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This study examines the adoption drivers of scale-appropriate mechanization in Nepal's maize-based farming systems. The authors also assess the contribution of scale-appropriate mechanization to the United Nations Sustainable Development Goals (SDGs) of zero hunger (SDG2) and no poverty (SDG1).

Propensity score matching and doubly robust inverse probability-weighted regression adjusted methods were applied to estimate the effects of mini-tiller adoption. These methods control the biases that arise from observed heterogeneities between mini-tillers users and nonusers.

The study findings show that farm size, labor shortages, draft animal scarcity, market proximity, household assets and household heads' educational level influence the adoption of mechanization in Nepal. Mechanized farms exhibited enhanced maize productivity, profits and household food self-sufficiency. Reduced depth and severity of poverty were also observed. Nevertheless, these effects were not uniform; very small farms (≤0.41 ha) facing acute labor shortages benefited the most.

The study results suggest that policymakers in developing nations like Nepal may wish to expand their emphasis on scale-appropriate mechanization to improve farm productivity and household food security, reduce poverty and contribute to the SDGs.

This first-of-its-kind study establishes the causal effects between scale-appropriate farm mechanization and SDG1 (no poverty) and SDG2 (zero hunger) in a developing nation.

Total factor productivity (TFP) has become a prominent concept in agriculture economics and policy over the last three decades. The main aim of this paper is to obtain a detailed picture of the field via bibliometric analysis to identify research streams and future research agenda.

The data sample consists of 472 papers in several bibliometric exercises. Citation and collaboration structure analyses are employed to identify most important authors and journals and track the interconnections between main authors and institutions. Next, content analysis based on bibliographic coupling is conducted to identify main research streams in TFP.

Three research streams in agricultural TFP research were distinguished: TFP growth in developing countries in the context of policy reforms (1), TFP in the context of new challenges in agriculture (2) and finally, non-parametric TFP decomposition based on secondary data (3).

This research indicates agenda of future TFP research, in particular broadening the concept of TFP to the problems of policy, environment and technology in emerging countries. It provides description of the current state of the art in the agricultural TFP literature and can serve as a “guide” to the field.

In the developing countries, formal credit has dominant role for the development of agriculture sector. It increases the farmer's purchasing power for better farm inputs and agricultural technology for high crop productivity. The main purpose of this study is to examine the influence of socioeconomic characteristics of smallholder farmers for credit demand in Sindh, Pakistan.

A cross-sectional data set randomly collected from 90 smallholder farmers in Thatta district, Sindh, Pakistan, is examined. Descriptive statistics, correlation and the OLS regression method were used to demonstrate the important factors affecting the demand for formal credit.

The results revealed that formal education, experience of farming, landholding size, road access and extension contacts positively and significantly influenced the demand for formal credit.

This study is the first, to the best of authors' knowledge, to demonstrate the influence of various socioeconomic characteristics of smallholder farmers on demand for formal credit in Sindh, Pakistan. It also illustrates the imperative contribution to the literature regarding credit access and demand to improve the agricultural productivity.

This article aims to investigate the financial constraints and nonlinearity of farm size growth.

Farm size growth is measured with land, labor and output using data from the Farm Accountancy Data Network (FADN) for Hungary and Slovenia. A dynamic panel model is applied to assess financial constraints and nonlinearity of farm size growth.

Results show that, except for land in Slovenia and output in Hungary, liquidity constraints are less important for farm size growth than endogenous factors based on farm size growth expectations and steady farm size restructuring. Smaller farms are growing faster than larger ones. The hypothesis that a higher level of subsidies would increase farm size is not supported for Hungary. When farms reach a certain size, the land area of the largest farms increases. Farm debts in Hungary are linked with land growth and in Slovenia with output growth.

Further research on the impact of liquidity constraints and subsidies can be conducted at a disaggregate farm-type level to examine whether there is variability in the underlying interlinkages at the farm-type specialization level.

The implication that farm size growth is dependent on initial size and that smaller farms are growing faster than bigger ones indicates that it is not necessary to favor the fastest growing smaller farms thus supports the application of a non-discriminatory farm size policy for observing farm size structural changes.

The dynamic panel econometric model that incorporates cash flow as a measure of financial constraints provides insight into farm size growth in cross-country comparison in relation to potential farm liquidity constraints, farm debt and the nonlinearity of farm size, which information is of relevance to policy makers and practitioners.

This paper investigates the impact of bank credit on agricultural productivity in the Central African Economic and Monetary Community (CEMAC) from 1990 to 2019. Studies’ results on the impact of bank credit on agricultural productivity are not conclusive. The studies demonstrate diverse outcomes which are debatable. The results are conflicting.

Agricultural value added (AGRVA) to the gross domestic product (GDP) proxies agricultural productivity while domestic credit to the private sector by banks (DCPSB), broad money supply, land, inflation (INF), physical capital (PHKAP) and labour supply are explanatory variables. The autoregressive distributed lag technique is utilized.

The co-integration test results show a long-run co-integration among the variables. The findings disclose that DCPSB, land and PHKAP impact positively on the AGRVA. Broad money supply, INF and labour impact negatively on the AGRVA to the GDP.

The results suggest that the CEMAC governments should encourage effective ways to increase bank credit flow to private enterprises in the agricultural sector through efficient bank's intermediation.

The governments should create more agricultural banks and improve the operation of existing ones to ensure direct credit to agricultural activities. The Bank of Central African Economic and Monetary Community should apply aggressive policy which eliminates all the bottlenecks undermining credit flow to the private sector in mutualism with agricultural productivity.

The commercial banks should give more credit to private sector to mutually benefit the agricultural sector and the banking sector. The governments of the CEMAC economies should expand funding into the capital market which considerably boosts agricultural productivity.

Studies’ results on the impact of bank credit on agricultural productivity are not conclusive. The studies demonstrate diverse outcomes which are debatable. The results are conflicting; some reveal positive impacts, some show negative impacts and others indicate U-shape behaviour. Hence, research is required to fill the lacuna.

This study analyses income inequality and distribution patterns among key actors in the cassava value chain. The study also identifies factors that influence profit of key actors in the cassava value chain.

The study was conducted in Oyo State, Nigeria, using primary data from 620 actors, consisting of 400 farmers, 120 processors and 100 traders in the cassava value chain. The Gini coefficient was used to estimate income inequalities within and between actors. Multiple linear regression was applied to identify factors that influence the profit of the actors in the cassava value chain.

The result shows a gender pattern in the participation in the cassava value chain: men dominate in the production, whereas women mostly engage in processing and marketing of processed cassava products. We also find that incomes are unequally distributed among actors, favouring traders and processors more than farmers in the value chain. Women are better off in processing and trading of value-added products than in the raw cassava production. Spatial differences also contribute to income inequality among farmers in the cassava value chain. An increase in farmers and processors’ incomes reduces inequality in the value chain while an increase in traders’ income widens inequality. Age is significantly negatively correlated with actors’ profit at 1%, while educational level significantly increases their profit at 5%. Processors and traders with large households have a higher profit. We also find that farm size, experience and labour input have significant positive effects on farmers’ profit only at 5%. Membership in an association increases farmers and processors’ profit at 1 and 10%, respectively.

The study recommends that agricultural policies that promote agrifood value chains should aim at minimizing income inequality by targeting vulnerable groups, particularly female farmers to achieve sustainable development in rural communities.

Existing studies recognise income inequality in agricultural value chains in sub-Saharan Africa. However, there are few rigorous quantitative studies that address this pressing issue. Our paper fills this knowledge gap and suggests ways to minimise income inequality in the agri-food value chain, using the example of the cassava value chain in Nigeria.

Higher productivity in the potato value chain in Rwanda requires good quality seed potatoes. The article analyzes how innovations were introduced in the framework of a development project resulting in a partnership between a firm and two educational institutions to produce better seed potatoes, using the Triple Helix approach.

In the Triple Helix model government, academia and the private sector work together to develop and introduce innovations. This led to producing and introducing improved seed potatoes at an affordable price through a public private partnership (PPP). Interviews with experts and a survey of local producers were carried out to identify factors influencing the success of the partnership.

A Service, Training and Innovation Center (STIC) has been created to produce the first clean potato seeds in Africa on a commercial scale, based on cultivation of in vitro potato plantlets and aeroponics to produce mini-tubers. It is called Seed Potato Advancement Centre, an education–enterprise partnership, using these plantlets to produce mini-tubers through aeroponics. Seed multipliers are responsible for the next three stages of seed multiplication. The final product is the certified potato, sold to ware potato farmers. The availability of disease-free seed potatoes in Rwanda gives a boost to the potato value chains and contributes to food security. The partnership was successful because of the support from the government and donors, with the private sector and the extension services helping to implement the innovations effectively.

The limitation is that the number of experts interviewed is limited and the survey did not only deal with potato-related activities. The focus is on one region only, but the most important potato growing area in Rwanda.

STICs function as a tool for cooperation between government, private sector and the knowledge sector to achieve commercial and development goals. They function as a channel for technology transfer. They allow applied research, including agronomic research; information collection; and dissemination, networking, training, organization of outreach activities. The model can be repeated in other sectors and countries.

The paper looks at a PPP in agriculture with educational institutions. Second, the Triple Helix and value chain literature is used to study the introduction and implementation of appropriate innovations, while factors determining the success of the partnership were identified. This concerns the first production of clean seed potatoes in Africa on a commercial scale.

In societies with strong presence of Islam, Islamic instruments with more scope for fairness and equity can be innovatively harnessed to play an increasing role in the development process and poverty alleviation schemes. Poor smallholder farmers dominate agricultural production in many developing countries and contribute a significant portion of global food production. This paper aims to develop a scheme to improve poor smallholder farmers’ vulnerable financial situation through the application of Zakah and Salam contract, using Bangladesh as a case study. Secondary goals are to show the effect of the scheme on food security and relevance to Nigeria.

The authors explore the existing traditional modes of financing available to poor smallholders, identify their challenges and propose an appropriate Islamic financing scheme.

With the Zakah-based Salam forward contract, the proposed scheme would procure food through Institutional Demand to offer interest free financing, fair price and access to new marketing channels and reduce income uncertainty for the rural smallholders. The discussions indicate that the local food security will be enhanced through incentivized farming activities and disbursement of food from the food bank to the Zakah-eligible food insecure local people.

This proposal brings forth a potentially powerful idea that needs further empirical validation.

The religion-based Institutional Demand initiative to promote smallholder agricultural development and social protection is a novel one. The attempt to apply the framework to Nigeria context shows the potential of the framework to generalize for other Muslim developing countries with similar characteristics, especially the poorer agriculture-based countries.

The purpose of this paper is to evaluate the impact of short-term loan (STL) vs long-term loan (LTL) on wheat productivity of small farms in Sindh, Pakistan.

The econometric estimation is based on cross-sectional data collected in 2016 from 18 villages in three districts, i.e. Shikarpur, Sukkur and Shaheed Benazirabad, Sindh, Pakistan. The sample data set consist of 180 wheat farmers. The collected data were analyzed through different econometric techniques like Cobb–Douglas production function and Instrumental variables (two-stage least squares) approach.

This study reconfirmed that agricultural credit has a positive and highly significant effect on wheat productivity, while the short-term loan has a stronger effect on wheat productivity than the long-term loan. The reasons behind the phenomenon may be the significantly higher usage of agricultural inputs like seeds of improved variety and fertilizers which can be transformed into the wheat yield in the same year. However, the LTL users have significantly higher investments in land preparation, irrigation and plant protection, which may lead to higher wheat production in the coming years.

In the present study, only those wheat farmers were considered who obtained agricultural loans from formal financial institutions like Zarai Taraqiati Bank Limited and Khushhali Bank. However, in the rural areas of Sindh, Pakistan, a considerable proportion of small-scale farmers take credit from informal financial channels. Therefore future researchers should consider the informal credits as well.

This is the first paper to examine the effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan. This paper will be an important addition to the emerging literature regarding effects of credit studies.

This paper aims to examine the competitiveness trends and rankings of the Irish dairy sector at the farm and trade levels, relative to selected European Union (EU) Member States, in the context of the removal of the EU milk quota in 2015.

Competitiveness indicators including partial productivity measures and accountancy-based indicators were used for farm competitiveness, and net export market share and normalised revealed comparative advantage (NRCA) were used for export competitiveness.

Amongst the countries examined, Ireland had the highest growth in partial productivity indicators and was ranked first with the lowest total costs and cash costs per kg of milk solids post-quota. However, the total economic cost sub-components showed that Irish dairy farmers had high opportunity costs for owned land and labour. While Irish dairy products such as butter and powders have demonstrated growth potential in competitiveness post-quota with Irish butter and whey ranked in top three relative to other countries, other products, i.e. cheese and liquid milk have declined in competitiveness according to key export competitiveness indicators used.

The challenge for Irish dairy farmers is how to mitigate relatively high land and labour costs, which can limit farm competitiveness in the long run. The key players in the Irish dairy industry can now better position themselves in the global dairy market, recognizing the competitiveness dynamics of the different dairy products and their competitors. Policy implications and further areas of research have been identified to help improve the overall competitiveness position. It is surprising that Irish butter is a leader in the EU, yet not much research has been done to understand the market dynamics of this sector.

To the best of the authors’ knowledge, this study is the first of its kind to use both farm and export competitiveness measures to analyse the Irish dairy industry relative to other countries in the context of quota abolition. Unlike previous studies on dairy export competitiveness, this study has disaggregated the processed dairy products, which allowed for the ranking of countries and comparability across countries using NRCA.