Research Catalog

Measuring GDP Forecast Uncertainty Using Quantile Regressions

Title
Measuring GDP Forecast Uncertainty Using Quantile Regressions [electronic resource] / Thomas Laurent and Tomasz Koźluk
Author
Laurent, Thomas.
Publication
Paris : OECD Publishing, 2012.

Available Online

Full text online available onsite at NYPL

Details

Additional Authors
Koźluk, Tomasz.
Description
34 p.; 21 x 29.7cm.
Summary
Uncertainty is inherent to forecasting and assessing the uncertainty surrounding a point forecast is as important as the forecast itself. Following Cornec (2010), a method to assess the uncertainty around the indicator models used at OECD to forecast GDP growth of the six largest member countries is developed, using quantile regressions to construct a probability distribution of future GDP, as opposed to mean point forecasts. This approach allows uncertainty to be assessed conditionally on the current state of the economy and is totally model based and judgement free. The quality of the computed distributions is tested against other approaches to measuring forecast uncertainty and a set of uncertainty indicators is constructed in order to help exploiting the most helpful information.
Series Statement
OECD Economics Department Working Papers, 1815-1973 ; no.978
Uniform Title
OECD Economics Department Working Papers, no.978.
Subject
Economics
LCCN
10.1787/5k95xd76jvvg-en
OCLC
oecd-lib-000846
Author
Laurent, Thomas.
Title
Measuring GDP Forecast Uncertainty Using Quantile Regressions [electronic resource] / Thomas Laurent and Tomasz Koźluk
Imprint
Paris : OECD Publishing, 2012.
Series
OECD Economics Department Working Papers, 1815-1973 ; no.978
OECD Economics Department Working Papers, 1815-1973 ; no.978.
Connect to:
http://dx.doi.org/10.1787/5k95xd76jvvg-en
Indexed Term
Economics
Added Author
Koźluk, Tomasz.
Other Standard Identifier
10.1787/5k95xd76jvvg-en doi
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