1. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 1 The Use and Abuse of Real-Time and Anecdotal Information in Monetary Policymaking Evan F. Koenig Senior Economist and Vice President Federal Reserve Bank of Dallas Dallas, Texas USA

2. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 2 Main points Data revisions complicate policy Usually, revisions are not given proper treatment Anecdotal/qualitative information potentially valuable

3. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 3 Example of the revisions problem: U.S. monetary policy in the 1990s

4. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 4 Professional forecasters over-predicted inflation during most of the 1990s

5. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 5 A candidate explanation: profitability profitability = (labor productivity)/(real wage) = price/(labor cost per unit output) high profitability ⇒ ▪expand output and employment ▪raise wages or cut prices 1970s: productivity deceleration + sluggish real wage ⇒ low profitability 1990s: productivity acceleration + sluggish real wage ⇒ high profitability

6. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 6 Profitability movements explain much of the NAIRU’s variation

7. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 7 Profitability apparently a powerful long-leading unemployment indicator

8. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 8 Profitability estimates are subject to large revisions

9. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 9 Inflation pressures: revised vs. real time

10. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 10 Apples and oranges Data relevant for policy are 1st release or lightly revised (oranges) Forecasting models usually estimated using heavily revised data (apples)

11. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 11 Correct procedure: estimate using “real- time-vintage” data “Real-time vintage” = at each point in sample, the 1st release and lightly revised data then available Requires short data series of many vintages

12. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 12 Alternatives to conventional statistics: anecdotal & qualitative data “Who are you going to believe? Me or your lying eyes?” –Groucho Marx

13. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 13 The Federal Reserve collects anecdotal information: Through Directors of 12 regional Reserve Banks and their 25 Branches Through calls to business contacts prior to each FOMC meeting ▪Each Reserve Bank prepares a call summary ▪Summaries are assembled and released as the “Beige Book”

14. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 14 How useful is the Beige Book? Receives substantial press attention Has predictive power for output and employment

15. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 15 The collapse of high-tech industrial production

16. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 16 The collapse of high-tech industrial production

17. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 17 “Sales growth weakened sharply for producers of high-tech equipment.” “Businesses have begun to curtail technology-related investment.” “Consumer demand for PCs has been weakening since the Fall of 2000.” –FRB-Dallas Beige Book report, January 2001

18. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 18 ISM Report on Business Survey of 400 manufacturing firms, nationwide Orders, output, jobs, etc.: expanding, contracting, or unchanged? Numerical index = % expanding + 0.5 × (% unchanged) PMI = weighted average of component numerical scores

19. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 19 Goldman-Sachs study shows PMI a big market mover

20. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 20 Limitations of PMI/Beige Book Sampling not scientific (small, unrepresentative) Responses not properly weighted Beige Book difficult to interpret

21. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 21 Advantages of PMI/Beige Book Timely Little if any revision Respondents filter out short-term fluctuations

22. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 22 The PMI captures trends in factory output growth

23. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 23 The PMI captures trends in factory output growth

24. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 24 Summary and Conclusions Don’t trust charts/forecasts that mix apples (heavily revised data) and oranges (lightly revised data) Archive statistical releases! Anecdotal/qualitative information potentially quite helpful

25. OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 25