The Accuracy of Macroeconomics Forecasts – Survey of Professional Forecasters

The Philadelphia Federal Reserve Bank maintains historic records of macroeconomic forecasts from the Survey of Professional Forecasters (SPF). These provide an outstanding opportunity to assess forecasting accuracy in macroeconomics.

For example, in 2014, what is the chance the “steady as she goes” forecast from the current SPF is going to miss a downturn 1, 2, or 3 quarters into the future?

1-Quarter-Ahead Forecast Performance on Real GDP

Here is a chart I’ve ginned up for a 1-quarter ahead performance of the SPF forecasts of real GDP since 1990.

SP!1Q

The blue line is the forecast growth rate for real GDP from the SPF on a 1-quarter-ahead basis. The red line is the Bureau of Economic Analysis (BEA) final number for the growth rate for the relevant quarters. The growth rates in both instances are calculated on a quarter-over-quarter basis and annualized.

Side-stepping issues regarding BEA revisions, I used BEA final numbers for the level and growth of real GDP by quarter. This may not completely fair to the SPF forecasters, but it is the yardstick SPF is usually judged by its “consumers.”

Forecast errors for the 1-quarter-ahead forecasts, calculated on this basis, average about 2 percent in absolute value.

They also exhibit significant first order autocorrelation, as is readily suggested by the chart above. So, the SPF tends to under-predict during expansion phases of the business cycle and over-predict during contraction phases.

Currently, the SPF 2014:Q1 forecast for 2014:Q2 is for 3.0 percent real growth of GDP, so maybe it’s unlikely that an average error for this forecast would result in actual 2014:Q2 growth dipping into negative territory.

2-Quarter-Ahead Forecast Performance on Real GDP

Errors for the 2-quarter-ahead SPF forecast, judged against BEA final numbers for real GDP growth, only rise to about 2.14 percent.

However, I am interested in more than the typical forecast error associated with forecasts of real Gross Domestic Product (GDP) on a 1-, 2-, or 3- quarter ahead forecast horizon.

Rather, I’m curious whether the SPF is likely to catch a
downturn over these forecast horizons, given that one will occur.

So if we just look at recessions in this period, in 2001, 2002-2003, and 2008-2009, the performance significantly deteriorates. This can readily be seen in the graph for 1-quarter-ahead forecast errors shown above in 2008 when the consensus SPF forecast indicated a slight recovery for real GDP in exactly the quarter it totally tanked.

Bottom Line

In general, the SPF records provide vivid documentation of the difficulty of predicting turning points in key macroeconomic time series, such as GDP, consumer spending, investment, and so forth. At the same time, the real-time macroeconomic databases provided alongside the SPF records offer interesting opportunities for second- and third-guessing both the experts and the agencies responsible for charting US macroeconomics.

Additional Background

The Survey of Professional Forecasters is the oldest quarterly survey of macroeconomic forecasts in the United States. It dates back to 1968, when it was conducted by the American Statistical Association and the National Bureau of Economic Research (NBER). In 1990, the Federal Reserve Bank of Philadelphia assumed responsibility, and, today, devotes a special section on its website to the SPF, as well “Historical SPF Forecast Data.”

Current and recent contributors to the SPF include “celebrity forecasters” highlighted in other posts here, as well as bank-associated and university-affiliated forecasters.

The survey’s timing is geared to the release of the Bureau of Economic Analysis’ advance report of the national income and product accounts. This report is released at the end of the first month of each quarter. It contains the first estimate of GDP (and components) for the previous quarter. Survey questionnaires are sent after this report is released to the public. The survey’s questionnaires report recent historical values of the data from the BEA’s advance report and the most recent reports of other government statistical agencies. Thus, in submitting their projections, panelists’ information includes data reported in the advance report.

Recent participants include:

Lewis Alexander, Nomura Securities; Scott Anderson, Bank of the West (BNP Paribas Group); Robert J. Barbera, Johns Hopkins University Center for Financial Economics; Peter Bernstein, RCF Economic and Financial Consulting, Inc.; Christine Chmura, Ph.D. and Xiaobing Shuai, Ph.D., Chmura Economics & Analytics; Gary Ciminero, CFA, GLC Financial Economics; Julia Coronado, BNP Paribas; David Crowe, National Association of Home Builders; Nathaniel Curtis, Navigant; Rajeev Dhawan, Georgia State University; Shawn Dubravac, Consumer Electronics Association; Gregory Daco, Oxford Economics USA, Inc.; Michael R. Englund, Action Economics, LLC; Timothy Gill, NEMA; Matthew Hall and Daniil Manaenkov, RSQE, University of Michigan; James Glassman, JPMorgan Chase & Co.; Jan Hatzius, Goldman Sachs; Peter Hooper, Deutsche Bank Securities, Inc.; IHS Global Insight; Fred Joutz, Benchmark Forecasts and Research Program on Forecasting, George Washington University; Sam Kahan, Kahan Consulting Ltd. (ACT Research LLC); N. Karp, BBVA Compass; Walter Kemmsies, Moffatt & Nichol; Jack Kleinhenz, Kleinhenz & Associates, Inc.; Thomas Lam, OSK-DMG/RHB; L. Douglas Lee, Economics from Washington; Allan R. Leslie, Economic Consultant; John Lonski, Moody’s Capital Markets Group; Macroeconomic Advisers, LLC; Dean Maki, Barclays Capital; Jim Meil and Arun Raha, Eaton Corporation; Anthony Metz, Pareto Optimal Economics; Michael Moran, Daiwa Capital Markets America; Joel L. Naroff, Naroff Economic Advisors; Michael P. Niemira, International Council of Shopping Centers; Luca Noto, Anima Sgr; Brendon Ogmundson, BC Real Estate Association; Martin A. Regalia, U.S. Chamber of Commerce; Philip Rothman, East Carolina University; Chris Rupkey, Bank of Tokyo-Mitsubishi UFJ; John Silvia, Wells Fargo; Allen Sinai, Decision Economics, Inc.; Tara M. Sinclair, Research Program on Forecasting, George Washington University; Sean M. Snaith, Ph.D., University of Central Florida; Neal Soss, Credit Suisse; Stephen Stanley, Pierpont Securities; Charles Steindel, New Jersey Department of the Treasury; Susan M. Sterne, Economic Analysis Associates, Inc.; Thomas Kevin Swift, American Chemistry Council; Richard Yamarone, Bloomberg, LP; Mark Zandi, Moody’s Analytics.