エチオピアの農業協同組合、農村組織、農村金融機関に関する実証分析

博士（学術）神戸大

Technical Efficiency of Major crops In Ethiopia: Stochastic Frontier Model

Production and productivity can be boosted either through increased use of inputs and/or improvement in technology or by improving the efficiency of producers or firms, given fixed level of inputs and technology. Even though agriculture stays the main stay of Ethiopian economy, level of agricultural productivity in general and crop productivity in particular is very low. Out of the total grain production in Ethiopia, cereals account for roughly 60 percent of rural employment and 80 percent of total cultivated land. However, Yield of cereals has been consistently well below world and even of least developing countries average yield, indicating poor productivity of the crops in the country. Given capital constraint in the country, it is difficult to adopt new technology to enhance productivity. Hence, working to improve production efficiency is best option on hand. As a result, there are a number of studies done on area of efficiency analysis in Ethiopia. However, the novelty of this study can be explained by three facts. First of all it has used national data, collected by International Food Policy Research Institute (IFPRI), with enough number of observations to do plot level analysis considering biological factors that determine inefficiency. Second, efficiency analysis is not based on a single crop rather on major crops in general as well as teff, wheat and maize independently. Last but not least, the study employed one stage approach in which both technical efficiency and factors of inefficiency are analyzed simultaneously. Therefore, this study was done to evaluate the efficiency and identify factors that explain the variation in inefficiency of crop production in Ethiopia. This study principally used the 2009 Ethiopia Rural Household Survey (ERHS) which is collected by IFPRI. As far as analysis is concerned, both descriptive and econometric methods were used. Descriptive statistics (mean, percentage, range, etc.) is used to summarize the variables in the model and describe the study area. Econometric model, Stochastic Production Frontier model, is used to estimate the elasticity of production function, determine the determinants of inefficiency and estimate the level of efficiency. Given that we are considering a developing country setting where by the main concern is output shortfall rather than input over use, preference has been given to primal or output oriented approach of measuring efficiency. In this study, effort was made to test the hypotheses before rushing to interpret the model outputs. First, the γ parameter estimates of all production functions were significant at 5% significance level, indicating Stochastic Frontier Production function is more appropriate than convectional production function or there is significant technical inefficiency variation among plots. The γ value of 0.636 for the major crops production function can be then interpreted as, 63% of the variation in output among plots is explained by technical inefficiency. Similarly, variation in out put due to technical inefficiency for teff, wheat and maize production were calculated to be 88.5, 45.5 and 77.8 percent respectively. The second step, following the existence of inefficiency, is to check if there exist one or more variables that could explain the variation in technical inefficiency. Log likelihood ratio was used to test the hypothesis. Accordingly, all calculated LL ratio values were greater than the critical value of LL ratio, with upper 5 % level of significance. Hence, the null hypotheses that determinant variables in the inefficiency effect model are simultaneously equal to zero are rejected. In other words, there exists at least one explanatory variable that explains the variation in the technical inefficiency among plots. The ML estimate results shown that, all variables were found to be binding in the production of major crops, meaning that an increase in one of inputs will enhance output keeping everything constant. As far as teff production is concerned, only land was a significant variable that explains the variation in teff output among plots. Land, DAP and seed were found to have significant and positive effect in wheat production. According to result of this study, land and seed were major determinants of maize production in Ethiopia. Generally, all significant input variables were found to affect output positively, as expected. Moreover, the model output depicted that the mean level of TE for major crops, Teff, Wheat and Maize production was found to be 63.56, 67.26, 84.16 and 91.41 percent, respectively. The inefficiency effect analysis shown that, age of the household head measured in years was found to be the determinant of technical inefficiency, of teff production and education was found to have negative and significant effect on major crops and wheat technical inefficiency (1% significance level). Knowledge about land policy was found to have significant and negative effect on technical inefficiency of wheat production (1% significance level). Similarly, participation in soil and water conservation activities was found to have negative and significant effect on technical inefficiency of major crops and wheat production. In this study frequency of extension contact was found to have unexpected and strange result; the more frequently the farmers meet extension workers the more it competes their time to do agricultural activities. The result of this study also confirmed as rich farmers are relatively less inefficient than poor once, in major crops production, and fertile plots of wheat are significantly less inefficient than infertile once. Similarly, flat teff and maize plots are more efficient than otherwise. The other plot specific variable that was found to have negative and significant effect on technical inefficiency of major crop production was adoption of improved seed. The last but not least, variable that explains variation in inefficiency was found to be livestock ownership. Generally, results of this study confirmed that there is a room to enhance productivity by improving the efficiency of production, given same level of input and current technology

LONG RUN DETERMINANTS OF CEREAL PRODUCTION IN ETHIOPIA: DOES CO2 EMISSION MATTER?

The study employed vector error correction model to examine the long run relationship between climate change and cereal production using time series data (1962-2014) in Ethiopia. The cointegrating equation shows that the parameters included in the model are jointly significant at 1% significant level. The study revealed that a 10% percent increase in CO2 emission would have 2.75 % cereal production loss in the country. However, land and fertilizer were found to have positive and significant long-term impact on cereal production in the country. The forecasted cereal production - using contingent equation – shows that cereal production is expected to grow annually by 2.8%, on average, for the next 10 years. As a concluding remark, efforts towards reducing CO2 should be strengthened to further enhance the cereal production growth in the country. Moreover, providing fertilizer for the farmers with a reasonable price on due time is decisive to benefit from intensive agriculture

Performance of Microfinance Institutions in Ethiopia: Integrating Financial and Social Metrics

Since their inception in the 1970s, microfinance institutions (MFIs) have received increasing attention both from policymakers and academic circles. Using unbalanced panel data (2000–2017) from Ethiopia, in this paper, we investigated the performance of MFIs and its determinants on the one hand and whether or not mission drift exists on the other hand. To this end, we employed seemingly unrelated regression (SUR) and fixed/random effect panel models. The results indicate that, based on different outreach and financial performance metrics, the MFIs in Ethiopia have good performance compared with those of the 10 biggest economies in Sub-Saharan Africa (SSA). The econometric estimation results show that asset holding and the yield on gross portfolio have a positive and significant effect on the social and financial performances of MFIs in Ethiopia. Furthermore, the number of loan officers, loan officer productivity, and personnel productivity have a positive and significant impact on the financial performance of MFIs. Our results also suggest that the null hypothesis—that MFIs are not shifting away from poorer clients—cannot be rejected, implying that there is no mission drift by MFIs in Ethiopia

Basis Risk, Social Comparison, Perceptions of Fairness and Demand for Insurance: A Field Experiment in Ethiopia

Index insurance is considered an important strategy to reduce agricultural risk and increase smallholder farmers’ investments. However, insured farmers may develop mistrust of insurance if they experience crop losses and do not receive a payout, for instance because index insurance covers only a subset of covariate risks. At the same time, insurance for idiosyncratic risks would introduce differences in payouts within social networks, which might be considered unfair, introduce jealousy, and further depress demand for insurance. We conduct lab-in-the-field experiments with farmers in Ethiopia to examine the effects of a novel insurance approach that ensures insurance payouts for farmers with crop losses due to idiosyncratic events. We also examine the effects of informing farmers about their neighbors’ experiences alongside their own. We find that such social comparison increases perceived fairness of weather index insurance. In addition, providing complete insurance coverage for crop losses increases farmers’ perceived fairness of outcomes and willingness to pay, without introducing jealousy over neighbors receiving different payouts. Finally, we find that the increase in willingness to pay for complete insurance is concentrated among men and risk averse respondents

A longitudinal investigation of dietary diversity during the COVID-19 pandemic in Mandinka households in Kanifing, Brikama, and the West Kiang region in The Gambia.

Peer reviewed: TrueAcknowledgements: The authors gratefully acknowledge the assistance of the data collection and data management teams at MRC Gambia/London School of Hygiene and Tropical Medicine, The Gambia.The Covid pandemic has exposed fissures of inequality through heightened food insecurity and nutritional deficiency for vulnerable social cohorts with limited coping mechanisms. Given the multi-dimensional pathways through which its effects have been felt, several researchers have highlighted the need to analyse the pandemic in specific contexts. Using random and fixed effect regression models, this study analyzed longitudinal survey data collected from 103 Mandinka households in rural and urban Gambia. The study employed convenience and snowball sampling and involved the monthly collection of detailed income, food consumption, expenditure, sourcing, migration, health, and coping mechanism data through mobile phone interviews which yielded 676 observations. Food insecurity was manifest in terms of quality, not quantity, and spread unevenly across food types and households. Dietary outcomes and sourcing strategies were associated with location, improved sanitation, household size, changes in monthly income, Covid policy stringency, and Covid cases but these associations varied by food group. Staples were the most frequently consumed food group, and dark green vegetables were the least. Rural communities were more likely to eat more healthy millets but much less likely to consume dairy products or roots and tubers. Access to own production was also important for Vitamin A-rich foods but higher incomes and markets were key for protein and heme-iron-rich foods. Tighter Covid policy stringency was negatively associated with dietary diversity and, along with fear of market hoarding, was positively associated with reliance on a range of consumption and production coping mechanisms. Resilience was higher in larger households and those with improved water and sanitation. The number of Covid cases was associated with higher consumption of protein-rich foods and greater reliance on own produced iron-rich foods. Very few households received Government aid and those that did already had access to other income sources. Our findings suggest that the nature of food insecurity may have evolved over time during the pandemic. They also reiterate not only the importance of access to markets and employment but also that the capacity to absorb affordability shocks and maintain food choices through switching between sources for specific nutritious food groups varied by household and location