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Seminario 440: Why Colombia is vulnerable to large and long cycles in commodity prices and what causes them?

CRU Research Director, Consulting CRU

 

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Hora: 12:00 m. (refrigerio) y 12:30 p. m. (inicio del seminario)

Tiempo de exposición: 12:30 p. m. a 2:00 p.m.
Lugar: Banco de la República, carrera 7 # 14-78, piso 13 (Sala de prensa), Bogotá D.C.

Idioma de la exposición: Inglés

 

Resumen del documento: The scale and correlation of price movements are large. The unpredictability in commodity prices at a ten-year horizon is much higher than that of other macroeconomic variables. This puts enormous strain of macroeconomic policies of commodity exporters not least because of the impact on exchange rates but also in managing loss making mines and processors. 
 

We decompose 27 commodity prices over a 100-year history and find that in general there are three sets of movements: temporary business cycle peaks, slower long-run changes and in between a cycle of about 20-30 years peak-to-peak, which can be called a super cycle. Long-run trends come with advance warning, short-term is reversible, but the 20-30 year super cycles cause the most trouble because of their longevity and scale.  I will look at other data on production and investment to better characterize anomalies in these cycles and draw out stylised facts.
 

Why do these large swings come about? I have built a dynamic general equilibrium model that seeks to explain commodity demand, investment and prices and can test different explanations of these cycles. The model is based on a recent QJE paper by Greenwood and Hansen on Dry Bulk Freight investment cycles. When we run the model in a mode where commodity investors take full account of competitors’ behaviours and on average predict peaks in demand, we find that the model predicts price movements that are too short-lived compared to theory. When we run the model with two behavioural biases: over-extrapolation of demand and competition neglect, we find that we can generate cycles of the size we observe in the data.



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