Work

Forecasting The Path of U.S. CO2 Emissions Using State-Level Information

Year: 2010

Type: article

Abstract: We compare the most common reduced-form models used for emissions forecasting, point out shortcomings, and suggest improvements. Using a U.S. state-level panel data set of CO2 emissions, we test the performance of existing models against a large universe of potential reduced-form models. We find that leading models in the literature, as well as models selected based on an emissions per capita loss measure or different in-sample selection criteria, perform significantly worse compared to the best model chosen based directly on the out-of-sample loss measure defined over aggregate emissions.

Source: The Review of Economics and Statistics

DOI: 10.1162/rest_a_00152

Authors: Maximilian Auffhammer, Ralf Steinhauser

Institutions: University of California, Berkeley, Australian National University

Language: English

Topic: Energy, Environment, Economic Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Climate action

Open Access status: bronze

OpenAlex ID: W2133248570