Discussion of Presentations on Real-Time Data Analysis

1. Discussion of Presentations on Real-Time Data Analysis Dean Croushore Associate Professor, University of Richmond Visiting Scholar, Federal Reserve Bank of Philadelphia May 2008

2. Data Sets • Real-Time Data Set for Macroeconomists • Philadelphia Fed (Tom Stark) • Need for good institutional support • Club good: non-rival but excludable

3. Data Sets • Unrestricted access: • U.S.: Philadelphia Fed, St. Louis Fed, BEA • OECD • Bank of England (recently updated) • Restricted access: • EABCN • Fate unclear: • Canada • One-time research projects: • Many, most not continuously updated

4. Role of Researchfor Data Production • Analysis of data revisions is not criticism of government statistical agencies! • May help agencies improve data production process • Revisions reflect limited resources devoted to data collection • Revised data usually superior to unrevised data (U.S. CPI vs. PCE price index)

5. Monetary Policy: Data Revisions • How Much Does It Matter for Monetary Policy that Data Are Revised? • Example: Fed’s favorite inflation measure is the Personal Consumption Expenditures Price Index Excluding Food & Energy Prices (core PCE inflation) • But it has been revised substantially; similar to revisions to overall PCE inflation, as Bob Tetlow showed

6. Monetary Policy: Data Revisions • How Much Does It Matter for Monetary Policy that Data Are Revised? • Charts show that instead of worrying about a substantial unwanted decline in inflation, the Fed should have been worried about a rise in inflation

9. Monetary Policy: Data Revisions • How Much Does It Matter for Monetary Policy that Data Are Revised? • Simple regressions show that the annual revision of PCE inflation data (both overall and core) is forecastable

10. Current Analysis • How Can Real-Time Data Be Used for Current Analysis? • Domenico Giannone’s research: extract real-time information to determine a real shock and a nominal shock, which represent fundamental dynamics of US economy • Surprising findings: surveys (especially Philadelphia Fed Business Outlook Survey) matter significantly

11. Current Analysis • Remaining issue: how helpful is nowcasting for monetary policy? • Fed spends many resources on nowcasting, but policy works with a lag, so forecasting is more important • Does nowcasting better help us forecast better? • Or are forecasts at the policy horizon unaffected by the nowcast?

12. Monetary Policy: Analytical Revisions • What Happens When Economists or Policymakers Revise Conceptual Variables? • Output gap • Natural rate of unemployment • Equilibrium real interest rate • Concepts are never observed, but are centerpiece of macroeconomic theory

13. Monetary Policy: Analytical Revisions • Research: Fed overreacted to perceived output gap in 1970s, causing Great Inflation; but output gap was mismeasured • Very difficult to measure output gap in real time (Simon van Norden) • Different methods lead to very different output gap measures; hard to choose “best” method • Productivity growth is revised substantially, so forecasting output gap is problematic

14. Monetary Policy: Analytical Revisions • Policy models may change: • Tetlow-Ironside (2007): changes in FRB-US model changed the story the model was telling to policymakers • Model changes exacerbated by data revisions

15. Monetary Policy: Analytical Revisions • What Happens When Economists or Policymakers Revise Conceptual Variables? • Key issue: end-of-sample inference for forward-looking concepts (filters) • Key issue: optimal model of evolution of analytical concepts • Most work is statistical; perhaps a theoretical breakthrough is needed