Research and development (R&D) offer promising clues to address a wide range of socioeconomic problems through the development of new products and services or often by improving the existing ones. High-income countries (HICs) have realized the worth of R&D and invested tremendously in that sector; however, resource-poor low-income countries (LICs) are still far behind in realizing the potential benefit that R&D could offer for economic growth and national development. Even if some LICs have a positive outlook towards the R&D sector, the trend of emulating works from HICs to solve local or regional issues have most often yielded counterproductive results. LICs are suggested primarily to focus on applied research by incorporating their socioeconomic and cultural aspects to solve their everyday problems whose investigation is often ignored in research-intensive nations. Moreover, applied research in LICs offers the potential to provide low-cost and innovative solutions to local and regional problems with global implications.

The working lands programs in the United States are specifically tailored to support farmers in initiating or enhancing conservation practices. The expectation is that farmers receiving financial assistance will continue implementing these practices even after their initial contracts end, thereby increasing the programs’ cost‐effectiveness and promoting natural resources conservation. However, little is known about the likelihood of persistence and disadoption of conservation practices once the initial cost‐share contracts expire. Using the first‐order Markov chain framework on state‐level conservation practices acreage data from the Mississippi Delta region (2005–2022), this study provides quantitative estimates of changing (dis)adoption patterns of four conservation practices: cover crops (CCs), conservation tillage (CT), nutrient and irrigation management (NIM), and conservation crop rotation (CCR). The findings reveal a higher probability of persistence of NIM practices. In contrast, acres devoted to CCs and CT tend to transition into other alternative practices, indicating a greater likelihood of disadoption. Importantly, the likelihood of acres that initially adopt conservation practices with funding shifting to a condition of no conservation activity is minimal. The transition probability estimates facilitate the prediction of future adoption rates of conservation practices and aid funding agencies in prioritizing their conservation efforts.

The agriculture of the Texas High Plains (THP) region is primarily dependent on groundwater irrigation. Changing weather patterns along with competing demands for water resources and other anthropogenic effects have dramatically increased withdrawals from the Ogallala aquifer. In addition to on-farm changes, policy tools based on off-farm mechanisms are equally indispensable in addressing sustainable groundwater use in the THP. One such policy tool is water pricing using estimates of price elasticity of irrigation water demand. This paper estimates the elasticity of irrigation water demand in the THP and assesses the influence of water price on major inputs used in dominant irrigated crops such as corn and cotton. Using the translog profit function on an annual county-level dataset of THP crop production, spanning 23 years (1998–2020), we find that irrigation water demand is price elastic for cotton (η = – 1.58) but inelastic for corn (η = – 0.81). Our findings suggest that a non-uniform pricing policy could be a useful tool to promote the efficient use of groundwater for irrigation.

Flood adaptation measures are indispensable to offset agricultural losses emanating from the increasing frequency and intensity of floods. Therefore, it is necessary to identify key precursors of adaptation for the success of flood‐related adaptation programs. Using cross‐sectional household survey data from rice farmers of eastern Nepal, this study explores existing adaptation practices along with the factors influencing farmers' adaptation strategies. Both parametric and semiparametric forms of the binary choice model are employed to assess key determinants of flood adaptation. The results reveal that existing adaptation practices are limited to conventional seed storage and few (bio)engineering techniques. Both household and farm characteristics, including flood impact indicators, significantly influence farmers' adaptation to flooding hazards. Thus, consideration of these multiple factors in adaptation‐related programs is anticipated to cope with future floods. Prioritising crop insurance over disaster relief programs and revitalization of existing adaptation measures are suggested. Furthermore, this study demonstrates that the semiparametric approach offers a better alternative by lifting the basic assumptions of parametric models. Findings from this article could aid in developing localised adaptation strategies that would ultimately contribute to the resiliency of farming households and the flood‐prone communities as a whole.