Predicting Armed Conflict, 2010–20501
Hegre, Håvard et al. (2012) Predicting Armed Conflict, 2010–2050. International Studies Quarterly, doi: 10.1111/isqu.12007 © 2012 International Studies AssociationThe article predicts changes in global and regional incidences of armed conflict for the 2010–2050 period. The predictions are based on...
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Veröffentlicht in: | International studies quarterly 2013-06, Vol.57 (2), p.250-270 |
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description | Hegre, Håvard et al. (2012) Predicting Armed Conflict, 2010–2050. International Studies Quarterly, doi: 10.1111/isqu.12007
© 2012 International Studies AssociationThe article predicts changes in global and regional incidences of armed conflict for the 2010–2050 period. The predictions are based on a dynamic multinomial logit model estimation on a 1970–2009 cross‐sectional data set of changes between no armed conflict, minor conflict, and major conflict. Core exogenous predictors are population size, infant mortality rates, demographic composition, education levels, oil dependence, ethnic cleavages, and neighborhood characteristics. Predictions are obtained through simulating the behavior of the conflict variable implied by the estimates from this model. We use projections for the 2011–2050 period for the predictors from the UN World Population Prospects and the International Institute for Applied Systems Analysis. We treat conflicts, recent conflict history, and neighboring conflicts as endogenous variables. Out‐of‐sample validation of predictions for 2007–2009 (based on estimates for the 1970–2000 period) indicates that the model predicts well, with an area under the receiver operator curve of 0.937. Using a p > .30 threshold for positive prediction, the true positive rate 7–9 years into the future is 0.79 and the False Positive Rate 0.085. We predict a continued decline in the proportion of the world's countries that have internal armed conflict, from about 15% in 2009 to 7% in 2050. The decline is particularly strong in the Western Asia and North Africa region and less clear in Africa south of Sahara. The remaining conflict countries will increasingly be concentrated in East, Central, and Southern Africa and in East and South Asia. |
doi_str_mv | 10.1111/isqu.12007 |
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© 2012 International Studies AssociationThe article predicts changes in global and regional incidences of armed conflict for the 2010–2050 period. The predictions are based on a dynamic multinomial logit model estimation on a 1970–2009 cross‐sectional data set of changes between no armed conflict, minor conflict, and major conflict. Core exogenous predictors are population size, infant mortality rates, demographic composition, education levels, oil dependence, ethnic cleavages, and neighborhood characteristics. Predictions are obtained through simulating the behavior of the conflict variable implied by the estimates from this model. We use projections for the 2011–2050 period for the predictors from the UN World Population Prospects and the International Institute for Applied Systems Analysis. We treat conflicts, recent conflict history, and neighboring conflicts as endogenous variables. Out‐of‐sample validation of predictions for 2007–2009 (based on estimates for the 1970–2000 period) indicates that the model predicts well, with an area under the receiver operator curve of 0.937. Using a p > .30 threshold for positive prediction, the true positive rate 7–9 years into the future is 0.79 and the False Positive Rate 0.085. We predict a continued decline in the proportion of the world's countries that have internal armed conflict, from about 15% in 2009 to 7% in 2050. The decline is particularly strong in the Western Asia and North Africa region and less clear in Africa south of Sahara. The remaining conflict countries will increasingly be concentrated in East, Central, and Southern Africa and in East and South Asia.</description><identifier>ISSN: 0020-8833</identifier><identifier>EISSN: 1468-2478</identifier><identifier>DOI: 10.1111/isqu.12007</identifier><language>eng</language><publisher>Cary: Blackwell Publishing Ltd</publisher><subject>Armed conflict ; Civil war ; Conflict ; Conflict theory ; Cross-sectional analysis ; Demography ; East Asia ; Endogenous ; Estimation ; False positive results ; Infant mortality ; Infants ; International conflict ; International studies ; Level of education ; Mortality rates ; Neighborhoods ; Neighbourhoods ; Petroleum ; Predictions ; Projections ; Prospects ; South Asia ; Southern Africa ; Systems analysis ; Validity ; World population</subject><ispartof>International studies quarterly, 2013-06, Vol.57 (2), p.250-270</ispartof><rights>Copyright Blackwell Publishing Ltd. Jun 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Hegre, Håvard</creatorcontrib><creatorcontrib>Karlsen, Joakim</creatorcontrib><creatorcontrib>Håvard Mokleiv Nygård</creatorcontrib><creatorcontrib>Strand, Håvard</creatorcontrib><creatorcontrib>Urdal, Henrik</creatorcontrib><title>Predicting Armed Conflict, 2010–20501</title><title>International studies quarterly</title><description>Hegre, Håvard et al. (2012) Predicting Armed Conflict, 2010–2050. International Studies Quarterly, doi: 10.1111/isqu.12007
© 2012 International Studies AssociationThe article predicts changes in global and regional incidences of armed conflict for the 2010–2050 period. The predictions are based on a dynamic multinomial logit model estimation on a 1970–2009 cross‐sectional data set of changes between no armed conflict, minor conflict, and major conflict. Core exogenous predictors are population size, infant mortality rates, demographic composition, education levels, oil dependence, ethnic cleavages, and neighborhood characteristics. Predictions are obtained through simulating the behavior of the conflict variable implied by the estimates from this model. We use projections for the 2011–2050 period for the predictors from the UN World Population Prospects and the International Institute for Applied Systems Analysis. We treat conflicts, recent conflict history, and neighboring conflicts as endogenous variables. Out‐of‐sample validation of predictions for 2007–2009 (based on estimates for the 1970–2000 period) indicates that the model predicts well, with an area under the receiver operator curve of 0.937. Using a p > .30 threshold for positive prediction, the true positive rate 7–9 years into the future is 0.79 and the False Positive Rate 0.085. We predict a continued decline in the proportion of the world's countries that have internal armed conflict, from about 15% in 2009 to 7% in 2050. The decline is particularly strong in the Western Asia and North Africa region and less clear in Africa south of Sahara. The remaining conflict countries will increasingly be concentrated in East, Central, and Southern Africa and in East and South Asia.</description><subject>Armed conflict</subject><subject>Civil war</subject><subject>Conflict</subject><subject>Conflict theory</subject><subject>Cross-sectional analysis</subject><subject>Demography</subject><subject>East Asia</subject><subject>Endogenous</subject><subject>Estimation</subject><subject>False positive results</subject><subject>Infant mortality</subject><subject>Infants</subject><subject>International conflict</subject><subject>International studies</subject><subject>Level of education</subject><subject>Mortality rates</subject><subject>Neighborhoods</subject><subject>Neighbourhoods</subject><subject>Petroleum</subject><subject>Predictions</subject><subject>Projections</subject><subject>Prospects</subject><subject>South Asia</subject><subject>Southern Africa</subject><subject>Systems analysis</subject><subject>Validity</subject><subject>World population</subject><issn>0020-8833</issn><issn>1468-2478</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>7UB</sourceid><recordid>eNpdjkFLw0AUhBdRMEYv_oKABz2Y-t7b3ezbYwnVFgp66D1skq2kpEmbbe7-B_-hv8SInpzLMMPHMELcIsxw0lMTjuMMCcCciQhVxikpw-ciAiBImaW8FFch7OAnWxuJ-7fB1011arr3ZD7sfZ3kfbdtp-YxIUD4-vgk0IDX4mLr2uBv_jwWm-fFJl-m69eXVT5fpwdrTCp1hdqXlqC2FrgyBM6RAW8zX2rmShPXUupSlUo7q73SPCHgSlayzpyMxcPv7GHoj6MPp2LfhMq3ret8P4YCFTKipAmPxd0_dNePQzedKwgznSlEQvkNvSRMmw</recordid><startdate>20130601</startdate><enddate>20130601</enddate><creator>Hegre, Håvard</creator><creator>Karlsen, Joakim</creator><creator>Håvard Mokleiv Nygård</creator><creator>Strand, Håvard</creator><creator>Urdal, Henrik</creator><general>Blackwell Publishing Ltd</general><scope>7UB</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>20130601</creationdate><title>Predicting Armed Conflict, 2010–20501</title><author>Hegre, Håvard ; Karlsen, Joakim ; Håvard Mokleiv Nygård ; Strand, Håvard ; Urdal, Henrik</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p977-35c15eb920d9908c720aa270e96eb588c528d335b4b45a95e45820a0ab843d6a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Armed conflict</topic><topic>Civil war</topic><topic>Conflict</topic><topic>Conflict theory</topic><topic>Cross-sectional analysis</topic><topic>Demography</topic><topic>East Asia</topic><topic>Endogenous</topic><topic>Estimation</topic><topic>False positive results</topic><topic>Infant mortality</topic><topic>Infants</topic><topic>International conflict</topic><topic>International studies</topic><topic>Level of education</topic><topic>Mortality rates</topic><topic>Neighborhoods</topic><topic>Neighbourhoods</topic><topic>Petroleum</topic><topic>Predictions</topic><topic>Projections</topic><topic>Prospects</topic><topic>South Asia</topic><topic>Southern Africa</topic><topic>Systems analysis</topic><topic>Validity</topic><topic>World population</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hegre, Håvard</creatorcontrib><creatorcontrib>Karlsen, Joakim</creatorcontrib><creatorcontrib>Håvard Mokleiv Nygård</creatorcontrib><creatorcontrib>Strand, Håvard</creatorcontrib><creatorcontrib>Urdal, Henrik</creatorcontrib><collection>Worldwide Political Science Abstracts</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>International studies quarterly</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hegre, Håvard</au><au>Karlsen, Joakim</au><au>Håvard Mokleiv Nygård</au><au>Strand, Håvard</au><au>Urdal, Henrik</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting Armed Conflict, 2010–20501</atitle><jtitle>International studies quarterly</jtitle><date>2013-06-01</date><risdate>2013</risdate><volume>57</volume><issue>2</issue><spage>250</spage><epage>270</epage><pages>250-270</pages><issn>0020-8833</issn><eissn>1468-2478</eissn><abstract>Hegre, Håvard et al. (2012) Predicting Armed Conflict, 2010–2050. International Studies Quarterly, doi: 10.1111/isqu.12007
© 2012 International Studies AssociationThe article predicts changes in global and regional incidences of armed conflict for the 2010–2050 period. The predictions are based on a dynamic multinomial logit model estimation on a 1970–2009 cross‐sectional data set of changes between no armed conflict, minor conflict, and major conflict. Core exogenous predictors are population size, infant mortality rates, demographic composition, education levels, oil dependence, ethnic cleavages, and neighborhood characteristics. Predictions are obtained through simulating the behavior of the conflict variable implied by the estimates from this model. We use projections for the 2011–2050 period for the predictors from the UN World Population Prospects and the International Institute for Applied Systems Analysis. We treat conflicts, recent conflict history, and neighboring conflicts as endogenous variables. Out‐of‐sample validation of predictions for 2007–2009 (based on estimates for the 1970–2000 period) indicates that the model predicts well, with an area under the receiver operator curve of 0.937. Using a p > .30 threshold for positive prediction, the true positive rate 7–9 years into the future is 0.79 and the False Positive Rate 0.085. We predict a continued decline in the proportion of the world's countries that have internal armed conflict, from about 15% in 2009 to 7% in 2050. The decline is particularly strong in the Western Asia and North Africa region and less clear in Africa south of Sahara. The remaining conflict countries will increasingly be concentrated in East, Central, and Southern Africa and in East and South Asia.</abstract><cop>Cary</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/isqu.12007</doi><tpages>21</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Armed conflict Civil war Conflict Conflict theory Cross-sectional analysis Demography East Asia Endogenous Estimation False positive results Infant mortality Infants International conflict International studies Level of education Mortality rates Neighborhoods Neighbourhoods Petroleum Predictions Projections Prospects South Asia Southern Africa Systems analysis Validity World population |
title | Predicting Armed Conflict, 2010–20501 |
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