Wages, prices and agriculture : how can Indian agriculture cope with rising wages?

Rapid economic growth in India has resulted in rapidly rising rural wages. Using the framework of variable profit functions and household level data, we study econometrically the wage impacts on crop agriculture. Rising wages are associated with decreasing crop output, other things being equal. Crop prices would need to increase by 80% in the short run to offset the effect of an agricultural wage increase, or by 140% in the short run to offset rural non-farm wage increases as well. However, because non-land farm assets respond positively to the non-farm wage, in the medium term this increase is reduced to 74%. During the period of 1999/00-2007/08, growth in non-land farm assets, the labour force, education and technology has easily compensated for the wage increase, and probably also for the accelerating wage growth. Focusing on growing these shifter variables is a much better policy option than raising prices that would come at the expense of consumers or taxpayers.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1477-95522020-06-01hj2017Agricultural Economics, Extension and Rural Developmen

Design factors influencing willingness-to-pay estimates in the Becker-DeGroot-Marschak (BDM) mechanism and the non-hypothetical choice experiment: a case of biofortified maize in Zambia

Two of the experimental methods used to estimate willingness‐to‐pay (WTP) for a non‐market good, the Becker‐DeGroot‐Marschak (BDM) mechanism and the non‐hypothetical choice experiment (nHCE) often lead to significantly different WTP estimates, complicating the choice between the methods. In Zambia the same group of researchers used both techniques to evaluate WTP for orange maize, which provides more vitamin A than other varieties. This provided an opportunity to analyse the sources of the difference. In the BDM experiment, one group of respondents was provided with more training opportunities than the other, and made higher bids. Accounting for lexicographic behaviour in the nHCE reduced the estimated WTP. These two design factors together resulted in a decrease in the WTP difference for orange maize (1,279–632 ZMK) although the difference remains statistically significant. More training was also shown to eliminate the effects of different orders in which maize varieties were presented.https://onlinelibrary.wiley.com/journal/147795522021-02-01hj2019Agricultural Economics, Extension and Rural Developmen

Agricultural labour productivity, food prices and sustainable development impacts and indicators

In the last few years high and unstable food and agricultural commodity prices and concerns about population growth, increasing per capita food demands and environmental constraints have pushed agriculture and food production up national and international political, policy and research agendas. Drawing on both theory and empirical evidence, this paper argues that fundamental impacts of links between agricultural productivity sustainability and real food price changes are often overlooked in current policy analysis. This is exacerbated by a lack of relevant and accessible indicators for monitoring agricultural productivity sustainability and real food prices. Two relatively simple and widely applicable sets of indicators are proposed for use in policy development and monitoring. Historical series of these indices are estimated for selected countries, regions and the world. Their strengths, weaknesses and potential value are then discussed in the context of the need for better sustainable agricultural development and food security indicators in any post 2015 successors to the current MDGs

Overcoming Ex-Post Development Stagnation: Interventions with Continuity and Scaling in Mind

Project interventions are important vehicles for development globally. However, while there is often allocation of resources for new and innovative (pilot) projects—with varying levels of success—there is seemingly less focus on consolidating and/or scaling the positive impacts of successful larger interventions. Assuming an overarching development goal to have long lasting impact at scale, this approach seems somewhat contradictory. Scaling is often not integrated into project planning, design and implementation and rarely pursued genuinely in the ex-post. However, where demand for further development remains outstanding beyond project completion, opportunities may exist to build upon project platforms and extend benefits in a cost effective manner. This paper examines existing scaling typologies, before introducing “scaling-within” as a concept to promote greater continuity of development to a wider range of stakeholders. Scaling-within offers the opportunity to “in-fill” intervention principles and practices to both project and non-project communities within a broader strategic framework to address disparities and to promote sustainable development. The authors draw on research from case studies of large-scale integrated watershed rehabilitation projects and assess scaling-within against a contemporary scaling framework drawn from the literature. While the concept is tested with watersheds as the administrative unit, the authors anticipate applications for other project management units

Who will make the 'best' use of Africa's land? Lessons from Zimbabwe

Conflict over African land – between small holders and large industrial farmers and between domestic farmers and global agribusinesses – raises key questions about who will make the best use of African land and which farmers do most to decrease poverty and produce more food, industrial inputs, and exports. Zimbabwe has already gone through two major changes in land occupation, and thus provides an important test of what is the 'best' use of the land. Three measures of 'best' use have been cited in Zimbabwe: reward for military victory, poverty reduction, and agricultural production. Initial evidence indicates that commercial small holder production is a better use of the land than larger, more mechanised farming

Historical extension of operational NDVI products for livestock insurance in Kenya

Droughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near real-time, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related insurance premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record (1981–2011) to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near-real time NDVI products: five from MODIS and one from SPOT-VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R2 statistics (leave-one-year-out) for the overlapping period 2002–2011. We found that division-specific models were more effective than a global model for linking the division-level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index

Climate risk management and rural poverty reduction

Climate variability is a major source of risk to smallholder farmers and pastoralists, particularly in dryland regions. A growing body of evidence links climate-related risk to the extent and the persistence of rural poverty in these environments. Stochastic shocks erode smallholder farmers’ long-term livelihood potential through loss of productive assets. The resulting uncertainty impedes progress out of poverty by acting as a disincentive to investment in agriculture – by farmers, rural financial services, value chain institutions and governments. We assess evidence published in the last ten years that a set of production technologies and institutional options for managing risk can stabilize production and incomes, protect assets in the face of shocks, enhance uptake of improved technologies and practices, improve farmer welfare, and contribute to poverty reduction in risk-prone smallholder agricultural systems. Production technologies and practices such as stress-adapted crop germplasm, conservation agriculture, and diversified production systems stabilize agricultural production and incomes and, hence, reduce the adverse impacts of climate-related risk under some circumstances. Institutional interventions such as index-based insurance, adaptive safety nets and climate services play a complementary role in enabling farmers to manage risk, overcome risk-related barriers to adoption of improved technologies and practices, and protect their assets against the impacts of extreme climatic events. While some research documents improvements in household welfare indicators, there is limited evidence that the risk-reduction benefits of the interventions reviewed have benefited significant numbers of chronically poor farmers. We discuss the roles that climate-risk management interventions can play in efforts to reduce rural poverty, and the need for further research on identifying and targeting environments and farming populations where improved climate risk management could accelerate efforts to reduce rural poverty