Global temperatures and greenhouse gases: a common features approach

Li Chen; Jiti Gao; Farshid Vahid

doi:10.1016/j.jeconom.2021.04.003

Global temperatures and greenhouse gases: a common features approach

Li Chen, Jiti Gao, Farshid Vahid

Econometrics & Business Statistics

Research output: Contribution to journal › Article › Research › peer-review

11 Citations (Scopus)

Abstract

We propose a common features approach for testing for common trends and estimating long-run relationships between variables with complex trends. Using this approach, we establish that global temperatures and the concentration of greenhouse gases share a common trend and we estimate their long-run relationship without conditioning on the exact nature of this trend.

Original language	English
Pages (from-to)	240-254
Number of pages	15
Journal	Journal of Econometrics
Volume	230
Issue number	2
DOIs	https://doi.org/10.1016/j.jeconom.2021.04.003
Publication status	Published - Oct 2022

Keywords

Complex trends
Endogeneity
Global warming
Instrumental variables
Testing for common trends

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10.1016/j.jeconom.2021.04.003

Cite this

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keywords = "Complex trends, Endogeneity, Global warming, Instrumental variables, Testing for common trends",

author = "Li Chen and Jiti Gao and Farshid Vahid",

note = "Funding Information: Li Chen acknowledges the financial support by the Fundamental Research Funds for the Central Universities, China (grant number 20720181060 ), and Jiti Gao and Farshid Vahid would also like to thank the Australian Research Council Discovery Grants Program under Grant Number: DP200102769 for its financial support. Publisher Copyright: {\textcopyright} 2021 Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

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KW - Instrumental variables

KW - Testing for common trends

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Global temperatures and greenhouse gases: a common features approach

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Keywords

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New methods for modelling complex trends in climate and energy time series

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Global temperatures and greenhouse gases: a common features approach

Abstract

Keywords

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New methods for modelling complex trends in climate and energy time series

Cite this