1 / 61

Real-Time Recession Prediction: Challenges and Approaches

This presentation by James D. Hamilton from UCSD delves into the complexities of predicting recessions in real-time. It discusses the historical challenges economists face, including forecast errors from both the Federal Reserve and firms, as well as changes in economic relationships over time. The talk covers various predictive methodologies and tools, such as the role of employment data, interest rates, and composite leading indicators. With insights from past recessions and alternative approaches, it provides a comprehensive overview of recession forecasting.

kirk
Télécharger la présentation

Real-Time Recession Prediction: Challenges and Approaches

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Calling Recessions in Real Time James D. Hamilton Dept of Econ, UCSD

  2. I. Overview of some of the issues II. Track record of alternative approaches

  3. Is our objective to: • predict at t whether we will be in a recession at t + j or • predict at t whether we were in a recession at t - j Theme: It’s very hard even to do (2) in real time.

  4. Why should it be hard? (1) recessions result in part from forecast errors (a) Fed misjudges economy (b) Firms misjudge markets (2) economic relations change over time

  5. Why should it be hard? (1) recessions result in part from forecast errors (2) economic relations change over time (3) data revisions

  6. Source: Leamer (2008)

  7. Nonfarm payroll employment as reported on different dates

  8. What is the definition of a recession? Possible answers: A. Ad-hoc qualitative summary of observable data (e.g., 2 quarters of falling real GDP) B. It’s a recession if and only if the NBER says so C. A recession is an objective but unobserved determinant of the data

  9. I. Overview of some of the issues II. Track record of alternative approaches A. Predicting an ad-hoc event

  10. In-sample: P(t|t)

  11. In-sample: P(t+3|t)

  12. In-sample: P(t+6|t)

  13. Out-of-sample: P(t+6|t)

  14. Out-of-sample: P(t+3|t)

  15. Out-of-sample: P(t|t) Recession began: July 1990 P(t|t) > 0.5 by Nov 1990

  16. I. Overview of some of the issues II. Track record of alternative approaches A. Predicting an ad-hoc event B. Predicting what the NBER is going to say

  17. Interest Rates FF Federal Funds rate 3M 3-month Treasury Bill rate 5Y 5-year Treasury Bond rate 10Y 10-year Treasury Bond rate AAA Moody's corporate bond yield AA Moody's corporate bond yield A Moody's corporate bond yield Term Spreads TS10YFF 10Y-FF Treasury term spread TS10Y3M 10Y-3M Treasury term spread TS10Y5Y 10Y-5Y Treasury term spread Credit Spreads CSAAA AAA - 10Y spread CSAA AA - 10Y spread CSA A - 10Y spread Employment Data EMP Δ log non-agricultural employment CEMP Δ log civilian employment UICLAIM Δ log unemployment claims UNEMP Unemployment rate UNEMPD Change in unemployment rate HOURS Δ log manufacturing hours Stock Price Indices DJ30 3-mo Δ log Dow Jones 30 average SP500 3-mo Δ log S&P 500 stock price index Monetary Aggregates M0 Monetary base (log-differenced) M1 (log-differenced) M2 (log-differenced) Other Macroeconomic Variables CLI11 Δ log composite leading indicators CPI, all urban, all items (log-differenced) EXP Consumer expectation EXPD Changes in consumer expectation HOUSE Building permits (log-differenced) VENDOR performance INCOME Δ log personal income IP Industrial production (log-differenced) SALES Δ log Manufacturing & trade sales Katayama (LSU, 2008)

  18. Evaluated with 7 different choices for F(.) by post-sample and leave-2-years-out cross-validation

  19. Conclusion: Improvements from F(.) with positive skew and excess kurtosis Best variables: • 10Y-3M treasury spread • S&P500 3-month growth • employment growth

  20. Chauvet and Potter (2002, 2005) Probit specification based on term spread allowing for serial correlation and structural breaks successfully predicted 2001 recession

  21. Wright (2006) • F(.) ~ Normal • 10Y-30M treasury spread • fed funds rate • tries to predict an NBER recession any time within next 12 months

  22. Leamer (2008): Choose thresholds for 6-month changes so as to fit NBER dates

  23. I. Overview of some of the issues II. Track record of alternative approaches A. Predicting an ad-hoc event B. Predicting what the NBER is going to say C. Recognizing a shift in the observed dynamics of economic variables

  24. = 4.7  = 3.5  = -1.2  = 3.5

More Related