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 Research for 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