Assessing the Economic Value of El NiÃ±obased seasonal climate forecasts for smallholder farmers in Zimbabwe
Drought constitutes the most dominant source of food insecurity in Zimbabwe and many other countries in Africa. With a majority of smallholder farmers practicing dry-land agriculture, seasonal forecasts hold promise as an effective risk management tool, giving farmers the ability to anticipate rainfall variability early enough to adjust crucial farm decisions and better prepared to handle climatic anomalies in ways that can reduce costly losses (crop, animal and even human). This study demonstrates the potential value of forecasts to smallholder farmers in Zimbabwe, a majority who often suffer severely from the impact of drought. Using crop simulation models to compare yield performances of farmers with and without forecasts, results indicate that for a drought year, farmers with forecasts (WF) record higher yield gains (28%) compared to those without forecasts (WOF); in particular, farmers located in driest regions (NR V) record the highest yield gains (42%). Similar results are observed for a neutral/ average year as farmers WF obtain predominantly higher yield gains (20%) than those WOF. However for a good year, results show a different pattern as no yield gains are observed. In fact farmers WOF perform better; suggesting forecasts in this case may not make much difference. Using gross margin analysis, results show farmers WF obtaining higher returns during a drought (US$0.14haâˆ’1) and neutral year (US$0.43haâˆ’1) but again not for good year as farmers WOF outperform those WF. In sum, forecasts can play an important role as loss-minimization instruments especially if the underlying year is a El Nino (drought) year. In conclusion, to attain full economic value of forecasts, complementary policies (currently missing) such as effective communication, improvement in forecast extension skills and promotion of farmer participatory and outreach activities, all could prove vital in enhancing the value of forecasts to smallholder farmers in general
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- Mjelde, James W. & Dixon, Bruce L., 1993. "Valuing the lead time of periodic forecasts in dynamic production systems," Agricultural Systems, Elsevier, vol. 42(1-2), pages 41-55.
- Patt, Anthony, 2001. "Understanding uncertainty: forecasting seasonal climate for farmers in Zimbabwe," Risk, Decision and Policy, Cambridge University Press, vol. 6(02), pages 105-119, June.
- Gonzales, Kathrina G. & Predo, Canesio D. & de Guzman, Rosalina G. & Reyes, Celia M., 2009. "Assessing the Value of Seasonal Climate Forecasts on Farm-level Corn Production through Simulation Modeling," Discussion Papers DP 2009-05, Philippine Institute for Development Studies.
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