sdal molfino, emily mapping conflict onto insfrastructure

Mapping Conflict onto Infrastructure: A study ofpost-conflict reconstruction

Emily Molfino

[email protected]

SCHOOL OF POLITICS AND GLOBAL STUDIES

* Do not cite or circulate without author permission *

mailto:[email protected]

Introduction Theory Methods Results Ethiopia Conclusion Extras References

Post-Conflict Infrastructure and Reconstruction

What is the relationship between infrastructure and conflict risk duringpost-conflict reconstruction?

Infrastructure and Conflict E Molfino Politics and Global Studies 2 / 54


Infrastructure Stability Theory

Short-term consequences (first order)Conflict increases after infrastructure provision (short-term goals)Infrastructure as a private good (Lichbach, 1987; Bueno de Mesquita andDown, 2005; Bueno de Mesquita et al., 2003)The populace reacts to this provision or non-provision—support/resent,mobilization, intermingling (Francisco, 1995; DeNardo, 1985; Gates,2002; Mason and Krane, 1989; Van Evera, 2001; Gompert et al., 2009)



Infrastructure Stability Theory

Long-term consequences (second order)Conflict can decrease as time passes (long-term goals/grievances)Infrastructure as part of a larger socio-technical system (infrastructurecontinuously interacts with power structures and the public at large)(Jasanoff, 2003)Connects areas physically to the political core, nation’s economy, andnational identityClash between the goals of the state with the goals of a group—conflictgroups exploit infrastructure’s socio-technical system (Habyarimana et al.,2007) or learn new ideational grievances by promoting physical andpsychological ethnic separations (Van Evera, 2001)



Hypotheses

H1: Conflict risks after infrastructure provision follows an inverted Upattern where conflict risks spike after provision and then drops as timepasses.

H2: If the lack of infrastructure cut peripheries from the core, there willbe an increased probability of conflict.



Methods

Cases: 33 post-conflict cases where reconstruction was needed fromaround the globe.

Unit of analysis: the PRIO grid (55 x 55 km) (Tollefsen et al., 2012)

Quadratic Time Trend: 10 years starting from the year conflict endstransformed into orthogonal measureData

IVs: Road density, power plant proximity, aeronautical proximity, andpresence of railwaysDV: Dichotomous measure if grid was in a conflict zone (Conflict Sitecoding v.3: conf) (Gleditsch et al., 2002; Themner and Wallensteen, 2002)Controls for political, social, economic, and terrain characteristicsGeneralized Linear Mixed Model (GLMM) with case-level randomintercept.



PRIO Grid

[

[

Iran

Iraq

Kuwait

[

[

Iran

Iraq

Kuwait



Infrastructure Data Description

Roads:Density measureEach density cell represented 10 square kmSearch radius was set at 30 square km

Power Plants:Density measureEach density cell represented 10 square kmSearch radius was set at 250 square km

Aeronautical:Density measureEach density cell represented 10 square kmSearch radius was set at 250 square km

Rail Roads:Dichotomous measure on the presence of rail infrastructure



Airport Density



Power Plant Density



Railroad Density



Road Density



Methods

Cases: 33 post-conflict cases where reconstruction was needed fromaround the globe.

Unit of analysis: the PRIO grid (55 x 55 km) (Tollefsen et al., 2012)

Quadratic Time Trend: 10 years starting from the year conflict endstransformed into orthogonal measureData

IVs: Road density, power plant proximity, aeronautical proximity, andpresence of railwaysDV: Dichotomous measure if grid was in a conflict zone (Conflict Sitecoding v.3: conf) (Gleditsch et al., 2002; Themner and Wallensteen, 2002)Controls for political, social, economic, and terrain characteristicsGeneralized Linear Mixed Model (GLMM) with case-level randomintercept.



Model Results

Condensed ModelRandom Effect

Case (Intercept) 4.39 (2.10)

Fixed Effects(Intercept) -3.69 (0.41) ***

Aero Proximity -0.75 (-0.16) ***Rail Presence 0.12 (0.04) **

Power Proximity 1.75 (0.11) ***Road Density 0.06 (0.00) ***Linear Wave -0.56 (0.05) ***

Quadratic Wave 2.02 (0.09) ***Aero Proximity : Quadratic Year 1.73 (0.43) ***

Rail Presence : Quadratic Year -1.09 (0.11) ***Power Proximity : Quadratic Year 1.37 (0.23) ***

Road Density : Quadratic Year -0.13 (0.01) ***AIC 34522.70BIC 34754.14

Standard errors listed in parentheses.Number of observations: 173,237Number of Groups: 33Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1



Change in Predicted Probabilities from Min to Max Infrastructure Level



Interaction Effects with Quadratic Time



Ethiopia

Ethiopia

Sudan

Somalia

Yemen

Kenya

Eritrea

Uganda

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Infrastructure in Ethiopia

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Note: Infrastructure listed are as of 2008.




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All-Weather Rural Road



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NGOs in the area increasedfrom 1 to 7

2 new schools; schooling rateincreased from 13% to 22%

200 to 300 public employees

Households using familyplanning from 0 to 6%

Businesses improved andrevenue from taxes increased

Increase in HIV infections

Lack of capacity building

Deforestation and illegalfarming increased



Afar Regions

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Conflict Events 1991-2

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Conclusion and Policy Implications

Infrastructure’s intrinsic long-term qualities must be accounted for.

Where research on the influence of different types of infrastructure isneeded, infrastructure’s mixed influences on conflict needs to beunderstood together—infrastructure does not exist independently ofother infrastructure.

Reconstruction and foreign aid ‘success’ is more than just about projectnumbers (technological fixes).

Goal of infrastructure reconstruction needs to be clear: reconstruction asan extension of political strategy, which requires better connectinginfrastructure rebuilding to the greater goal of democratization (Office ofthe Special Inspector General for Iraq Reconstruction, 2009)



Future Research

Urban and Rural Development/Smart Cities

National Infrastructure SystemsGeo-coded Big Data

How to incorporate with existing dataInnovative ways to operationalize political and social variables



Conclusion

Thank you



Road in East Amhara



IST



Cases

Table : Cases for Longitudinal Study

Location (abbr.) Years Grids per Year Location (abbr.) Years Grids per Year

Afghanistan (AF) 2001—2008 19 Iraq (IQ3) 2003—2008 8Angola (AO) 2002—2008 478 Israel (IL) 1996—2005 15Azerbaijan (AZ) 1994—2003 49 Liberia (LR) 1995—2004 28Bangladesh (BD) 1992—2001 73 Myanmar (MM) 1992—2001 245Bosnia & Herzegovina (BA) 1995—2004 36 Nepal (NP) 2006—2008 29Chad (TD) 1994—2003 205 Peru (PE) 1999—2008 400Croatia (HR) 1995—2004 40 Russia (RU) 1996—2005 11,991Ethiopia (ET1) 1991—2000 379 Rwanda (RW) 2002—2008 5Ethiopia (ET2) 2001—2008 379 Serbia (RS) 1999—2008 19Guatemala(GT) 1995—2004 46 Somalia (SO) 1986—1995 1India (IN1) 1997—2002 793 Sierra Leone (SL) 2000—2008 35India (IN2) 2003—2008 793 Sri Lanka (LK) 2001—2008 35Indonesia (ID1) 1989—1998 1045 Tajikistan (TJ) 1996—2005 31Indonesia (ID2) 2005—2008 1045 Uganda (UG) 2007—2008 53Iran (IR) 1996—2005 377 United Kingdom (UK) 1991—2000 211Iraq (IQ1) 1991—1995 8 Yemen (YE) 1994—2003 26Iraq (IQ2) 1996—2002 8Time covered is 10 years from the year conflict ended or is cut short to the year beforethe next conflict in that case begins or 2008, whichever comes first.Data comes from UCDP/PRIO Armed Conflict Dataset, v.4(Gleditsch et al., 2002; Themner and Wallensteen, 2002)



PRIO Grid



Infrastructure Data Sources

Roads:

Global Roads Open Access Data Set, version 1 (gROADS)

Power Plants:

Davis et al. (2012) and Global Energy Observatory (2013)

Rail Roads:

United States and Defense Mapping Agency (1992).

Aeronautical:

United States and Defense Mapping Agency (1992).



All Models

Table : Full Model ResultsReduced Model Control Model Full Model

Random EffectCase (Intercept) 6.06 (2.46) 3.87 (1.84) 4.39 (2.10)

Fixed Effects(Intercept) -3.52 (0.44) *** -3.10 (.36) *** -3.69 (0.41) ***

Aero Proximity -0.48 (-0.16) ** -0.75 (-0.16) ***Rail Presence 0.26 (0.04) *** 0.12 (0.04) **

Power Proximity 2.39 (0.10) *** 1.75 (0.11) ***Road Density 0.09 (0.00) *** 0.06 (0.00) ***Linear Wave -0.51 (0.05) *** -0.45 (0.51) *** -0.56 (.05) ***

Quadratic Wave 1.88 (0.09) *** 1.33 (0.05) *** 2.02 (0.09) ***Disjointed -3.29 (0.99) *** -3.32 (1.13) **

Capital Distance -0.00 (0.00) *** -0.00 (0.00) **Drug 0.34 (0.04) *** 0.33 (0.05) ***

Mining -0.12 (0.10) -0.25 (0.10) *Oil 0.30 (0.04) *** 0.35 (0.04) ***

Mountainous -0.04 (0.04) 0.00 (0.05) .Forested -0.00 (0.00) *** -0.00 (0.00) ***

Political Status 0.02 (0.04) -0.05 (0.04)Never Autonomous -0.14 (0.03) *** -0.04 (0.04)

GCPPC 0.00 (0.00) *** 0.00 (0.00) ***Pop Density -0.00 (0.00) *** -0.00 (0.00) ***

Aero Proximity : Quadratic Year 2.22 (0.43) *** 1.73 (0.43) ***Rail Presence : Quadratic Year -1.13 (0.11) *** -1.09 (0.11) ***

Power Proximity : Quadratic Year 1.49 (0.23) *** 1.37 (0.23) ***Road Density : Quadratic Year -0.13 (0.01) *** -0.13 (0.01) ***

AIC 35086.61 35555.66 34522.70BIC 35207.36 35706.59 34754.14

Standard errors listed in parentheses.Number of observations: 173,237Number of Groups: 33Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1



Mean Proportion of Conflict Presence



Model Residuals



Random Effect




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ISIS



Chad Infrastructure



Chad Conflict



LKA Power Plants



LKA Road Network



LKA Railways



LKA Airports



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