As recently as late 2014, financial papers were filled with dour forecasts warning that the breakneck expansion of the emerging market economies, China in particular, would keep the price of oil above $100 per barrel for a decade or more. In October 2014, the International Monetary Fund’s respected World Economic Outlook pegged the commodity at $102 a barrel in 2014 and forecasted $99 for 2015. Soon after, prices collapsed, and the same pundits who predicted that oil would stay high now say that $30 a barrel or below will be the new normal for a long time to come.
The conventional wisdom has also declared dead the “commodity supercycle,” the explosion of commodity prices behind the economic growth of the BRICS countries (Brazil, Russia, India, China, and South Africa) and other emerging market economies in the first decade of this century. These days, oil is cited as evidence in this argument.
A LOOK AT THE NUMBERS
Forecasting is more art than science. Whether for personal finance, a multinational corporation, or the covert invasion of a neighboring nation, decisions must be made on some kind of intelligence. Best practice suggests that basing decisions on the worst-case and best-case scenarios is unwise; rather, forecasters need to look at middle-range outcomes. One only has to think back to 2013 to see how certainty over the existence of supercycles, the notion that long-term patterns not only exist but can be forecasted, was used to extrapolate growth for decades into the future by the world’s leading economists. But now, those double-digit growth rates attributed to Brazil, China, and other emerging markets have all been proven incorrect.
In fact, the whole concept of supercycles was a cheery oversimplification of best-case supply-and-demand dynamics, used for everything from gold to natural gas. Just months after the supercycle’s bust, it is easy to see how the concept included classic symptoms of a financial bubble—complete with assumptions that this time would be different. For emerging market experts and their investors, forecasts were built upon optimism rather than measured and pragmatic modeling.
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