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Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate

Yoosoon Chang (), Robert Kaufmann (), Chang Kim, J. Miller (), Joon Park and Sungkeun Park
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Chang Kim: Department of Economics, Sungkyunkwan University
Joon Park: Department of Economics, Indiana University and Sungkyunkwan University
Sungkeun Park: Korea Institute for Industrial Economics and Trade

No 1622, Working Papers from Department of Economics, University of Missouri

Abstract: We analyze a time series of global temperature anomaly distributions to identify and estimate persistent features in climate change. Temperature densities from globally distributed data between 1850 and 2012 are treated as a time series of functional observations that change over time. We employ a formal test for the existence of functional unit roots in the time series of these densities. Further, we develop a new test to distinguish functional unit roots from functional deterministic trends or explosive behavior. Results suggest that temperature anomalies contain stochastic trends (as opposed to deterministic trends or explosive roots), two trends are present in the Northern Hemisphere while one stochastic trend is present in the Southern Hemisphere, and the probabilities of observing moderately positive anomalies have increased, but the probabilities of extremely positive anomalies has decreased. These results are consistent with the anthropogenic theory of climate change, in which a natural experiment causes human emissions of greenhouse gases and sulfur to be greater in the Northern Hemisphere and radiative forcing to be greater in the Southern Hemisphere. This Version:

Keywords: attribution of climate change; temperature distribution; global temperature trends; functional unit roots (search for similar items in EconPapers)
JEL-codes: C14 C23 C33 Q54 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-agr, nep-ecm and nep-env
Date: 2015-09-09, Revised 2016-12-19
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