HR: 1340h
AN: H13G-1391    [Abstracts]
TI: Impacts of Considering Climate Variability on Investment Decisions in Ethiopia
AU: * Strzepek, K
EM: Kenneth.Strzepek@Colorado.EDU
AF: Dept of Civil and Environmental Engineering, University of Colorado at Boulder 428 UCB, Boulder, CO 80309-0428 United States
AU: Block, P
EM: Paul.Block@Colorado.EDU
AF: Dept of Civil and Environmental Engineering, University of Colorado at Boulder 428 UCB, Boulder, CO 80309-0428 United States
AU: Rosegrant, M
EM: m.rosegrant@cgiar.org
AF: International Food Policy Research Institute, 2033 K Street, NW, Washington, DC 20006-1002 United States
AU: Diao, X
EM: x.diao@cgiar.org
AF: International Food Policy Research Institute, 2033 K Street, NW, Washington, DC 20006-1002 United States
AB: In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.
DE: 1884 Water supply
DE: 6344 System operation and management
SC: Hydrology [H]
MN: Fall Meeting 2005