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Eidgenössische Technische Hochschule Zürich
Swiss 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 Coding


1. 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 Coding


1. 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 Coding


2. 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 Coding


2. 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 public's, 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 Analyses


3. 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 (Cooperative
Events)
First Empirical Results - Spatial Dispersion in Jordan (Conflictive
Events)
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 Patterns


4. 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?
Outlook


5. 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.

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

  • 1. Eidgenössische Technische Hochschule Zürich Swiss 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
  • 2. 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.
  • 3. 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
  • 4. Data Collection and Coding 1. 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).
  • 5. Data Collection and Coding 1. 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).
  • 7. Data Collection and Coding 2. 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.
  • 8. Data Collection and Coding 2. 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.
  • 9. 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?
  • 10. 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 public's, 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%
  • 11. 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%
  • 12. Data Collection and Coding: Water Events Scale (WES)
  • 13. Data Collection and Coding: Water Events Scale (WES)
  • 14. Data Collection and Coding: Water Events Scale (WES)
  • 15. Quantitative Analyses 3. 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.
  • 16. First Empirical Results – Spatial Dispersion (All Events)
  • 17. First Empirical Results – Spatial Dispersion in Jordan (All Events)
  • 18. First Empirical Results - Spatial Dispersion in Jordan (Cooperative Events)
  • 19. First Empirical Results - Spatial Dispersion in Jordan (Conflictive Events)
  • 20. Spatial Dispersion in Jordan (Cooperative & Conflictive Events)
  • 21. First Empirical Results - Spatial Dispersion in Jordan over Time (1997)
  • 22. First Empirical Results - Spatial Dispersion in Jordan over Time (1998)
  • 23. First Empirical Results - Spatial Dispersion in Jordan over Time (1999)
  • 24. First Empirical Results - Spatial Dispersion in Jordan over Time (2000)
  • 25. First Empirical Results - Spatial Dispersion in Jordan over Time (2001)
  • 26. First Empirical Results - Spatial Dispersion in Jordan over Time (2002)
  • 27. First Empirical Results - Spatial Dispersion in Jordan over Time (2003)
  • 28. First Empirical Results - Spatial Dispersion in Jordan over Time (2004)
  • 29. First Empirical Results - Spatial Dispersion in Jordan over Time (2005)
  • 30. First Empirical Results - Spatial Dispersion in Jordan over Time (2006)
  • 31. First Empirical Results - Spatial Dispersion in Jordan over Time (2007)
  • 32. First Empirical Results - Spatial Dispersion in Jordan over Time (2008)
  • 33. First Empirical Results - Spatial Dispersion in Jordan over Time (2009)
  • 34. First Empirical Results – Preliminary Data Patterns 4. 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).
  • 35. Which Factors Drive Water-Related Conflict and Cooperation?
  • 36. Outlook 5. 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.