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Forecasting Is Fallible, Yet Necessary

Nov 9, 2018 Mark Cliffe

Given that economic forecasters are so often caught out by shocks, one might reasonably ask why they bother. The short answer is that they have no choice, even when they are well aware of the imperfection of their analyses, because people simply cannot live without predictions.

AMSTERDAM – In a complex and uncertain world, making predictions is a fraught business, not least for economists, whose forecasts are notoriously inaccurate. Even worse, economic forecasts tend to let you down just when you need them most. The Nobel laureate economist Paul Samuelson once quipped that “the stock market has called nine of the last five recessions,” which seems forgivable when compared with economic forecasters who rarely predict any.

Given that economic forecasters are so often caught out by shocks, one might ask why they bother. The short answer is that they have no choice, even when they are well aware of the fallibility of their analyses. People simply cannot live without predictions. Because all decisions – in business, politics, or even one’s personal life – are based on some idea of what the future holds, demand for forecasts is insatiable. People want to be able to justify decisions that they would have made anyway for other reasons. And when things go wrong, they can always blame the “experts.”

The Problem of Overconfidence

Forecasts – and the stories behind them – can comfort us, but they can also lead us astray by creating an illusion of control. This is why investment projects are often late or over budget. Similarly, official forecasts published by government agencies and central banks tend to be overly optimistic. This not just because they are based on assumptions of a policy’s future success, but because they are designed to change people’s expectations and behavior.

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0 Comments on this paragraph, 8 in all 8 Comments on this article

Angel Gavieiro Nov 17, 2018

Very interesting reflection, having said that I feel there is a critical angle that has not been fully addressed: why do we forecast in the first place? Ultimately the answer to this question could help to determine the guidance for that forecast (ie accuracy, level of depth, resources/effort required,...), because quite often the forecasting effort is performed ignoring that guidance.

In my view, we forecat to facilitate decision making. Hence, the scope and nature of the forecasting effort should align with the type and impact of the decision at hand. Hence, given the variety of the latter it follows the forecasting palette to pick from should be equally large and varied. Thus, part of the ‘art of forecasting’ requires wisdom in picking the right colours and mix to use in the canvas... so, even if painting the Monalisa, the effort and skill dedicated to the top right corner of the clouds in the painting must be different to the one dedicated to portray the lady’s mouth.
It seems obvious, but quite often ignored by practioners.
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Per Kurowski Nov 12, 2018

If you forecast that something is risky, it becomes safer; if you forecast that something is safe, it becomes riskier. That is sadly what regulators; with their credit risk weighted capital requirements for banks, evidence they fail to understand.

http://subprimeregulations.blogspot.com/2018/08/risk-weighted-capital-requirements-for.html
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Hari Venkatesh Nov 10, 2018

True. But many Economists and analyst came up with new macroeconomic forecasting models. They have shown that they succeed in the complete prediction of economic factors e.g. GDP growth, exports, and output. As my opine, no one can 100% predict the economic outcomes with based on econometric tools and past information. Yes! they can but only some extent. Thus, this kind of economists who represent themselves as great forecasters may be wrong I felt. Dear Sir, please can you clarify my understand.
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David Punabantu Nov 10, 2018

Some thing economists have yet to understand. A calender year does not make an economic unit. Any tax above 8 percent causes government to collect spend and recollect and re spend etc in a cyclical pattern the nation budget. Much like printing money under Keynesian economics, it is instead recycling it creating deficits. The higher the tax above 8 percent the greater the recycling. Hence in a calender year a nation can go through 52 budgets for example, 52 economic years in a calender year, against which statistical data representing a calender year compresses into a week. The underlying axiom to statistical data is counting systems. Figures may count in hexadecimal (base 16), or Vigesimal (base 20) or Hexavigesimal (base 26) or Pentasexagesimal (base 65) or may change from one base system to another but are all expressed expressed in a decimal system. Take time a second is broken into hundreds, sixty seconds make a minute it's not 100 seconds. 60 minutes make an hour and 24 hours a day. A set of figures may be counting in binary but expressed in decimal systems will appear to rise much faster, but if it is counting in hexadecimal system but expressed in decimal it will appear to rise much slower. Therefore the true nature of statistical behaviour is identifying the counting system with specific counting or "time" frames in relation to other time frames to determine its exact behaviour. Even famous physicist Albert Einstein (1879-1955) in 1926 in a letter to Max Born (1882-1970) when he talked of the statistical nature of quantum physics said, "is certainly imposing. But an inner voice tells me that it is not yet the real thing. The theory says a lot, but it does not bring us closer to the secret of the Old One. I at any rate am convinced that He does not throw dice, (Clark)."
Therefore it is not surprising in that reading financial and economic statistics, especially when they exhibit a behaviour that humans fail to interpret the hieroglyphics, creates a crisis. The crisis has always been a problem associated with the mathematical laws inherent in heterogeneous numerical systems against human built equations functioning in a homogenous numerical system being used to interpret them as not being good enough to understand the higher statistical laws needed to as Descartes said, "perceive all things at once."
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Len Charlap Nov 9, 2018

I try, not always successfully, to regard economics as an experimental science. In such a science, one proposes a theory, and if relevant experiments have been performed, see if your theory gives results consistent with the data. This can never prove the theory (cf. mechanics, Newtonian), but at least it will not disprove it.

In economics, history is the result of experiments. Here is an important example. Most economic theories tells us that when times are good, the national debt should be significantly paid down. Keynes wrote, "The Boom, not the Slump, is the time for Austerity at the Treasury." So suppose we look at history:

The federal government has balanced the budget, eliminated deficits for more than three years, and paid down the debt more than 10% in just six periods since 1776, bringing in enough revenue to cover all of its spending during 1817-21, 1823-36, 1852-57, 1867-73, 1880-93, and 1920-30. The debt was paid down 29%. 100%, 59%, 27%, 57%, and 38% respectively. A depression began in 1819, 1837, 1857, 1873, 1893 and 1929.

Here a depression means 6 quarters or more of a reduction in per capita GDP.

Modern Monetary Theory (MMT) on the other hand has an explanation. Briefly, the federal deficit measure the flow of money from the federal government to the private sector. When we have a surplus, that reverses the flow. It sucks money OUT of the private sector. This places great stress on the banking system which eventually leads to a financial crisis.

Using this theory, MMT economists noticed that starting in about 1996, the trade deficit was larger than the federal deficit (except for a brief period in 2003). Thus as in the 6 periods noted above, money was flowing OUT of the private sector. This enabled them to forecast the crash in 2008 although they did not get the date exactly right.

The moral of the story is that when you see a forecast, look at the theory behind it to see what its record has been.

"The definition of insanity is doing the same thing over and over and expecting different results."

"This who ignore history are doomed to repeat it."

Len Charlap
Princeton, NJ
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Murtaza Haider Nov 9, 2018

In summary, and as George Box reminded us, all forecasts (models) are wrong, some are useful.
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Oeufs Bruns Nov 9, 2018

"The only function of economic forecasting is to make astrology look respectable."

― John Kenneth Galbraith
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Jeremy Smilg Nov 9, 2018

It would be really interesting if you could publish or provide a link to research on the degree of forecasting error i.e over time do consensus forecasts provide any valuable information whatsoever? Does any particular style of forecasting in the long run produce valuable information? Economists seem remarkably reluctant to conduct such tests whilst happy to conduct such analysis where the data problems are far greater. This really matters e.g if there is only limited value in forecasting then perhaps the Fed should stop using it as a justification for interest rate decisions and follow a rules based policy other than in extremis such as 2008?
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