The development of the microfinance sub-sector in Kenya is seen as a favourable catalyst for increasing performance of Micro and Small Enterprises (MSEs). Despite the development, MSEs continue to suffer from high levels of financial exclusion and shortage of operating funds. This scenarios raise policy questions on whether participation in microfinance has effects on performance of MSEs. While past studies on this relationship have demonstrated that the effects are mixed, an understanding of the effects on participation of microfinance on different segments on MSEs - especially the youth and women owned businesses and age of businesses, is necessary in designing relevant policy changes in the MSE subsector. To address this, the study used the 2016 FinAccess Dataset and estimated these effects using the propensity score matching technique. This model was considered suitable since it accounted for potential endogeneity biases associated with self-selection into participation, unobserved entrepreneurial abilities and risk taking behaviour of MSEs. Apart from showing that participation in microfinance has positive effects on performance of MSEs, the study has demonstrated that there is presence of constraints limiting the impact of microfinance especially in firms owned by the youth and women. As such, there is need for policy and product designs to address these hindrances even as participation in microfinance is encouraged. Based on the results, it is recommended that government and microfinance providers should design policies and products that increase firm participation in microfinance. This may be through scaling up financial literacy programmes and encouraging acquisition of permits. Finally, policy should address obstacles that hinder the youth and women owned MSEs from benefiting from microfinance.
This article provides empirical evidence on technical efficiency differences and efficiency distribution for three Kenyan manufacturing subsectors, namely food, metal and textile, using an unbalanced panel data covering two periods. Econometric production frontiers are estimated for each subsector in each period. The confidence predictions for these efficiencies were, however, found to be quite wide. The results indicate variation of technical efficiency estimates of the sampled firms in each period. The technical efficiency distribution for each subsector changed not only in relation to itself, but also in relation to the other subsectors across the two periods of analysis. The efficiency distribution of the firms for both food and textile (metal) subsectors improved (declined) during the study period but with the food subsector firms remaining relatively inefficient. The improvement of the technical efficiency distribution for both the textile and food subsectors is an indication of intra‐plant improvement during the period of analysis. The decline of the technical efficiency distribution for the metal subsector suggests that the market orientation during the structural reform period did not promote firm efficiencies or the firms were slow in responding to the reforms.
The relationship between output growth and employment elasticities has been of intense debate among many economists. Though there is no conflict between the two objectives, the question that arises is the rate at which employment growth responds to economic growth. The policy focus on employment in Kenya is manifested by the sheer number of employment targeted development plans and Sessional papers that have been formulated. Basically, all the policy documents developed by the government have premised employment creation on economic growth. The purpose of the study was therefore to determine the drivers of employment elasticities in Kenya. Empirical findings indicated that the first lag of employment elasticity, average wage, inflation rate, labour force participation rate, first and second lags of labour force participation rate, population density, first and second lags of foreign direct investment to be the short run drivers of employment elasticity. Empirical findings also indicated that exchange rate, foreign direct investment and population density were the long run drivers of employment elasticity in Kenya. The study recommends that policy measures to control inflation should be tightened and more efforts to attract foreign direct investment to be undertaken. The study further recommends that a stable exchange rate should be maintained. Lastly, the government should harmonize the salary scale framework to regulate the wages in the country. This could be realized through salary adjustments based on a periodical and systematic evaluation of wage parameters in the public sector and taking cognizance of the prevailing economic dynamics.
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