ECONOMY-WIDE EFFECTS OF EL NINO / SOUTHERN OSCILLATION (ENSO) IN MEXICO AND THE ROLE OF IMPROVED FORECASTING AND TECHNOLOGICAL CHANGE

Weather fluctuations, such as those caused by the El Niño Southern Oscillation (ENSO),add to the riskiness associated with agricultural production. Improved predictive capacitymay help ameliorate negative impacts of climate and weather shocks on agriculture, but itis possible that the benefits of an improved forecast will be distributed unevenly. Inparticular, poor farmers may not have access to improved forecasts, or they may not havethe means to adapt to new weather information.This paper uses a stochastic computable general equilibrium (CGE) model to examine thedistributive effects of improved forecasting of ENSO in Mexico. The particular focus ison agriculture, one of the most vulnerable sectors in the face of ENSO, as well as a sectorwhich provides income to many of the country's poorest households. The model is usedto investigate the responsiveness of various sectors of the economy under differentdegrees of improved predictive capacity and improvements in agricultural technology.The CGE model used in this study is augmented with a stochastic component, whichallows us to simulate a range of stochastic shocks using Monte Carlo methods. With thisframework we can compute the mean values and variances of key variables, such asproduction levels and incomes under stochastic shocks. Given that the model is highlynonlinear, Monte Carlo methods provide information on the sources of volatility in theeconomy and the built- in shock absorbers that help dampen that volatility.The results show that while agricultural losses are small as a share of the overalleconomy, improved forecasting techniques can eliminate these losses. ENSO eventsharm some regions – particularly the Central, Pacific South, and South East regions –more than others. Agricultural production in these regions benefits the most fromimproved forecasting. Since these regions also are the regions with higher poverty, theyshould be targeted by policy makers who are concerned with alleviating the effects ofENSO events on the poor. The simulations also show that poor households are the leastable to take advantage of improvements in forecasting, since at higher levels ofpreparedness agricultural production shifts to sectors from which poor households receiveless income. Finally, in Mexico, ENSO events contribute only a small share of overallvariability in agriculture. It might be better to focus efforts on the latter problem, interms of improved agricultural seeds, extension services, and schemes to protect alreadyfragile lands.