Workshop on the Quantitative Analysis: The PRIO/ETH Contribution to CLICO
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Workshop on the Quantitative Analysis: The PRIO/ETH Contribution to CLICO

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Tobias Böhmelt

Tobias Böhmelt
Monday 11 July 2011

Workshop on the Quantitative Analysis: The PRIO/ETH Contribution to CLICO.

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Workshop on the Quantitative Analysis: The PRIO/ETH Contribution to CLICO Workshop on the Quantitative Analysis: The PRIO/ETH Contribution to CLICO Presentation Transcript

  • Eidgenössische Technische Hochschule ZürichSwiss Federal Institute of Technology Zurich Workshop on Quantitative Analysis: The PRIO/ETH Contribution to CLICO Tobias Böhmelt ETH Zurich tobias.boehmelt@ir.gess.ethz.ch International Relations
  • Research Objectives• Collect and code data on cooperative and conflictive water-related events in 35 Mediterranean and Sahel countries between 1997 and 2009.• Employ time-series cross-sectional data in quantitative analyses: political, economic, and climatic factors work as explanatory factors that drive or mitigate water-related conflict and cooperation.• Qualitative case studies on countries that may appear as “outliers” in the quantitative research in order to further theoretical knowledge on processes of water-related conflict and cooperation.
  • Why a New Event Data Set? Models of Inter- or Intrastate Conflict Issue Coding• Impact of water-related factors • Frequency and intensity of on conflict along various water-related conflictive and causal pathways cooperative events• Limitations: • Limitations: – Water as a cause of conflict? – Existing data focus on – Focus on extreme forms of international water conflict cooperation and conflict – Absence of conflict – Association of an event with ≠cooperation “water” is frequently only assumed
  • Data Collection and Coding1. Download of Media Articles from BBC Monitoring • Provides translations of local media sources from around the world. • Allows extensive content analysis for creating event data – more comprehensive coverage than Western press agencies such as Reuters. • Use of other data sources (e.g., Factiva) discussed, but rejected. • PRIO: Turkey, Israel, Egypt, West Bank & Gaza, Lebanon, Niger, Nigeria, Senegal, and Chad (total: about 26,000 media articles). • ETH: Albania, Algeria, Bosnia-Herzegovina, Croatia, Cyprus, France, Greece, Italy, Jordan, Libya, Malta, Monaco, Montenegro, Morocco, Portugal, Slovenia, Spain, Syria, Tunisia, Burkina Faso, Eritrea, Ethiopia, Mali, Mauritania, Somalia, and Sudan (total: about 52,000 media articles).
  • Data Collection and Coding1. Download of Media Articles from BBC Monitoring Employed search string: water* OR lake OR river OR canal OR dam OR stream OR tributary OR dike OR dyke OR purification OR sewage OR effluence OR drought* OR irrigation* OR rain* OR fish* OR flood* OR precipitation 78,000 media articles in total. More than 12,000 water-related events in period under study (so far, 6,250).
  • Data Collection and Coding
  • Data Collection and Coding2. Coding of Water-Related Events• Original data structure: one observation per distinct event.• Event may comprise one-sided actions by individuals, firms, NGOs, and/or state authorities.• Event may comprise interactions between these kinds of actors.• Event is also defined by temporal and geographical dimensions, i.e., there are clearly defined temporal starting and end points, while the event takes place in a defined location or region.• Events that merely “happen” without a specific social influence from the actors above are excluded.
  • Data Collection and Coding2. Coding of Water-Related Events• More than 25 variables in data set.• Specifically: – General information: case, ccode, cname, date, year, location, latitude, longitude, cluster. – Event information: event, description, wes_dom, coop, conflict, scale, impact, violence, actor*, direction, international, int_code. – Control covariates from media sources: neusource, sourceloc, source, med_cover.
  • Data Collection and Coding: Water Events Scale (WES)2. Coding of Water-Related Events• Core variable: Domestic Water Events Scale (WES). – 13-point ordinal scale, where +6 stands for the most cooperative event and -6 signifies the most conflictive activity. – Scale builds upon three dimensions: • Source dimension (i.e., who causes an event). • Target dimension (i.e., who is the target of an event). • Intensity/impact dimension (i.e., how significant is the impact of an event). – Intensity/impact dimension: which scale effect(s) on water quality and/or quantity do we observe at the grass-roots, regionally, country-wide?
  • Data Collection and Coding: Water Events Scale (WES)WES Value WES Value Description Frequency Percentage Official governmental policies that substantially increase water 6 quality/quantity for the whole country/society 23 0.37% Official governmental policies that substantially increase water 5 quality/quantity at a sub-state level 56 0.90% General publics, major firms, and interest groups activities 4 that contribute to better water quantity/quality 23 0.37% Official policies or general actions at a moderate level, which may increase water quality/quantity of the nation or sub- 3 national entities 660 10.56% Agreements signed or verbal statements given intended to 2 mobilize greater public support for domestic water issues 692 11.07% Events that increase water quality/quantity at the grass-roots 1 level and/or with minimal impact 845 13.52% Routine and purposive actions on water issues that neither have 0 a positive nor a negative impact 2,827 45.23%
  • Data Collection and Coding: Water Events Scale (WES) Events that decrease water quality/quantity at the grass-roots –1 level and/or with minimal impact (i.e., small-scale tensions) 415 6.64% Tensions within governments (intra-state) and between countries (inter-state) that may affect water quality/quantity at a domestic –2 level 205 3.28% General opposition of the public, major firms, and interest –3 groups toward any official governmental policies 218 3.49% Official governmental policies that impose minor restrictions on –4 water quality/quantity 169 2.70% Official governmental policies that impose major restrictions on –5 water quality/quantity and affect the population at large 27 0.43% –6 Physical violence or casualties over water-related issues 90 1.44%Total 6,250 100%
  • Data Collection and Coding: Water Events Scale (WES)
  • Data Collection and Coding: Water Events Scale (WES)
  • Data Collection and Coding: Water Events Scale (WES)
  • Quantitative Analyses3. Cleaning-Up of Collected Information and First Paper• “Intrastate Water-Related Conflict and Cooperation: A New Event-Data Set.” Thomas Bernauer, Tobias Böhmelt, Halvard Buhaug, Nils Petter Gleditsch, Theresa Tribaldos, Eivind Berg Weibust, and Gerdis Wischnath.• Presented at the Annual Meeting of the International Studies Association, March 16-19, 2011.• Overview of the coding procedures and the data collection process.• Discusses key challenges and the “pros and cons” of particular solutions to these challenges.• Preliminary empirical analysis.
  • First Empirical Results – Spatial Dispersion (All Events)
  • First Empirical Results – Spatial Dispersion in Jordan (All Events)
  • First Empirical Results - Spatial Dispersion in Jordan (CooperativeEvents)
  • First Empirical Results - Spatial Dispersion in Jordan (ConflictiveEvents)
  • Spatial Dispersion in Jordan (Cooperative & Conflictive Events)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(1997)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(1998)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(1999)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2000)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2001)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2002)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2003)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2004)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2005)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2006)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2007)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2008)
  • First Empirical Results - Spatial Dispersion in Jordan over Time(2009)
  • First Empirical Results – Preliminary Data Patterns4. Preliminary Data Patterns• Gizelis and Wooden (2010) suggest that political institutions can perform mediating roles in the realm of water scarcity.• Political elites generally seek to satisfy large parts of the electorate to ensure political survival in democracies (e.g., Bueno de Mesquita, Morrow, Siverson, and Smith 1999)• In turn, democracies generally develop and have more effective and responsive governance systems that help providing a political outlet to the expression of grievances and to the consequences of environmental risks such as water scarcity.• Ultimately, democracies will be more successful in ensuring an efficient allocation of resources and in adapting to / mitigating potential problems of water scarcity for the population (Gizelis and Wooden 2010: 446).
  • Which Factors Drive Water-Related Conflict and Cooperation?
  • Outlook5. Qualitative Case Studies and Further Research• Qualitative research via case studies scheduled for 2012.• Other projects include: – Use of geographic information systems (GIS). – Further uncovering spatial and temporal dynamics. – The conditions of third-party involvement. – Etc.