Rice is the staple food for about half of the world's population and mills are the essential processing link between farmers and consumers, making rice milling one of the most important agro-processing sectors globally. This paper assesses changes in rice and paddy prices, and processing margins during the COVID-19 pandemic shock through the lens of rice mills in Myanmar. Our data, collected through telephone surveys with a large number of medium- and large-scale rice millers in September 2020, reveal significant disruptions from the COVID-19 pandemic, including transportation restrictions, employee lay-offs, and reduced operations relative to normal times. However, milling margins, and paddy and rice prices were mostly stable, showing only minor increases compared to 2019. Rice prices increased most for the varieties linked to export markets, though the gains were mostly passed through to farmers as higher paddy prices. Similarly, higher rice prices achieved by modern mills-due to extra processing-were mostly transmitted to producers. Our results also highlight the major importance of byproducts-broken rice and rice bran-sales to overall milling margins as byproduct sales allowed mill operators to sustain negative paddy-to-rice margins.

Adoption of new plant varieties has played a significant role in eradicating global hunger. Previous research has mainly focused on farmer adoption and impact of new crop varieties, although upstream adoption of technologies in plant breeding can generate substantial multiplier effects on downstream impacts. This study moves upstream in the innovation system to generate policy advice on adoption and transfer of accelerated rice breeding technologies. More specifically, we assess the determinants of global adoption of rapid generation advance (RGA) through a sample of 158 rice breeders operating in various research institutes worldwide. Moving upstream in the innovation system has important theoretical and empirical implications due to the smaller number of decision-making units in the adoption process and the increasing role of institutional and managerial factors that may overrule individual adoption motivations. We revisit multi-stage models and devise the most robust estimation method that can be used in this situation. To generate insights on the impact of individual versus institutional adopter characteristics on upstream technology adoption, we juxtapose the response curves of the determinants of RGA adoption in rice breeding among alternative adoption stages, levels of conditionality and model specifications. Our findings confirm the importance of institutional and managerial factors and suggest that adoption and transfer of breeding technologies require breeding institutes to provide an enabling environment in which breeders are encouraged to take risks and are given sufficient freedom to experiment with and implement new technologies.

Using an experimental methodology based on investment games, we examine whether smallholder rice farmers from Nueva Ecija, Philippines have heterogeneous preferences for improvements in 10 rice varietal traits. We use a latent class cluster approach to identify different segments of rice producing households and their distinct preferences for trait improvements. These clusters were characterised using household, farm, and marketing characteristics. On average, farmers invested the most in rice varietal trait improvements that offered opportunities to reduce losses caused by lodging, insects and diseases. We found four classes of farmers with distinct preferences for improvements in variety traits. The clusters were significantly different in terms of household and farm characteristics. These findings can guide breeding research in the development of varieties that have the traits farmers identified for improvement, and that will address the unique needs of distinct farmer segments.

Determining farmers' real demand for crop insurance is difficult, especially in developing countries, where there is a lack of formal financial sector integration and a high reliance on informal risk mitigation options. We provide some new estimates of farmers' willingness-to-pay for insurance in the context of a large-scale subsidised programme in India. We conducted a discrete choice experiment with agricultural households across four states in India, enabling us to estimate preferences for specific insurance policy attributes such as coverage period, method of loss assessment, timing of indemnity payments and the cost of insurance. Our results suggest that farmers do value crop insurance under certain conditions and some are willing to pay a premium for such coverage in excess of the subsidised rates they are currently required to pay under this programme. In particular, farmers value the assurances that they will receive timely payouts when they incur losses, and may not have a strong preference for the method with which losses are assessed. On the other hand, farmers are quite sensitive to coverage periods. Our baseline assessment shows that when optimised to farmer requirements, there can be a sizeable demand for crop insurance by developing country farmers.

Given the marked heterogeneous conditions in smallholder agriculture in Sub-Saharan Africa, there is a growing policy interest in site-specific extension advice and the use of digital extension tools to provide site-specific information. Empirical ex-ante studies on the design of digital extension tools and their use are rare. Using data from a choice experiment in Nigeria, we elicit and analyze the preferences of extension agents for major design features of ICT-enabled decision support tools (DSTs) aimed at site-specific nutrient management extension advice. We estimate different models, including mixed logit, latent class and attribute non-attendance models. We find that extension agents are generally willing to use such DSTs and prefer a DST with a more user-friendly interface that requires less time to generate results. We also find that preferences are heterogeneous: some extension agents care more about the effectiveness-related features of DSTs, such as information accuracy and level of detail, while others prioritise practical features, such as tool platform, language and interface ease-of-use. Recognising and accommodating such preference differences may facilitate the adoption of DSTs by extension agents and thus enhance the scope for such tools to impact the agricultural production decisions of farmers.

The 'high speed' rotavator is used for shallow tillage to create a fine tilth and incorporate crop residues, often with a single tractor pass. Rotavator tillage has spread quickly in many parts of South Asia, despite short-term experimental trials suggesting deteriorating soil quality and crop yield penalties. Evidence of rotavator impacts on farmer fields across soil gradients and time is largely absent. From a farm household survey conducted among wheat farmers in Nepal, we estimate wheat yield and profitability outcomes for rotavator adopters and non-adopters using propensity score matching. We find that rotavator adoption leads to inferior outcomes, despite significant cost savings for land preparation (US$ 11-15 per hectare). With rotavator adoption, farmers lose about 284-309 kg of wheat grain and about US$ 93-101 of profits on average per hectare per season, and these penalties increase with longer-term use of the technology. Adoption of rotavator appears to be driven by the cost and time savings for land preparation. Against this backdrop, new policy and extension efforts are required that discourage rotavator use and favour more sustainable tillage technologies.

Most studies of input subsidy programmes confine their analyses to measuring programme effects over a one-year period. This article estimates the potential longer-run or enduring effects of fertiliser subsidy programmes on smallholder farm households' demand for commercial fertiliser and maize production over time. We use four waves of panel data on 462 farm households in Malawi for whom fertiliser use can be tracked for eight consecutive seasons between 2003/2004 and 2010/2011. Panel estimation methods are used to control for potential endogeneity of subsidised fertiliser acquisition. Results indicate that farmers acquiring subsidised fertiliser in three consecutive prior years are found to purchase slightly more commercial fertiliser in the next year. This suggests a small amount of crowding in of commercial fertiliser from the receipt of subsidised fertiliser in prior years. In addition, acquiring subsidised fertiliser in a given year has a modest positive impact on increasing maize output in that same year. However, acquiring subsidised fertiliser in multiple prior years generates no statistically significant effect on maize output in the current year. These findings indicate that potential enduring effects of the Malawi fertiliser subsidy programme on maize production are limited. Additional interventions that increase soil fertility can make using inorganic fertiliser more profitable and sustainable for smallholders in sub-Saharan Africa and thereby increase the cost-effectiveness of input subsidy programmes.

Drought Tolerant Maize Varieties (DTMV) and Rainfall Index Insurance (RII) are potential complements, though with limited empirical basis. We employ a multivariate spatial framework to investigate the potential for bundling DTMV with a simulated multi-site and multi-environment RII, designed to insure against mild, moderate and severe drought risk. We use yield data from on-farm trials conducted by the International Maize and Wheat Improvement Center (CIMMYT) and partners over 49 locations in Eastern and Southern Africa spanning 8 countries and 5 mega-environments (dry lowland, dry mid altitude, wet lower mid altitude, low wetland and wet upper mid altitude) in which 19 different improved maize varieties including DTMV were tested at each location. Spatially correlated daily rainfall data are generated from a first-order two-state Markov chain process and used to calibrate the index and predict yields with a hierarchical Bayes multivariate spatial model. Results show high variation in the performance and benefits of different bundles which depend on the maize variety, the risk layer insured, and the type of environment, with high chances of selecting a sub-optimal and unattractive contract. We find that complementing RII with a specific DTMV produces contracts with lower premiums and higher guaranteed returns especially in dry lowland increasing the chances of scaling up RII within this environment.