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The author would like to acknowledge comments from Jörg Decressin, Vladimir Klyuev, Alasdair Scott, Krishna Srinivasan, and Emil Stavrev. The paper outlines the methodology behind financial conditions indexes that appear in the World Economic Outlook.
Hatzius, Hooper, Mishkin, Schoenholtz, and Watson (2010) use a similar methodology to construct an FCI for the United States, but do not take account of publication lags at the end of the sample in their forecasting experiment and the real-time revision properties of their FCI are not examined.
The quarterly series are linearly interpolated, whereas the daily series are converted to monthly averages. Quarterly log differences are taken of the non-stationary indicators. Note, the in-sample results are very similar if the FCIs are estimated using quarterly data, but using monthly data offers more timely estimates of financial conditions at the end of the sample in real time.
The assumption that ψ is diagonal is relaxed when backdating these indicators.
The output gap and the real short-term interest rate are taken from a much larger, more sophisticated model – the Global Projection Model (GPM). See Carabenciov, Freedman, Garcia-Saltos, Laxton, Kamenik, and Manchev (forthcoming).
Due to a lack of available data, the data vintages the would have existed in real time are not used. Instead, the most recent vintage of data is used to simulate the data available each time a forecast is made. Real-time output gaps and short-term real interest rates are simply truncated from the most recent GPM estimates.
In each month, the end point for the FCI estimate matches that of the GDP data that would have been available at the time.