International Environmental Agreements under Uncertainty, Learning and Asymmetry
碩士 === 國立高雄大學 === 應用經濟學系碩士班 === 107 === This paper establishes the heterogeneous IEA’s model to analyze self-enforcing international environmental agreements (SEIEA). Countries face the uncertainty of cost-benefit ratio in abatement decision, but it is assumed that all countries are able to know the...
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ndltd-TW-107NUK004120062019-10-20T07:02:42Z http://ndltd.ncl.edu.tw/handle/rhvj2k International Environmental Agreements under Uncertainty, Learning and Asymmetry 不確定性,學習與不對稱下之國際環境協議 HSU HUAI-JEN 許懷仁 碩士 國立高雄大學 應用經濟學系碩士班 107 This paper establishes the heterogeneous IEA’s model to analyze self-enforcing international environmental agreements (SEIEA). Countries face the uncertainty of cost-benefit ratio in abatement decision, but it is assumed that all countries are able to know the outcome at the same time by learning, reduce emission. This paper analyzes whether the country joins IEA and reduces emission. We indicate that, with a heterogeneous model and three different modes of learning, results under no learning and partial learning are different from the model in Kolstand(2007) without heterogeneity. In the absence of heterogeneity the size of IEA under no learning is larger than partial learning, so learning reduces the size of IEA; with heterogeneity, the biggest IEA under no learning is the smallest, but that of partial learning is larger than complete learning. To the contrary, the ranking of minimum size of IEA is the same, i.e., the minimal size of complete learning is largest, followed by no learning and partial learning. Also, when the probability of good outcome is large enough, the increase in learning enhances the size of IEA. Otherwise, the increase in learning will reduce the size of IEA. When the risk is higher, the size of IEA will be reduced under full learning of the bad situation or no learning. When the heterogeneity among countries is not significant, the size of IEA will decline if the low cost-benefit ratio increases. However, if the high cost-benefit ratio rises, the size of IEA is not changed She Chih-Min 佘志民 2019 學位論文 ; thesis 37 zh-TW |
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碩士 === 國立高雄大學 === 應用經濟學系碩士班 === 107 === This paper establishes the heterogeneous IEA’s model to analyze self-enforcing
international environmental agreements (SEIEA). Countries face the uncertainty of
cost-benefit ratio in abatement decision, but it is assumed that all countries are able to
know the outcome at the same time by learning, reduce emission. This paper analyzes
whether the country joins IEA and reduces emission.
We indicate that, with a heterogeneous model and three different modes of learning,
results under no learning and partial learning are different from the model in
Kolstand(2007) without heterogeneity. In the absence of heterogeneity the size of IEA
under no learning is larger than partial learning, so learning reduces the size of IEA;
with heterogeneity, the biggest IEA under no learning is the smallest, but that of partial
learning is larger than complete learning. To the contrary, the ranking of minimum size
of IEA is the same, i.e., the minimal size of complete learning is largest, followed by
no learning and partial learning.
Also, when the probability of good outcome is large enough, the increase in learning
enhances the size of IEA. Otherwise, the increase in learning will reduce the size of
IEA. When the risk is higher, the size of IEA will be reduced under full learning of the
bad situation or no learning. When the heterogeneity among countries is not significant,
the size of IEA will decline if the low cost-benefit ratio increases. However, if the high
cost-benefit ratio rises, the size of IEA is not changed
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She Chih-Min |
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She Chih-Min HSU HUAI-JEN 許懷仁 |
author |
HSU HUAI-JEN 許懷仁 |
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HSU HUAI-JEN 許懷仁 International Environmental Agreements under Uncertainty, Learning and Asymmetry |
author_sort |
HSU HUAI-JEN |
title |
International Environmental Agreements under Uncertainty, Learning and Asymmetry |
title_short |
International Environmental Agreements under Uncertainty, Learning and Asymmetry |
title_full |
International Environmental Agreements under Uncertainty, Learning and Asymmetry |
title_fullStr |
International Environmental Agreements under Uncertainty, Learning and Asymmetry |
title_full_unstemmed |
International Environmental Agreements under Uncertainty, Learning and Asymmetry |
title_sort |
international environmental agreements under uncertainty, learning and asymmetry |
publishDate |
2019 |
url |
http://ndltd.ncl.edu.tw/handle/rhvj2k |
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