• 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 ...
    • Volatility Estimation When the Zero-Process is Nonstationary 

      Francq, Christian; Sucarrat, Genaro (Journal article; Peer reviewed, 2021)
      Financial returns are frequently nonstationary due to the nonstationary distribution of zeros. In daily stock returns, for example, the nonstationarity can be due to an upwards trend in liquidity over time, which may lead ...