Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

We propose a structural augmented dynamic factor model for U.S. CO 2 emissions. Variable selection techniques applied to a large set of annual macroeconomic time series indicate that CO 2 emissions are best explained by industrial production indices covering manufacturing and residential utilities. We employ a dynamic factor structure to explain, forecast, and nowcast the industrial production indices and thus, by way of the structural equation, emissions. We show that our model has good in-sample properties and out-of-sample performance in comparison with univariate and multivariate competitor models. Based on data through September 2019, our model nowcasts a reduction of about 2.6% in U.S. per capita CO 2 emissions in 2019 compared to 2018 as the result of a reduction in industrial production in residential utilities.

Original languageEnglish
Article number105118
JournalEnergy Economics
Volume96
Number of pages17
ISSN0140-9883
DOIs
Publication statusPublished - Apr 2021

    Research areas

  • CO emissions, Dynamic factor model, Forecasting, Macroeconomic variables, Nowcasting, Variable selection

See relations at Aarhus University Citationformats

ID: 211660344