Adoption of Farm Management Systems for Cross Compliance - An empirical case in Germany.

In Germany, Farm Management Systems (FMS) have been introduced as a support to farmers' compliance with environmental and other regulations, aiming at the increase of farm level performance and sustainable farming practices. Different kinds of FMS were developed and promulgated with various approaches, determined by each federal state's agricultural advisory system. Knowledge on the FMS' uptake and effectiveness has been lacking so far. The overall aim of this paper is to provide an analysis of the implementation process and selected outcomes of the policy-driven instrumental innovation of FMS. In particular, the objectives are i) to reveal how and with what success the introduction of FMS has been realised in Germany and ii) to analyse and discuss the FMS' adoption in the federal state of Brandenburg. For the first part of the study, we elaborate a situational analysis of the policy implementation through a desk study and expert interviews. In the second part, selected results from a farmers' survey in Brandenburg are presented and a switching regression model is developed to assess the factors responsible for the uptake of FMS and to understand the role of FMS in improving the confidence in complying with Cross Compliance regulations. We found a high degree of diversity among FMS developed in the different federal states. FMS adoption rates varied, but were generally low. Institutional environment seems to have a significant influence as the same FMS had very different adoption rates among federal states. For Brandenburg, our findings show that farmers' confidence to face CC check was increased by the adoption of FMS. However, counterfactual scenario analysis proved that especially farmers who did not adopt FMS would have benefitted most if they had adopted the tool. Our study shows that there is a need for systems supporting farmers in dealing with bureaucratic requirements. Future FMS should be easy to understand, adaptable to individual farmers' needs and be available at low costs. Furthermore, there is a need to design FMS in a participatory way that integrates farmers' expectations.

Application of a bias-corrected meta-frontier approach and an endogenous switching regression to analyze the technical efficiency of conservation tillage for wheat in South Asia.

Conservation tillage (CT) options are among the most rapidly spreading land preparation and crop establishment techniques globally. In South Asia, CT has spread dramatically over the last decade, a result of strong policy support and increasing availability of appropriate machinery. Although many studies have analyzed the yield and profitability of CT systems, the technical efficiency impacts accrued by farmers utilizing CT have received considerably less attention. Employing a DEA framework, we isolated bias-corrected meta-frontier technical efficiencies and meta-technology ratios of three CT options adopted by wheat farmers in Bangladesh, including bed planting (BP), power tiller operated seeding (PTOS), and strip tillage (ST), compared to a control group of farmers practicing traditional tillage (TT). Endogenous switching regression was subsequently employed to overcome potential self-selection bias in the choice of CT, in order to robustly estimate efficiency factors. Among the tillage options studied, PTOS was the most technically efficient, with an average meta-technology ratio of 0.90, followed by BP (0.88), ST (0.83), and TT (0.67). The average predicted meta-frontier technical efficiency for the CT non-adopters under a counterfactual scenario (0.80) was significantly greater (P = 0.00) than current TE scores (0.65), indicating the potential for sizeable profitability increases with CT adoption. Conversely, the counterfactual TE of non-adopters was 23% greater than their DEA efficiency, also indicating efficiency gains from CT adoption. Our results provide backing for agricultural development programs in South Asia that aim to increase smallholder farmers' income through the application of CT as a pathway towards poverty reduction. JEL Codes C06 ● C14 ● Q12 ● C34 ● C51.

Key indicators for monitoring food system disruptions caused by the COVID-19 pandemic: Insights from Bangladesh towards effective response.

In the context of developing countries, early evidence suggests that the impacts of the COVID-19 pandemic on food production systems is complex, heterogenous, and dynamic. As such, robust monitoring of the impact of the health crisis and containment measures across agricultural value chains will likely prove vitally important. With Bangladesh as a case study, we discuss the building blocks of a comprehensive monitoring system for prioritizing and designing interventions that respond to food system disruptions from COVID-19 and preemptively avoid further cascading negative effects. We also highlight the need for parallel research that identifies pathways for enhancing information flow, analysis, and action to improve the efficiency and reliability of input and output value chains. In aggregate, this preliminary work highlights the building blocks of resilient food systems to external shocks such as COVID-19 pandemic in the context of developing nations. In doing so, we call attention to the importance of 'infection safe' agricultural input and output distribution logistics, extended social safety nets, adequate credit facilities, and innovative labor management tools alongside, appropriate farm mechanization. In addition, digital extension services, circular nutrient flows, enhanced storage facilities, as well as innovative and robust marketing mechanisms are required. These should be considered in parallel with effective international trade management policies and institutions as crucial supportive measures.

Modeling ENSO impact on rice production in the Mekong River Delta.

The Mekong River Delta is the rice production hub in South-east Asia and has a key role in determining rice prices in the world market. The increasing variability in the local climate due to global climate changes and the increasing severity of the ENSO phenomenon threatens rice production in the region, which has consequences for local and global food security. Though existing mapping efforts delineate the consequences of saline water intrusion during El Niño and flooding events during La Niña in the basin, research to predict future impacts in rice production is rather limited. The current work uses ORYZA, an ecophysiological model, combined with historical climate data, climate change scenarios RCP4.5 and 8.5 and climate-related risk maps to project the aggregate productivity and rice production impacts by the year 2050. Results show that in years of average salinity intrusion and flooding, the winter-spring rice crop in the MRD would experience an average annual decrease of 720,450 tons for 2020-2050 under the RCP4.5 scenario compared to the baseline of 2005-2016 average and another 1.17 million tons under the RCP8.5 scenario. The autumn-winter crop would decrease by 331,480 tons under RCP4.5 and 462,720 tons under RCP8.5. In years of severe salinity intrusion and flooding, the winter-spring rice crop would decrease by 2.13 million tons (10.29% lower than the projection for an average year) under RCP4.5 and 2.5 million tons (13.62%) under RCP8.5. Under severe conditions, the autumn-winter crop would have an average decrease of 1.3 million tons (7.36%) under RCP4.5 and 1.4 million tons (10.88%) for the RCP8.5 scenario. Given that most of the rice produced in this area is exported, a decline in rice supply at this scale would likely have implications on the global market price of rice affecting global food security. Such decline will also have implications for the rural economy and food security of Vietnam. Suggestions for corrective measures to reduce the impacts are briefly discussed.

Sustainable survival under climatic extremes: linking flood risk mitigation and coping with flood damages in rural Pakistan.

Various measures are adopted by flood-prone households for the mitigation of flood risk along with various post-flood coping strategies. We analyze the role of various ex ante household-level flood mitigation strategies in influencing riverine flood damages. The study also presents an account on the linkages of various ex post coping strategies and flood damages experienced in a flood event in Pakistan. For achieving a uniform flood damage indicator, polychoric principle component analysis (PCA) is employed to construct a composite flood damage index considering various aspects of economic, social, and psychological impacts of a flood event. The adjusted flood damage index is regressed on various socioeconomic features and ex ante mitigation actions to know their effect on the former. Results indicate that distance from river, elevating house, and pre-shifting investigating about flooding problem help in significantly reducing the overall flood damages. Likewise, group-based actions like voting political candidates based on their flood-control promises, organizing grass-root group meetings, and raising voices through memos/petitions are found to significantly reduce flood-related damages while leaving house premises before flooding is found to increase the overall flood damage. Post-flood coping strategies comprise of social and financial support along with some livelihood diversification and disinvestment strategies such as selling livestock, jewelry, and withdrawing children from schools. Borrowing money, reducing food consumption, and agricultural diversification are more prevalent strategies among low and medium damage groups while consuming savings is more conspicuous among high damage group. The study concludes with the emphasis on policy interventions for effective early warning, location-specific flood intensity information, and proper streamlining of planning process and compensation system.