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Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.

The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.

The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.

This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.

To effectively meet their social objectives, humanitarian organizations need to be more innovative and find novel ways to stay competitive. Yet there has been limited focus on innovation by humanitarian organizations. Part of the issue is the lack of new practices and novel approaches that can be used as benchmarks. This study focuses on food banks, a critical hub for the delivery of food in humanitarian supply chains and where the use of innovation seems to be more reported on.

Focusing on resource scarcity, a commonly referenced constraint by humanitarian organizations, the authors study how food and fund scarcity (versus abundance) influence the innovation efforts of twelve food banks in the United States. This study observes variations in behavior before and during the coronavirus disease 2019 (COVID-19) pandemic.

The authors find that food banks operating in high resource scarcity (food-scarce and fund-scarce) settings focus on process innovations. Food banks operating in low resource scarcity (food-abundant and fund-abundant) settings focus on product innovations. Food banks operating in food-abundant and fund-scarce settings focus on marketing innovations. Food banks operating in food-scarce and fund-abundant settings show the most extensive focus on innovation by relying on imitative innovations. The innovation focus for most food banks switches to process innovation during the COVID pandemic.

The study breaks down resource scarcity specific to food banks by differentiating food and funds, a novel approach to studying scarcity. Findings are novel as they suggest that operating context has a highly differentiating effect on what food banks focus on in terms of innovation. Operating context can lead to focus on process, product, imitative of market-related innovations. Finally, the study is novel because it explores how change in the environmental context due to disruptions can drastically modify the innovation focus of food banks.

This study assessed the heterogeneous impact of the Anchor Borrower Program (ABP) on the welfare distribution of rice farming households in Nigeria.

Self-selection bias and treatment endogeneity were accounted for by employing the Instrumental Variable Quantile Regression (IVQR) model. The estimates obtained from the IVQR model were further compared with those from the conventional quantile regression, and quantile regression using Propensity Score Matching. This was to highlight the extent to which endogeneity bias has been purged from the treatment, in order to establish a consistent causal link between participation in the ABP and the welfare of a cross-section of rice farming households.

ABP farmers had significantly higher rice yields across all quantiles of the yield distribution under treatment exogeneity assumption, and in only two quantiles upon controlling for observable confounders. However, this yield gain did not translate to higher Per capita Consumption Expenditure (PCE). The estimates of the more robust IVQR model provided further evidence that the rice yield and PCE of ABP farmers are not statistically different from that of non-ABP farmers across all quantiles of the welfare distribution.

The negligible impact of ABP was relatively higher for lower-yielding households. Thus, implying that, although the ABP is a pro-poor development intervention, the program has not been sufficiently implemented to significantly improve the welfare of the dominant resource-poor farming households in Nigeria.

This study assessed the impact of ABP beyond the conventional potential mean outcome framework by accounting for heterogeneity in treatment effect.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0083

This study aims to investigate the determinants of the food security status of participants and non-participants of livestock extension services living under similar socioeconomic conditions as livestock farming households in the Feed the Future zone of Bangladesh.

Cross-sectional data of 906 farm-households extracted from a total of 2064 from the Feed the Future representative Bangladesh Integrated Households Survey 2018 were used. A triple hurdle model combined with a structural equation model were used to analyze the data. The causal relationship between food security status, livestock extension services, technology adoption and women's empowerment was investigated by estimating structural equation modeling with second-order latent factors.

The results indicate that livestock extension services have increased livestock technology adoption and have a positively significant (p < 0.01) relationship with household wealth, food security, welfare and women's empowerment.

The results suggest that livestock extension services have an impact on new technology adoption and enhancing women's empowerment; thus, the services should be widely made available in the region.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2021-0647.

This study aims at exploring the choices of livelihood strategies amongst the rural youth and how these choices relate to food security and income poverty.

The study used data from the 2016/17 wave of Integrated Household Living Condition Survey, with a sample size of 1,050 rural youths. Statistical and econometrics methods including descriptive statistics and the Multinomial Endogenous Treatment Effect (METE) model were used to analyse the data.

Livelihood choices were grouped into five categories, namely agriculture, non-farm wage employment, agriculture plus non-farm wage, agriculture plus self-employment and agriculture plus non-farm wage plus self-employment. The estimates from METE indicate that the youths' choice of non-farm wage, agriculture plus non-farm wage and agriculture plus self-employment contributes substantially to household food security improvement and poverty reduction. These findings show that agriculture is necessary but not a sufficient livelihood strategy to sustain the rural youth's contribution to youth's household welfare. The rural youth will pursue agriculture as a reliable source of livelihood not only for food self-sufficiency, but also for ensuring adequate return to labour.

This paper extends single choice analysis to multiple choices impact analysis, which has the advantage of accounting for selection bias due to both observed and unobserved heterogeneity. This paper assesses the differential impact of the choice of single as well as multiple livelihood strategies.

The purpose of this study was to evaluate the impact of a waqf-based microfinance program on clients’ well-being during the COVID-19 pandemic.

This study obtained primary data from a survey distributed to 282 respondents, consisting of 150 clients and 132 nonclients of the Bank Wakaf Mikro (BWM) Al Kausar in Indonesia. This study constructed a well-being index (WBI) and compared clients’ and nonclients’ WBI before and during the pandemic using the difference-in-differences (DID) method. DID measures the effect of a treatment in a “treatment group” versus a “control group” using data from two periods.

This study found that clients and nonclients alike experienced an increase in well-being throughout the pandemic, but the increase was greater for clients than for nonclients. This study argues that the waqf-based microfinance program run by Bank Waqf Mikro model can assist their clients – as more vulnerable groups in society – to maintain their well-being during the pandemic.

To ensure the effectiveness of waqf-based microfinance programs in diverse settings, this study should include more respondents from different institutions.

This research has several practical recommendations, particularly for integrating Islamic charity for microfinance. The findings of this study suggest that the BWM model, which combines three institutions – the government, zakat groups and Islamic boarding schools (pesantrens) – can play a substantial role in enhancing the welfare of its members during the pandemic.

This study contributes to the body of knowledge on Islamic microfinance by providing empirical evidence of the importance of waqf-based microfinance in reducing the pandemic’s impact on clients well-being.

This study investigates the observed resurgence in religious beliefs seen across many societies during the COVID-19 pandemic. Using the economic theory of religious clubs, the author models religious participation during the pandemic as a mechanism for alleviating the financial distress associated with the health distress from the pandemic.

Using data from the COVID-19 National Longitudinal Phone Survey (NLPS) in Nigeria, the author investigates the economic motivation for religious intensity during the COVID-19 pandemic. To address endogeneity concerns, the author exploits geographic variables of temperature and longitudes as sources of COVID-19 risk.

Overall, health distress stimulates religious intensity. Consistent with the economic theory of religious clubs, adverse health shocks stimulate financial distress, and the effect is stronger among religious participants. Similarly, people see God and not the government as a source of protection against COVID-19.

The study’s model sees religious organizations as public goods providers, especially when governments and markets are inefficient.

The study’s recommendations support an expanded role for religious networks in healthcare delivery and more public funding to attenuate the post-pandemic resurgence of social violence in economically distressed regions.

Despite the research interest in the COVID-19 pandemic, the long-term implications, many of which relate to social behavior adjustments that cause individuals to identify more closely with their social group, need greater understanding. Suppose religious intensity is linked to economic distress. In that case, this is a major source of worry for countries whose economies are subject to higher fluctuations and where the governments and markets are inefficiently organized. These regions may be more susceptible to a resurgence in religious fundamentalism associated with the economic shocks from the pandemic. Consequently, these regions would require more public funding to attenuate the potential for costly activities like organized violence, suicide attacks and terrorist activities in the aftermath of the pandemic.

Prompted by the observation of the increase in religious identity through religious intensity during the pandemic, the author contributes by developing theoretically-based hypotheses that are incentive-compatible to provide a rational justification for the observation. The author empirically validates the hypothesis by taking advantage of the COVID-19 National Survey in Nigeria by specifically using survey rounds 4 and 7 which have more comprehensive religious items included.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0719

This paper aims to explore the construction of a valid and reliable measure for the competitiveness of cities that excludes the drivers of competitiveness from the index construction. Not incorporating these drivers in the index avoids the problem of assuming relative contributions (i.e. weights) of these drivers on competitiveness as a maintained hypothesis.

From the definition that competitiveness is the ability of a city to sustain prosperity, this study derives a model called the hedonic well-being index (HWI) in which prosperity is measured by using the consumption of goods and service including leisure. This study then uses secondary data sources to construct an exploratory HWI (assuming a Cobb Douglas functional form) and compare this index to three benchmarks, namely, income, gross domestic product (GDP) per capita and the World Happiness Report (WHR) index. This study also review the component expenditure of the index across geographical locations.

The HWI is better predicted by the WHR index (a subjective well-being index) than by the GDP per capita (a measure of output), owing to the inclusion of leisure and household production absent in per capita GDP. This study explored and found regional variations in the distribution of the expenditure components in the HWI.

This paper demonstrates the feasibility of constructing an exploratory HWI to measure the competitiveness of cities using secondary data. The reliability of the index can be improved using primary data in future research. Separating the drivers from the definition of competitiveness allows testing of the contribution and interaction of these drivers on competitiveness.

Efforts to reduce farmers' market risks and improve buyers' access to farm commodities have encouraged contract farming (CF) in Ghana's cashew sector in recent years. Consequently, the existence of CF shows that farmers who use it may be benefiting from it, as it is their economic responsibility to decide how to sell agricultural products. However, the magnitudes of these benefits or otherwise have been inadequately explored. This paper aims to empirically estimate the impact of CF on farm performance and welfare of smallholder cashew farmers.

The study used probit-two-stage least square (probit-2sls) as a primary estimator to account for self-selection bias and endogeneity that could arise from both observed and unobserved heterogeneities among farming households to estimate the causal effects of CF on farm performance and household welfare.

The results indicated that participation in CF contribute significantly to the gains in farm performance (price margins, yields and net farm revenue) and welfare (consumption expenditure per capita), and that the non-participants of CF would have benefited substantially if they had participated. An analysis of the farm size disaggregated into small, medium and large with regards to the outcome variables produces mixed results.

It can be concluded that participating in CF enhances farm performance and household welfare.

While many other studies do not account for changes in farm performance and welfare due to differences in farm size or other observed factors, this study fills a crucial void.

Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.