In brief

New issues related to forecasting in macroeconomics and finance. have emerged as larger and richer data sets have become available. The FHDDA Group at CIRANO has taken up two lines of research:

  • We address the gains in forecast accuracy attainable in "data-rich" environments where the number of series available for use in a forecast may number in the dozens or hundreds. Research has focused on useful ways to summarize their information in dimensionally-reduced models such as factor models, or by combining models by techniques such as Bayesian model averaging.
  • We have investigated the potential effects on our models, estimation procedures, and evaluations caused by the use of preliminary data which are later revised. "Real-time" data analysis studies the revisions to measured data across different "vintages" of series, and the impact on our economic analyses. The past three years CIRANO has hosted a "Real-time" conference. We will continue to do so.
This WEB page summarizes the work undertaken at CIRANO in these area and provides links to conferences and relevant data sources. Please contact us with additional information that may be of interest to the research community.

CIRANO FHDDA Members

Campbell, Bryan bryan.campbell@cirano.qc.ca 514-985-4000p4008 Concordia University
Galbraith, John W. john.galbraith@cirano.qc.ca 514-985-4000p3032 McGill University
Van Norden, Simon simon.van_norden@cirano.qc.ca 514-985-4000p3024 HEC Montréal

Cahiers scientifiques (8)

2010s-46 CS ++ Jan P. A. M. Jacobs et Simon van Norden. Lessons From the Latest Data on U.S. Productivity
2009s-36 CS John Galbraith et Simon van Norden. Calibration and Resolution Diagnostics for Bank of England Density Forecasts
2008s-28 CS John Galbraith et Simon van Norden. The Calibration of Probabilistic Economic Forecasts
2003s-01 CS Athanasios Orphanides et Simon van Norden. The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time
2001s-46 CS Marc Brisson, Bryan Campbell et John Galbraith. Forecasting Some Low-Predictability Time Series Using Diffusion Indices
2001s-57 CS Athanasios Orphanides et Simon van Norden. The Unreliability of Output Gap Estimates in Real Time
99s-17 CS John Galbraith. Content Horizons for Forecasts of Economic Time Series
95s-08 CS Bryan Campbell et Eric Ghysels. An Empirical Analysis of the Canadian Budget Process

Conférences (12)

In brief

New issues related to forecasting in macroeconomics and finance. have emerged as larger and richer data sets have become available. The FHDDA Group at CIRANO has taken up two lines of research:

  • We address the gains in forecast accuracy attainable in "data-rich" environments where the number of series available for use in a forecast may number in the dozens or hundreds. Research has focused on useful ways to summarize their information in dimensionally-reduced models such as factor models, or by combining models by techniques such as Bayesian model averaging.
  • We have investigated the potential effects on our models, estimation procedures, and evaluations caused by the use of preliminary data which are later revised. "Real-time" data analysis studies the revisions to measured data across different "vintages" of series, and the impact on our economic analyses. The past three years CIRANO has hosted a "Real-time" conference. We will continue to do so.
This WEB page summarizes the work undertaken at CIRANO in these area and provides links to conferences and relevant data sources. Please contact us with additional information that may be of interest to the research community.