Beware of economic forecasters who achieve better-than-average accuracy in predicting extreme outcomes. They are less accurate than the average forecaster in predicting run-of-the-mill outcomes. Furthermore, it may not be by chance that certain prognosticators issue extreme forecasts with greater frequency than their peers. Those whose firms bear their own names depart from the consensus more often than other forecasters. Making a splash by “calling” a major setback can expand a forecaster’s following (and revenue base), even if the feat is achieved by acting as a “broken clock”—that is, predicting an economic decline year in and year out until it inevitably comes to pass as a function of the business cycle.
None of this is to imply that business planners or investors will necessarily prosper by relying on the consensus. In none of the last seven recessions did the Survey of Professional Forecasters (SPF) consensus predict the initial contraction in gross domestic product (GDP) more than two quarters in advance. Only three times in those seven instances did the consensus SPF forecast issued during the first quarter of the recession correctly indicate that GDP growth for that quarter would be negative. In all seven cases, the magnitude of the decline during the worst quarter of the recession was greater than the consensus-expected magnitude.
Clearly, UBS Chief Economist for the Americas Maury Harris is no cheerleader for the forecasting community. In Inside the Crystal Ball: How to Make and Use Forecasts, he maintains that some of his fellow soothsayers are biased by their political opinions, failing to recognize the effects of unwise economic policies initiated by the party they favor. In a similar vein, economic forecasts by the Office of Management and Budget, which is directly accountable to the US president, have proven more optimistic and less accurate than forecasts made by government agencies less directly under the administration’s control.
Even when forecasting more mundane microeconomic events, economists sometimes make elementary errors. Harris recounts how Denver tourism officials predicted that hosting the National Basketball Association’s 2005 All-Star Game would draw 100,000 visitors to the city. They evidently overlooked the facts that the stadium in which the game would be played had only 20,000 seats and that Denver had only 6,000 hotel rooms.1
A natural response to this aggregation of unflattering research findings is to ask whether Harris has done any better than the forecasters whose performance he faults. He makes a credible case that he has. A 1993 Wall Street Journal study of interest rate forecasters ranked Harris the second most accurate among 34 bond-yield forecasters in the 1980s. He and his UBS colleague James O’Sullivan were named the most accurate week-ahead forecasters by MarketWatch in 2004, 2006, and 2008. A 2011 Bloomberg News report identified Harris and his UBS team as the most accurate forecasters over a two-year span for a wide range of economic indicators.
At the reviewer’s behest, Barron’s economics editor Gene Epstein obtained data from Blue Chip Economic Indicators regarding Harris’s accuracy in predicting five items over the latest five years. Epstein scored Harris on both frequency of achieving greater accuracy than the consensus and the magnitude by which his forecasts were more accurate or less accurate than the consensus. Epstein found that Harris underperformed the consensus on GDP, the three-month Treasury bill rate, and the unemployment rate and did essentially as well as the consensus on the consumer price index. However, Harris’s record on forecasting the 10-year Treasury note yield was outstanding; he beat the consensus five years in a row.
To the extent that Harris has excelled as a forecaster, it has not been by accident. Inside the Crystal Ball details his impressively rigorous process. Shunning ideological blinders, he draws on all major schools of macroeconomic thought and keeps his analysis up to date through intensive study of new research findings. One such finding is that accuracy improves when forecasters leaven their quantitative models with judgment formed through experience. Harris provides several examples of forecasts that went awry because the forecasters failed to adjust their models for unprecedented developments, such as the impact of the loose subprime lending standards of the early 2000s on housing price appreciation.
Aspiring forecasters will be negligent if they fail to scour this book for the invaluable pointers that its author generously shares. For example, Harris urges them not to reinvent the wheel when it comes to identifying cause-and-effect relationships. The goal is not originality, he observes, but accuracy.
Harris also asserts that it is imperative to understand how economic indicators are compiled and reported. A case in point is the nonfarm payroll number. To determine whether an event that occurs on a particular date, such as a strike or a blizzard, will affect this monthly figure, a forecaster must be aware that the survey covers only a two-week pay period that includes the 12th day of the month.
Harris clearly has a passion for getting these details right, even though he emphasizes that forecasters must accept the reality that they will sometimes be wrong. Being imperfect, he trips up on one of the quotations that he uses to introduce the themes of his chapters. The baseball great Yogi Berra did not say, “It’s tough to make predictions, especially about the future,” as page 1 indicates. This humorous aphorism has been attributed to everyone from Niels Bohr to Samuel Goldwyn, but the best evidence suggests that it originated with a Danish author whose identity is unknown.2
Notwithstanding this small misstep, Inside the Crystal Ball is an invaluable resource for anyone striving for a command of the inner workings of the economy. The author dives deep into the data to explain why he expects structural unemployment to produce a higher nonaccelerating inflation rate of unemployment (NAIRU) than in the past and why he believes the recent rise in inequality of income distribution will subside over the next decade. Many readers will be surprised to learn that the variable most highly correlated with the 10-year Treasury yield is the federal funds rate, explaining more variance than even the expected inflation rate. Maury Harris has truly rendered a great service by providing economics junkies a proverbial drink from a fire hose in clear, unmannered, and consistently engaging prose.