1 / 22

Increasing uncertainties? A post-mortem on the Federal Planning Bureau’s medium-term projections

Increasing uncertainties? A post-mortem on the Federal Planning Bureau’s medium-term projections. Francis Bossier Igor Lebrun 39 th CMTEA - Romania, Iaşi, September 25-27 th , 2008. How to address uncertainty in forecasting?. Scenario analysis (‘variants’):

tad-butler
Download Presentation

Increasing uncertainties? A post-mortem on the Federal Planning Bureau’s medium-term projections

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. Increasing uncertainties? A post-mortem on the Federal Planning Bureau’s medium-term projections Francis Bossier Igor Lebrun 39th CMTEA - Romania, Iaşi, September 25-27th, 2008 http://www.plan.be

  2. How to address uncertainty in forecasting? • Scenario analysis (‘variants’): To illustrate effects of potential risks surrounding baseline (results are often presented as deviations from baseline) • Confidence intervals: Traditionally symmetric (ECB projections for the euro area) but can also be asymmetric to reveal unbalanced risks (‘fan chart’ in IMF WEO)

  3. Why is it useful to evaluate past forecast performances ? • To assess whether forecasts meet basic quality standards: • Unbiasedness and absence of serial correlation (weak efficiency) • Information set fully exploited (informational efficiency) • Size of error declines when forecasting horizon shortens • Directional accuracy • Prediction of turning points

  4. Why is it useful to evaluate past forecast performances? (2) • To identify possible methodological weaknesses that should be improved • To give users a broad idea of the precision of the forecast  International organizations tend to asses their forecasts on a relatively regular basis: • IMF: Working Paper by Allan Timmerman (2006) • OECD: Working Paper by Lukas Vogel (2007) • EC: Economic paper by Melander et. al. (2007)

  5. The Belgian Federal Planning Bureau:Short-term macro-economic forecasts • Economic budget: • Released twice a year: September for the year t+1 and February for the year t • Produced with quarterly macro-econometric model but adjusted for recent business cycle information • 2004: track record for GDP growth and inflation (WP 13-04) • 2006: update of post-mortem analysis (WP 4-06) • Project: evaluation of forecasts for larger set of variables

  6. The Belgian federal Planning Bureau:Medium-term macro-economic projections • Economic outlook: • Released in Spring with an update in Autumn • Very detailed macroeconomic projection • Forecast for current year based on a economic budget • Simulation with six-year horizon using the HERMES model • Unchanged policy scenario with regard to fiscal and social policies • 2006: evaluation of GDP growth and budgetary projections (in European Economy, Economic Papers No. 275) • 2007: evaluation of past projection errors for a large set of variables (WP 8-07)

  7. The methodology used to evaluate the medium-term projections • Focus on GDP trend growth and trend inflation • Methodology proposed by Jonung and Larch (EP, 2006): • For each historical data vintage trend growth is obtained by HP-filtering the series (historical data + projections) • The value of year t+1 of the filtered series is taken as the one-year-ahead forecast of trend growth • The outcome is computed by applying recursively the HP-filter on a rolling sample based on the latest data vintage • Sample starts with 1986 outlook (covering 1987-1990) and ends with 2006 issue (covering 2007-2011) • Outcome given by the 2008 issue (covering 2009-2013)

  8. GDP trend growth: one-year-ahead forecast

  9. GDP trend growth: one-year-ahead forecast vs. actual estimates

  10. GDP trend growth: Forecasting error

  11. GDP trend growth: Forecasting error and output gap

  12. GDP trend growth and potential export markets: Forecasting errors

  13. Output gap: one-year-ahead vs. actual estimates

  14. GDP trend growth: Contributions to forecasting errors

  15. Descriptive statistics for projection errors (1987-2007) Mean errorNo bias No corr GDP -0.10 0.37 0.00 Productivity -0.30 0.00 0.00 Employment 0.20 0.03 0.00 Positive (negative) mean error = underestimation (overestimation) No bias = probability for zero mean error No corr = probability for uncorrelated errors

  16. Productivity growth: actual and trend

  17. Productivity growth: one-year-ahead forecast vs. actual estimates

  18. Trend inflation: one-year-ahead forecast

  19. Trend inflation: one-year-ahead forecast vs. actual estimates

  20. Trend inflation: Forecasting errors

  21. Price trend growth: Forecasting errors

  22. Conclusions • Difficulty to disentangle trend from cycle at the end of the sample • Risk of running behind the facts because trend growth only “observable” with a huge delay • Increased uncertainty? No clear indication that projection errors have increased recently but only future will tell • Despite size and inertia of projection errors we believe our medium-term outlook remains an important tool for policy-makers, social partners and public in general in terms of diagnosis for the Belgian economy

More Related