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Working Paper
Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach
This paper focuses on forecasting quarterly energy prices of commodities, such as oil, gas and coal, using the Global VAR dataset proposed by Mohaddes and Raissi (2018). This dataset includes a number of potentially informative quarterly macroeconomic variables for the 33 largest economies, overall accounting for more than 80% of the global GDP. To deal with the information in this large database, we apply a dynamic factor model based on a penalized maximum likelihood approach that allows us to shrink parameters to zero and to estimate sparse factor loadings. The estimated latent factors show ...
Journal Article
Energy Investment Variability Within the Macroeconomy
Over the past 10 years, the U.S. energy sector has exerted substantial influence?both positive and negative?on overall U.S. business fixed investment. From 2010 to 2014, a time when energy production in the United States was expanding, investment in the energy sector was a boon to aggregate investment. However, following the sharp oil price decline in 2014, the energy sector was a drag on aggregate investment. {{p}} Assessing the energy sector?s contribution to aggregate investment requires an understanding of both the size of the sector as well as its individual segments. David Rodziewicz ...