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We present evidence that farmers adjust agricultural inputs in response to within-season temperature variation, undertaking defensive investments to reduce the adverse agro-ecological impacts of warmer temperatures. Using panel data from Kenyan maize-growing households, we find that higher temperatures early in the growing season increase the use of pesticides, while reducing fertiliser use. Warmer temperatures throughout the season increase weeding effort. These adjustments arise because greater heat increases the incidence of pests, crop diseases and weeds, compelling farmers to divert investment from productivity-enhancing technologies such as fertiliser to adaptive, loss-reducing, defensive inputs such as pesticides and weeding labour. [ABSTRACT FROM AUTHOR]

Most existing program evaluation methods examine the average impact of a program. This necessarily overlooks the potential for different program impacts over different parts of the distribution of the variable of interest. To overcome this limitation, we develop a novel methodology for program evaluation which combines stochastic dominance with difference‐in‐differences methods. We use this new method to evaluate the impact of a large decentralization program in Kenya on changes in child nutritional status, where one's primary concern is about sharp adverse (i.e., negative) changes. Using standard difference‐in‐differences regression as a baseline, we find , no statistically or practically significant mean impact. In contrast, our stochastic dominance estimations reveal that project expenditures have had different impacts on different parts of the distribution. In particular, they are associated with less deterioration in children's nutritional status among the worst‐off children, indicating that the program effectively functions as a nutritional safety net. [ABSTRACT FROM AUTHOR]

The U.S. is the main country in the world that delivers its food assistance primarily via transoceanic shipments of commodity-based in-kind food. This approach is costlier and less timely than cash-based assistance, which includes cash transfers, food vouchers, and local and regional procurement, where food is bought in or nearby the recipient country. The U.S.’s approach is exacerbated by a requirement that half of its transoceanic food shipments need to be sent on U.S.-flag vessels. We estimate the effect of these U.S. food assistance distribution policies on child mortality in northern Kenya by formulating and optimizing a supply chain model. In our model, monthly orders of transoceanic shipments and cash-based interventions are chosen to minimize child mortality subject to an annual budget constraint and to policy constraints on the allowable proportions of cash-based interventions and non-US-flag shipments. By varying the restrictiveness of these policy constraints, we assess the impact of possible changes in U.S. food aid policies on child mortality. The model includes an existing regression model that uses household survey data and geospatial data to forecast the mean mid-upper-arm circumference Z scores among children in a community, and allows food assistance to increase Z scores, and Z scores to influence mortality rates. We find that cash-based interventions are a much more powerful policy lever than the U.S.-flag vessel requirement: switching to cash-based interventions reduces child mortality from 4.4% to 3.7% (a 16.2% relative reduction) in our model, whereas eliminating the U.S.-flag vessel restriction without increasing the use of cash-based interventions generates a relative reduction in child mortality of only 1.1%. The great majority of the gains achieved by cash-based interventions are due to their reduced cost, not their reduced delivery lead times; i.e., the reduction of shipping expenses allows for more food to be delivered, which reduces child mortality. [ABSTRACT FROM AUTHOR]

In this article, we draw out a set of axioms for food security measurement that follow directly from the internationally agreed 1996 FAO definition. Building on recent work on the theory and measurement of development resilience, we then propose an empirical strategy to measure food security that addresses these measurement axioms better than do prevailing measures. We empirically illustrate this approach using a panel data set from northern Kenya. [ABSTRACT FROM AUTHOR]

This article describes a novel index-based livestock insurance (IBLI) product piloted among pastoralists in Northern Kenya, where insurance markets are effectively absent and uninsured risk exposure is a main cause of poverty. We describe the methodology used to design the contract and its underlying index of predicted area-average livestock mortality, established statistically using longitudinal observations of household-level herd mortality fit to remotely sensed vegetation data. Household-level performance analysis based on simulations finds that IBLI removes 25-40 percent of total livestock mortality risk. We describe the contract pricing and the risk exposures of the underwriter to establish IBLI's reinsurability on international markets. [ABSTRACT FROM AUTHOR]

We use a simple theoretical model of seasonal market participation in the presence of liquidity constraints and transaction costs to explain the 'sell low, buy high' puzzle in which some households do not take advantage of inter-temporal price arbitrage through storage and sell output postharvest at prices lower than observed prices for purchases in the subsequent lean season. We test our model with data from western Kenya using maximum likelihood estimation of a multivariate sample selection model of market participation. Access to off-farm income and credit indeed seem to influence crop sales and purchase behaviours in a manner consistent with the hypothesised patterns. [ABSTRACT FROM AUTHOR]

Fertilizer interventions have attained prominence in rural poverty reduction programs in Africa. Using data from maize plots operated by small farmers in western Kenya, we find a von Liebig-type relationship between soil organic matter (SOM) and maize yield response to nitrogen application. Low SOM commonly limits the yield response to mineral fertilizer application. Although fertilizer is, on average, profitable in our sample, on roughly one-third of the plots degraded soils limit the marginal productivity of fertilizer such that it becomes unprofitable at prevailing prices. Moreover, because poorer farmers most commonly cultivate soils deficient in SOM, fertilizer interventions might be less pro-poor than is widely assumed and may instead reinforce ex ante income inequality. [ABSTRACT FROM AUTHOR]

Studies of fertilizer use in sub-Saharan Africa have been dominated by analyses of economic and market factors having to do with infrastructure, institutions, and incentives that prevent or foster increased fertilizer demand, largely ignoring how soil fertility status conditions farmer demand for fertilizer. We apply a switching regression model to data from 260 farm households in western Kenya in order to allow for the possibility of discontinuities in fertilizer demand based on a soil carbon content (SCC) threshold. We find that the usual factors reflecting liquidity and quasi-fixed inputs are important on high-SCC plots but not on those with poorer soils. External inputs become less effective on soils with low SCC, hence the discernible shift in behaviors across soil quality regimes. For many farmers, improved fertilizer market conditions alone may be insufficient to stimulate increased fertilizer use without complementary improvements in the biophysical conditions that affect conditional factor demand. [ABSTRACT FROM AUTHOR]

Abstract: Mitigating the negative welfare consequences of crises such as droughts, floods, and disease outbreaks, is a major challenge in many areas of the world, especially in highly vulnerable areas insufficiently equipped to prevent food and livelihood security crisis in the face of adverse shocks. Given the finite resources allocated for emergency response, and the expected increase in incidences of humanitarian catastrophe due to changing climate patterns, there is a need for rigorous and efficient methods of early warning and emergency needs assessment. In this paper we develop an empirical model, based on a relatively parsimonious set of regularly measured variables from communities in Kenya’s arid north, that generates remarkably accurate forecasts of the likelihood of famine with at least 3months lead time. Such a forecasting model is a potentially valuable tool for enhancing early warning capacity. [Copyright &y& Elsevier]

Understanding and alleviating poverty in Africa continues to receive considerable attention from a range of diverse actors, including politicians, international celebrities, academics, activists and practitioners. Despite the onslaught of interest, there is surprisingly little agreement on what constitutes poverty in rural Africa, how it should be assessed, and what should be done to alleviate it. Based on data from an interdisciplinary study of pastoralism in northern Kenya, this article examines issues of poverty among one of the continent's most vulnerable groups, pastoralists, and challenges the application of such orthodox proxies as incomes/expenditures, geographic remoteness, and market integration. It argues that current poverty debates ‘homogenize’ the concept of ‘pastoralist’ by failing to acknowledge the diverse livelihoods and wealth differentiation that fall under the term. The article concludes that what is not needed is another development label (stereotype) that equates pastoralism with poverty, thereby empowering outside interests to transform rather than strengthen pastoral livelihoods. [ABSTRACT FROM AUTHOR]

Summary: Temporal climate risk weighs heavily on many of the world’s poor. Model-based climate forecasts could benefit such populations, provided recipients use forecast information to update climate expectations. We test whether pastoralists in southern Ethiopia and northern Kenya update their expectations in response to forecast information. The minority of herders who received these climate forecasts updated their expectations for below normal rainfall, but not for above normal rainfall. This revealed preoccupation with downside risk highlights the potential value of better climate forecasts in averting drought-related losses, but realizing any welfare gains requires that recipients strategically react to these updated expectations. [Copyright &y& Elsevier]

Do rural households in developing countries make market participation and volume decisions simultaneously or sequentially? This article develops a two-stage econometric method to test between these two competing hypotheses regarding household-level marketing behavior. The first stage models the household's choice of whether to be a net buyer, autarkic, or a net seller in the market. The second stage models the quantity bought (sold) for net buyers (sellers) based on observable household characteristics. Using household data from Kenyan and Ethiopian livestock markets, we find evidence in favor of sequential decision making, the welfare implications of which we discuss. [ABSTRACT FROM AUTHOR]

This paper introduces a simple method of price risk decomposition that determines the extent to which producer price risk is attributable to volatile inter-market margins, intra-day variation, intra-week (day of week) variation, or terminal market price variability. We apply the method to livestock markets in northern Kenya, a setting of dramatic price volatility where price stabilization is a live policy issue. In this particular application, we find that large, variable inter-market basis is the most important factor in explaining producer price risk in animals typically traded between markets. Local market conditions explain most price risk in other markets, in which traded animals rarely exit the region. Variability in terminal market prices accounts for relatively little price risk faced by pastoralists in the dry lands of northern Kenya although this is the focus of most present policy prescriptions under discussion. [Copyright &y& Elsevier]

Weather-related shocks are a major threat to the health and livelihoods of vulnerable farmers and herders in low-income, arid, and semi-arid regions of the world. Index insurance represents a promising tool for mitigating the impacts of such risk but in practice has exhibited low uptake rates by potential clients. Basis risk—the remaining risk faced by an insured individual—is widely acknowledged as the Achilles heel of index insurance, and yet direct measurements of basis risk have never been used to study its role in determining demand for index insurance. Further, client knowledge of season-specific environmental information and spatial variation in basis risk introduces the possibility of adverse selection, a feature often presumed to be absent for index products. We used longitudinal household data to determine which factors affected demand for index based livestock insurance (IBLI). While both price and the non-price factors studied previously are indeed important, our findings indicate that basis risk and spatiotemporal adverse selection also play a major role in determining demand for IBLI. [ABSTRACT FROM AUTHOR]

Summary This paper evaluates the welfare impacts of an index-based livestock insurance designed to compensate for satellite-based predicted livestock mortality in northern Kenya, where previous work has established the presence of poverty traps. We simulate household wealth dynamics based on rich panel and experimental data. The bifurcated livestock dynamics associated with the poverty trap gives rise to insurance valuation that is highly nonlinear in herd size. Estimated willingness to pay among vulnerable groups who most need insurance is, on average, lower than commercially viable rates. Targeted premium subsidization nonetheless appears to offer more cost-effective poverty reduction than need-based direct transfers. [ABSTRACT FROM AUTHOR]

Summary: This study investigates variation over time, space and household and individual characteristics in how people perceive different risks. Using original data from the arid and semi-arid lands of East Africa, we explore how individuals assess their relative level of concern about risks. The primary determinants of risk rankings are found to be changing community level variables over time, with household specific and individual specific variables exhibiting much less influence. Individuals throughout this area are most concerned about food security and human health, so that development efforts that directly address these problems should be given the highest priority. [Copyright &y& Elsevier]