2016 NBER NSF Time Series Conference


Welcome and opening remarks: 10:50am

Session 1 (IAB 1501): 11am-12:30pm.

Chair: Mike West (Duke University)

  • On consistency of the bootstrap testing for a parameter on the boundary of the parameter space
    Anders Rahbek (University of Copenhagen), G. Cavaliere and Heino Bohn Nielsen
  • Dynamic Covariance Estimation Using Sparsity Priors with a Bayesian Framework
    Sylvia Fruhwirth Schnatter (WU Vienna University of Economics and Business)
  • Rank Tests at Jump Events
    Viktor Todorov (Northwestern University), J. Li, G. Tauchen, and H. Lin

Lunch and Poster Session 1 (IAB 1101): 12:30-2pm 

Session 2 (IAB 1501): 2:00pm-3:30pm

Chair: Richard Davis (Columbia University)

  • Detecting Regime Switching: Analytic Power
    Douglas Staigerwald (University of Californa, Santa Barbara), Andrew Carter and Benjamin Hansen
  • Dating structural breaks in functional data without dimension reduction
    Alexander Aue (University of California, Davis), G. Rice and O. Sonmez
  • Likelihood Ratio Based Tests for Markov Regime Switching
    Zhongjun Qu (Boston University) and Fan Zhuo

Coffee break 

Session 3 (IAB 1501): 4:00pm-5:30pm

Chair: Victor Solo (University of New South Wales)

  • Bayesian Dynamic Modeling and Analysis of Streaming Network Data
    Xi Chen (Duke University), Karou Irie, David. Banks, Robert. Haslinger, Jewell Thomas, and M. West
  • Bayesian Inference on Structural Impulse Response Functions
    Mikkel Plagborg-Moller (Harvard University)
  • Directed Multi-graph Models for Network Data
    N. H. Chan (Chinese University of Hong Kong)

6-10pm: Dinner at Calle Ocho, 45 W. 81 St. 


Breakfast: Saturday, 8:30am-9am 

Session 4 (IAB 1501): 9am-10:30am

Chair: Michael McCracken (Federal Reserve of St. Louis)

  • HAR Inference: Recommendations for Practice
    James Stock (Harvard University), E. Lazarus, D. Lewis and M. W. Watson
  • High Dimensional Forecasting via Interpretable Vector Autoregression
    David Matteson (Cornell University), W. Nicholson and J. Bien
  • Regularized estimation of linear functionals for high-dimensional time series
    Xiaohui Chen (University of Illinois), Mengyu Xu and Wei Biao Wu

Coffee Break 

Session 5 (IAB 1501): 11am-12:30pm

Jushan Bai (Columbia University)

Lunch and Poster Session 2: 12:30pm-2pm (IAB 1101) 

Session 6 (IAB 1501): 2pm-3:30pm

Chair: Tim Vogelsang (MSU)

  • Normality tests for latent variables
    Dante Amengual (CEMFI), T. Almuzara and Enrique Sentana
  • Is Robust Inference with OLS Sensible in Time Series Regressions?
    Richard Baillie (Michigan State University) and K. H. Kim
  • Spatio-temporal models with space-time interaction and their application to air pollution data
    Ruey Tsay (University of Chicago) and Soudeep Deb



Poster Session 1, Friday

  1. A regularization approach to the dynamic panel data model estimation
    Marine Carrasco (University of Montreal)
  2. Large-dimensional factor modeling based on high-frequency observations
    Markus Pelger (Stanford University)
  3. The Discretization Filter: A Simple Way to Estimate Nonlinear State Space Models
    Leland Farmer (University of California, San Diego)
  4. Estimation with Aggregate Shocks
    Guido Kuersteiner (University of Maryland)
  5. Dynamic Bayesian predictive synthesis for time series forecasting
    Kenichiro McAlinn (Duke University)
  6. Wild Multiplicative Bootstrap for GMM Estimators in Time Series
    Lorenzo Camponovo (University of St. Gallen)
  7. Conditional Tail Expectation for Non-stationary Processes
    Henghsiu Tsai (Academia Sinica)
  8. Identification of Long-run Effects in Near-Integrated Systems
    Peter Boswijk (Tinbergen Institute)
  9. Identification, estimation and applications of a bivariate long-range dependent time series model with general phase
    Stefanos Kechagias (SAS Institute)
  10. Nonparametric Change Point Detection in Multivariate Nonstationary Time Series
    Raanju Sundararajan (Texas A and M University)
  11. Estimation of Quadratic Forms for High Dimensional Time Series
    Haoyang Liu (University of California, Berkeley)
  12. Indirect Inference Estimation of Nonlinear Dynamic General Equilibrium Models: With an Application
    Francisco Ruge-Murcia (Mcgill University)
  13. News or Noise: The Missing Link
    Kyle Jurado (Duke University)
  14. How Risky is Consumption in the Long-Run? Benchmark Estimates from a Robust Eimator
    Ian Dew-Becker (Northwesten University)

Poster Session 2, Saturday

  1. Estimating Risk Premia Using Only Large Cross-Sections
    Valentina Raponi and Paolo Zaffaroni (Imperial College)
  2. A Max-Correlation White Noise Test for Weakly Dependent Time Series
    Kaiji Motegi (Waseda University)
  3. Empirical Characteristic Function-based Inference for Locally Stationary Processes
    Marco Meyer (University of Mannheim)
  4. Identifying Long-Run Risks: A Bayesian Mixed-Frequency Approach
    Dongho Song (Boston College)
  5. Estimated Wold Representation and Spectral Density Riven Bootstrap for Time Series
    Jonas Krampe (TU Braunschweig)
  6. The Cepstral Model for Multivariate Time Series: The Vector Exponential Model
    Scott Holan (University of Missouri)
  7. Large Vector Autoregressions with Stochastic Volatility and Flexible Priors
    Andrea Carriero (University of London, Queen Mary)
  8. Inflation and Professional Forecast Dynamics: An Evaluation of Stickiness, Persistence, and Volatility
    Elmar Mertens (Federal Reserve Board)
  9. Modeling seasonal adjustment of daily time series
    Tucker McElroy (U.S. Census Bureau)
  10. The Effects of Seasonal Heteroskedasticity in Time Series on Trend Estimation and Seasonal Adjustment
    Thomas Trimbur (U.S. Census Bureau)
  11. A Bayesian Infinite Hidden Markov Structural Vector Autoregressive Model
    Didier Nibbering (Econometric Institute)
  12. Pre-test Based Inference for Panel Autoregression
    John Chao (University of Maryland)
  13. Monte Carlo Two-Stage Indirect Inference (2SIF) for Autoregressive Panel
    Lynda Khalaf (Carleton UNiversity)
  14. Semiparametric Estimation for Non-Gaussian Non-minimum Phase ARMA Models
    Jing Zhang (Columbia University)