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This study aims to analyse the consumption inequality between farm and non-farm households in rural Vietnam, using the data from the 2016 Vietnam household living standards survey.

The present paper applies the “recentered influence functions (RIF)” in “Oaxaca-Blinder (OB)” type decomposition as proposed by Firpo et al. (2018) to allow for the flexible distribution of the outcome variables and the non-randomness of non-farm employment that violates the classical linearity assumption.

Non-farm households have significantly higher per capita consumption expenditure than farm households for the entire distribution. The gap in expenditure is large at low percentiles and narrowing with higher percentiles. At 10th percentile, the gap is estimated at 27.1%, but it is decreasing to 11.1% at 90th percentile. Most of the gaps are explained by the differences in the observed characteristics between farm and non-farm households such as ethnicity, education, income, internal transmittances and household composition. Non-farm households are endowed with more productive factors that result in higher per capita consumption expenditure.

Gaps in ethnicity and education are found to be key predictors of the inequality in consumption expenditures between farm and non-farm households, then, government policies that are aimed at increasing access to non-farm employment and education for ethnic minorities and for rural poor households are pathways to improve rural household welfare and hence reduce inequality.

This paper aims to understand the perception of smallholder farmers on climate change, identify major livestock related climate change adaptation (CCA) strategies and their determinants in selected neighboring districts of Tigray and Amhara regions of Ethiopia.

A total of 416 household heads were involved in a questionnaire survey using a multistage sampling approach. To understand the socio-economic factors that influence farmers’ perception on climate change (CC) and/or variability, a binary logit model was used. Multinomial logit model was used to identify the determinants of smallholder farmers’ choices of adaptation strategies.

Milk reduction, weight loss, feed shortage and frequent animal disease outbreak were indicated as major impacts of CC on livestock production. About 86.2% of the farmers’ exercise CCA measures where livestock health care and management (25%), followed by livelihood diversification (21.5%) and shifting and diversification of livestock species (20.9%) were the top three adaptation measures implemented. Education, knowledge on CCA strategies, access to veterinary service and extension, market access, annual income, non-farm income, total livestock unit, sex of household head and household size were the major determinant factors to farmers’ choice of CCA.

Concerned authorities working in CC related sectors should give due attention to improve smallholder farmers’ access to extension and veterinary services, market access and climate information to enhance their adaptive capacity to CC impacts. In addition, incorporating climate change awareness trainings into the existing extension packages is crucial to enhance the awareness of farmers on climate change and implement appropriate adaptation strategies. Moreover, it is very essential to provide appropriate herd management and marketing strategy based on the production system to avoid the significant price reduction during drought periods.

Concerned authorities working in CC related sectors should give due attention to improve smallholder farmers’ access to extension and veterinary services, market access and climate information to enhance their adaptive capacity to CC impacts. In addition, incorporating climate change awareness trainings into the existing extension packages is crucial to implement appropriate adaptation strategies. Moreover, it is very essential to provide appropriate herd management and marketing strategy based on the production system to avoid the significant price reduction during drought periods.

This research is focused on smallholder crop-livestock farmers, livestock-based CCASs and presents the determinant factors to their choice of adaptation.

The authors examined the impact of the Market Facilitation Program (MFP) and Coronavirus Food Assistance Program (CFAP) payments to United States agricultural producers on non-real estate agricultural loans.

The authors used quarterly, state-level commercial bank data from 2016–2020 to estimate dynamic panel models.

The authors found MFP and CFAP payments not associated with the percentage of non-real estate agricultural loans with payments over 90 days late. However, these payments associated with the percentage of non-real estate agricultural loans with payments between 30 and 89 days late. The available data utilized cannot consider when producers received the actual payment and what they specifically did with those funds.

The contribution of this study is for US policymakers and agricultural lenders. The findings could be helpful in designing and implementing future ad hoc payment programs and provide an understanding of potential shortcomings of the current safety net for agricultural producers in the Farm Bill. Additionally, findings can assist agricultural lenders in predicting the impact of ad hoc payments on their distressed loan portfolios.

Background: A range of local social and environmental factors has an impact on farmers' views of climate change and choices on the use of coping mechanisms. This study examines the factors that are limiting farmers' perceptions of climate change and their coping mechanisms in Gimbi district, Western Ethiopia.

Methods: A household survey and focus group discussion were employed to collect relevant data. A total of 402 randomly selected households and six focus group discussions containing 72 participants were used to gather data. Binary logit models were used to analyze the collected data.

Results: Farmers noted that some of the signs of climate change included increasing temperature, erratic rainfall, late onset of rainfall, and early cessation of rainfall. We discovered that there are three distinct sets of climate adaption strategies used by farmers: crop management, soil and water conservation and intensive farm management. The primary determinants of farmers' perceptions of climate change and adaptation techniques were household head age, education, soil fertility, market access, and agricultural training. Age, education, and soil fertility level were the characteristics that significantly impacted farmers' perspectives and coping mechanisms among the primary drivers evaluated in the area. Use of agroforestry, shifting planting dates, and fertilizer application were all essential farming practices used as climate adaptation measures.

Conclusions: Both socioeconomic and environmental factors have found to affect farmers' perceptions of climate change in the area. The existing socioeconomic and environmental factors, in turn, affect their choice of strategies to adapt to climate change. When implementing climate change adaption strategies, it is critical to assess farmers' level of awareness of climate change and their coping strategies, as well as the factors limiting their ability to adapt to climate change.

The purpose of this study results and recommendations will have a paramount significance for policymakers, policy advocates, development planners and practitioners who may be in need of such information for reconsideration, evaluation and inclusion into their respective development and humanitarian programming and operational strategies. Above all, the study result has further provided the local community with viable adaptation strategies to climate-induced changes in the study area.

This study was conducted to measure the livelihood vulnerability of Borana pastoralists to climate change and variability in southern Ethiopia. Pastoralists’ households were sampled using multistage sampling techniques. A total of 27 socio-economic and biophysical indicators were used to reflect vulnerability components: adaptive capacity, exposure and sensitivity. Principal component analysis was used to develop weights for indicators and to produce livelihood vulnerability index to classify households according to their level of vulnerability. Ordinal logistic regression was used to identify the determinants of vulnerability to climate-induced stresses.

The results showed that 24.4% of households were highly vulnerable, 60.3% were moderately vulnerable and 15.3% of households were less vulnerable to climate-induced stresses. Factor estimates of the logistic model further revealed that early warning information, bush encroachment, coping strategy, temperature, drought frequency, provision of humanitarian services and food shortage during the normal season of the year have a significant influence on vulnerability in the study area.

The study’s results and recommendations will be of great significance to policymakers, development planners, and practitioners who require such information for reconsideration, evaluation, and inclusion in their respective development and humanitarian program and operational strategies. Most importantly, the study’s findings have provided the local community with practical adaptation strategies to climate-induced changes in the study area.

The study explored pastoralist perception of climate change and variability and measured the livelihood vulnerability of pastoralists’ households to climate change and variability and finally investigated viable adaptation and coping strategies in the study area.

This study aims to examine the effect of climate variability on smallholders’ crop income and the determinants of indigenous adaptation strategies in three districts (Mieso, Goba-koricha and Doba) of West Hararghe Zone of Ethiopia. These three districts are located in high-moisture-stress areas because of crop season rainfall variability.

Primary data collected from 400 sample households were used for identifying factors that affect households’ crop income. The study used ordinary least square (OLS) regression to examine the effect of climate variability. Given this, binary logit model was used to assess smallholders’ adaptation behavior. Finally, the study used multinomial logistic regression to identify determinants of smallholders’ indigenous adaptation strategies.

The OLS regression result shows that variability in rainfall during the cropping season has a significant and negative effect, and cropland and livestock level have a positive effect on farmers’ crop income. The multinomial logistic regression result reveals that households adopt hybrid crops (maize and sorghum) and dry-sowing adaptation strategies if there is shortage during the cropping season. Variability in rainfall at the time of sowing and the growing are main factors in the area’s crop production. Cropland increment has positive and significant effect on employing each adaptation strategy. The probability of adopting techniques such as water harvesting, hybrid seeds and dry sowing significantly reduces if a household has a large livestock.

The three districts are remote and accessibility is difficult without due support from institutions. Thus, this study was conducted on the basis of the primary data collected by the researchers after securing grant from Swedish International Development Agency (SIDA).

The results of this study have significant policy implications for charting a new course toward enhancing agricultural productivity among Chinese farmers.

By establishing a rural household decision-making model based on the transfer market of farmland operation rights, this paper systematically analyzes the effects of land transfer-in and land transfer-out on the productivity (per labor income) of rural households. The authors conducted basic regression analysis and robustness tests using propensity score-matching and proxy variable approaches based on the micro survey data from rural households in 30 counties in 21 provinces/municipalities/autonomous regions in 2013.

After the completion of land transfer, the total productivity of rural households transferring in lands will increase with an increase in the agricultural productivity; the total productivity of rural households transferring out land will increase due to a rise in non-agricultural productivity and the absolute total productivity of rural households not involved in land transfer will remain unchanged.

Unlike previous literature, this paper discusses the impacts of land transfer-in and transfer-out on total productivity, agricultural productivity and non-agricultural productivity among various rural households (i.e. those transferring in land, transferring out land or which are self-sufficient).

Despite the potential for co-operatives to improve smallholder farmers' livelihoods, membership in the co-operatives is low. This study examines factors that influence smallholder farmers' decisions to join agricultural co-operatives.

This study involved a survey of 1,274 smallholder chicken farmers. The data were analysed through a two-sample t-test of association, Pearson's Chi-square test and binary probit regression model.

The results suggest that farming as the main source of income, owning a chicken house, education attainment, attending training or accessing information, vaccination of goats and keeping a larger herd of goats are the key factors which significantly influence co-operative membership. However, gender, age, household size, distance to the nearest agrovet, vaccinating chicken and the number of chickens kept do not influence co-operative membership.

The survey did not capture data on some variables which have been shown to influence co-operative membership. Nevertheless, the results show key explanatory variables which influence membership in co-operatives.

These findings have implications for development agencies that seek to use co-operatives for agricultural development and improvement of smallholder farmers' livelihoods. The agencies can use the results to initiate interventions relevant for different types of smallholder farmers through co-operatives.

This study highlights the influence of smallholder farmers' financial investments in farming and the extent of commercialisation on co-operative membership. Due to low membership in co-operatives, recognising the heterogeneity of smallholder farmers is the key in agricultural development interventions through co-operative membership.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2022-0165.

In recent years, climate-smart agriculture (CSA) was introduced to Vietnam to enhance farmers’ resilience and adaptation to climate change. Among the climate-smart agricultural technologies (CSATs) introduced were water-saving techniques and improved stress tolerant varieties. This study aims to examine the determinants of farmers’ adoption of these technologies and the effects of their adoption on net rice income (NRI) in three provinces as follows: Thai Binh (North), Ha Tinh (Central) and Bac Lieu (South).

Determinants of adoption of CSATs and the adoption effects on NRI are analyzed by using a multinomial endogenous switching regression framework.

The results showed that gender, age, number of family workers, climate-related factors, farm characteristics, distance to markets, access to climate information, confidence on the know-how of extension workers, membership in social/agricultural groups and attitude toward risk were the major factors affecting the decision to adopt CSATs. However, the effects of these factors on the adoption of CSATs varied across three provinces. These technologies when adopted tend to increase NRI but the increase is much greater when these are combined.

It is important to consider first the appropriateness of the CSA packages to the specific conditions of the target areas before they are promoted. It is also necessary to enhance the technical capacity of local extension workers and provide farmers more training on CSATs.

This study is the first attempt to identify key determinants of adoption of CSATs either singly or in combination and the adoption effects on NRI in Vietnam.

The much-trumpeted Green Climate Fund and several other official financial mechanisms for financing adaptation to climate change under the UN Framework Convention on Climate Change have fallen short in meeting adaptation needs. Many poorer people are still grappling with the scourge of climate change impacts. Consequently, there has been a dominant research focus on climate change financing emanating from official development assistance (ODA), Adaptation Fund, public expenditure and private sector support. However, there has been little attempt to examine how migrants’ remittances can close adaptation financing gaps at the local level, ostensibly creating a large research gap. This paper aims to argue that migrants’ remittances provide a unique complementary opportunity for financing adaptation and have a wider impact on those who are extremely vulnerable to climate change.

The paper is aligned to the qualitative research approach. Both secondary and primary data acquired through interviews and focus group discussions were used for the study. Multiple sampling methods were also used to select the respondents.

The findings show that remittances are used to finance both incremental costs of households’ infrastructure and consumption needs, as well as additional investment needs to be occasioned by ongoing or expected changes in climate.

In the wake of dwindling government/public revenue, ODA and poor commitment of Annex II countries to fulfil their financial obligations, the study makes the following recommendations: First, the financial infrastructure underpinning money transfers in both sending and recipient countries should be improved to make transfers attractive. Second, significant steps should be taken to reduce the fees on remittance services, especially for the small transfers typically made by poor migrants. Finally, adequate climatic information should be made available to local people to ensure that remittances are applied to the right adaptation option to avoid maladaptation.