Reassessing the climate change cooperation performance via a non-compensatory composite indicator approach

2020 ◽  
Vol 252 ◽  
pp. 119387 ◽  
Author(s):  
L.P. Zhang ◽  
P. Zhou ◽  
Y.Q. Qiu ◽  
Q. Su ◽  
Y.L. Tang
2005 ◽  
Vol 51 (5) ◽  
pp. 69-78 ◽  
Author(s):  
C. Sullivan ◽  
J. Meigh

It is known that climate impacts can have significant effects on the environment, societies and economies. For human populations, climate change impacts can be devastating, giving rise to economic disruption and mass migration as agricultural systems fail, either through drought or floods. Such events impact significantly, not only where they happen, but also in the neighbouring areas. Vulnerability to the impacts of climate change needs to be assessed, so that adaptation strategies can be developed and populations can be protected. In this paper, we address the issue of vulnerability assessment through the use of an indicator approach, the climate vulnerability index (CVI). We show how this can overcome some of the difficulties of incommensurability associated with the combination of different types of data, and how the approach can be applied at a variety of scales. Through the development of nested index values, more reliable and robust coverage of large areas can be achieved, and we provide an indication of how this could be done. While further work is required to improve the methodology through wider application and component refinement, it seems likely that this approach will have useful application in the assessment of climate vulnerability. Through its application at sub-national and community scales, the CVI can help to identify those human populations most at risk from climate change impacts, and as a result, resources can be targeted towards those most in need.


2016 ◽  
Vol 136 (3) ◽  
pp. 999-1029 ◽  
Author(s):  
Cristina Davino ◽  
Pasquale Dolce ◽  
Stefania Taralli ◽  
Vincenzo Esposito Vinzi

2019 ◽  
Vol 9 (4) ◽  
pp. 12
Author(s):  
Ann-Ni Soh ◽  
Chin-Hong Puah ◽  
M. Affendy Arip

This study attempts to scrutinize the fluctuations of the Fijian tourism market and forecast the early warning signals of tourism market vulnerability using the tourism composite indicator (TCI). The data employed on a monthly basis from 2000M01 to 2017M12 and the indicator construction steps were adopted from the ideology of the National Bureau of Economic Research (NBER). A parsimonious macroeconomic and non-economic fundamental determinant are included for the construction of TCI. Subsequently, the procedure then employed the seasonal adjustment using Census X-12, Christiano-Fitzgerald filtering approach, and Bry-Boschan dating algorithm. Empirical evidence highlighted the signalling attributes against Fijian tourism demand with an average lead time of 2.75 months and around 54 percent of directional accuracy rate, which is significant at 5 percent significance level. Thus, the non-parametric technique can forecast the tourism market outlook and the constructed TCI can provide information content from a macroeconomic perspective for policymakers, tourism market players and investors.


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