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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.

Farmers' inability to successfully participate in the maize value chain due to the threats of some risk factors is one of the key reasons for rising food insecurity. This study analyses farmers' responses to risks involved in maize production in Cameroon. Data on maize production risks were collected from smallholder maize farmers operating in selected communities along the River Sanaga. The Criticality Risk Matrix model was employed to determine the severity of these risks based on their criticality and likelihood of occurrence. After deriving farmers' risk preferences from the categorization of their farm decisions, a Multinomial Logit Regression model was then used to investigate the extent to which risk severity influences farm decisions. Additionally, a Graded Response Model was utilized to predict farmers' risk responses by categorizing their probable patterns of action. The results revealed that production risks with fatal consequences such as pest invasion had a negative significant influence on-farm decisions and their perceived threats were more likely to provoke risk-averse responses. Less fatal risk threats such as fertilizer unavailability, poor farm infrastructure, labour shortage, and health risks were all significant and induced risk-averse responses from farmers. Furthermore, gender, experience and employment status also significantly influence farm decision-making. The farmers’ response patterns presented on the Graded Response Model Characteristic Curves further indicated the willingness of farmers to continue farm activities despite perceived risks and the probability of engaging in diversification as an added measure to mitigate risks. We recommended that more effective measures for information dissemination on production risks as well as sustained Extension Service support to mitigate these risks be made available to farmers.