ORCID Profile
0000-0002-0563-5158
Current Organisation
University of Tasmania
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Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 06-2018
Publisher: Elsevier BV
Date: 09-2018
Publisher: Elsevier BV
Date: 03-2021
Publisher: Wiley
Date: 28-06-2022
DOI: 10.1002/JAE.2905
Abstract: Contemporary structural models of the global market for crude oil jointly specify precautionary and speculative demand shocks as a composite shock, named a storage demand shock. We resolve this identification problem and examine the effects of these distinct shocks, along with conventional demand and supply shocks, on the global price of crude oil. We find that uncertainty driven precautionary demand for crude oil is, on average, the primary driver of real price of oil fluctuations that have previously been associated with storage demand shocks. Historically, these shocks have had distinct effects on the real oil price dynamics since the 1970s.
Publisher: Elsevier BV
Date: 06-2022
Publisher: Elsevier BV
Date: 05-2019
Publisher: Wiley
Date: 09-2019
DOI: 10.1002/APP5.287
Publisher: Wiley
Date: 26-03-2018
Publisher: Wiley
Date: 11-10-2022
DOI: 10.1002/FOR.2913
Abstract: This paper evaluates the real‐time forecast performance of alternative Bayesian autoregressive (AR) and vector autoregressive (VAR) models for the Australian macroeconomy. To this end, we construct an updated vintage database and compare the predictive ability of a wide set of specifications that takes into account almost all possible combinations of nonstandard errors existing in the current literature. In general, we find that the models with flexible covariance structures can improve the forecast accuracy as compared with the standard variant. For forecasting GDP, both point and density forecasts consistently suggest small VARs tend to outperform their counterparts while AR models often predict inflation better. With the unemployment rate, large VAR models provide superior forecasts to the alternatives at almost all forecast horizons. The forecasting performance of these models slightly changes when we consider the first, second, and latest‐available vintage as actual values, highlighting the importance of using real‐time data vintages in forecasting.
Publisher: Elsevier BV
Date: 02-2017
No related grants have been discovered for Bao Nguyen.