Asset management, Commodity risk, Complexity, Economics, Expertise, Hedging, Market research, Policy, Risk management

Economic forecasting is exercise in futility

Economists can’t forecast for a toffee… They have missed every recession in the last four decades. And it isn’t just growth that economists can’t forecast; it’s also inflation, bond yields, unemployment, stock market price targets and pretty much everything else.” – James Montier

Forecasting commodity prices and economic indicators is demonstrably an exercise in futility. Our markets and economies are complex systems and as such, their future unfolding is impossible to predict with any degree of certainty. Concretely, let’s take a look at how the leading economic analysts did at predicting oil prices, GDP growth, unemployment and stock market indices.

The Livingston Survey

Twice a year since 1946, the US Federal Reserve Bank of Philadelphia publishes the Livingston Survey which summarizes the forecasts of 31 prominent economists from industry, government and leading academic and financial institutions. These panelists regularly submit predictions about significant economic indicators including the GDP, unemployment rate, interest rates and the S&P 500 stock market index. Only three months before the onset of the year 2000 recession, these forecasters saw no signs of the imminent economic downturn and stock market collapse. Their forecasts of the unemployment rate, GDP growth and the level of S&P 500 index were widely off mark:


The next, 2007-2009 recession and the 2008 market crash caught them equally unawares. The survey released in June 2007, five months before the onset of the recession, stated that, “the panelists think that real GDP will grow 3.0% annually over the next 10 years.” They also projected that the S&P 500 index, which traded just above 1500 at the time, would rise to 1600 by June 2008 and 1635 by the end of 2008. In fact, by June 2008, the S&P 500 dropped to around 1400. In light of these events, the Livingstoneans duly revised their next batch of forecasts, only this time they got it even wronger: the S&P 500 lost another 700 points, collapsing nearly 50% below the level predicted by these prominent economists.


In addition to commissioning surveys, the U.S. Federal Reserve itself retains several hundred economists[1] who gather economic data and feed it into elaborate economic models that seek to describe how the economy works through complex mathematical algorithms. These impressive troops of learned economists and sophisticated models they built have equally failed at predicting important developments over time.

As hedge fund manager Paul Singer expressed it ever so impolitely in his October 2013 letter to investors, “… the Fed’s models and predictions were catastrophically wrong about the financial system, financial institutions and risks in the period leading up to and during the [2008] financial crisis.

EIA oil price forecasts

Economists’ ability to predict commodity prices appears to be no better than their ability to predict economic growth, employment or stock markets. The oil market, the world’s largest and most closely studied commodity market, offers another example of the failure of forecasting. Every year, the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy, publishes an exhaustive report titled International Energy Outlook that, amongst other information, provides long-term oil price forecasts. The forecasts are generated by the EIA as well as a group of the industry’s leading research institutions.


In 2003, as oil was still trading between $20 and $30 per barrel, all the submitted forecasts[2] for 2005 were clustered between $19 and $24 per barrel. Indifferent to these authoritative predictions, crude oil continued rising with the year’s average vaulting to over $55 per barrel – 2.5 times higher than the average EIA forecast.

Realizing perhaps the futility of generating specific price forecasts, the EIA subsequently changed the way it projected the evolution of the oil price in the near-term and longer-term future, projecting the likely outcomes in a broadening band between the low and high world oil price. As it extends into the future, the band widens covering as much as $70 per barrel and more.

With such a broad brush, there’s a better chance of hitting the right answer. Sadly, this may well be the best way of going about predicting future outcomes, short of giving up altogether. But even this broad-brush approach put the limitations of forecasting on display: while its 2014 forecast projected the low oil price falling no lower than about $70 per barrel, within two years – by January 2016 the actual price dipped below $30!


Of course, not all forecasts are wrong. Many  – perhaps half or so – will turn out to be correct, but to seriously entertain the notion that economic forecasting adds value in trading, hedging or investment management, the majority of forecasts would need to be right most of the time. This unfortunately is not the case, posing a not-so trivial problem for decision makers affected by the vagaries of fluctuating markets: why do we bother with economic forecasting and what credible alternatives should we consider to help us navigate the markets.

These are among the most important problems for managers and policymakers to solve, because, as Frank Knight compellingly argued in his “Risk, Uncertainty and Profit,” only by resolving this type of uncertainty that cannot be reduced by measurement and analysis can form the basis for firms to generate profits in a sustainable way.


[1] According to some reports in 2012, the total number was about 730: 189 worked for the Federal Reserve Board, another 171 at different regional banks; adding in statisticians and support staff – generally also economists, the total arrives at 730. (Source: “How the Federal Reserve Bought the Economics Profession” by Ryan Grim, Huffington Post, 23 October 2009.)

[2] The forecasts were produced by Altos, DBAB (Deutsche Bank Alex Brown), EEA (Energy and Environmental Analysis), EIA (Energy Information Administration), IEA (International Energy Agency), GII (Global Insight, formed in Oct. 2003 through the merger of Data Resources Inc. and Wharton Econometric Forecasting Associates), NRCan (Natural Resources Canada), PEL (Petroleum Economics), and PIRA. Source: Energy Information Administration “International Energy Outlook 2003.”


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