Impact of El Niño southern oscillation (ENSO) and El Niña on the brazilian soy market

Abstract

The extreme climatic events associated with the atmospheric-oceanic phenomenon known as El Niño Oscilação Sul (ENOS) have significant socioeconomic impacts in different Brazilian regions. In the Northeast of Brazil, agricultural losses resulting from severe droughts can be observed in El Niño years, leading to a reduction in income from rural activities. On the other hand, the South region is affected by strong floods that cause human, infrastructure and compromised agricultural production losses. In La Niña years, the droughts that affect the South region cause crop failures, generating strong pressure on food prices, while in the Northeast there is a greater volume of rainfall. The soy production chain stands out in Brazilian agribusiness, both for the value of production, and for occupying the first place in the list of agricultural exports. In view of this, Brazil, a major world producer, any change in the quantity offered would cause several effects on the international soybean market. In this context, this article aims to assess the economic impact of climatic events associated with ENOS on production, exports and the real price of Brazilian soybeans. The database used consists of monthly data from September 2006 to June 2019, totaling 154 observations. In the construction of the model, the technique of Structural Autoregressive Vectors (structural VAR) was used, thus, it was possible to estimate the impulse response functions and the decomposition of the variance of the considered variables. The results showed that El Niño (that is, positive shocks to ENOS) is beneficial for production and export and decreases the real price of soybeans in grains. On the contrary, La Niña (ie negative shocks to ENOS) depresses production and exports and raises the real price. However, the general impact of the changes occurred by the ENOS phenomenon is small, both in the short and medium term, changes in international demand are more relevant than the supply side shocks in explaining the dynamics of the Brazilian soy market. Finally, the political actions to the studied phenomenon must be elaborated considering the causes of these shocks.

Keywords: Brazil. Structural Var model. El Niño. La Niña. Environment.