Purpose: The purpose of this paper is to investigate how credit access affects the welfare of households and sheds light on how household characteristics influence the decision to take credit and the efficiency in credit use.Design/methodology/approach: This study uses data from the fourth round of the Ethiopian Rural Household Survey conducted in 2009, and examines factors that determine the decision to take credit and the effect of such decision on household welfare. The household welfare variable is measured by the food security indicator and total food expenditure. The study employs endogenous Regime Switching model to account for endogeneity in access to credit and self-selection bias in the decision to participate in credit.Findings: The result from the kernel distribution shows households with access to credit have more consumption expenditure than those without access to credit. The ordinary least square regression shows that access to credit increases total consumption by 12 percent without considering self-selection bias. Participation in non-farm activity increases the demand for credit by 17 percent. Land holding, household size, and participation in saving associations increase the probability of getting credit by 5, 11, and 20 percent, respectively. Access to credit appears to have a positive impact on food security in both actual and counterfactual cases for the current credit receivers.Originality/value: This study provides a thorough analysis of the impacts of access to credit on household welfare in Ethiopia. The study contributes to the debate on the link between access to credit and household welfare and provides valuable input for policy makers.

(1) Background: Even though agriculture is the backbone of the Ethiopian economy, the improvements made regarding crop productivity appeared insufficient and had slow progress. Several studies suggest possible ways to identify the challenges in the productivity of the crop sub-sector. Nevertheless, there are gaps in the empirical literature in both knowledge and methods. The current study intends to identify the factors that affect growth in the productivity of teff, maize, barley, wheat, and sorghum crops. (2) Methods: Cobb-Douglass stochastic production function is estimated using a panel data set of the Living Standard Measurement Survey. To address the objectives of the study, a parametric estimation with a time-varying decay model with deterministic and stochastic components was adopted. (3) Results and Discussion: The effect of inputs on aggregate output was positive and significant at the 1% significance level, implying the presence of economies of scale. Variation in the inefficiency term explained 46.4% of the total variance in the composed error term. The average productivity of major crops was 6.19 per year. This study implied that technical change in the production of major crops increased by 22% with better use of available technology. (4) Conclusions and Policy Implication: The findings pinpoint that farmers should focus on technical change and intensification of improved agricultural inputs.

In this study the technical efficiency of crop-producing households and the factors that influence it are explored, and comparisons are made using rural–urban migration as a comparative measure, in Gurage Zone, Ethiopia. The data were collected from 384 arbitrary picked rural households and analyzed using a stochastic frontier approach. Non-migrant households, migrant-sending households, and total samples had mean technical efficiency of 45.5%, 72.3%, and 57.4%, respectively, according to the findings. The household head’s age and distance from a neighboring town have a downbeat impact on technical inefficiency, whereas schooling, soil infertility, migratory experience, and distance to a nearby market have an upbeat upshot. With the diversified and specific solutions provided, the study is recommended the government body to focus on making the best use of available agricultural inputs, boosting soil fertility, and regulating the sources of technological inefficiency.

Previous studies investigated the effects of seed rates and seed recycling practices on the yield and yield-related variables. However, higher yield does not always guarantee cost-efficiency. This study aimed to investigate the yield effects of plot-level seed rate and the cost–benefit analysis of seed recycling practices. This study has introduced the dose–response model to the existing analytical methods used in analyzing the effect of different agrochemicals on crop yield. A multi-stage stratified sampling technique was used to select a total of 450 sample respondents. Data were gathered using a mix of data collection tools. Descriptive statistics along with the dose–response model were applied for data analysis. Farmers of the study were found to be dissimilar in terms of their seed rate application. A dose–response analysis indicated that the highest average wheat yield was associated with a seed rate of 50 kg ha⁻¹ above what is recommended. The yield effect of seed recycling was also assessed, and a one-time seed recycling has caused a yield decline of 665 kg ha⁻¹ compared to the non-recycled seeds. The cost reduced using recycled seed is by far lower than the economic gains associated with using unrecycled and fresh seeds. The cost–benefit analysis made clear that farmers can reduce their seed costs through seed recycling, but their yields and net income can be best improved by using unrecycled certified bread wheat seed (CBWS). Thus, farmers must be encouraged to use unrecycled seed by establishing agricultural credit schemes geared towards seed procurement and seed price subsidy as key strategies to reduce economically wasteful seed recycling practices.

Previous studies investigated the effects of seed rates and seed recycling practices on the yield and yield related variables. However, higher yield does not always guarantee cost-efficiency. This study aimed at investigating the yield effects of plot-level seed rate along with the cost-benefit analysis of seed recycling practices. This study has introduced the dose-response model to the existing analytical methods used in analyzing the effect of different agrochemicals on crop yield. A multi-stage stratified sampling technique was used to select a total of 450 sample respondents. Data was gathered using a mix of data collection tools. Descriptive statistics along with the dose-response model have been applied for data analysis. Farmers of the study were found to be dissimilar in terms of their seed rate application. The dose-response analysis indicated that the highest average wheat yield has been associated with a seed rate of 50 kg ha-1 above what is recommended. The yield effect of seed recycling has also been assessed and a one-time seed recycling has caused a yield decline of 665 kg ha-1 as compared to the non-recycled seeds. The cost reduced by using recycled seed is by far lower than the economic gains associated with using unrecycled and fresh seeds. The cost-benefit analysis made clear that farmers can reduce their seed costs through seed recycling but their yields and net income can be best improved by using unrecycled CBWS. Thus, farmers must be encouraged to make use of unrecycled seed by establishing agricultural credit schemes geared towards seed procurement and seed price subsidy as key strategies to reduce economically wasteful seed recycling practices.