Page 106 - Climate Change and Food Systems

climate change and food systems: global assessments and implications for food security and trade
Using this complex modeling approach, and within the large uncertainties linked to this exercise, Arndt et al. find that climate change will reduce Mozambique’s welfare by up to US$7.4 billion
over the period 2002-2050. They decompose
the effects of each of the four pathways, finding that although agriculture is adversely affected by climate change, the dominating effect will be the impact of flooding on transport infrastructure. While losses in agriculture, a key sector, directly affect Mozambique’s economic growth, transport-system disruptions have widespread, indirect effects throughout the economy.
Since CGE models can describe household employment and income, they can be used to analyse the poverty and distributional effects of climate change. Ahmed et al. (2011a) analyse the effects of climate change on income distribution due to the change in inter-annual climate volatility between the late 20th and early 21st century.
Their analysis is based on a sequence of models in which outputs from GCMs for SRES A2 are used as inputs into statistical crop yield models estimated for three crops in each of 17 regions of Tanzania. The estimated yield impacts are introduced as shocks into a static, single-country CGE model, which is linked to a household micro-simulation model that stratifies Tanzanian households into seven groups based on their sources of income.
To address climate model uncertainty, the authors implement four future climate scenarios into the crop models: the mean climate projections of all 22 GCMs, and projections from three GCMs that describe the greatest volatility in temperature and precipitation combined, and in temperature and precipitation separately. Climate change volatility is measured as a change in the standard deviation of monthly average temperature and precipitation over the January-June growing season for grains between 1971-2001 and 2001- 2031.
Combining national or global CGE models with detailed spatial models has grown in the context of climate analysis and policy, including in agriculture and land use. Rutten et al. (2014)
applies a dual modelling approach combining
a global macroeconomic CGE model (Modular Applied GeNeral Equilibrium Tool, MAGNET) with
a spatial land use model (Conversion of Land Use and its Effects, CLUE) to analyse future land use patterns in Vietnam under various scenarios for
the period 2007-2030. The global CGE makes it possible to account for trade linkages important for an export-oriented Vietnam. The analysis examines how the structural change toward manufacturing and services, and urbanization influenced the loss of natural forests in Vietnam landscape, biodiversity and GHG emissions. Moreover, the loss of large paddy rice and other agricultural lands (through sea level rise) in the Red River delta and the Mekong River delta have significant impacts on food security. Combined with a macro-economic model, the analysis identifies inherent trade-offs in policy objectives (growth and urbanization versus GHG emissions and loss of forest land).
Some CGE models analyse the economics of food security in terms of poverty, which is a net result of changes in incomes and changes in the prices of food and other goods in the consumer basket. An increase in poverty goes hand in hand with increased food insecurity due to a decline in the affordability of food. Based on their modelling approach, Ahmed et al. project that, depending on the future weather, poverty in Tanzania could decrease in 2031 relative to 2001. However, in the most unfavourable climate scenarios, poverty could increase by as much as 2 percent, or approximately 650,000 people.
Tubiello and Fischer (2007) carried out an analysis of the effects of climate change on food that offers a contrasting treatment of food security. They use IIASA’s Basic Linked System (BLS) model of the world food system, which comprises a set of 34 agriculture-focused, national and regional CGE models that are linked through financial flows and trade in ten commodities, of which nine are agricultural. The BLS model’s calculation of food insecurity is based on the correlation between shares of undernourished in the population and the available national food supply, including domestic production and net imports. The authors first
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