1. Forecast Surveys

2. Introduction Two Philadelphia Fed surveys of private-sector forecasters – Livingston Survey – Survey of Professional Forecasters (SPF) Provide timely forecasts for policymakers and economic analysts Used to answer numerous research questions

3. Introduction Philadelphia Fed economists pushed to have surveys here – Livingston Survey: Don Mullineaux (?) – SPF: Dean Croushore Current research department keeps them here & makes them ever more useful – Loretta Mester (research director) – Tom Stark (maestro)

4. Introduction Both surveys – Available to the public at no charge (Fed’s public education mission) – Used by news media, policymakers, economic analysts, labor unions, consumers

5. Introduction Livingston Survey – Begun in 1946 – Joe Livingston, journalist – 1970s: economists discover survey – 1978: Philadelphia Fed takes over database – 1990: Philadelphia Fed takes over administration of survey

6. Introduction SPF – ASA/NBER survey begun in 1968 – Victor Zarnowitz & other founders – ASA/NBER folds survey in 1990 – Philadelphia Fed takes over in 1990 – Renamed Survey of Professional Forecasters

7. What Variables Do the Participants Forecast? Both surveys: Nominal GDP Real GDP Inflation (CPI) Unemployment rate Industrial production Interest rate: 3-month T- bills Interest rate: 10-year T- notes Corporate profits after tax Housing starts Business fixed investment

8. What Variables Do the Participants Forecast? Livingston survey: Producer price index S&P 500 stock prices Average weekly earnings Retail trade sales Auto sales Prime interest rate Average over the next 10 years: – Real GDP growth – CPI inflation rate

9. What Variables Do the Participants Forecast? SPF: GDP price index Payroll employment Interest rate: AAA bonds Remaining GDP components Inflation rates: – CPI excluding food & energy prices (core CPI) – PCE price index – PCE price index excluding food & energy prices (core) Probability that real GDP will decline Distribution forecasts: – Real GDP – GDP price index – Core CPI – Core PCE price index Long-term forecasts: – CPI price index – PCE price index

10. What Variables Do the Participants Forecast? SPF: First Quarter: – Long-term projections Real GDP growth Productivity growth Stock returns Long-term bond returns Short-term bond returns Third Quarter: – Estimates of natural rate of unemployment Special Questions – Declines in house prices – Effects of stimulus package – Effect of Y2K

11. Anonymity Both surveys promise anonymity – Can’t match forecaster to a forecast – Allows forecasters to reveal their true forecast, without attribution – Prevents herding and extreme forecasts

12. Evaluating the Survey Forecasts Are the forecasts accurate? Statistical tests – Unbiasedness (forecast errors have zero mean) – Efficiency (forecast errors are uncorrelated with information known when forecast was made)

13. Evaluating the Survey Forecasts Unbiasedness – Over long samples, forecasts of major variables appear unbiased (Figure 1)

15. Evaluating the Survey Forecasts Unbiasedness – Over long samples, forecasts of major variables appear unbiased (Figure 1) – Formal statistical tests: Test: α = 0, β = 1

16. Evaluating the Survey Forecasts Unbiasedness – Or: Test: α = 0

17. Evaluating the Survey Forecasts Sub-periods show poor performance

19. Evaluating the Survey Forecasts Sub-periods show poor performance Persistent forecast errors in 1970s and 1990s Those periods require explanation: failure to recognize impact of faster money growth; errors in evaluating natural rate of unemployment and rate of potential GDP growth

20. Evaluating the Survey Forecasts Inefficiency with respect to other variables Test: forecast errors should be uncorrelated with other variables known when survey was conducted – Example from Ball-Croushore (Figure 3)

22. Evaluating the Survey Forecasts Inefficiency with respect to other variables – Example from Ball-Croushore (Figure 3) – SPF forecasters seem not to change output forecasts enough in response to change in monetary policy

23. Evaluating the Survey Forecasts Accuracy of probability distribution forecasts – Results from Diebold-Tay-Wallis (1999) Forecasts are reasonably accurate But too much probability of a large reduction in inflation Persistent inflation forecast errors

24. Evaluating the Survey Forecasts Conclusion – SPF & Livingston survey forecasts fairly accurate— passing most tests – Some imperfections