant, 36 percent is insignificant, and 25 percent is negatively significant, the estimates in ourstudy shows greater prevalence of insignificant outcomes. The effect size for labor marketactivities is 0.065 on average, but 0.192 among the positively significant estimates. 21 This isslightly lower than the effect size (0.21) estimated for OECD programs in Card et al. (2010a)suggesting that improving labor market activities especially in self-employment may be morechallenging to see large impacts in developing countries.Standardized effect sizes enable comparisons across diverse studies with different outcomemeasures. Effect size substantially varies by intervention types, outcomes of interest, beneficiaries,providers, regions, and income levels (Table A2 in Appendix). Training combined with counselingor financing shows that they have larger effect size. In contrast, the combination of financing andcounseling yields the lowest effect size even among the positively significant outcomes. Withrespect to the outcome categories, among the positively significant estimates, business practiceshows the largest effect size whereas the effect size of labor market income and businessperformance is smallest. The results for financial behavior appear to widely vary where the effectsize gap between positively significant and insignificant estimates is quite large. Youth and higheducation group, and multiple providers tend to have larger effect size as well as Africa region andlow income countries. However, the summary statistics should be interpreted with caution becausethey take average over impacts estimated from different studies, population groups, and differentdimensions of the programs.5. Results of the Meta Regression Analysis20 See Table A2 in Appendix for average effect sizes by intervention types, population groups, providers, regions andcountry income levels.21 A binary variable such as the probability of employment, for example, has a standard deviation of maximum 0.5.Hence the average 0.062 effect size corresponds to 12.4 percentage points increase when the average employment rateis 50 percent.12