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The paper aimed to examine the determinants of agricultural commercialisation of farmers and measured its commercialisation level in the highland of Vietnam.

A sample size of 360 was randomly chosen from a total population of 5,771 farmers, and a structured questionnaire was developed to collect data. Descriptive and inferential statistics, including linear regression analysis, were used to analyse the data.

The descriptive statistics showed that the average commercialisation level of farmers was 56.3%. The regression model result indicated that number of off-farm income sources, farmer's risk perception, farming practices, number of agricultural activities, motorbikes value, ethnicity, distance from the city centre, number of customers, non-traded inputs value, participation in training programmes, family size, farm size, mobile phones value, traded inputs value, land tenure, distance from the local market and education of household head significantly affected agricultural commercialisation of farmers.

Any development strategies that assist farmers in adopting commercial farming in the highland of developing countries should consider these determinants.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2022-0161

The purpose of this paper is to measure technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from actual inefficiency using comprehensive household-level panel data.

This paper estimates technical efficiency based on the true random-effects stochastic production frontier estimator with a Mundlak adjustment. By utilising comprehensive panel data with 4,694 observations from 39 districts of four major maize-producing regions in Ethiopia, the author measures technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from technical inefficiency. By using competing stochastic production frontier estimators, the author provides insights into the influence of farm heterogeneity on measuring farm efficiency and the subsequent impact on the ranking of farmers based on their efficiency scores.

The study results indicate that ignoring unobservable farmer heterogeneity leads to a downwards bias of technical efficiency estimates with a consequent effect on the ranking of farmers based on their efficiency scores. The mean technical efficiency score implied that about a 34% increase in maize productivity can be achieved with the current input use and technology in Ethiopia. The key determinants of the technical inefficiency of maize farmers are the age, gender and formal education level of the household head, household size, income, livestock ownership, and participation in off-farm activities.

While the findings of this study are critical for informing policy on improving agricultural production and productivity, a few important things are worth considering in terms of the generalisability of the findings. First, the study relied on secondary data, so only a snapshot of environmental factors was accounted for in the empirical estimations. Second, there could be other sources of unmeasured potential sources of heterogeneity caused by persistent technical inefficiency and endogeneity of inputs. Third, the study is limited to one country. Therefore, future research should extend the analysis to ensure the generalisability of the empirical findings regarding the extent to which unmeasured potential sources of heterogeneity caused by persistent technical inefficiency, endogeneity of inputs and other unobservable country-specific features – such as geographical differences.

This paper contributes to the literature on agricultural productivity and efficiency by providing new evidence on the influence of unobservable heterogeneity in a farm efficiency analysis. While agricultural production is characterised by heterogeneous production conditions, the influence of unobservable farm heterogeneity has generally been ignored in technical efficiency estimations, particularly in the context of smallholder farming. The value of this paper comes from disentailing producer-specific random heterogeneity from the actual inefficiency.

The authors investigated cocoa farmers' access to subsidized fertilizer in Ghana and implications on productivity.

Primary data were sourced from 435 cocoa farmers. Cragg hurdle and two-step Tobit model with continuous endogenous regressors/covariates were applied for the drivers of cocoa farmers' participation in fertilizer subsidy programme and productivity. Propensity score matching (PSM), inverse-probability weights (IPW) and augmented inverse-probability weights (AIPW) were applied for productivity impact assessment of fertilizer subsidy.

All the farmers were aware of fertilizer subsidy for cocoa production in Ghana. Farmers became aware of fertilizer subsidy through extension officers, media and other farmers. Half of cocoa farmers benefitted from fertilizer subsidy. Averagely, cocoa farmers purchased 292 kg of subsidized fertilizer. Many socio-economic, farm-level characteristics and institutional factors determine cocoa farmers' participation in fertilizer subsidy programme, quantity of subsidized fertilizer obtained and productivity. Beneficiaries of fertilizer subsidy recorded higher cocoa productivity than non-beneficiaries. Hence, fertilizer subsidy for cocoa production in Ghana leads to a gain in productivity.

There should be more investments in fertilizer subsidy so that all cocoa farmers benefit and obtain the required quantities.

The authors provide new evidence on cocoa productivity gain or loss emanating from fertilizer subsidy by combining different impact assessment techniques for deeper analysis: PSM, IPW and AIPW.

Nonfamily farms are responsible for a disproportionate amount of US agriculture production. The importance of these operations to the volume of agriculture production in the United States has led researchers and policymakers to understand nonfamily farms as large commercial operations. This paper examines whether the distinction between family and nonfamily helps explain the financial outcomes of farm operations and households.

We test for differences in financial outcomes of the household and operations of family and nonfamily farms using an Oaxaca-Blinder decomposition. We compare these results to a decomposition of other possible typologies.

We present evidence that nonfamily farms are a heterogeneous group with a majority of small operations that are dominated by a small number of large operations. We discover that differences associated with the family-nonfamily distinction are largely explained by observable farm and operator characteristics that arise mechanically from the definition. However, we find suggestive evidence that family-nonfamily classification captures differences in economic behavior that lead to higher profitability measures to nonfamily farms. We find little evidence of any inherent structural differences between family and nonfamily farms that helps explain financial outcomes related to leverage or household finances.

We conclude that including nonfamily farms in official statistics of farm households may provide a more comprehensive overview of the farm sector, as our results suggest that family and nonfamily farms do not have innate differences that help explain many of their financial outcomes.

We incorporate previously unused data on nonfamily farm households and test the difference in mean financial outcomes between family and nonfamily farms.

This study assesses the extent to which integrated extension services contribute to the adoption of climate-smart agriculture (CSA) innovations within the cotton value chain in Burkina Faso.

To address the research question, a probit multivariate econometric model with sample selection is utilized. The model is applied to a random sample of farmers (n = 510), and the endogeneity is addressed through a control function approach.

The study highlights the central role of value chains, particularly in the cotton sector, in overcoming resource scarcity through integrated extension services. Findings show that smallholder farmers who benefit from sound extension services are more willing to adopt and diversify CSA technologies. These include improved seeds, conservation techniques, adapted planting dates and mechanization. This study confirms the synergistic nature of these technologies and emphasizes that effective climate risk mitigation depends on the combined adoption of CSA technologies.

The use of cross-sectional data limits the analysis of long-term farmer behavior, and due to data limitations, the focus was primarily on the contributions of cotton companies and farmers to climate risk mitigation. Future research using panel data across the value chain could provide a more robust insights for policy decision-making.

The study contributes to the existing body of knowledge by emphasizing the crucial role of integrated extension services within the cotton value chain in developing countries. This highlights the critical benefits for farmers and emphasizes the need to diversify modern technologies to effectively combat climate change and its variability in agriculture.

Beginning Farmer and Rancher programs are available for operators with ten years of experience or less on any farm. These programs support farmers who are starting operations, often without an initial asset allocation. However, some beginning farmers acquire operations that are already established, with substantial assets in place. The authors investigate whether a profitability gap exists between beginning farmers entering the industry ex novo and those operating a preexisting operation and if so, what factors contribute to the gap.

The authors utilize the Blinder-Oaxaca decomposition to determine what drives financial differences between first-generation beginning farmers, second-generation beginning farmers and established farmers using a unique farm-level panel dataset from 1997 to 2021.

Results indicate that first- and second-generation beginning farmers have similar operating profit margins, but first-generation beginning farmers have a statistically higher rate of return on assets than second-generation beginning farmers. Established farmers outperform second-generation beginning farmers on both the operating profit margin and rate of return on assets. These results suggest that economic viability for beginning farmers differs depending upon the initial status of their operation, suggesting that heterogenous policies may be more impactful in supporting various pathways to enter agriculture.

This analysis is the first to identify beginning farmers that enter the industry without an asset base and those that take over a principal operator role on an established farm through an assumed farm transition. The authors quantify differences in financial performance using detailed accrual-based financial data that tracks farms over time in one dataset.

Ecosystem-based livelihood diversification (ESLD) approaches have been identified as one of the best solutions to alleviate poverty and improve living standards in rural communities in developing nations. This study aims to elucidate the motivations that drive Sri Lankan women in rural agri-based community to adopt ESLD activities.

The sustainable livelihood approach (SLA) five pillars were used as a theoretical framework. This study was carried out with women living in farmer families located in Anuradhapura District, Sri Lanka. A purposive sampling technique was used, and semistructured interviews were performed with 46 women in a noncontrived setting. Deductive content analysis approach was used for answering research questions.

Making handcrafts using different plants, composting and home gardening are the major sources of ESLD of women in the study areas. Under the SLA factors, human resources include family size, education, vocational training, age and attitude. Social resources like participation in community work, family support received and becoming members in cooperatives encourage the women to partake in ESLD. Nonagriculture natural resources were considered as an incentive to engage in ESLD. Satisfaction with the income generated by the livelihood, other income sources and loans from the informal sector were the vital financial resources. Regarding the physical resources, the respondents were profound with infrastructure, marketplaces, training centers and tools/equipment.

Knowing the existing ESLD strategies and pointing out the determinant factors affecting women in practicing ESLD activities are unquestionably important in the provision of information to formulate an appropriate strategy for the development of the rural agri-based community.

Little is known about the ESLD efforts and the extent of adoption of ESLD practices by women in rural communities. The findings based on the SLA framework help to understand what is happening in livelihood diversifications in agri-based community and suggest important implications for the development of ESLD for the future.

Outgrower scheme as a contractual agreement between farmers and some funding entities has in recent times found proliferation among resource poor farmers in Ghana, especially in northern Ghana. This contractual arrangement, which involves the provision of farm inputs, and in some cases, technical support by the implementing company and the repayment by farmers with portions of their harvest, is often regarded as an effective way to mutually improve the outcomes of both smallholder farmers and outgrower companies. The study aims to analyse. the level of awareness, nature of input package, determinants of participation and intensity of participation in input credit scheme by smallholder rice farmers in the Mamprugu Moagduri District of Ghana’s North East Region, using the Integrated Water Management and Agriculture Development (IWAD) scheme as a case.

Using a quantitative analytical approach, the study gathers information from 233 randomly selected smallholder rice farmers consisting of 150 participants and 83 non-participants using a structured questionnaire. Descriptive statistics, as well as the Tobit model, are the methods used in the analysis.

The results show that while factors such as age, marital status, number of dependents and farming experience only influenced participation in the scheme, religion, age, sex, number of dependents and farming experience influenced intensity of participation.

This study calls for the adoption of sustainable approaches by input credit companies in their credit support to smallholder farmers rather than the current ad hoc support during each cropping season.

As rural nonfarm activities grow in developing countries, less attention is being paid to the opportunities they may provide for women. The purpose of this study is to examine the gender-differentiated impact of nonfarm diversification strategies in rural Senegal.

This study uses data collected from the Senegalese poverty monitoring survey and employs an instrumental variable (IV) approach and a multinomial endogenous treatment model to investigate the extent to which diversification strategies lead to improved outcomes for rural women and their households.

While nonfarm diversification is a male-dominated livelihood strategy, rural women make the most of it, regardless of whether they diversify into low- or high-return nonfarm activities. At the individual level, diversification improves rural women’s well-being through large income-increasing effects and higher empowerment but has no effect on rural men’s well-being. At the household level, the authors find that, when only women diversify, households have lower per capita income but are less likely to be food insecure than when only men or both genders diversify.

This study is based on cross-sectional data, making it impossible to examine the dynamic effects of nonfarm diversification strategies on well-being outcomes.

This study contributes to the current literature on rural livelihood diversification. While much attention has been paid to the feminization of agriculture, remarkably little is known about the expanding role of rural women in the nonfarm sector.

Access to formal financial services is one of the main obstacles to the adoption of agricultural technologies such as Sustainable Agricultural Practices (SAPs). In order to increase financial inclusion and lessen farmers' liquidity restrictions, Village Savings and Loans Associations (VSLA) are being promoted in rural farming communities. However, there extent to which VSLA contributes to the acceleration of agricultural practices, such as SAP, remains little explored in existing literature. The objective of this study was to quantitatively assess the impact of VSLA on the intensity of adoption of SAPs.

This study used cross-sectional data from 376 farming households in the East Gonja district of Ghana. An Endogenous Poisson Treatment Regression (EPTR) was applied to correct for self-selection bias that might emanate from both observed and unobserved differences in household characteristics.

The empirical results indicated that farmers' engagement in non-farm economic activities, ownership of land and size of agricultural land under cultivation positively and significantly influence the intensity of SAPs adoption. Moreover, participation in VSLA improves the adoption of SAPs, and that VSLA-participants adopted about three more SAPs than they would have if they did not participate in VSLA.

This study re-affirmed the significance of VSLA in rural farming communities and recommend that it should be promoted as an alternative to formal financial services to enhance financial inclusiveness, and consequently boost the uptake of SAPs.

In the search of literature, this study is the first to estimate the impact of VSLA on adoption of SAPs. The use of EPTR helps to bring out the true treatment effects of VSLA on SAPs.