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Despite a reduction in poverty the global population in 2015, the incidence of poverty remains very high in Sub-Saharan African countries. Most of the countries in the region are agrarian, with most of their population residing in rural areas, and a majority of the poor in the region are found in Nigeria. This study examined the nexus between participation in nonfarm enterprises (NFEs) and poverty among rural farm households in Nigeria and across the six geopolitical zones.

The Nigerian Living Standard Survey (NLSS) conducted in 2018–2019 by the National Bureau of Statistics was used. We made use of 13,440 farm households with useful information for the purpose of this study. The sample comprises 6,885 households that participated in NFEs and 6,555 nonparticipating households. The data were analyzed with Foster, Greer, and Thorbecke (FGT) (1984) metrics, probit, and fractional probit models at p = 0.05.

The incidence of poverty was lower among the participating households than in the nonparticipating households. Participation in NFEs had a mitigating effect on poverty. We also established that zonal differentials in poverty rates exist among households in all the analyses. Participation in NFEs was influenced by individual, household, and institutional factors and was also able to explain the depth of poverty among the respondents.

It is suggested that poverty alleviation policies should be targeted at improving access to nonfarm economic activities by rural farm households residing in vulnerable geopolitical zones.

This study is the first attempt to profile household poverty based on the type of NFEs they are involved in. The study also provides an insight into the effect of the state of residence on zonal poverty models, which is expedient if the country must achieve Sustainable Development Goal 1 on the eradication of poverty everywhere.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0493

The study attempts to estimate farm subsidies the governments can save by transitioning to a millet-based production system, replacing GHG emission-intensive crops.

It updates a 131 × 131 commodity input–output (IO) table of the year 2015–16 into 2021–22 using the RAS procedure and simulates the economy-wide impacts of replacing rice and wheat with pearl millet and sorghum using consumption and production approaches. It then quantifies fertilizer, electricity and credit subsidy expenses the government can save through this intervention. It also estimates the potential reduction in GHG emissions that the transition could bring about. India is taken as a case.

Results show pearl millet expansion brings greater benefits to the government. It is estimated that when households return to their pearl millet consumption rates that prevailed in the early-reform period, this could save the Indian government Rs. 622 crores (USD 75 m). The savings shall be reinvested in agriculture to finance climate adaptation/mitigation efforts, contributing to a sustainable food system. Net GHG emissions also decline by 3.3–3.6 MMT CO2e.

Indian government has been actively aiming to bring down paddy areas since 2013–14 through the Crop Diversification Program and promoting millets (and pulses and oilseeds) on these farms. The prime reason is to check rapidly declining groundwater irrigation in Green Revolution states. Regulations in the past in these states have not brought the intended results. Meanwhile, electricity and fertilizers are heavily subsidized for agriculture. A slight shift in the cropping system can help conserve these resources. Meanwhile, GHG emissions could also be brought down and subsidies could well be saved. The results of the study indicate the same.

A less warm society is what governments and nongovernment organizations across the world are aiming for at present. Financial implications affect actions against climate change to a greater extent, apart from technological innovations. The effects of policy strategies discussed in the study, taking a large country as a case, when implemented appropriately around the regions, could help move a step closer to action against climate change.

The paper addresses a key but rarely explored research issue – that how a climate-sensitive crop choice will help reduce the government’s fiscal burden to finance climate adaption/mitigation. It also offers a mechanism to estimate the benefits within an economy-wide framework.

This study aims to understand the socioeconomic impact of flood events on households, especially household welfare in terms of changes in consumption and coping strategies to deal with flood risk. This study is based on Bihar, one of the most frequently flood-affected, most populous and economically backward states in India.

Primary data were collected from 700 households in the seven most frequently flood-affected districts in Bihar. A total of 100 individuals from each district were randomly selected from flood-affected villages. Based on a detailed literature review, an econometric (probit) model was developed to test the null hypothesis of the availability of consumption insurance, and the multivariate probability approach was used to analyze the various coping strategies of these households.

The results of this study suggest that flood-affected households maintain their consumption by overcoming various losses, including income, house damage and livestock loss. Households depend on financial transfers, borrowings and relief, and migrate to overcome losses. Borrowing could be an extra burden as the government compensates for house damage and crop loss late to the affected households. Again, there is no compensation to overcome livelihood loss and deal with occurrences of post-flood diseases, which further emphasizes the policy implications of strengthening the health infrastructure in the state and generating alternative livelihood opportunities.

This study discusses flood risk in terms of changes in household welfare, identifies the most effective risk-coping capabilities of rural communities and contributes to the shortcomings of the government insurance and relief model.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0569

Focusing on micro-level indicators, we investigate financial inclusion levels in rural China, examining its determinants and impact on household welfare. We construct a financial inclusion index of four essential financial services: savings, digital payments, credit and insurance. We identify factors influencing financial inclusion among Chinese rural households and assess the effects of financial inclusion on household welfare.

With the entropy method, we use data from the 2019 China Household Finance Survey to assess financial inclusion levels in rural China. Determinants and their impact on welfare are analyzed through probit and ordinary least squares models, respectively. Propensity scoring matching is applied to address potential endogeneity.

We reveal that rural households exhibit limited usage of formal financial services, with notable regional disparities. The eastern region enjoys the highest financial inclusion and the central region lags behind. Household characteristics such as family size, education level of the household head, income, employment status and financial literacy significantly influence financial inclusion. Financial inclusion positively impacts household welfare as indicated by household consumption expenditure. The use of different types of financial services is crucial with varying but significant effects on household welfare.

This study offers valuable insights into China’s rural financial inclusion progress, highlighting potential barriers and guiding government actions.

The Gulf Cooperation Council (GCC) of countries has some of the highest electricity consumptions and carbon dioxide emissions per capita in the world. This poses a direct challenge to the GCC government’s ability to meet their CO₂ reduction targets. In this review paper the current household electricity consumption situation in the GCC is reviewed.

Three scenarios for reducing energy consumption and CO₂ emissions are proposed and evaluated using strengths, weaknesses, opportunities and threats (SWOT) as well as the political, economic, social, technical, legal and environmental (PESTLE) frameworks.

The first scenario found that using solar Photovoltaic (PV) or hybrid solar PV and wind system to power household lighting could save significant amounts of energy, based on lighting making up between 8% to 30% of electricity consumption in GCC households. The second scenario considers replacement of conventional appliances with energy-efficient ones that use around 20% less energy. The third scenario looks at influencing consumer behavior towards sustainable energy consumption.

Pilot trials of these scenarios are recommended for a number of households. Then the results and feedback could be used to launch the schemes GCC-wide.

The proposed scenarios are designed to encourage responsible electricity consumption and production within households (SDG12).

All three proposals are found viable for policymakers to implement. However, to ensure successful implementation GCC Governments are recommended to review all the opportunities and challenges associated with these schemes as laid out in this paper.

The purpose of this study is to explore the potential and challenges of biogas utilization as an alternative and sustainable energy source in the Gurage zone of Southern Ethiopia, where traditional energy sources such as firewood and charcoal are widely used.

The study adopts a mixed-methods approach to collect and analyze data from different sources and perspectives. The research collects quantitative data from structured interviews with 200 rural households who use biogas or other energy sources, and qualitative data from key informant interviews and focus group discussions with biogas experts, local authorities and community leaders. Socioeconomic analysis is conducted to assess the importance of biogas in terms of income, expenditure, health and environmental benefits, and a multivariate probit model is used to identify the factors influencing biogas energy adoption among rural households.

The findings indicate that biogas users are more likely to substitute traditional energy sources with biogas for cooking, lighting and heating purposes. The model reveals that age, sex, education level, land size and livestock quantity influence biogas energy adoption, whereas income, distance to market and access to credit do not have a significant effect. The findings also show that biogas users have higher income, lower expenditure, better health and lower greenhouse gas emissions than nonusers.

The study concludes that the socioeconomic impact of biogas varies among households based on location and lifestyle. The study also highlights the need for further research on the technical, institutional and behavioral aspects of biogas utilization in different contexts.

To address the challenges faced by biogas users and their energy choices, such as lack of awareness, maintenance, quality control and affordability, the study suggests exploring biogas energy to meet the diverse needs of cattle owners in different regions. The study also recommends enhancing the capacity of local stakeholders, promoting public–private partnerships, and developing supportive policies and regulations for biogas development in Ethiopia.

The study implies that biogas utilization can contribute to social development by improving the living standards, health status and gender equality of rural households. The study also suggests that biogas utilization can foster social cohesion and empowerment by creating opportunities for collective action, knowledge sharing and income generation among biogas users and their communities.

The study provides a comprehensive and empirical analysis of the socioeconomic landscape of biogas utilization and the determinants of energy choice in the Gurage zone of Southern Ethiopia. The study also offers valuable insights and recommendations for policymakers, practitioners, researchers and other stakeholders involved in biogas development in Ethiopia and other developing countries.

This study aims to examine the impact of socioeconomic factors on electricity usage and assess the feasibility of implementing a mini-grid system in Kasangazi, Malawi. The primary aim is to understand the community’s current and potential utilisation of electrical equipment.

A mixed-methods approach was used to collect quantitative and qualitative data. Information was gathered through structured questionnaires, and energy audits were conducted among 87 randomly selected households from 28 Kasangazi communities. Data analysis relied on descriptive statistics using IBM SPSS version 28.

The study indicates that every household in Kasangazi uses non-renewable energy sources: 60 households use disposable batteries for lighting, 20 for radios and all use firewood, freely sourced from local forests, for cooking and heating water. The study shows that firewood is the community’s preferred energy source, illustrating the challenges faced in the fight against deforestation. Most household income comes from farming, with smaller contributions from businesses, employment and family remittances. Access to higher education is scarce, with only one out of 349 family members receiving tertiary education. Despite the constraints of low education levels and income, there is a demand for larger electrical appliances such as stoves and refrigerators. This underscores the need for mini-grid solutions, even in less technologically advanced, agriculture-dependent communities.

This study underscores that in Sub-Saharan Africa, factors like household size, income and education levels do not significantly influence the electricity demand but should be taken as part of the fundamental human rights. Rural populations express a desire for electricity due to the convenience it offers, particularly for appliances like refrigerators and stoves. Mini-grids emerge as a viable alternative in regions where grid electricity provision is challenging. It is concluded from this paper that the issue of using renewable energy should not only be taken for environmental preservation but also to promote energy access, augmenting efforts in supplying electricity to the remotest parts of the country.

Financial inclusion and digital finance go side by side and help enhance agricultural activities; however, the magnitude of digital financial services varies across countries. In line with this argument, this study aims to examine whether financial inclusion enhances agricultural participation and decompose the significance of the difference in determinants of agricultural participation between financially included – not financially included households and digital finance – no digital finance households.

This study uses Pakistan’s household integrated economic survey 2018/19 to test hypotheses. The logit model is used to examine the effect of financial inclusion on agriculture participation. Moreover, this study employs a nonlinear Fairlie Oaxaca Blinder technique to investigate the difference in determinants of agricultural participation.

This study reports that financial inclusion positively influences agricultural participation, meaning households may have access to financial services and participate in agricultural activities. The results suggest that the likelihood of participating in agriculture in households with mobiles and smartphones is higher. Moreover, household size, income, age, gender, education, urban, remittances from abroad, fertilizer, pesticides, wheat, cotton, sugarcane, fruits and vegetables are the significant determinants of agricultural participation. To distinguish the financially included – not financially included households’ gap, this study employs a nonlinear Fairlie Oaxaca Blinder decomposition and finds that differences in fertilizer explain the substantial gap in agricultural participation. Likewise, this study tests the digital finance – no digital finance gap and finds that the difference in fertilizer is a significant contributor, describing a considerable gap in agricultural participation.

Empirically identified that various factors cause agricultural participation including financial inclusion and digital finance. Regarding the research limitation, this study only considers a developing country to analyze the findings. However, for future research, scholars may consider some other countries to compare the results and identify their differences.

The accessibility of fertilizer can reduce the agricultural participation gap. However, increased income level, education and cotton and sugar production can also overcome the differences in agriculture participation between digital finance and no digital finance households.

This is the first study to decompose the difference in determinants of agricultural participation between financially and not financially included households.

The purpose of the study is to estimate the willingness to pay (WTP) for major chemical fertilizers and revisit the fertilizer subsidy policy in Nepal.

We surveyed 619 households from six districts and assessed farmers’ WTP for urea, diammonium phosphate (DAP) and muriate of potash (MOP) during the fertilizer crisis. Our study elicited the WTP for fertilizers when fertilizers were not available on the market. A modified payment card approach was used to elicit farmers’ WTP.

The study found that farmers who buy fertilizer from agrodealers, buy from gray markets, have bank accounts, are willing to take a risk, have strong or medium economic conditions and incur higher travel costs have a higher WTP for fertilizers. Farmers in sampled areas, on average, are willing to pay 31 percent more for urea, 13 percent more for DAP and 19 percent more for MOP than the government recommended fertilizer price.

The design of the payment card and the estimation techniques used to fit the valuation function are likely to influence WTP.

Overall, literature on households’ WTP for fertilizers in developing countries is scarce. Our study contributes to the knowledge of WTP for fertilizers.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.