IMF Working Papers

How Well Do Economists Forecast Recessions?

By Zidong An, João Tovar Jalles, Prakash Loungani

March 5, 2018

Download PDF

Preview Citation

Format: Chicago

Zidong An, João Tovar Jalles, and Prakash Loungani. How Well Do Economists Forecast Recessions?, (USA: International Monetary Fund, 2018) accessed December 22, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

We describe the evolution of forecasts in the run-up to recessions. The GDP forecasts cover 63 countries for the years 1992 to 2014. The main finding is that, while forecasters are generally aware that recession years will be different from other years, they miss the magnitude of the recession by a wide margin until the year is almost over. Forecasts during non-recession years are revised slowly; in recession years, the pace of revision picks up but not sufficiently to avoid large forecast errors. Our second finding is that forecasts of the private sector and the official sector are virtually identical; thus, both are equally good at missing recessions. Strong booms are also missed, providing suggestive evidence for Nordhaus’ (1987) view that behavioral factors—the reluctance to absorb either good or bad news—play a role in the evolution of forecasts.

Subject: Economic theory, Production, Production growth, Rational expectations

Keywords: Bias, Comparing recession, Efficiency, Forecast comparison, Forecasted recession, Global, IMF World Economic Outlook, Information rigidity, Production growth, Rational expectations, Recession, Recession episode, Recession year, WP

Publication Details

  • Pages:

    31

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2018/039

  • Stock No:

    WPIEA2018039

  • ISBN:

    9781484344873

  • ISSN:

    1018-5941