scholarly journals Does credit utilization lead to increasing farm outcome? a micro-perspective of tea production from Rwanda

Agro-Science ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 92-100
Author(s):  
A. Kabayiza ◽  
G. Owuor ◽  
K.J. Langat ◽  
P. Mugenzi ◽  
F. Niyitanga
Keyword(s):  
Raw Materials ◽  
Causal Effect ◽  
Agricultural Practices ◽  
Potential Effect ◽  
Farm Income ◽  
Switching Regression ◽  
Endogenous Switching Regression ◽  
Endogenous Switching ◽  
Tea Production ◽  
Farm Inputs

Credit is a crucial factor for tea growers to pay for physical farm inputs mainly input fertilizers, research and development of high yielding tea clones and labour in order to improve the production of green tea leaf and to meet factories’ demand for raw materials. However, mismanagement of accessed credits by farmers has been reported among the snags affecting the sector development. The study analyzed the determinants and impact of credit utilization on farm income among smallholder tea growers in Nyaruguru District, Rwanda. Crosssectional tea household level data were collected from 358 farmers randomly selected from tea cooperatives. The credit utilization and causal effect were estimated using the Endogenous Switching Regression model. Results showed a positive and significant relationship between credit utilization and tea farm income. Precisely, the causal effect of credit is a 7% increase in tea income for farmers who utilised credit for tea production, while its potential effect is up to a 55% decrease in tea income for those who divert credit for out-off tea production uses. Furthermore, training on good agricultural practices and credit management, cost of farm inputs, labour and access to group credit significantly influence utilization of credit for tea production. However, the size of credit (cash) and off-farm businesses significantly increase the diversion of credit and level of tea farm income. Tea farmers are encouraged to use tea credits for planned projects. Sensitizing farmers to procure farm input fertilizers in bulk through cooperatives should be vigorously pursued to discourage credit diversion. Key words: tea credits, tea farming households, farm income, endogenous switching regression

Distance Traveled in Times of Pandemic: An Endogenous Switching Regression Approach

2021 ◽  
pp. 135481662110594
Author(s):  
David Boto-García ◽  
Veronica Leoni
Keyword(s):  
Potential Change ◽  
Behavioral Adaptation ◽  
Selection Effects ◽  
Switching Regression ◽  
Population Composition ◽  
Endogenous Switching Regression ◽  
Endogenous Switching ◽  
Regression Approach

This paper studies the change in the distance traveled by domestic tourists considering the pre- and post-pandemic outbreak summer periods of 2019 and 2020. Using representative monthly microdata involving more than 31,000 trips conducted by Spanish residents, we examine the heterogeneity in behavioral adaptation to COVID-19 based on sociodemographic and trip-related characteristics. To account for selection effects and the potential change in the population composition of travelers between the two periods, we estimate an endogenous switching regression that conducts separate regressions for the pre- and post-pandemic periods in a unified econometric framework. Our results point to heterogeneous shifts in the distance traveled by domestic travelers after COVID-19 outbreak per sociodemographic group, with notable differences by travel purpose and lower relevance of traditional determinants like income.

scholarly journals Poverty Reduction Effect of New-Type Agricultural Cooperatives: An Empirical Analysis Using Propensity Score Matching and Endogenous Switching Regression Models

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zhineng Hu ◽  
Qiong Feng ◽  
Jing Ma ◽  
Shuangyi Zheng
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Agricultural Cooperatives ◽  
Switching Regression ◽  
Cross Sectional ◽  
Endogenous Switching Regression ◽  
Endogenous Switching ◽  
Poor Households ◽  
Esr Model ◽  
New Type

Agricultural cooperatives have been found to effectively alleviate poverty in developing countries because of their specific socioeconomic functions that allow poor households to overcome marketing and production constraints. However, cooperative evaluations are inevitably influenced by other poverty alleviation measures and rarely consider the characteristics of specific ethnic groups. Using cross-sectional surveys in Southwest China and employing propensity score matching (PSM) and endogenous switching regression (ESR) models, this paper analyzed the participation of poor households in New-type Agricultural Cooperatives (NACs) in ethnic areas and assessed the income impacts of NAC membership by eliminating unobserved biases and group heterogeneity. This study detected heterogeneous policy perceptions and behavioral differences between the member and nonmember groups, and the PSM and ESR model results indicated that, overall, participation in the NACs had a positive effect on household income. The ESR model was found to be more plausible as it was able to reveal the significant income gaps under a counterfactual inference framework. Local policymakers need to focus on the policy perception and behavioral and earning capability differences between groups and increase the balanced policy implementation.

scholarly journals Farmers’ Exposure to Climate Hazards and Reforestation in Selected African Villages: An Endogenous-Switching Regression Model

2019 ◽  
Author(s):  
Tolulope Olayemi Oyekale ◽  
Abayomi Oyekale
Keyword(s):  
Burkina Faso ◽  
Treatment Effect ◽  
Smallholder Farmers ◽  
Average Treatment Effect ◽  
Tree Planting ◽  
Switching Regression ◽  
Endogenous Switching Regression ◽  
Hazard Exposure ◽  
Endogenous Switching ◽  
Household Headship

Abstract Background: Deforestation remains a serious concern for Africa’s economic development and global climatic stability. Emphases are now placed on promoting some essential adaptive and mitigation strategies among smallholder farmers. This paper analyzed the effect of exposure to climate-related hazards on tree planting among smallholder farmers in nine selected African countries. The data were from baseline surveys which were conducted by the CGIAR’s research programme on Climate Change, Agriculture and Food Security (CCAFS). The included countries were Burkina Faso, Ethiopia, Ghana, Kenya, Mali, Niger, Senegal, Tanzania and Uganda. Data were analyzed with Endogenous Switching regression considering the endogeneity potentials of climate-hazard exposure. Results: The results showed that Uganda and Ethiopia had the highest average numbers of tree planting with 1.082 and 1.000 respectively, while Senegal (89.86%), Kenya (87.77%), Burkina Faso (82.86%) and Ethiopia (82.86%) had the highest exposure to climate-related hazards. Endogenous Switching regression results showed that climate hazard exposure was truly endogenous going by statistical significance of the Wald Chi Square test (p<0.05) and it was significantly influenced by female household headship, perception of more droughts, floods and low ground water. The number of tree that were planted increased significantly (p<0.05) with climate hazard exposure, degraded land areas, asset indices and residence in East Africa, while it reduced with female household headship. In addition, Average Treatment Effect (ATE) result indicated that an average household will plant 0.745 trees more when it had been previously exposed to climate shocks while Average Treatment Effect on the Treated (ATET) revealed that an average household that was exposed to climate hazards would plant 0.54 more trees than it would if it had not been exposed to hazards. Conclusion: The major implication of the findings is that without having previously experienced some climatic adversities, farmers may not see the need to engage in tree planting as a mitigating strategy. It was concluded that many farmers had been affected by climate-related shocks and efforts to safeguard future climate through tree planting should be gender sensitive and concentrated among previously affected farmers.

scholarly journals Impact of contract farming on rice farm performance: Endogenous switching regression

2019 ◽  
Vol 7 (1) ◽  
pp. 1618229 ◽  
Author(s):  
John Kanburi Bidzakin ◽  
Simon C. Fialor ◽  
Dadson Awunyo-Vitor ◽  
Iddrisu Yahaya ◽  
Goodness Aye
Keyword(s):  
Switching Regression ◽  
Contract Farming ◽  
Endogenous Switching Regression ◽  
Endogenous Switching ◽  
Farm Performance

Cotton Yield and Climate Change Adaptation in Pakistan: Application of Multinomial Endogenous Switching Regression Model

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Muhammad Masood Anwar ◽  
Aisha Siddiqua ◽  
Aftab Anwar ◽  
Jamshaid Ur Rehman
Keyword(s):  
Climate Change ◽  
Regression Model ◽  
Management Practices ◽  
Household Survey ◽  
Switching Regression ◽  
Cotton Yield ◽  
Sources Of Information ◽  
Cotton Production ◽  
Endogenous Switching Regression ◽  
Endogenous Switching

Purpose:Cotton is the backbone of Pakistan economy, as country is the 4th largest producer of cotton in the world. Despite this importance there is steep decline in cotton production over time due to climate change. The need to evaluate the potential of adaptation in improving cotton yield has necessitated this study. Design/Methodology/Approach:This study is based on the farm household survey of four cotton producing districts, two from each Punjab and Sindh that were purposively selected from heat stress regions of Pakistan. Data were analyzed through multinomial endogenous switching regression model and treatment effect framework. Findings:Farm management practices were evaluated for their significance in reducing adverse impacts of climatic extremes on cotton yield. Adaptation in the combination of first three strategies observed to be the most successful strategies in increasing yield. Implications/Originality/Value:For effective adaptation access to credit and extension, education, farming experience, and sources of information revealed to be important predictors

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