FORECASTING THE PATH OF US CO2 EMISSIONS USING STATE-LEVEL INFORMATION

• 成果类型: Article
• 署名作者: Auffhammer, Maximilian; Steinhauser, Ralf
• 署名单位: University of California System; University of California Berkeley; National Bureau of Economic Research; Australian National University
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/REST_a_00152
• 发表日期: 2012-02
• 页码: 172-185
• 关键词: environmental kuznets curve; pollution; GROWTH; models; biases

摘要

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.