• A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors 

      Juodis, Artūras; Sarafidis, Vasilis (Peer reviewed; Journal article, 2022)
      A novel method-of-moments approach is proposed for the estimation of factor-augmented panel data models with endogenous regressors when T is fixed. The underlying methodology involves approximating the unobserved common ...
    • Measurement Error Without the Proxy Exclusion Restriction 

      Chalak, Karim; Kim, Daniel (Journal article; Peer reviewed, 2019)
      This article studies the identification of the coefficients in a linear equation when data on the outcome, covariates, and an error-laden proxy for a latent variable are available. We maintain that the measurement error ...
    • Proper Scoring Rules for Evaluating Density Forecasts with Asymmetric Loss Functions 

      Iacopini, Matteo; Ravazzolo, Francesco; Rossini, Luca (Peer reviewed; Journal article, 2022)
      This article proposes a novel asymmetric continuous probabilistic score (ACPS) for evaluating and comparing density forecasts. It generalizes the proposed score and defines a weighted version, which emphasizes regions of ...
    • Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil 

      Aastveit, Knut Are; Cross, Jamie; van Dijk, Herman K. (Peer reviewed; Journal article, 2022)
      We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil using a combination of probabilistic individual model forecasts. Our combination method extends earlier ...