A bullet a day keeps the doctor away:

the effect of war over health expenditure

RITA ABDEL SATER & MARIA JOSE OSPINA FADUL, 2014

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Average Domestic per Capita Health Expenditure ( at average exchange rate)

Introduction

• Our article examines if conflict affects the overall level of healthcare expenditure and itscomposition, as we would expect changes in the behavior of the main funders of health (public andprivate sector as well as third parties), and examine whether this effect is different with differentintensities of war.

Theoretical Framework 1

H1: In countries exposed to high intensity of conflict, war spells decrease overall domestic Health Expenditure but this will not happen

countries with a low intensity of conflict.

• Economic Growth and GDP

Private sector: increased uncertainty and chaos inhibits investments and there is relocation of most

productive facilities.

Public sector: erosion of the tax base and, additionally, due to a decrease in the efficiency of tax

administration that is caused by the political distress.

• Human and fixed capital of the health system

• BUT although the effect on economic growth and activity would still be persistent in mild wars because of the

increased uncertainty and instability in the country, the destructive effect would be somewhat absent and public

spending may still be able to compensate the decrease.

Theoretical Framework 2

H2: Government health expenditure as percentage of total health expenditure decreases when the country is exposed to a war, in

countries with both in high and low intensity of conflict, but the effect is lower in the case of the latter

• Crowding out effect within the public budget

- Increase in military and security expenditure (nearly 2 %)

- 10% increase in the risk of conflict0.4% increase in military spending

• Crowding out effects of the public resources by third parties:

- By the private sector

- By Foreign Aid

$1 of aid $0·46 decrease in government health expenditure

Methods

Data

1. Information on conflict for every country from the Peace Research Institute Oslo (PRIO): conflicts of low intensity (less than 1000 fatal victims) and high intensity (more than 1000 fatal victims) from 1946 until 2008.

2. Data for health expenditure and its composition was obtained from the WHO, as reported in the National Health Accounts from 1995 to 2011.

3. Data on Gross Domestic Product (GDP) per capita was obtained from the World Bank for the same period of time.

4. Intersection of available data: from 1995 to 2008

Methods

War spells

• Two or more consecutive years with a registration of conflict

• Recodification of the war registers for smooth war spells (started from 1992)

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1995 2000 2005 2010

congo

Con

flic

t R

ep

ort

yearGraphs by Country

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1995 2000 2005 2010

congo

Wars

pell

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cod

e

yearGraphs by Country

Methods

Sample and intensity classification0

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1990 1995 2000 2005 20101990 1995 2000 2005 2010

1990 1995 2000 2005 2010

Congo Eritrea Indonesia

Nepal Rwanda Senegal

Sierra Leone

Type

of w

ar

YearGraphs by Country

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1990 1995 2000 2005 2010 1990 1995 2000 2005 2010 1990 1995 2000 2005 2010 1990 1995 2000 2005 2010 1990 1995 2000 2005 2010

C?te d'Ivoire Cambodia Central African Republic Croatia Djibouti

Egypt Georgia Guatemala Guinea Guinea-Bissau

Iraq Liberia Niger Pakistan Papua New Guinea

Peru Somalia Tajikistan Thailand Uzbekistan

Type

of w

ar

YearGraphs by Country

High-Intensity Cluster Low-Intensity Cluster

Overall levels of health expenditure

Statistical model 2

Methods

Per capita government health expenditure (current US)

Per capita domestic health expenditure (current US)

Changes in the composition of the health expenditure and percentage within

the public budget

Statistical model 2

Methods

Government health expenditure as % of total health expenditure

Government health expenditure as % of total government expenditure

Results

Estimation issues

• Fixed vs. Random Effects: Hausman test (p<0.05 for all models)

• Presence of serial autocorrelation of first order: Wooldrigde test (p<0.05for all models)

• Arellano Bond GMM estimator, robust to heterosckedasticity

Results: overall levels of expenditure

Per capita health expenditure

Per capita government health

expenditure

Pc health expenditure (lag instrumented)

0.563***

Pc government health expenditure (lag instrumented)

0.737***

GDP per capita lag 0.0434*** 0.0357***

Foreign aid for health lag -0.045 -0.808

War (High Intensity Cluster) 3.288 6.712*

War (Low Intensity Cluster) -5.290** -1.223

Constant-17.48*** -22.88**

Results: percentages and composition

VARIABLES GHE/ THE GHE/ TGE

GHE/ THE(lag instrumented)

0.391***

GHE/ TGE(lag instrumented)

0.520***

GDP per capita lag -0.023 -0.0126

Foreign aid for health lag3.975* 1.199*

War (High Intensity Cluster)-1.76 -1.039

War (Low Intensity Cluster)-0.148 -0.731**

Constant0.519 -2.707

• High-intensity: No apparent effect on THE , GHE PHE

No apparent effect on GHE / TGE No crowding out effect

Total Government Expenditure

• Low-intensity: THE , no apparent effect on GHE PHE

GHE / TGE crowding out effect TGE

Discussion

• Measurement of war

• Civil conflicts → clear ending date? comparison of conflicts across

countries?

• Relatively large sample and applying clustering

Main limitations

Conclusions and further developments

• Our empirical findings disagree with our hypothesis; nevertheless they do show a change in thepatterns of health expenditure.

• In countries with low intensity of conflict:

A disruption in the growth of health expenditure + long terms effects of these kind of wars on publichealth = increased negative effect over health status

• For future assessments:

Type of war

Lingering effect

Time series

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