Analysis of Armed Conflict Data in Africa€¦ · Chloe Fearn Supervisor: Christian...

Introduction Exploratory Data Analysis Modelling Framework Modelling Africa Results

Analysis of Armed Conflict Data in Africa

Chloe Fearn Supervisor: Christian Rohrbeck

Lancaster University

August 30, 2017

Chloe Fearn Supervisor: Christian Rohrbeck Lancaster University



1 Introduction

2 Exploratory Data Analysis

3 Modelling Framework

4 Modelling Africa

5 Results




Introduction

Is there a relationship between level of cropland in Africa andincidents of violence against civilians?

Using data collected by the Armed Conflict & Event DataProject (ACLED) between 1997-2009.




Data

Data collected on an annual basis in blocks of 0.5◦ longitude× 0.5◦ latitude.

There are 296 covariates.




Data

The response variable, n, is the number of incidents ofviolence per year in a 0.5◦ × 0.5◦ square.

Used AIC to decide which covariates were best to include inthe model.

The covariates that were selected to be included in the designmatrix, X, are:

cropland,log(population), andlog(GCP).




Model Fitting

Figure: A map to show croplanddensity in Africa.

Figure: A map to show frequencyof incidents of violence in Africa.




Hurdle Model

The response variable is 97% zeros so we use a hurdle model.

First we consider P (N > 0) .

Then we consider P (N = n | n > 0) .




Modelling P (N > 0)

We fit a logistic regression model with

logit [ P(N > 0) ] = β̂̂β̂βTX ,

where β̂̂β̂β is the vector of parameter estimates, and

logit (p) = log

(p

1− p

).

Binary response.

Covariates can be discrete or continuous.




Modelling P (N = n | n > 0)

We find that the Poisson model is not flexible enough to be agood fit for the data.

Figure: A QQ plot to show the poor fit of the Poisson model to the data.




Modelling P (N = n | n > 0)

Instead of Poisson, we consider a negative binomial model,and find that the fit is much better.

Figure: A QQ plot to show the fit of the negative binomial model to thedata.




Koren & Bagozzi

In the study, Living Off The Land: The connection betweencropland, food security, and violence against civilians, Koren& Bagozzi found:

cropland adds a pacifying effect when there is already peace,andcropland increases violence against civilians where there isalready conflict.

However, they did not take into account that some countries’violence may react differently to changes in cropland.




Modelling Africa

When we fit all of Africa, the fit isnot ideal.

The association between number ofincidents of violence and ourcovariates varies between countriesin Africa.

We can test whether there is adifference in values for β̂̂β̂β using alikelihood ratio test.

Figure: A QQ plot to showthe fit of the negativebinomial model for all ofAfrica.




Likelihood Ratio Test

Our null and alternative hypotheses are:

H0 : βββ1 = βββ2 = . . . = βββ26 , and

H1 : βββ1 6= βββ2 6= . . . 6= βββ26 .

The test statistic is

D = 2 (l̂ for alternative model− l̂ for null model)

= 2 (26∑k=1

l̂k − l̂ )

which we compare with a critical value from the χ2

distribution.




Likelihood Ratio Test

When we calculate the critical value and test statistic, we findthat, using the likelihood ratio test, we reject the null.

Negative binomial Logistic regressionCritical value 152 124

Test statistic 846 2376




Grouping Countries

Since we have found that it is better to consider countriesseparately, we can group them into neighbouring countriesand assess the fit of the models.

Red: Algeria, Morocco.

Green: Senegal, Guinea, Sierra Leone,Liberia, Ghana.

Blue: Eritrea, Ethiopia, Kenya, Uganda,Rwanda, Burundi, Tanzania.

Cyan: Malawi, Mozambique, SouthAfrica, Namibia, Angola, Zambia.

Magenta: Niger, Nigeria, Chad,Cameroon, Central African Republic,Congo.




Results

Figure: A QQ plot to show the fit ofthe negative binomial model for allof Africa.

Figure: A QQ plot to show thenegative binomial model fit of thegroup of countries in the south.




Results

We can use AIC to test model fit.

AIC = 2k − 2l̂

where k denotes number of parameters in the model and l̂denotes the log(MLE).

AIC negative binomial AIC logistic regressionSeparate 6252 13679

Combined 6507 14996




Thank You

Thank you for listening.Any questions?



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Analysis of Armed Conflict Data in Africa€¦ · Chloe Fearn Supervisor: Christian...

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