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AbstractMultivariate probit models have been popularly utilized to analysis multivariate ordinal data. However, the identifiable multivariate probit models entail the covariance matrix for the underlying multivariate normal variables to be a correlation matrix, which brings a rigorous task to conduct efficient statistical analysis. Parameter expansion to make the identifiable model to be non-identifiable has been inevitably explored. However, the effect of the expanded parameters on the convergence of Markov chain Monte Carlo (MCMC) is seldomly investigated; in addition, the comparison of MCMC developed based on the identifiable model and that based on the non-identifiable model is hardly ever explored, especially for data with large sample sizes. In this paper, we conduct a thorough investigation to illustrate the effect of the expanded parameters on the convergence of MCMC and compare the behavior of MCMC between the identifiable and non-identifiable models. Our investigation provides a practical guide regarding the construction of non-identifiable models and development of corresponding MCMC sampling methods. We conduct our investigation using simulation studies and present an application using data from the Russia Longitudinal Monitoring Survey-Higher School of Economics (RLMS-HSE) study. [ABSTRACT FROM AUTHOR]

Integration of climate information in farm-level adaptation decision is crucial to manage climate change induced risks. The Government of Kenya is mandated to manage and disseminate climate information to enhance adaptation to climate change. However, the use of climate information on farm-level adaptation has not been explored. The purpose of this study was to: identify the climate information accessed by farmers, establish the association between using climate information and the adaptation strategies adopted, examine the factors influencing adaptation decisions, find out how climate information were used and the benefits and constraints of using the information. Data was collected from 432 households randomly selected from semi-arid areas in Machakos, Makueni and Kitui counties. The Multivariate probit model was used to analyse data. The results showed that farmers accessed short and medium-term forecasts; decadal forecasts and agrometeorological advisories. There was a significant association between using climate information and the climate change adaptation strategies adopted by the farmers. Demographic, socio-economic and institutional factors significantly influenced farmers' adaptation decisions. Farmers used the climate information for tactical, short-term farm operations. Benefits of using climate information were manifested in reduced crop loss, increased yield and farm revenue. However, farmers' use of climate information was constraint by economic and technical factors. The study recommends that the Government enforces policies that empowers farmers to access the requisite farm inputs and facilitate the provision of agrometeorological advisories to increase local-level utility of climate information. The Government should formulate and implement policies that strengthen the provision of timely, simplified and adequately actionable climate information that suit farmers' climate change adaptation needs. [ABSTRACT FROM AUTHOR]

Summary: Multivariate longitudinal ordinal and continuous data exist in many scientific fields. However, it is a rigorous task to jointly analyse them due to the complicated correlated structures of those mixed data and the lack of a multivariate distribution. The multivariate probit model, assuming there is a multivariate normal latent variable for each multivariate ordinal data, becomes a natural modeling choice for longitudinal ordinal data especially for jointly analysing with longitudinal continuous data. However, the identifiable multivariate probit model requires the variances of the latent normal variables to be fixed at 1, thus the joint covariance matrix of the latent variables and the continuous multivariate normal variables is restricted at some of the diagonal elements. This constrains to develop both the classical and Bayesian methods to analyse mixed ordinal and continuous data. In this investigation, we proposed three Markov chain Monte Carlo (MCMC) methods: Metropolis–Hastings within Gibbs algorithm based on the identifiable model, and a Gibbs sampling algorithm and parameter‐expanded data augmentation based on the constructed non‐identifiable model. Through simulation studies and a real data application, we illustrated the performance of these three methods and provided an observation of using non‐identifiable model to develop MCMC sampling methods. [ABSTRACT FROM AUTHOR]

The response envelope model proposed by Cook et al. (2010) is an efficient method to estimate the regression coefficient under the context of the multivariate linear regression model. It improves estimation efficiency by identifying material and immaterial parts of responses and removing the immaterial variation. The response envelope model has been investigated only for continuous response variables. In this paper, we propose the multivariate probit model with latent envelope, in short, the probit envelope model, as a response envelope model for multivariate binary response variables. The probit envelope model takes into account relations between Gaussian latent variables of the multivariate probit model by using the idea of the response envelope model. We address the identifiability of the probit envelope model by employing the essential identifiability concept and suggest a Bayesian method for the parameter estimation. We illustrate the probit envelope model via simulation studies and real-data analysis. The simulation studies show that the probit envelope model has the potential to gain efficiency in estimation compared to the multivariate probit model. The real data analysis shows that the probit envelope model is useful for multi-label classification. [ABSTRACT FROM AUTHOR]

The relationship between entrepreneur's gender and business performance has been studied in existing literature assuming that it is a straight-forward direct relationship. Instead, in this study we examine how gender affects business performance through the introduction of innovations. Our aim is to explore the differences between men-led and women-led businesses as regards the performance results they obtain from innovating. We use a sample of 1376 Spanish small and medium enterprises (SMEs) to analyse the effect of entrepreneur's gender on business performance considering the mediating effect of innovations, that is, the possibility that gender indirectly influences business performance by affecting the introduction of innovations. Using econometric techniques, we estimate discrete choice models to investigate the relationship amongst gender, innovations and performance. Our main results show that men-led SMEs are more likely to achieve superior performance from innovations, and particularly, from their higher propensity to implement process innovations, in comparison to women-led SMEs. One limitation of our study is that data is cross-sectional, so that caution is needed regarding the causal interpretation of results. We contribute to uncover the role of gender on SMEs performance and the need to incorporate a policy gender perspective when dealing with enhancing SMEs innovativeness and performance. [ABSTRACT FROM AUTHOR]

This study explores the role of diverse climatic vulnerabilities and socio- economic variables in explaining Bangladeshi rural households' livelihood choices and the synergies that exist across the choices. We develop a multivariate probit model for analysing a dataset of 5,604 households that is representative of rural Bangladesh. The findings reveal a landscape where agriculture-based strategies predominate, with households strategically combining various approaches. Households complement agriculture-based strategies, while substituting beyond agriculture-based strategies. Climate stressors such as flood, salinity, river erosion, drought, storms and cyclones induce notable shifts in livelihood choices. Among these, the most prominent is the substantial influence of storm and cyclone vulnerability. Migration is more prevalent in areas susceptible to salinity, storms and cyclones, while casual labour prevails in drought-prone and flood-vulnerable regions. Households residing in the economically marginalized and environmentally vulnerable feed-the-future (FtF) zone make distinct decisions regarding income strategies compared to their counterparts in other rural areas across the country. Households in this zone exhibit a higher likelihood of opting for specific agriculture-based income sources and casual labour, while self-employment, migration and salaried jobs are less favoured. Furthermore, we elucidate the pivotal role of infrastructure, information access and institutional factors in shaping income sources. Households in different divisions make distinct livelihood choices, especially in agriculture. Ultimately, the findings advocate for precise interventions tailored to climate vulnerabilities. This includes enhancements in road connectivity, the utilization of mobile banking and the provision of extension services, with a specific focus on geographically marginalized and climate-vulnerable regions. [ABSTRACT FROM AUTHOR]

This document provides a concise summary of various articles related to energy-saving practices and household energy consumption in Ecuador. The articles explore factors such as gender, education, income, and internet access that influence energy-saving behaviors in households. They also highlight regional disparities in energy-saving practices and recommend strategies such as education initiatives, improved internet access, and citizen participation in social organizations to promote energy conservation. The document emphasizes the need for caution in interpreting the findings and suggests further research on the interrelation between different energy-saving practices and comparisons between different locations. Additionally, it includes a list of references and further reading on related topics. [Extracted from the article]

Based on the field survey data for 1216 apple growers in three provinces from China's Loess Plateau Region, this paper adopted Multivariate Probit (MVP) model and intermediary effect model to analyze the influence mechanisms of digital technology adoption (DTA) on farmers' choices of Fertilizer-reduction and Efficiency-improving Technologies (FETs) from the perspective of farmers' cognition (FC). The correlation effects of three typical FETs of soil testing and formula fertilization, integrated water-fertilizer fertilization and slow/controlled release fertilizer, were tested empirically. The results showed that DTA could significantly affect the adoption of FETs by apple growers, and FC played a partial mediating role, and there were complementary effects among the three typical FETs. The results were further confirmed by the propensity score matching (PSM) robustness test and the instrumental variable (IV) endogeneity test conducted in the conditional mixed-process (CMP). The results of our heterogeneity analysis showed that the promotion effect of DTA on FETs in the group with junior high school education or below was more significant than that in the group with higher education, and the promotion effect was more significant in the group with large operation scale. Therefore, the improvement in Internet penetration should not be taken as the ultimate goal, but more attention should be paid to farmers' mastery and effective use of DTA, promote the improvement in farmers' cognitive level, and implement the "bundled" publicity and guidance strategy of FETs adoption, so as to help in the green transformation of agriculture. [ABSTRACT FROM AUTHOR]

Climate change presents significant challenges to agriculture in developing nations, affecting farmers' livelihoods and food security. In Ethiopia, agriculture is crucial to the economy and the well-being of millions. This study focuses on analyzing the determinants that affect smallholder farmers' adoption of climate-smart agriculture (CSA) technologies in the North Wello administrative zone, northern Ethiopia. Through multivariate and ordered probit econometric models, data from 411 rural household heads were analyzed. Results reveal the synergy among climate-smart agricultural practices in rainfed farming systems, essential for crafting a comprehensive CSA package within an agroecological framework. The multivariate probit estimation results show that education, membership in local organizations, farm size, tropical livestock unit (TLU), irrigated land ownership, plot number, steep slope, farmland distance to home, and access to a local media source are positive determinants for the decision to use the type and several climate-smart agricultural practices. Lack of credit, large family size, distance from extension services, and proximity to the nearest market were all associated with lower adoption of all CSA technologies. The findings suggest that blanket recommendations for climate-smart agricultural technologies for smallholder farmers can be avoided. The complementarities that exist between CSA technologies may require further investigation into how such complementarities have benefits in terms of improving land productivity and food security and reducing climate-related risks for smallholder farmers in Ethiopia and other contexts. Moreover, by emphasizing an agroecological framework, the study promotes environmentally sustainable and socially equitable agricultural practices that are economically viable, contributing to broader environmental sustainability and development goals. [ABSTRACT FROM AUTHOR]

This study examines the governance structures selected by pineapple farmers in the agroforestry system of Bangladesh and the determinants that impact their choices for these structures. To evaluate the factors influencing farmers' decisions to participate in spot markets, bilateral agreements, or association transactions, the study utilizes both quantitative and qualitative approaches, including surveys of 200 farmers, 15 focus group discussions (FGDs), and 2 key informant interviews (KIIs). In order to choose individual participants, the study employed a stratified random sampling technique. Utilising a multivariate probit (MVP) model, the study reveals crucial factors like age, education, farming experience, farm size, market certainty, weather influence, market connection, and pre-delivery conditions. Analysis indicates that spot market is the most favored governance structure (GS) among the three options in the agroforestry system, followed by bilateral transactions and association agreements. Evidence suggests that younger and less educated farmers tend to favor associations, whereas more experienced farmers tend to favor bilateral partnerships. Farms of bigger size typically refrain from joining groups, and unfavorable weather circumstances decrease the probability of engaging in spot markets. The study also demonstrates that robust market links exert an impact on the selection of governance frameworks. Considering the results, the study suggests enhancing training programs to facilitate farmers' understanding and involvement in associations, motivating farmer associations to appeal to larger farms and small farmers, and enhancing market information systems to establish robust market connections.

Agroforestry is a land-use system integrating trees, crops, and sometimes livestock, offering a promising solution for both environment and agricultural resilience. The primary objectives of the study were to examine the determinants of market choice and quantity of market supply of pineapple in the agroforestry system in the Sal-forest under Tangail district in Bangladesh. Data were collected by using stratified randomly selected 200 pineapple farmers of Madhupur sub-district in Bangladesh and conducted 15 Focus Group Discussions (FGDs) and 2 In-depth Interviews (IDIs). The study employed a multivariate probit model and multivariate linear regression. The pineapple farmers simultaneously selected 3 markets to maximize their profit: local market, district market and central market. Small and medium farmers are more likely to sell their products in local markets, and large farms are more likely to sell products in central and district markets. Multivariate probit regression analysis showed that training, farm size, and farmer ambition negatively influence local market selection by farmers. Ethnicity, training, experience, farm size, and knowledge of quality requirements had a positive influence on district market selection. Investment in production and uncertainty in buyers’ stability had a negative influence on central market selection. Multivariate linear regression analysis indicated that the age of respondents, total production, and association involvement positively impacted quantity of supply in the local market. Training, total production, and farmers’ ambition positively impacted district market supply. Farm size and average price of the pineapple positively impacted the quantity supply in the central market. The district and central markets offered better returns although several obstacles limited pineapple producers’ access to these markets. The uncertainty of buyers in accessing the central market (more profitable markets) needs to be addressed by stakeholders to encourage more agroforestry pineapple-based producers to select the right markets.

Abstract Selecting appropriate market outlets offer the opportunity for farmers to capture a bigger share of the price paid by final consumers. However, smallholder farmers in developing countries are still confronted with myriad challenges regarding selecting profitable market outlets. Thus, the main objective of this study was to analyze determinants of market outlet choices by smallholder mango farmers in Aleta Chuko District, Sidama Region, Ethiopia. The study's representative 391 sample mango producers were selected using a multi-stage sample selection technique and a cross-sectional research approach. Descriptive statistics and the multivariate probit model were used to analyze the data. The result of the study showed that the probability of mango producers to choose consumer, collector, and retailer and wholesaler market outlets was 38%, 39.4%, 41% and 25%, respectively. This shows that retailer was the most likely chosen market outlet while wholesaler was the less likely chosen market outlet. The joint probability of farmers to choose the four market outlets is (0.042%) lower than the likely of not choosing four market outlets (23.21%). The result of the multivariate probit model showed that the sex of the household head, age of the household head, educational level of the household head, the quantity of mangoes produced, size of the land allocated for mango production, use of market information, credit access, livestock holdings, and distance to the nearest market were all statistically and significantly influencing factors in the market outlet choice behavior of mango producers. Based on the results of this study, the government and other concerned organizations should take action to improve the efficient marketing of mango producers in all outlets by providing market information, expanding and following up on extension services, increasing credit access, and building roads and other marketing infrastructure in the study area.

Land use/land cover (LULC) changes driven by human activities are major environmental challenges in many developing regions. This study assessed local community perceptions and household-level drivers of LULC change in northwest Ethiopia. The study combined remote sensing analysis of LULC change with household surveys to understand local perspectives and the socioeconomic, biophysical, and institutional factors influencing household engagement in deforestation activities. The household survey data was collected from 384 randomly selected household heads, as well as from focus group discussions and key informant participants. The remote sensing component used ERDAS IMAGINE 2014 software to classify satellite images and assess LULC changes over time. The quantitative socio-economic data was analyzed using descriptive statistics and econometric methods of the multivariate probit (MVP) model. The study revealed that population growth, poverty, and food insecurity were the major proximate driving factors, while agricultural land expansion, settlement growth, fuelwood collection, overgrazing, and forest fires were the major underlying causes of LULC change. The MVP model result indicated that gender, off-farm income, access to training, family size, educational level, and agroecology were key determinants of households’ involvement in deforestation drivers such as forestland clearing for agriculture, fuelwood collection, timber harvesting, and overgrazing. These findings highlight the need for integrated land use policies and programs that address the socioeconomic and biophysical root causes of LULC change. This study recommends supporting alternative livelihoods, promoting fuel-efficient technologies, and tailoring interventions to different agroecological contexts of sustainable land use planning and natural resource management in the study site. Future studies should compare perceptions and drivers of land use change across different regions to identify common patterns and unique challenges. This approach will enhance understanding and inform targeted interventions for sustainable land management.

The paper attempts to examine the factors that influence climate-smart adaptation (CSA) strategies. The study used binary logit and multivariate probit models to understand the dynamics and factors of agricultural households' behavioural decisions on CSA strategies. Based on the results of the binary logit model, the study indicated that factors such as access to extension services and training, gender, educational level, land ownership, access to irrigation, access to credit and crop damage level positively and significantly influenced farmers' decisions to use CSA strategies. Similarly, the results of the multivariate probit model reveal that factors such as educational level, access to extension services and training, and land ownership had significant impacts on the adoption of the majority of CSA strategies. To improve the intensity of CSA strategies, the study recommends expanding training and extension services to farming masses, the expansion of irrigation facilities and weather information at the farm level. [ABSTRACT FROM AUTHOR]

Selecting appropriate market outlets offer the opportunity for farmers to capture a bigger share of the price paid by final consumers. However, smallholder farmers in developing countries are still confronted with myriad challenges regarding selecting profitable market outlets. Thus, the main objective of this study was to analyze determinants of market outlet choices by smallholder mango farmers in Aleta Chuko District, Sidama Region, Ethiopia. The study's representative 391 sample mango producers were selected using a multi-stage sample selection technique and a cross-sectional research approach. Descriptive statistics and the multivariate probit model were used to analyze the data. The result of the study showed that the probability of mango producers to choose consumer, collector, and retailer and wholesaler market outlets was 38%, 39.4%, 41% and 25%, respectively. This shows that retailer was the most likely chosen market outlet while wholesaler was the less likely chosen market outlet. The joint probability of farmers to choose the four market outlets is (0.042%) lower than the likely of not choosing four market outlets (23.21%). The result of the multivariate probit model showed that the sex of the household head, age of the household head, educational level of the household head, the quantity of mangoes produced, size of the land allocated for mango production, use of market information, credit access, livestock holdings, and distance to the nearest market were all statistically and significantly influencing factors in the market outlet choice behavior of mango producers. Based on the results of this study, the government and other concerned organizations should take action to improve the efficient marketing of mango producers in all outlets by providing market information, expanding and following up on extension services, increasing credit access, and building roads and other marketing infrastructure in the study area. [ABSTRACT FROM AUTHOR]

Bangladesh experienced widespread wheat blast infections for the first time in 2016. The outbreak of the disease has significantly affected wheat acreage and production. This study uses an 'action theory' framework to identify the determinants that affected wheat growers to adopt certain production practices to deal with the situation. We followed a multistage sampling procedure and interviewed 150 wheat growers from two severely blast-affected districts, Meherpur and Kustia. According to 91.3% of farmers, the most remarkable adoption strategies were 'improved intercultural practices,' 'shifting variety,' 'shifting crops', and 'undertaking off-farm activities,' of which farmers mostly followed the former. We also used multivariate probit model analysis to identify factors that shape farmers' adaptation choices in wheat blast-affected areas. The adaptation strategies are influenced mainly by farmers' education, primary occupation, family size, government incentives, extension services, access to Information and Communications Technology (ICT), and annual income. According to the notable similarities between the four adoption strategies, an adoption study should consider all potential factors influencing farmers' adoption decisions. Policy implications include strengthening extension services, developing tailored adaptation strategies, and conducting relevant research. [ABSTRACT FROM AUTHOR]

In addition to scrutinizing the decision process behind energy efficiency investment, this study investigates its association with energy-saving behavior. Its conceptual underpinnings are based on the intersection of behavioral change and "energy efficiency paradox" theories. Based upon a rich, disaggregated dataset representative of the French housing sector, it develops an energy-saving score based on the item response theory model, which considers household attributes and ability levels. Then this score is used as an independent factor of a multivariate probit model to examine the drivers of household investment decisions for various energy performance solutions. The results highlight that: (i) contextual and attitudinal attributes are two major drivers of energy efficiency investments, and (ii) depending on the energy solution considered, there is a significant inverse relationship between energy-savings behavior and energy efficiency investments. This reveals that environmental awareness is not necessarily a driving factor behind energy efficiency investments and emphasizes the so-called "rebound effect" issue. The results support the view that promoting energy-saving behaviors and energy efficiency investments necessitate differentiated public policies that consider both individual preferences and housing stock heterogeneity. The analysis offers valuable policy guidance and research agenda outlining future energy efficiency research priorities. [ABSTRACT FROM AUTHOR]

Energy poverty is a challenging issue that hampers economic and sustainable development and lowers people's standard of living. While trying to understand energy poverty, it is imperative to focus on the disadvantaged individuals mentioned in the literature, as they are often most vulnerable to the problem. Focusing on them is essential to achieving sustainable development goals, especially in developing countries, particularly regarding poverty, energy poverty, and gender equality. Therefore, the paper aims to examine the impact of economic precarity on working-age females' energy poverty perceptions using 2018–2020 TURKSTAT-SILC pooled cross-sectional data. Our findings from the bivariate probit, multivariate probit and Bayesian bivariate probit models suggested that economic precarity has a disruptive role on females' energy poverty perceptions. Furthermore, inefficient energy use is an important factor in influencing females' perceptions of energy poverty. Females' inability to pay required housing expenses increases their perceived energy poverty. Therefore, social-welfare policies and energy policies should be considered together by the policymakers to resolve females' energy poverty problem to achieve a more sustainable future. [ABSTRACT FROM AUTHOR]

Climate-smart agriculture (CSA) can improve the resilience of farming systems in the face of climate-related shocks, providing a win–win for food security and environmental protection. Despite such promising benefits, its level of adoption, as well as the drivers of adoption, are still not well understood due to insufficient scholarship in this domain. This study assesses the determinants of the adoption of five CSA practices among 247 randomly selected farmers across five agricultural zones in Seychelles. A multivariate probit model was used to evaluate the determinants of adoption, allowing for the examination of synergies and trade-offs between the CSA practices. These practices include crop and livestock diversity, agroforestry, irrigation, and shade houses. Though the adoption rate varied, all farmers have adopted at least one of five CSA practices. The level of adoption of shade houses was low at 18.2%, while crop diversity recorded a high of 92.7%. Some practices, such as agroforestry and livestock diversity, irrigation, and crop diversity, and the use of shade houses and irrigation, complemented each other. Trade-offs were observed between irrigation and livestock diversity. The number of years of schooling, household size, and resources such as land tenure, farm size, use of hired labor, livestock, and nature of farmland, and farm location were crucial drivers of the adoption of CSA practices among the surveyed farmers. Agricultural strategies should recognize the complementarity of CSA practices to enhance its intensity of adoption in Seychelles. We recommend re-evaluating the current CSA technologies and identifying new technologies to ensure optimal production in an island state with a limited land area. [ABSTRACT FROM AUTHOR]

Based on the field survey data for 1216 apple growers in three provinces from China’s Loess Plateau Region, this paper adopted Multivariate Probit (MVP) model and intermediary effect model to analyze the influence mechanisms of digital technology adoption (DTA) on farmers’ choices of Fertilizer-reduction and Efficiency-improving Technologies (FETs) from the perspective of farmers’ cognition (FC). The correlation effects of three typical FETs of soil testing and formula fertilization, integrated water-fertilizer fertilization and slow/controlled release fertilizer, were tested empirically. The results showed that DTA could significantly affect the adoption of FETs by apple growers, and FC played a partial mediating role, and there were complementary effects among the three typical FETs. The results were further confirmed by the propensity score matching (PSM) robustness test and the instrumental variable (IV) endogeneity test conducted in the conditional mixed-process (CMP). The results of our heterogeneity analysis showed that the promotion effect of DTA on FETs in the group with junior high school education or below was more significant than that in the group with higher education, and the promotion effect was more significant in the group with large operation scale. Therefore, the improvement in Internet penetration should not be taken as the ultimate goal, but more attention should be paid to farmers’ mastery and effective use of DTA, promote the improvement in farmers’ cognitive level, and implement the “bundled” publicity and guidance strategy of FETs adoption, so as to help in the green transformation of agriculture.

Understanding the energy transition process in developing countries is crucial to implement policies to reduce the use of traditional fossil fuel-based energy sources, which increase pollution, worsen global climate change, and negatively impact people's health. Existing literature indicates that households account for approximately 25% of total energy consumption for consumption and production activities. However, understanding the energy consumption patterns of choices of energy sources and their determinants has largely been neglected in the existing literature. As such, this study uses the multivariate probit model to identify the factors influencing household energy choices in Vietnam, using data from 2016 to 2020 from the Vietnamese Households Living Standard Surveys (VHLSS). Our study focuses on how households' multiple occupations, particularly in rural areas, affect energy sources choices. We find that households participate in different agricultural sub-sectors simultaneously, resulting in differential access to multiple energy sources. Households engaging in cultivation, forestry, and animal husbandry activities are more likely to choose coal, fuelwood, and biomass as the primary energy sources for production and daily uses. In contrast, higher household income and household head with higher education level also increases the likelihood of choosing cleaner energy choices for daily uses and production activities. In addition, our empirical findings confirm the validity of the ''energy stacking” hypothesis rather than the “energy ladders'' hypothesis – two contrasting hypotheses concerning household energy transition in the literature. Policy implications have emerged based on the findings of this paper to enhance the clean energy transition in Vietnam in achieving sustainable economic development and social transformation and her commitment to combating global climate change issues.

The penetration of digital technologies to enhance market participation by farmers, and intensify farmers' access to support services such as finance, farm inputs, and agricultural production information is on the rise in developing countries. However, the drivers and intensity of the adoption of these technologies by Ghanaian farmers have received little attention in policy and academic circles. This study analyzed the factors that drive the adoption and intensity of adoption of digital agricultural solutions by smallholder farmers in the Bono East Region of Ghana. The study used a survey questionnaire to collect data from 1199 randomly selected smallholder farmers in 2023. The multivariate probit model and the Heckpoisson regression model were used to analyze the drivers of different digital agricultural solutions and the intensity of adoption of these solutions, respectively. The results show that there is a joint demand for technologies that enhance access to extension services and those that accelerate access to inputs. Market-oriented solutions and agricultural extension solutions exhibited a complementary relationship. In addition to selected socio-demographic factors, the study found that membership in farmer-based organizations, access to credit, and participation in agronomic training increased farmers’ propensity to adopt different digital agricultural solutions and increased the number of solutions adopted by farmers. Receiving visits from extension officers reduced the likelihood and intensity of adopting digital agricultural solutions. The results suggest that government and development partners should enhance access to credit and promote capacity development programmes among farmers. This will capacitate them to adopt digital agricultural solutions.

Nepal is one of the most vulnerable countries to climate change, which is negatively affecting agricultural production and food security. However, the role of agro‐ecological zones and social groups in climate change adaptation (CCA) and its impact on smallholder farmers in Nepal remains unexplored. To fill this gap, this study aimed to identify the effect of agro‐ecological zones and social groups on smallholder farmers' adaptation to climate change using the multivariate probit model. Multistage sampling was used to collect data from 400 households in three agro‐ecological zones of Nepal. These zones were highland (mountainous region), midland (hilly region) and lowland (terai/plain region). The results of our study showed that farmers in the Mountain region are more likely to adopt off‐farm activities and temporary migration as a CCA strategy than those in the Terai/plain agro‐ecological zone. In the Terai/Plain, farmers mainly adopt small‐scale irrigation and agroforestry. In terms of social groups, the Brahmin group was more likely to adopt new crop varieties and small‐scale irrigation than the Sudra group. The Sudra farmers preferred temporary migration and off‐farm activities more than the Brahmins. Our study shows that policies to promote the adoption of CCA strategies need to take into account location and social group differences in order to improve the adaptive capacity of the most vulnerable farmers. Mountain and Sudra farmers need support to adapt to climate change and sustain agriculture. [ABSTRACT FROM AUTHOR]

Does land security matter in climate change adaptation strategies choice? To provide answers to this, the paper used a survey data collected from a random sample of 341 agricultural households in 2020 in Benin. Descriptive statistics and multivariate probit model were used to analyze the data. The main adaptations strategies identified are adjustment in sowing time, tree planting, crop and livestock integration, use of irrigation, use of improved variety, and endogenous beliefs, while family land, own land and rented land are the types of land tenure arrangements. Results from a multivariate probit model show that the use of family land increases the likelihood of planting tree, crop and livestock integration, use of improved variety, and endogenous beliefs. Farmers using own land are more likely to adopt tree planting and endogenous beliefs as adaptation strategies, while they are less likely to adopt irrigation. The use of rented land increases the likelihood of adjusting the sowing time, crop and livestock integration, use of irrigation, use of improved variety, and use of endogenous beliefs. These findings suggest that the choice of adaptation strategies to cope with climate change depends on the type of land tenure arrangements. [ABSTRACT FROM AUTHOR]

This study investigated the gender dimensions in the adoption of CSA technologies among smallholder farmers in Benin. A multistage sampling procedure was used in selecting 272 respondents for the study, comprising equal proportions of male- and female-headed households. Focus group discussions, key informant interviews, and structured interviews were used to obtain responses from interviewees. Descriptive statistics, principal component analysis, and multivariate probit regression model were used in analyzing the data. The results of the study showed that a higher percentage (89.0%) of women sourced information on CSA technologies from their family/peers compared to men (66.2%). Men adopted more CSA technologies than women. Specifically, the CSA technologies adopted by the respondents were crop rotation (92.7% women vs. 86.0% men), animal health services (44.9% women vs. 66.2% men), and organic fertilizer (46.3% women vs. 59.6% men), among others. These climate-smart agricultural technologies were further delineated into three broad packages, namely soil and water conservation practices (SWC), improved livestock management system (ILM), and improved crop production system (ICP). More men than women adopted SWC and ILM. On the other hand, women (94.9%) adopted ICP more than men (87.5%). Gender, age, farm size, land ownership, access to labour, project contact, climate change information, and livestock ownership are significant determinants of the adoption of CSA options among the respondents. The study reinforces the need to consider context-specific local factors and co-design gender-based solutions to extreme climatic threats with the local communities. [ABSTRACT FROM AUTHOR]

Abstract Background The livelihood of rural households in Ethiopia, like in most developing countries, largely depends on land resource. However, nowadays most rural households are denied access to arable land in the highland of Ethiopia due to high population growth and shortage of arable land. Landlessness is, therefore, becoming a serious social and economic problem in the rural highland areas of Ethiopia in general and Tigrai region in particular. This study, therefore, intends to explore the choice of livelihood strategies of landless rural households and assess the challenges and opportunities of the livelihoods of landless rural households in selected districts of Tigrai region. Methods This study is conducted in three randomly selected districts of Tigrai region, namely, Kilte-Awlaelo, Degua-Tembien, and Hintalo-Wajerat districts. For the purpose of this study, two Tabias were randomly chosen from each districts. Then, afterward, both primary and secondary data sources were consulted to address the specific objectives of this study. The primary data were collected from 258 randomly selected households and six focus group discussions. This study used Multivariate Probit and Negative Binomial Regression to analyze factors influencing the choice of livelihood strategies and the number of livelihood options adopted by the landless rural households, respectively. Results This study finds that the livelihood sources of the landless rural households in the study area include farm (90%), non-farm (72%), and off-farm (41%) economic activities. The result of the Multivariate Probit regression indicates that household head characteristics, human capital, social capital, physical capital, financial capital, and institution-related factors were significantly influencing the choice of livelihood strategies of the landless rural households. The results of the negative binomial regression model, on the other hand, assert that household head-related factors, social capital, and institution-related factors were significantly influencing the number of livelihood options adopted by the landless rural households. This study affirms that stone or sand selling, dairy farming, poultry production, animal fattening, and bee keeping are the major opportunities to improve the livelihood of the landless rural households. Moreover, this study also identifies that shortage of arable land, youth unemployment, lack of access to infrastructure, poor land administration, and lack of access to financial capital were the major challenges facing the landless rural households. Concluding remarks This study concludes that all stakeholders efforts to address the problem of landlessness need to be geared to enhance access of landless rural households to different livelihood capitals, such as human, social, financial, physical, and natural capitals. Moreover, rural township and village enterprises could enhance the access of landless rural households to market and job opportunities.

Climate is one of the most important factors in agricultural productivity, which could directly or indirectly influence productivity since the climate is linked to physiological processes. This study investigates the level of adoption of multiple climate change adaptation strategies (CCAS) in Southwest Nigeria. A multistage sampling technique was employed to select 330 smallholder maize farmers, while secondary data on rainfall and temperature of the study area was sourced from the Nigerian Meteorological Agency (NiMet). Descriptive statistics, a multivariate probit model and fractional response model were employed for the study. The results show that smallholder maize farmers adopt mainly complementary adaptation strategies. The results also indicate that the maize farmer's membership of an association, sex, age, education, farming experience, farm size, access to credit and climate information are the main factors influencing the adoption of multiple CCAS in Southwest Nigeria. The result of fractional response model shows that socioeconomic and institutional factors significantly influenced the level of adoption of climate change adaptation strategies among smallholder maize farmers in the study area. Hence, the study recommends that the provision of a climate advisory service and credit facility to smallholder maize farmers be intensified.

The closure of markets in the city of Ouagadougou due to COVID-19 pandemic has had consequences on the food security status of households, in particular households of informal sector. The objective of this paper is to analyze the effect of COVID-19 on households' likelihood to resort to food coping strategies taking into account their resilience capacities. A survey was carried out among 503 households of small traders in five markets in the city of Ouagadougou. This survey identified seven mutually inclusive food coping strategies which are endogenous and exogenous to households. Thus, the multivariate probit model was used to identify the factors explaining the adoption of these strategies. The results indicate that the COVID-19 pandemic has had an impact on households' likelihood to use certain food coping strategies. Furthermore, the results show that assets and access to basic services is the main pillar of household resilience that reduces how likely a household resort to coping strategies due to COVID-19. Therefore, strengthening adaptive capacity and improving social security of households of informal sector are relevant. [ABSTRACT FROM AUTHOR]

Smallholder farmers who rely on home garden agroforestry are experiencing significant impacts from climate change. To mitigate these effects, it is crucial for farmers to have access to various adaptation strategies. This study collected data from 384 randomly selected respondents in 18 kebeles over three districts, using descriptive statistics and a multivariate probit model to evaluate the factors influencing smallholder farmers' decisions on their adaptation strategies against climate change. In Ethiopia's Gedeo zone, this study found that smallholder farmers employ a range of adaptation methods, including expanding their agroforestry system, implementing modern agriculture techniques, conserving soil and water, diversifying their livelihoods, and employing various coping mechanisms. By analyzing data using the multivariate probit model, this study found several factors that had a significant impact on smallholder farmers' choice of adaptation options. These factors include social network, age, education level, farming experience, household size, cultivated land size, annual income, and livestock holding. In addition, factors such as perception of climate change, previous experience of crop failure, recurrent drought, and access to information about climate change, occurrence of frost, agricultural extension contacts, access to farmer-to-farmer extension services, and perception of land infertility also influence their decision-making process. Our findings highlight the importance of improving institutional services in rural areas, promoting education on climate change, and strengthening social networks to enhance the ability of smallholder farmers to cope with the effects of climate change. [ABSTRACT FROM AUTHOR]

The literature examining the role played by family life cycle in farm households’ decisions to adopt sustainable agricultural technology (SAT) remains scant. To bridge this gap, we evaluate the impact of family life cycle on farm households’ adoption of SATs by using multivariate probit regression analyses of survey data from 902 farm households in Hubei Province, China. The results show that most farm households belong to the middle stages of the family life cycle. Straw returning is the most frequently adopted SAT among farm households. Farm households’ SAT adoption decisions are closely related to family life cycle. SAT adoption by farm households differs at each family life cycle stage. Based on this finding, when stimulating SAT adoption, the government should consider the different capital endowments and needs of farm households at different family life cycle stages as well as conduct differential and targeted technology promotion measures.

Agricultural greenhouse gas emission is a well-known contributor to anthropogenic climate change. It is imperative to encourage farmers to adopt low-carbon agricultural technologies (LATs). In this paper, the Delphi method was used to select nine LATs with good carbon emission reduction effects among all possible technologies adopted in the agricultural production process. Moreover, based on the survey data of 1114 farmers in Hubei province of China, we identified the potential determinants of rice farmers' decisions to adopt LATs and obtained the hierarchical structure of these determinants by employing the multivariate probit model, ordered probit model, and interpretative structural model. Results showed that there were strong complementary relationships between the nine LATs, and most rice farmers (83.48%) adopted three or fewer LATs simultaneously. It was also found that rice farmers' decisions to adopt LATs were mainly influenced by four types of factors, namely individual characteristics, family resource endowments, production managerial factors, and external environmental factors, with production managerial factors exerting the most significant effect. Specifically, for rice farmers who joined agricultural cooperatives, who thought the agricultural machinery costs were acceptable, and who had paddy fields with a higher concentration degree, the probability of the adoption of three or more LATs would increase by 18.05%, 3.81%, and 0.11%, respectively (21.97% in total). In addition, the key determinants of rice farmers' decisions to adopt three or more LATs were divided into three levels, i.e., surface factors, middle-level factors, and deep factors. To promote LATs, policymakers should offer targeted incentives, such as agricultural machinery purchase subsidies, technical guidance, and agricultural cooperative services. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has significantly altered employment and income distribution, impacting women and men differently. This study investigates the negative effects of COVID-19 on the labour market, focusing on the gender gap in five countries in the Middle East and North Africa (MENA) region. The study indicates whether women are more susceptible to losing their jobs, either temporarily or permanently, switching their primary occupation, and experiencing decreased working hours and income compared to men during the COVID-19 outbreak. The study utilizes a multivariate Probit model to estimate the relationship between gender and adverse labour outcomes controlling for correlations among outcomes. Data are obtained from the Combined COVID-19 MENA Monitor Household Survey, covering Egypt, Tunisia, Morocco, Jordan, and Sudan. The findings of this study offer empirical evidence of the gender gap in labour market outcomes during the pandemic. Women are more likely than men to experience negative work outcomes, such as permanent job loss and change in their main job. The increased childcare and housework responsibilities have significantly impacted women's labour market outcomes during the pandemic. However, the availability of telework has reduced the likelihood of job loss among women. The study's results contribute to a better understanding of the impact of COVID-19 on gender inequality in understudied MENA countries. Mitigation policies should focus on supporting vulnerable women who have experienced disproportionate negative effects of COVID-19.

Due to the rising demand for agricultural use and intensive crop management on existing croplands to meet the needs of a growing global population, water scarcity in agriculture is becoming increasingly important. Given the recurrent drought in South Africa and the rest of Africa, irrigation has a lot of potential to boost crop production and productivity. The objective of this study was to look at the factors that influence smallholder farmers' choice of irrigation systems. Multivariate probit (MVP) was used to analyze the determinants of choice of irrigation systems using primary data collected from 406 farmers in four irrigation schemes in KwaZulu-Natal. To this end, the study integrates different socioeconomic, institutional, and production factors in the empirical analysis. Bucket, flood, and sprinkler irrigation are the three common irrigation types found in and around the four irrigation schemes. The empirical findings show the importance of socioeconomic (such as age, household size, farmer occupation, and farming experience), technical, and biophysical factors when smallholders choose irrigation systems. These factors should be considered when developing policies and initiatives aimed at supporting irrigation systems. Such policies/programs should be designed such that they promote and support the uses of all irrigation systems highlighted in this study as they were found not to be mutually exclusive.

Agriculture is a sector that is very vulnerable to the effects of climate change while contributing to anthropogenic greenhouse gas (GHG) emissions to the atmosphere. Therefore, applying Climate-Smart Agriculture (CSA) technologies and practices (referee hereafter as CSA technologies) that can sustainably boost productivity, improve resilience, and lower GHG emissions are crucial for a climate resilient agriculture. This study sought to identify the CSA technologies used by farmers and assess adoption levels and factors that influence them. A cross-sectional survey was carried out gather information from 384 smallholder farmers in the Great Rift Valley (GRV) of Ethiopia. Data were analyzed using percentage, chi-square test, t test, and the multivariate probit model. Results showed that crop diversification, agroforestry, and integrated soil fertility management were the most widely practiced technologies. The results of the chi-square and t tests showed that there are differences and significant and positive connections between adopters and non-adopters based on various attributes. The chi-square and t test results confirmed that households who were older and who had higher incomes, greater credit access, climate information access, better training, better education, larger farms, higher incomes, and more frequent interactions with extension specialists had positive and significant associations with CSA technology adopters. The model result showed that age, sex, and education of the head; farmland size; livestock ownership; income; access to credit; access to climate information; training; and extension contact influenced the adoption of CSA technologies. Therefore, considering barriers to the adoption of CSA technologies, in policy and action is anticipated to support smallholder farmers in adapting to climate change while lowering GHG emissions. [ABSTRACT FROM AUTHOR]

The steep parts of Vietnam face more rain, frost, flash flooding, and landslides than the plains and lowlands, making them more vulnerable to disasters and experience severe natural calamities every year. In mountainous areas, water shortages are becoming increasingly problematic as a result of the impacts of climate change and measures to promote water conservation in mountainous areas are more challenging. In an attempt to optimize the environmental advantages of water conservation strategies, it is critical to understand the factors that influence household water consumption decisions. This study aims to focus on assessing the adoption behavior of water conservation among 778 households in 8 mountainous provinces of Vietnam. In this study, the multivariate probit model (MPV) is used to examine the relationship between intrinsic and extrinsic variables and five household water-use activities. The current study looked at the factors that influence the adoption of five different water conservation measures by households and variables related to the cognition of climate change, household characteristics and innate human qualities. The findings of this study reveal positive correlations between intrinsic and extrinsic variables and five household water-use activities. The results suggest that all intrinsic factors had a positive effect on the likelihood of implementing all five water-conserving strategies. However, extrinsic factors such as access to microcredit, rain, and cooperation are all factors that have a detrimental impact on water conservation measures. Based on the outcomes of the MPV model, we may assert that awareness of the effects of climate change is a contributing factor in explaining the adoption of water preservation strategies. The study areas and other similar regions in the country could benefit from a better understanding of the intrinsic and extrinsic characteristics of households to build relevant interventions for water conservation. Future studies are needed to determine how psychological mechanisms of behavior change and how perception of water scarcity affects intention of water usage. [ABSTRACT FROM AUTHOR]

The paper aims to identify major strategies applied by small-scale farm households to adapt to climate change and determine factors that affect their choice of adaptation strategies. A logistic regression model and a multivariate probit model were applied to a set of primary data collected from a survey of 290 farm households in two mountainous provinces of Northeastern Vietnam. Results show that farm households combined various strategies in response to the impacts of climate hazards. Changes in farm activities and livelihood diversification were the two most widely used adaptation strategies. Farm households' choice of adaptation strategies was influenced by a set of complex factors related to demographic characteristics, economic well-being, access to resources, and perception. Age and farming experience negatively affected farm households' adaptation. Meanwhile, access to resources, savings, extension services, membership of associations, access to information, and perception had a significantly positive effect on the adoption of adaptation strategies. Social-economic barriers restricted female-headed and ethnic minority households from taking up adaptation measures that required new technologies, updated knowledge, or resources. It is essential to issue policies and implement projects to enhance adaptive capacity and facilitating the adaptation process for farm households in mountainous areas, taking into account the barriers and disadvantages of female and ethnic minority farmers. [ABSTRACT FROM AUTHOR]

Using the Community Innovation Survey data, in this paper we explore the external and internal drivers influencing the four types of eco-innovation in the Baltic manufacturing sector. For this purpose, we estimate a quadrivariate probit model to reveal potential complementarities across the four types of eco-innovation and identify the differences among sectors and countries. The empirical findings show that: i) some factors such as future eco-policies and voluntary actions are significant for most categories eco-innovation; ii) cost saving is the main driver for the eco-process; iii) government grants, subsidies or other financial incentives and current regulation are never significant and finally iv) cooperation is a crucial driving factor for the productive process. [ABSTRACT FROM AUTHOR]

The increased threat of more frequent extreme climatic events (ECEs) poses significant challenges to household crops and livestock production, exacerbated by their weak adaptability. To explore ways to improve households' adaptation awareness and behaviors, a typical agro-pastoral ecotone on the northeastern Qinghai Tibet Plateau (QTP), Gonghe Sandy Land (GSL), was selected as the study area. This study analyses the impact of ECEs, and the adaptation measures taken by households, and innovatively includes the perception of government services from households in the factor system to identify the key driving mechanism of coping strategies. The results revealed that (1) 74.07 % of households experienced an extreme drought, and livestock production was 29.63 % more affected than crop production was; (2) households adopted different adaptation strategies with weather forecasts being the prevailing measure among households for crop (25.93 %) and livestock (42.33 %) production adaptation; and (3) different strategies are key to improving adaptive capacity. We found that production experience sharing, demographic and economic coordination, and early warning system and support by the government can increase farmers' awareness of adaptation strategies. While enhancing cognitive levels regarding measures, optimizing a household's health, rationally allocating assets, and increasing timely and stable government services can improve adaptive behaviors. On the basis of these findings, this study provides recommendations from the perspective of human well-being, with the aim to achieving the SDGs, enhancing regional climate change adaptation capacity and ensuring the safety and efficiency of crop and livestock production in the QTP. [Display omitted] • Extreme climatic events had severely affected crop and livestock production. • Adaptation of households in agro-pastoral ecotone of QTP is deficient. • Follow the weather forecast is the frequently-used, lowest-cost, simplest measures. • Experience share, socioeconomic trade-off, resource support raise adapts awareness. • Educate, health, asset allocate, government service raise adapts behavior. [ABSTRACT FROM AUTHOR]

Understanding the determinants of farmers’ disaster adaptation is significant for risk reduction. This study explores farmers’ willingness and influencing factors to adopt various agricultural and non-agricultural adaptation measures to mitigate irrigation-induced landslides on the Loess Plateau, northern China. Multivariate probit models are applied to address the joint decision-making of multiple choices considering their inter-correlations, using data from 397 farmer survey questionnaires. The results reveal that farmers’ characteristics, landslide experience, social factors, landslide perception, and the present adaptation situation play important but different roles in their adaptation decisions regarding various measures (drip irrigation, drought-tolerant crops, income diversification, and migration). Heterogeneity among farmers is considered: Government support, social network, and perception of landslide causation are essential in affecting all of the farmers’ adaptation decisions, while the impacts of the annual income, gender, land scale, and risk perception on non-agriculture farmers and full-time or part-time farmers are opposite. Notably, current adaptation hinders farmers’ future actions. The probability of adopting a specific measure is estimated to be higher than that of joint adoption. Barriers to adaptation are also addressed, and policy implications are discussed. This study provides a theoretical and practical reference for mitigating landslide risks that are caused by artificial triggers.

AbstractInformation communication technology is energetic for rural transformation and plays a great role in agricultural development. However, there are factors affecting farmers’ use of information. This study focused on determinants of various agricultural information sources. Household survey from 165 respondents and multi-stage sampling techniques were used. Multivariate probit model regression output shows that social participation and distance are significantly related with the use of all information sources at different significance levels. Age, extension contact, education, sex, credit access, land size, non/off-farm income and farm income are significant with the use of different information sources at different significance levels. The Wald test (χ2 (56) = 101.39, p = 0.000) is significant, which indicates that MVP model fits the data. LR (χ2 (6) = 232.942, Prob > χ2 = 0.0000) indicates the goodness of fit of the model. For more use of agriculture-related information, Ministry of Agriculture and NGOs need to intervene in rural agricultural programs.

AbstractPoor identification of Contagious caprine pleuropneumonia diseases from its signs and symptoms is a major problem to goat farmers which leads to use of wrong method of disease control. The uptake of control strategies like vaccination by farmers depends on many factors while awareness and knowledge become the foundation of the technology adoption processes. This therefore necessitated a study to understand the level of awareness and knowledge of Contagious caprine pleuropneumonia, which is a highly infectious goat disease. The study analysed and used cross-sectional data collected from 342 households interviewed in October, November, and December 2020 in Kajiado County and Taita Taveta County in Kenya. These two counties are dominated by agro pastoralists and goat keeping is predominant. The study examines the factors influencing the agro pastoralists’ knowledge and level of awareness on the six major signs and symptoms of Contagious Caprine Pleuropneumonia disease differentiating it from other goat diseases. Multivariate probit model was the main data analysis method used. Results show that agro pastoralists’ level of knowledge and awareness on Contagious Caprine Pleuropnemonia disease depend significantly on other factors such as the gender of household head, age, education level, household size, access to extension services, and group dynamics. The findings imply that policymakers and agricultural development partners should increase public and private investment on agro pastoralists’ training and education programmes which is one of the main pathways for increasing public awareness in livestock dominated areas.

Agricultural environment in many developing economies has become increasingly unpredictable in recent decades as a result of climate change, increasing the risk of crop failure. Access to meaningful information is required to mitigate the negative effects of the changing environment. This study examined the impact of agricultural extension services on the adoption of soil and water conservation (SWC) practices using data obtained from farming households in Northern Ghana. A multivariate probit model was used to assess the simultaneous or/and substitution adoption of SWC practices, while endogenous switching probit (ESP) was used to estimate the impact of extension services on adoption of SWC practices to account for observed and unobserved heterogeneities. The results showed that most of the SWC practices were adopted jointly, and factors such as non-farm economic activites and farm size influence the adoption of SWC practices. Moreover, farmers who accessed agricultural extension services had a higher probability of adopting most of the SWC practices (crop rotation, contour ploughing and manure application), and those who did not benefit from extension services would have had an equally higher likelihood of adopting the SWC practices had they accessed the services. The findings of the study imply that enhancing agricultural extension services will reduce adoption gaps in SWC practices, and consequently reduce farmers’ exposure to climate-related agricultural production risks. With growing information and communication technologies, pluralistic extension service delivery that mixes governmental and private-sector-led approaches to extension operations to foster demand-driven extension delivery services are highly recommended.

Sustainable agriculture is essential for food security, which can sometimes be undermined by rural migration triggered by many factors, including climate change. This article aims to analyze its effects on the dynamic of rural migration. Using a database of 623 agricultural households, a multivariate probit model (MVP) was estimated. The results show that regardless of the nature of migration, variables related to climate factors positively and significantly affect decisions to move. In addition, other non-climatic variables relevant to environmental migration are cattle transhumance, which creates conflicts between herders and farmers, along with poor access to agricultural credit, agricultural and offfarm income. Gender, age, household size, accessibility to educational and health facilities in the area of origin and experience in agricultural production must be considered. Emphasis should be placed on agricultural policies aimed at diversifying the income sources of rural households in developing countries. The study highlights the importance of both farm and non-farm income in controlling migration. In the case of our study area, it is the combination of livestock and agriculture that seems to respond best. Producers are encouraged to diversify crops and, during periods of climatic disruption, the priority of households should be based on the production of food crops for subsistence. [ABSTRACT FROM AUTHOR]

Consumption of roots and tubers (R&Ts) among urban households can be low. Understanding factors influencing consumption decisions for R&Ts is important in enhancing their utilization. This study assessed determinants of consumer preference for selected R&Ts using a multivariate Probit model. A stratified multistage sampling technique was adopted to select 385 respondents, and data collected using a pretested semi-structured questionnaire. Irish potatoes (Solanum tuberosum L.) had the highest preference level (70%), followed by sweet potatoes (Ipomoea batatas L. Lam.) at 61%. Arrowroot (Maranta arundinacea L.) had a preference of 42%. Cassava (Manihot esculenta Crantz) and yams (Dioscorea alata L.) were the least preferred at 22% each. Education, monthly income, cultural orientation, nutritional knowledge, Covid-19 pandemic, market distance, farming of R&Ts, retail prices, production location, availability of R&Ts, size, quality, taste, and preparation time influenced preferences for R&Ts by urban households. Inadequate time to prepare R&T meals at home and availability of conveniently prepared alternatives likely explains their low preference by urban residents. [ABSTRACT FROM AUTHOR]

This study examines the core factors that determine consumer choices of distribution channels for fresh food during the COVID‐19 pandemic, focusing on online distribution channels and the substitution patterns between online and offline distribution channels. Using 1436 responses to a survey conducted by Gallup Korea, a specialized survey agency in Korea, we adopted a multivariate probit model for the empirical analysis. The results show that consumers who pursued ease of use or had high awareness of online food delivery tended to choose online distribution channels for fresh food, unlike consumers who were sensitive to high quality or low prices. Consumers with high consumer spending, who are living in Seoul or a metropolitan area, have children of 10 years old or younger, and have a high educational level had positive relationships with the choice of an online distribution channel. Additionally, the estimates of the variance‐covariance matrix showed a complementary relationship between large markets and small and medium‐sized markets, with the possibility of a weak substitution effect between small and medium‐sized markets and online distribution channels. [ABSTRACT FROM AUTHOR]

Looking for alternative livelihood strategies is getting the remarkable attentions to reduce poverty in peripheral pastoralist areas of developing countries. This study is an effort to assess pastoral livelihoods and determinants of livelihood strategy of Boorana pastoralists by integrating sustainable livelihood framework into pastoralist livelihood study. The study was based on the household survey (n = 332), interviews and focus group discussions. Data were analyzed by descriptive statistics, summarizations of qualitative responses and Multivariate Probit Model (MVP). The result showed that pastoralists are vulnerable to conflicts, climate changes and resulting crisis due to outbreak of livestock diseases and death of livestock, crop damage, food insecurity and hunger. The study found that pastoralists manage risks by engaging into diverse set of income generating portfolios. The findings of study showed that respondents prefers to choose intensive rain-fed farming and non-farm activities, pastoralism, labour works, diversifications, mobility and hired herder as ways of living. Inaddition, MVP result showed that the decisions of household to simultaneous engage in these livelihood strategies are determined by various socioeconomic characteristics (head sex, marital status, head literacy), and skill training, microfinance, assess to credit, and livestock diversification of households. The study therefore suggests the need for more diversified opportunities to reduce pastoralist vulnerabilities to livelihood shocks and to reduce poverty. [ABSTRACT FROM AUTHOR]