On Crop Biodiversity, Risk Exposure, and Food Security in the Highlands of Ethiopia

Abstract

This paper investigates the effects of crop genetic diversity on farm productivity and production risk in the highlands of Ethiopia. Using a moment-based approach, the analysis uses a stochastic production function capturing mean, variance, and skewness effects. Welfare implications of diversity are evaluated using a certainty equivalent, measured as expected income minus a risk premium (reflecting the cost of risk). We find that the effect of diversity on skewness dominates its effect on variance, meaning that diversity reduces the cost of risk. The analysis also shows that the beneficial effects of diversity become of greater value in degraded land.Key words: barley, diversity, Ethiopia, food security, land degradation, risk.Production risk is one of the quintessential features of agriculture. Unpredictable weather can expose farm households to significant production uncertainty and serious hardship. Under harsh climatic and agroecological conditions, this can result in food insecurity and famine. The highlands of Ethiopia are a prime example of such environment. During the last forty years, Ethiopia has experienced many severe droughts, 1 leading to production levels that fell short of basic subsistence levels for many farm households (Relief Society of Tigray (REST) and NORAGRIC at the Agricultural University of Norway 1995, p. 137). Harvest failure due to drought is the most important cause of risk-related hardship of Ethiopian rural households, with adverse effects on farm household consumption and welfare (Dercon 2004(Dercon , 2005. When facing prospects of harvest failure, ex-ante farm production decisions, such as crop or varietal choice, remain a part of risk management strategies (Just and Candler 1985;Fafchamps 1992;Chavas and Holt 1996;Dercon 1996;Smale et al. 1998). The authors would like to thank the editor, three anonymous referees, Melinda Smale, Chris Barrett, and Fitsum Hagos for useful comments on an earlier draft of the paper. We also thank John Pender for making the data available. The usual disclaimer applies.1 Ethiopia experienced droughts in 1965Ethiopia experienced droughts in , 1974Ethiopia experienced droughts in , 1983Ethiopia experienced droughts in , 1984Ethiopia experienced droughts in , 1987Ethiopia experienced droughts in , 1990Ethiopia experienced droughts in , 1991Ethiopia experienced droughts in , 1999Ethiopia experienced droughts in , 2000Ethiopia experienced droughts in , and 2002 In this environment, management options are somewhat restricted. Insurance and risk coping mechanisms often function poorly because of credit constraints, information asymmetries, and commitment failures (Deaton 1989;Fafchamps 1992;Kurosaki and Fafchamps 2002). Safety nets typically provide only limited support We argue that, in dry environments, farmers' reliance on crop biodiversity is an essential part of ex-ante risk management strategies. Diversity in genetic resources embedded in crop seeds can support productivity and help manage risk . Ethiopia is a recognized global center of g...

Does Adaptation to Climate Change Provide Food Security? A Micro‐Perspective from Ethiopia

“…The production environment is characterized by a joint combination of low land productivity and harsh weather conditions (e.g., high average temperature, scarce and erratic rainfall). These result in very low yields and food insecurity (Di Falco and Chavas 2009).…”

Transgenic crops, production risk and agrobiodiversity

“…But on-farm varietal diversity also has private benefit components. One can discern two possible functions that varietal diversity may offer to farmers, first, an insurance function, and second, a productivity enhancement function (Di Falco and Chavas, 2009). …”

“…For the analysis, we use the framework proposed by Just and Pope (1979) in a heteroscedastic regression model of the cotton production function. The Just and Pope (1979) framework has been used previously to analyze effects of Bt cotton (Crost and Shankar, 2008;Shankar, Bennett and Morse, 2008) and of varietal diversity (Smale et al, 1998;Di Falco and Chavas, 2009), but not jointly in one study. Here, we use cotton production per farm as dependent variable and regress this on a vector of inputs and production factors.…”

“…In a first model (model 1), we express varietal diversity as explained above, namely in terms of the total number of cotton varieties grown on a farm. Yet there are also more specific indices that can be used to express varietal diversity, such as the Margalef index of varietal richness or Simpson's evenness index that both account for the size of the farm (Di Falco and Perrings, 2003;Benin et al, 2004;Nagarajan, Smale, and Glewwe, 2007;Di Falco and Chavas, 2009 (Karihaloo and Kumar, 2009;James, 2012). We expect that the number of Bt varieties locally available in the seed market will affect the diversity on Bt adopting farms, so we use an interaction term between the number of approved Bt varieties and Bt adoption.…”

“…Modern high-yielding varieties may be attractive for farmers from a short-term profit maximizing perspective, but it is argued that a narrower genetic base may increase production risk and disrupt the stability and resilience of farming systems in the long run (Cooper, Engels and Frison, 1994;Tripp, 1996). Indeed, there is broad evidence that varietal diversity has a natural insurance function (Baumgärtner and Quaas, 2010;Di Falco and Chavas, 2009). Against this background, some argue that the Green Revolution (i.e., the introduction of HYVs of wheat and rice since the late 1960s in Asia and other parts of the developing world) has contributed to serious ecological and social problems in the small farm sector (Shiva 1991).…”