Agricultural extension service, technology adoption, and production risk nexus: Evidence from Bangladesh.

Rice production is inherently risky and volatile, and farmers in Bangladesh face a wide range of risks, including weather, pest and disease attacks, interruptions to input supply, and market-associated risks. Moreover, poor farm households often perceive risks in adopting new technology, even though it could improve productivity and food security. Such households are thus caught in a "risk-induced trap" that precludes them from realizing the benefits of technological innovation. Extension service is one way to help farmers improve risk management skills and escape risk-induced traps, but there is limited empirical analysis of its impact in Bangladesh. The objective of the study is to measure the nexus between agricultural extension services, technology adoption, and production risks as well as women empowerment in agriculture index. IFPRI utilized stratified random sampling to determine the 5603 households in 2018 (which is nationally called the BIHS-2018 dataset) from rural and pre-urban areas of Bangladesh. Out of these 5603 households, 2663 households were specifically selected for the study related to rice farming to achieve the main objective of the study. Focusing on rice farming, a moment-based Poisson regression model is estimated with 2SLS and identifies risks associated with key technologies and potential productivity and risk-reducing effects. The results revealed that wealthier households are more likely to adopt technology for minimizing production risk and women's empowerment which can positively affect productivity by mitigating risk. The result revealed a positive and significant difference in WEAI between the AES participant and non-participant group. We find that engagement in agricultural extension services was associated with technology adoption and production risk reduction. The agricultural extension services increased, technology adoption by 4.2 % and decreased production risk by 2.4 %. Based on the findings, it is concluded that more comprehensive extension services can enhance rice production and ameliorate farmers' risk in rice production to some extent.

The impact of COVID-19 on livelihood assets: a case study of high-value crop farmers in North-West Bangladesh.

The COVID-19 pandemic has had a catastrophic impact on public health, extending to the food system and people's livelihoods worldwide, including Bangladesh. This study aimed to ascertain the COVID-19 pandemic impacts on livelihood assets in the North-Western areas (Rajshahi and Rangpur) of Bangladesh. Primary data were collected from 320 farmers engaged in high-value agriculture using a multistage sampling method. The data were analysed using first-order structural equation modelling. The findings reveal a significant impact (p < 0.01) of the pandemic on all livelihood assets in Bangladesh. Notably, human assets exhibited the highest impact, with a coefficient of 0.740, followed sequentially by financial (0.709), social (0.684), natural (0.600), physical (0.542), and psychological (0.537) assets. Government-imposed lockdowns and mobility restrictions were identified as the major causes of the pandemic's negative effects on livelihoods, which included lost income, rising food prices, decreased purchasing power, inadequate access to food and medical supplies, increased social insecurity, and a rise in depression, worry, and anxiety among farmers. The effects of COVID-19 and associated policy measures on the livelihoods of high-value crop farmers have reversed substantial economic and nutritional advances gained over the previous decade. This study suggests attention to the sustainable livelihoods of farmers through direct cash transfer and input incentive programs to minimize their vulnerability to a pandemic like COVID-19 or any other crisis in the future.

Gender differences in job satisfaction among gig workers in Bangladesh.

The gig economy (temporary, contract, and freelance online jobs rather than permanent positions) is a component of the fourth industrial revolution and preview of future work. The rise of digital platforms has increased career opportunities and income potential, particularly for women. Yet, the sex-disaggregated evidence regarding platform usage, employment characteristics, and working motivations and satisfaction remains untapped. Using data from a quantitative survey of Bangladeshi gig workers (242 men and 201 women) conducted in 2022, this paper addresses these gaps between male and female workers. The gig economy appears to be gender-segregated across digital platform usages and working categories. Women tend to prioritize digital work options for managing multiple responsibilities, while men are often driven by the potential for higher income. This study conceptually utilized the two-factor theory and empirically ordered a probit model to identify gender differences in job satisfaction. Job satisfaction was significantly increased by work-life balance, monthly income, and social-media connection, while an increase in working hours, complexity in payment systems, and unstable networks all led to a decrease in job satisfaction. The findings have implications for the future growth of the gig economy, provide new insights into gender differences in job satisfaction, and underscore the need for gender-sensitive policies in the online labor market.

Does rural transformation affect rural income inequality? Insights from cross-district panel data analysis in Bangladesh.

Rural transformation plays a crucial role in enhancing the income and employment prospects of the rural labor force. We investigate the effects of rural transformation on rural income inequality at the district level in Bangladesh using data from five years of nationally representative Household Income and Expenditure Surveys. The Gini coefficient is used to measure rural income inequality. In contrast, the share of high-value agricultural outputs and the share of rural non-farm employment are used as indicators of rural transformation. We find that rural income inequality is positively associated with the share of high-value agricultural outputs and the share of rural non-farm employment. The non-linear regression result shows an inverted U-shaped relationship between rural transformation and income inequality, which indicates that income inequality initially increases with rural transformation but decreases in the long run. Additionally, we find that rural income inequality is positively correlated with the proportion of household education expenditures, agricultural rental activity, and the share of remittances. This study also reveals that income inequality in rural areas of Bangladesh has a significant negative correlation with the government's social safety net program.

Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm.

Droughts pose a severe environmental risk in countries that rely heavily on agriculture, resulting in heightened levels of concern regarding food security and livelihood enhancement. Bangladesh is highly susceptible to environmental hazards, with droughts further exacerbating the precarious situation for its 170 million inhabitants. Therefore, we are endeavouring to highlight the identification of the relative importance of climatic attributes and the estimation of the seasonal intensity and frequency of droughts in Bangladesh. With a period of forty years (1981-2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotranspiration Index (SPEI). Out of 24 ML algorithms, the four best ML methods, ranger, bagEarth, support vector machine, and random forest (RF) have been identified for the prediction of multi-scale drought indices. The RF classifier and the Boruta algorithms shows that water balance, precipitation, maximum and minimum temperature have a higher influence on drought intensity and occurrence across Bangladesh. The trend of spatio-temporal analysis indicates, drought intensity has decreased over time, but return time has increased. There was significant variation in changing the spatial nature of drought intensity. Spatially, the drought intensity shifted from the northern to central and southern zones of Bangladesh, which had an adverse impact on crop production and the livelihood of rural and urban households. So, this precise study has important implications for the understanding of drought prediction and how to best mitigate its impacts. Additionally, the study emphasizes the need for better collaboration between relevant stakeholders, such as policymakers, researchers, communities, and local actors, to develop effective adaptation strategies and increase monitoring of weather conditions for the meticulous management of droughts in Bangladesh.