Now showing items 1-4 of 4

  • Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions 

    Dufour, Jean Marie; Khalaf, Lynda (Université de Montréal. Département de sciences économiques., 2000)
    This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo ...
  • Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing 

    Dufour, Jean Marie; Jouini, Tarek (Université de Montréal. Département de sciences économiques., 2005)
    Statistical tests in vector autoregressive (VAR) models are typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with ...
  • Inflation dynamics and the New Keynesian Phillips Curve: an identification robust econometric analysis 

    Dufour, Jean Marie; Khalaf, Lynda; Kichian, Maral (Université de Montréal. Département de sciences économiques., 2005)
    In this paper, we use identification-robust methods to assess the empirical adequacy of a New Keynesian Phillips Curve (NKPC) equation. We focus on the Gali and Gertler’s (1999) specification, on both U.S. and Canadian data. Two variants of the model ...
  • Short run and long run causality in time series: Inference 

    Dufour, Jean Marie; Pelletier, Denis; Renault, Éric (Université de Montréal. Département de sciences économiques., 2003)
    We propose methods for testing hypotheses of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at ...