El Niño, La Niña, and world coffee price dynamics

Abstract

Coffee is produced in equatorial and subequatorial regions of the world, which are also most affected by El Niño Southern Oscillation (ENSO). ENSO events have a tendency to amplify weather conditions such as droughts or excess precipitation in the affected regions, resulting in production shortage or excess supply, subsequently impacting agricultural commodity prices. In this research we assess effects of ENSO events on world coffee price dynamics using the monthly data between March 1989 and December 2010. We employ smooth transition autoregression framework to examine nonlinear dynamics of ENSO and coffee prices, and illustrate the results of this research using generalized impulse-response functions. We find that ENSO events indeed have short-term impacts on coffee prices. The research findings are of interest to coffee producers and intermediaries in the coffee markets as well as researchers in the fields of environmental and development economics.JEL classifications: C32, Q11, Q54

Economic impacts of El Niño southern oscillation: evidence from the Colombian coffee market

“…Although climatologists have made substantial progresses in modeling ENSO and can now predict the arrival of its warm and cold phases months in advance (see, e.g., Chen et al., ), past El Niño and La Niña episodes have had severe impacts on the Colombian economy (Hoyos et al., ; Poveda et al., ), which is largely dependent on the production of high‐quality Arabica coffee (Ubilava, , ). During the 2014–2015 marketing year, Brazil, Vietnam, and Colombia accounted, respectively, for 35.4%, 17.9%, and 8.7% of world coffee production.…”

“…In this way, we are able to isolate the impacts of extreme ENSO events from shocks to economic fundamentals. Other studies on the “ENSO‐commodity price inflation” nexus do not control for supply and demand shocks, although they are expected to be the main drivers of the real prices of coffee and of other commodities (Ubilava, , ). Moreover, most studies model and forecast the price of coffee with reduced form specifications that cannot identify the causes underlying coffee price shocks (see Ghoshray, ; Vogelvang, ).…”

Welfare‐at‐Risk and Extreme Dependency of Regional Wheat Yields: Implications of a Stochastic CGE Model

“…The literature on the economic implications of teleconnections has focused mainly on climate cycles such as the El Niño (Nicholls, 1985;Cane et al, 1994;Phillips et al, 1999;Naylor et al, 2001;Brunner, 2002;Chen et al, 2008;Zhang et al, 2008;Mehta et al, 2012;Ubilava, 2012). However, other major areas of agricultural production are exposed to similar short-or long-term climate patterns (not necessarily in the form of a cycle), which can be observed when similar weather conditions affect neighbouring regions and countries.…”

Forecasting ENSO with a smooth transition autoregressive model

“…Since its introduction, the STAR modelling approach has gained in popularity and has been increasingly applied to examine potential nonlinearities of unemployment rates, GDP, money demand, and interest rates (e.g. Terasvirta, 1995;Eitrheim and Terasvirta, 1996;Sarantis, 1999;Skalin and Terasvirta, 2002), and more recently to investigate nonlinear features of climate variables, including ENSO (Hall et al, 2001), and their effects on commodity prices (Ubilava, 2012).…”