Changing Ethnic Composition and Potential Violent Conflict in Riau Archipelago, Indonesia: An Early Warning Signal

2006 ◽  
Vol 45 (1) ◽  
Author(s):  
Aris Ananta

2019 ◽  
Vol 62 (5) ◽  
pp. 1307-1332 ◽  
Author(s):  
Daniel L. Gamache ◽  
Gerry McNamara ◽  
Scott D. Graffin ◽  
Jason Kiley ◽  
Jerayr Haleblian ◽  
...  


Chemoecology ◽  
2008 ◽  
Vol 18 (4) ◽  
pp. 255-261 ◽  
Author(s):  
Meaghan A. Vavrek ◽  
Chris K. Elvidge ◽  
Robert DeCaire ◽  
Brenna Belland ◽  
Christopher D. Jackson ◽  
...  


2008 ◽  
Vol 105 (38) ◽  
pp. 14308-14312 ◽  
Author(s):  
V. Dakos ◽  
M. Scheffer ◽  
E. H. van Nes ◽  
V. Brovkin ◽  
V. Petoukhov ◽  
...  


2013 ◽  
Vol 6 (3) ◽  
pp. 309-317 ◽  
Author(s):  
Vasilis Dakos ◽  
Egbert H. van Nes ◽  
Marten Scheffer


2020 ◽  
Author(s):  
Lidia Ceriani ◽  
Carlos Hernandez-Suarez ◽  
Paolo Verme

AbstractThe paper provides some initial evidence that daily mortality rates (for any cause) by municipality or province can be used as a statistically reliable predictor of looming COVID-19 crises. Using recently published deaths figures for 1,689 Italian municipalities, we estimate the growth in daily mortality rates between the period 2015–2019 and 2020 by province. All provinces that experienced a major COVID-19 shock in mid-March 2020 had increases in mortality rates of 100% or above already in early February 2020. This increase was particularly strong for males and older people, two recognizable features of COVID-19. Using a panel fixed effect model, we show that the association between these early increases in mortality for any cause and the March 2020 COVID-19 shock is strong and significant. We conclude that the growth in mortality rates can be used as a statistically reliable predictor of COVID-19 crises.



2020 ◽  
Vol 12 (1) ◽  
pp. 101
Author(s):  
Kehinde Damilola Ilesanmi ◽  
Devi Datt Tewari

The devastating effects of the global financial crisis (GFC) have led to a renewed, global interest in the development of an early warning signal (EWS) model. The purpose of the EWS model is to alert policymakers and other stakeholders to the possibility of the occurrence of a crisis. This study estimates a EWS model for predicting the financial crisis in four emerging African economies using a multinomial logit model and a data set covering the period of January 1980 to December 2017. The result of the study suggests that emerging African economies are more likely to face financial crisis as debts continue to rise without a corresponding capacity to withstand capital flow reversal as well as excessive foreign exchange risk due to currency exposure. The result further indicates that rising debt exposure raises the likelihood of the economies remaining in a state of crisis. This result confirms the significance of a financial stability framework that addresses the issues confronting Africa’s emerging economies such as rising debt profile, liquidity and currency risk exposure.



2019 ◽  
Vol 22 (3) ◽  
pp. 323-340
Author(s):  
Daeyup Lee ◽  
Hail Park


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