a bullet a day keeps the doctor away: the effect of war over health expenditure
DESCRIPTION
Barcelona GSE Master Project by Rita Abdel Sater and María José Ospina Fadul Master Program: Health Economics and Finance About Barcelona GSE master programs: http://j.mp/MastersBarcelonaGSETRANSCRIPT
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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20
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80
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140
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)
0.5
1
1995 2000 2005 2010
congo
Con
flic
t R
ep
ort
yearGraphs by Country
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1
1995 2000 2005 2010
congo
Wars
pell
Re
cod
e
yearGraphs by Country
Methods
Sample and intensity classification0
.51
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1.5
2
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
0.5
11.5
20
.51
1.5
20
.51
1.5
20
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1.5
2
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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