The population of the Sub-Saharan region increased by 670 million between 1990 and 2005. According to the latest global population projections published by the United Nations in 2007, 80% of the world’s population growth will be concentrated in developing countries where pressures on food production due to climate change are also predicted to be highly intensified. Due to the joint intensifications of climate change and population growth expected in these regions, studies of agricultural mitigation and its efficacy in boosting crop yields are now vital to future policy decisions. Population and climate changes will increase food requirements and make growing those foodstuffs even more difficult. With the Sub-Saharan population predicted to grow to between 1.5 and 2 billion between now and 2050, agricultural responses to climate change must begin now to maintain future food security in the region. Di Falco et al. analyzed geographic climate and yield data in a simultaneous equations model with endogenous switching to account for unobservable factors or skills that effect food productivity and individual farmers’ decisions to adapt their techniques to changing climate.—Michael Gazeley-Romney
Di Falco, S., Varonesi, M., Yesuf, M., 2011. Does Adaptation to Climate Change Provide Food Security? A Micro-Perspective from Ethiopia. American Journal of Agricultural Economics. 93, 829—846.
Di Falco et al. elected to use a pre-existingan Ethiopian database of climate values and crop yields of the five major annual crops (teff, maize, wheat, barley, and beans) in considering the future food security of the region. Ethiopia, having less than 60% of observed farms employing irrigation, 95% of the national yield being produced on family farms, and 75% of that yield being consumed at the household level typifies the poor, rain-fed regions where production in rain-fed agriculture is predicted to fall 50% by 2020 according to a 2007 IPCC report. This makes it an ideal sample population. The team analyzed seasonally disaggregated climatic data at the individual farm level through a simultaneous equations model with endogenous switching using the thin plate spline method of spatial interpolation, inputting household specific rainfall and temperature data at the correct geographic coordinates.
An important distinction in this analysis is the use of real and predicted food production instead of land value in analyzing the economic effects of climate change. Di Falco et al. insist that due to the high primary consumption of food crops and inconsistent property rights in the developing world, crop production is more readily linked to living conditions than to land value. Subsistence farming exists somewhat separate from the market system, making land market analysis an unreliable indicator of well-being in the at risk regions.
In the first phase of the analysis, the researchers surveyed 1000 households in 20 districts, sampling data from 50 farm units within each district. In surveying the farmers, Di Falco et al. discovered a direct correlation between the availability of information on climate change, access to credit, and the decision to adopt climate-adaptive farming techniques. Most respondents perceived rising temperature and falling annual precipitation, but 40—50% of households because of lack of concrete information failed to act on their perceptions of climate change. The importance of education programs in the form of farmer-to-farmer education and government extension is clear; especially in the developing world where literacy and access to current climate research are low, education is the most important factor in the ability of the population to adapt.
In the second phase of analysis, the team analyzed the effects on food production of the adoption of agricultural adaptation techniques including changing crop varieties, adoption of soil and water conservation strategies, and tree planting. There was a statistically significant correlation between rainfall and food production only in the households that did not adapt—leading the researchers to conclude that adaptation techniques made farms less susceptible to the extreme weather conditions that make food-production in the Sub-Saharan region difficult in the first place. Crop rotation, which might be a good adaptation strategy elsewhere is ineffective in Ethiopia because crops are already highly diversified.
In comparing the expected food productivity of the four test conditions (households that did adapt, households that did not, and the production values for those conditions if the opposite had been true; i.e. the households that did not, had adapted) within the endogenous switching regression model Di Falco et al. concluded that adapted households grew more food than non-adapted ones, and that taking adaptive measures eliminated this discrepancy.
The analysis of Di Falco et al. suggests that future policy objectives should be to concentrate on farms that have not yet embraced climate-linked adaptation techniques. The team points out the obvious need for further research to differentiate the most effective methods of adaptation, but the results demonstrate the importance in raising the productivity in the bottom 1% performers in raising national food-production, weather-proofing yield estimates, and increasing food security in the region.