Tobias Böhmelt Monday 11 July 2011 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).

6. Data Collection and Coding

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.