Big Data in Predictive Dynamic Econometic Modeling Papers and Slides

THURSDAY, May 18
SESSION I: Shrinkage, Selection, Combination and Sparsity, I

Chair: Andrea Carriero (Queen Mary, University of London)

   
 SESSION II: High‐Dimensional Covariance Matrices
Chair: Tim Bollerslev (Duke)
    
SESSION III: Shrinkage, Selection, Combination and Sparsity, II  
Chair: Nour Meddahi (Toulouse)

SESSION IV:  Network Econometrics
Chair: George Tauchen, Duke
FRIDAY, May 19
  
SESSION V: High‐Dimensional Dynamic Factor Modeling, I  
Chair: Andrew Patton (Duke)
  • Serena Ng (Columbia) and Jushan Bai, “Estimation of Common Factors by Regularized Principal Components” Download Slides
  • Viktor Todorov (Northwestern), Torben Andersen, Nicola Fusari, and Rasmus Varneskov, “Unified Inference for Nonlinear Factor Models from Panels with Fixed and Large Time Span”  Download Slides
  • Christian Brownlees (Pompeu Fabra) and Geert Mesters, “Detecting Granular Time Series in Large Panels” Download Slides
SESSION VI: High‐Dimensional Dynamic Factor Modeling, II  
Chair: Giorgio Primiceri (Northwestern)
  • Glenn Rudebusch (FRB San Francisco), Jens Christensen, and Martin Andreasen, “Term Structure Modeling with Big DataDownload Slides
  • Matteo Barigozzi (London School of Economics) and Matteo Luciani, “Common Factors, Trends, and Cycles in Large Datasets” Download Slides
  • Eric Ghysels (UNC) and Xi Chen, “Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty” Download Slides
SESSION VII: Time‐Varying Parameters and Mixed‐Frequency Data in High‐Dimensional Filtering
Chair: Silvia Goncalves (Western Ontario)