Adoption and impact of integrated rice–fish farming system in Bangladesh

About the authors

Poor financial environment of rural developing economy leads to underinvestment and inefficiency of marginal and small-scale farm households. Development interventions for providing improved market access and credit at subsidized interest rate to small farm households are therefore considered as the preconditions in the transformation process of rural agrarian economy. Hence, the question of whether access to resources influences farm households’ production decisions, performance and efficiency is very important. In this paper, we attempt to estimate the impact of a subsidized credit on farm output and efficiency of small and marginal rice farmers of Bangladesh. Using survey data of a field experimental study, we show that relaxing the credit constraint has significant positive impact on farm output and efficiency. On an average, small-scale rice farms with access to subsidized credit are found to be 13% more efficient than farms with no credit access. The increase is 76% on average when we use the randomized access to credit as instrument for farm credit. We also examine the impact heterogeneity of access to credit by rice variety. We find that cultivation of modern Hybrid rice variety is significantly higher (on average 17%) for treatment farm households compare to the control group. However, we do not find much evidence of heterogeneous productivity impact of access to credit by HYV vs. Hybrid rice. Combining the results, we conclude that access to credit is effective in improving the overall output and efficiency of marginal and small-scale rice farm households. Thus, policies enhancing the credit access of marginal farmers are important for sustainable agricultural development of rural developing economy.

This chapter applies the first-order dominance (FOD) approach to assess spatial and temporal multidimensional welfare in Zambia from 1996–2010. Additionally, it extends the methodology to evaluate welfare by rural agricultural strata and urban housing cost areas. This modification is particularly insightful in rural areas, where monetary poverty has made only modest gains over the study period. Finally, it considers the sensitivity of FOD results to indicator definitions in the context of data limitations. FOD analyses indicate broad-based gains in multidimensional rural welfare driven by small-scale farm and non-agricultural rural households. Despite these welfare gains, rural households, particularly small-scale farm households, continue to lag significantly behind their urban counterparts.

The construction and development of digital infrastructure have emerged as a crucial indicator of national competitiveness, which holds significant importance in driving the sustained growth of the national economy and the comprehensive advancement of society. This paper explores the impact of digital infrastructure on farm households’ scale management, aiming to reveal the role and potential of digital technology in agricultural modernization. Additionally, it seeks to offer a scientific foundation for the government to formulate agricultural policies and advance agricultural modernization. Using the OLS (Ordinary Least Squares) model, moderating effect model, and other methods, this study investigates how digital infrastructure affects farm households’ scale management based on micro-level research data of 2510 farm households from the CRRS (China Rural Revitalization Survey). The following conclusions are drawn: Firstly, the enhancement of digital infrastructure can motivate farm households to expand the land management area and increase the unit output of land. Secondly, farm households’ digital literacy positively moderates the effect of digital infrastructure on their land unit output; moreover, digital skills training for farm households exhibits a positive moderating effect on the influence of digital infrastructure on their management area. Finally, there is a heterogeneity in the impact of digital infrastructure on farm households’ scale management. Specifically, the promotion of farm households’ scale management is stronger in plain areas and weaker in hilly and mountainous areas; stronger for middle-aged and older and small-scale farm households; and weaker for youth groups and large-scale farm households. Based on this, this paper suggests increasing the investment in digital infrastructure construction, improving farm households’ digital literacy, carrying out digital skills training, and formulating differentiated regional policies for reference.

Contract Farming in Vietnam: Empirical Research on Marketing Determinants, Farm Performance and Technical Efficiency of the Export-oriented Rice Sector in the Mekong River Delta

Adequate access to credit is necessary for the sustainable development of agriculture. This study uses a double hurdle model to investigate what affects farming households’ credit participation and amount, and a Probit model to find out credit constraints. For this purpose, the data from a survey of 292 farming households in Afghanistan was utilized. The study finds that households obtain credit for their agricultural activities from various formal and informal sources. The results of the double hurdle model reveal that the financial activities of the households were positively determined by crop diversity, education, number of adults in a household, size of land, and access to extension. Non-agricultural income decreases the likelihood of participation. The results of the analysis of credit constraints indicate that formal credit did not help small-scale and remoter farming households; however, these households relied on informal credit, especially when they faced income shock. Furthermore, religious belief increased the chances of avoiding formal credit but not informal credit. It is suggested that formal credit should be expanded to rural areas, especially to small-scale farming households. Policy makers should also consider increasing access to extension. Formal financial institutions should provide Sharia-compliant credit, which increases the confidence level of households in using formal credit in Afghanistan.

This paper investigates the associations between agricultural diversification and dietary diversity among men, women and children of farm households in Bangladesh. Using three waves of nationally representative Bangladesh Integrated Household Survey (BIHS- 2011-12, 2015 and 2018) data and a panel data model, the study found that agricultural production diversification can emphasize the dietary diversification across the life cycle of farm household members. The balanced panel data reveals that agricultural production diversification has a statistically significant and positive impact on dietary diversity of individual members (men, women and children) of farm households. Moreover, other important factors that impact on agricultural diversification and improve dietary diversity like women's education and employment, commercialization of farm households, access to non-farm income sources, and access to information facilities also have a strong association in improving dietary status, food and nutritional security as well. Although there is currently limited diversity in the diets of adult men, women and children of rural farm households, the situation can be improved over time with proper and consistent support. The findings suggest policy interventions should target not only agricultural diversification but also improve women's education and on and off farm employment opportunities and facilitate better access to information for rural households. These recommendations can support improved dietary diversity for all household members under different settings.

This study analyzed the effect of social capital and other relevant factors on poverty of farm households and identified constraints militating against effective social capital formation among poor rural farm households belonging to associations in Akwa Ibom State, Nigeria. A multi-stage sampling technique was utilized to choose 180 rural farm households within the research location. The FGT methodology was used to generate indices of poverty. Descriptive statistics, Tobit model and factor analytical procedures were employed to analyze the objectives of the study. The estimated model showed high degree of fitness, thus justifying the estimation method used. The results revealed that, the following social capitals: farm size acquired from the association, income derived from membership of association, number of visits of extension agents, interest amount paid on loan acquired from association, fertilizer, seeds, pesticides and farm land acquired from the association have a significant negative relationship with the poverty of rural farm households in the study area. By implication, increase in the stock of these social capitals by poor farm households would significantly enhance the reduction of poverty depth among them. Moreover, other factors which affected farm household poverty status were sex of household heads, age, household size, years of formal education, farm income and ownership of assets. The results also found 8 categories of constraints militating against effective social capital formation among poor rural farm households. The constraints categories are: leadership, management style and low income; financial constraint and unconcerned attitude of members towards group activities; executive characters; ineffective coordination and unfair distribution of benefits to members; lack of seriousness of members; poverty; illiteracy and incompetence as well as defaults and partiality. From the result, it is concluded that social capital accumulations reduce the probability of being poor. Based on the high percentage of poverty prevalence in the State, it is concluded that poverty is endemic in the rural areas of Akwa Ibom State and specifically among farm households. This study lends support to recent emphasis on investing in social capital as a major means of poverty reduction in the rural areas.

Rural farming households in Sub-Saharan Africa, facing limited land access, engage in land purchase, rental, and other land access practices. However, the highly unregulated land markets expose these farmers to wide-ranging vulnerabilities. In this study, we investigated the land access mechanisms and the related constraints among the small-scale farmers in the densely populated Eastern part of The Democratic Republic of the Congo (DRC). We randomly selected 240 consenting farmers for inclusion in the study and collected data using semi-structured interviews to obtain data on land access characteristics. Then, the data was subjected to descriptive statistics to obtain measures of central tendency and dispersion on the responses and correlation statistics to understand the patterns and relations of factors affecting the land access and strategies used to cope with the limited land situation in the South Kivu province of DRC. Our results showed an insecure land tenure system among smallholder farmers. Most of the farmers in the study purchased and leased land to cope with poor land access and, in so doing, faced high price-related limitations that were unsustainable to these farmers; they also faced highly restrictive leasehold contracts. Given the limited access to financial resources and support, improving regulations of land markets and resource support interventions could promote land access among these smallholder farmers. We conclude that the challenges of land access and the current methods farmers use to obtain additional land among the smallholder farming households in the south Kivu province of DRC are precarious and unsustainable and continue to pose a food insecurity and poverty risk among these farmers. We recommend developing and implementing measures to support resource access by these farmers, such as finance, farmer-focused cooperative societies, and better land policy reforms and tenure systems to improve access to land among these farmers and farmers facing similar scenarios in other parts of sub-Saharan Africa.

The study has investigated the growth in income of rural households in Bangladesh with a view to analysing distributional consequences in the post-liberalisation era. Using data from secondary sources, it has applied a quintile-growth approach by dividing each group of households into five income clusters (quintiles) to analyse the incidence of growth in real income. It has found that although all groups of rural households experienced a moderate to high increase in real income, non-farm households experienced a larger increase than farm households due to a large reduction in consumer price. Farm households gained from the increase in productivity but experienced losses from producer price reduction. The two opposite forces – increase in productivity and reduction in producer price – offset the effects of each other, thereby affecting the income growth of farm households. Amongst the farm households, large and medium farmers gained the most and small farmers gained the least from the growth in real income, indicating that rich households experienced a much higher increase in real income than poor households – thereby adversely affecting the distribution of income and widening the income gap between rich and poor households. These findings demonstrated that while agricultural trade liberalisation benefited rural households generally, the benefits were not distributed equally and in fact, inequality increased amongst rural households. This study argues that the growth in real income of rural household was not pro-poor during 1985- 86 to 2005. This study suggests that agricultural trade liberalisation contributed to higher growth in the rural economy but it contributed to greater inequality in income distribution amongst the rich and poor income groups (quintiles). Government should reduce inequality through policy interventions with income transfer from the rich to the poor.

European politicians encourage the income diversification of rural households through various measures. Although a knowledge of farm households’ potential for non-farm income diversification seems important for finely targeting such policy measures, thus far no attempt has been made to summarise the various determinants of income diversification in a single figure. This contribution aims to close this gap. A composite fuzzy indicator that measures farm households’ potential for non-farm income diversification is developed and applied to 626 small-scale farm households in Bulgaria, Hungary, Poland, Romania and Slovenia. The indicator summarises the incentives and capacities for non-farm income diversification on the individual household member level and on the household and regional levels in a single measure using fuzzy logic methodology. The composite fuzzy indicator performs well and the results for the single small-scale farm households can easily be retraced. The indicator not only singles out the households that have the potential for non-farm income diversification but also shows the reasons for this. The indicator shows that most of the 626 households studied have a high potential for non-farm income diversification and that all are pushed toward diversification by the small size of their farms. The composite fuzzy indicator also identifies farm households that are trapped in a desperate situation due to unfavourable chances of finding a job in the labour market and long distances to the nearest large urban centre. Decision makers could utilise the composite fuzzy indicator to finely target diversification measures to the multifaceted conditions of farm households.

Modelling the impact of market imperfections on farm household investment in stand-alone solar PV systems

Tea is a major economic activity in Kenya. However, its contributions in eradicating poverty has not been studied and documented, especially on small-scale tea farmers. The purpose of this study was to investigate the effect of farming household characteristics on poverty levels among tea farmers in Konoin sub-County. The objectives of the study were to determine the effect of family size, age, gender of household head and number of labour units engaged on poverty levels among tea farmers. To achieve the purpose of the study, the hypothesis tested was: farm household characteristics (family size, age gender of household head, number of labour units engaged) have a significant effect on poverty levels among tea farmers. The sample that took part in the study was 380, selected from a target population of approximately 36,000 small-scale tea farming households. The sample was selected proportionately from 12 tea catchment areas. Generalized Linear Model (GLM) and censored Tobit regression models were used to analyze data. The household characteristics; household size, gender of the household’s head, labour units engaged, age and dependency ratio were found to significantly influence the income levels of the households. Family size was found to be significant in predicting the poverty levels of tea farming households, while the age of the household head and dependency ratio significantly influence both poverty gap and depth of the households. As a recommendation, interventions targeting on family size closely linked to dependency ratio and the age of the households should more inform policy formulation targeting poverty reduction among small-scale tea farming households.

Sustainable agricultural technologies have impacted positively on staple crop yields in Asia and some parts of Sub-Sahara Africa. However, the adoption of similar technologies in vegetable subsector is still low among small-scale farmers in Tanzania. Several efforts aimed at promoting the adoption of the technologies such as improved vegetable varieties, mineral fertilizers, manure and pest management practices to raise output, have not yielded the desired impacts. We examine dynamics of farmers’ adoption of these technologies and the factors influencing technology choice. We also predict the peak level and speed of adoption of these sustainable technologies. Findings show that complementarities exist among improved varieties, fertilizers and pest management practices, while tradeoffs exist between manure and mineral fertilizers. These complementarities and tradeoffs should be sufficiently exploited for farmers to adopt technologies that are suited for their specific circumstances. Better knowledge, access to credit, group membership, farmer participation in demonstration trials, and, more substantial livestock holdings drive technology adoption decision. Technologies have different peak levels of adoption, which are reached at different time intervals. The policy option is to strengthen collaborative efforts to scale out sustainable agricultural technologies to respond to the increasing demand for nutrient-dense vegetables for income, food and nutrition security.

This survey study was conducted in Tangail, Jamalpur, Bogra, Sirajganj, Pabna and Thakurgaon districts for household farming, and in Bhola, Noakhali, Lakshmipur and Patuakhali districts for bathan farming to undertake an assessment on the management factors in household and bathan farming for identifying the potentiality and constraints in milk production from buffalo. A 90 number of pre-designed questionnaire was used for data collection by direct interviewing of buffalo farmers. From this study, it was revealed that 82% of the farmers have 1 to 3 buffalo per household and 73% of the farmers have 51 to 200 buffalo per bathan. Buffaloes were raised in homestead and approximately 5-7 hours were grazes per day in household farming. Small quantity of concentrate feeds were offered to buffalo by the rich farmers during dry season. On the other hand, in bathan, farmers were fully depended to feed the buffalo on grazing at public land. In household, the average daily milk production was 3 to 8 liters and total milk yield was 799 liters in a lactation length of 270 days. In bathan, the average daily milk production was 1 to 2 liters and total milk yield was 435 liters in a lactation length of 215 days. The average age of first calving, service per conception, gestation period and calving interval were 39 months, 1.9 numbers, 310 days and 490 days, respectively in household farming. The average age of first calving, service per conception, gestation period and calving interval were 40 months, 2.1 numbers, 315 days and 530 days, respectively in bathan farming; however, further study is required on the buffalo nutrition in the bathan farming.Bang. J. Anim. Sci. 2016. 45 (1):69-77