2. Main results and hypothesis
• Terrorism can impose significant costs on an economy. This
paper analyses the effect of geography on terrorism. In
particular, this paper hypothesises that a terrorist attack in the
financial hubs of a country will have significantly higher
economic costs than a similar attack in a remote part of the
country.
• In particular, this paper focuses on the case study of Pakistan
and Net Foreign Direct Investment (NFDI), finding that
terrorism in financial hubs of Pakistan has imposed a
significant cost on NFDI, but similar attacks in remote areas
have had insignificant impacts. This heterogeneity of the
geography of terrorism has long been ignored in the literature,
and as such is likely to be a significant contribution.
2
4. Definition
• This paper uses the definition of Enders and
Sandler for terrorism: “Terrorism is the premeditated
use or threat to use violence by individuals or subnational groups to obtain a political or social
objective through the intimidation of a large
audience beyond that of the immediate victim”.
ENDERS, W. & SANDLER, T. 2006. The political
economy of terrorism, Cambridge University Press.
• Other definitions include that of UN and state
department.
4
5. Literature review
• Terrorism can impose significant economic costs.
Most important is the number of lives lost.
• Economic growth (Blomberg et al., 2004, Eckstein
and Tsiddon, 2004);
• Net Foreign Direct Investment (NFDI)
(Enders and Sandler, 1996);
• Trade (Nitsch and Schumacher, 2004) and
• Tourism (Enders et al., 1992).
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6. Why geography matters
• This paper argues that the economic costs of a
terrorist incident vary by the geography of the
terrorist incident.
• In particular, this paper argues that a terrorist attack
in one of the financial hubs of a country will have a
significantly higher impact on the economy than a
similar attack in a remote area. For the purpose of
this paper, a financial hub is defined to be a high
economic activity area of the country.
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7. Why geography matters
• Five main reasons
• 1) A terrorist attack in a major city is likely to attract
bigger media coverage. This extra media coverage
is likely to dampen both consumer and business
confidence. This can be particularly relevant for
foreign investors as it can be hypothesized that FDI
has a high elasticity to terrorism.
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8. Why geography matters
• 2) An attack in a major city is also likely to have a
bigger psychological impact, as this signals to
various stakeholders that the state may be weak
and that the terrorist may be well organised. Such
kinds of signals may force stakeholders to rationally
expect future terrorist attacks and as such they
would be forced to alter their behaviour. This may be
particularly bad for foreign investors.
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9. Why geography matters
• 3) There are more businesses, employees and
economic activity in a major city, compared to a
remote area. As such, disruption in a major city is
likely to cause higher economic costs than
disruptions in remote areas.
• 4) Financial institutions such as stockmarkets, banks
and other financial intermediaries tend to gravitate
towards financial hubs. A major attack near these
organisations is likely to cause a bigger negative
shock to the financial sector.
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10. Why geography matters
• 5) Finally, there are more economic assets in a
financial hub. These include infrastructure, property,
and higher human and physical capital.
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11. Why geography matters
• 5) Finally, there are more economic assets in a
financial hub. These include infrastructure, property,
and higher human and physical capital.
11
12. Decision making by terrorists
• For the terrorist, the decision making is rational and
involves weighing the costs and benefits of attacking
a financial hub versus a remote area. Attacking a
financial hub gets terrorists more political leverage
but at the same time it is more difficult and more
costly
• Expected (benefit from attacking a financial hub –
cost of attack) > 0 (2.1)
• Expected (benefit from attacking a remote area –
cost of attack) > 0 (2.2)
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13. Background and context for Pakistan
• After the terrorist attacks on September 11, 2001,
Pakistani military bases and land routes were used
by the US and NATO to attack the Taliban in
Afghanistan. As a consequence, the Taliban saw the
government of Pakistan as a puppet of the US and
started retaliating against the people and the state
of Pakistan.
• These organisations have successfully attacked
across all over Pakistan. These attacks include
major cities like Karachi, Lahore, Islamabad and
Rawalpindi. In addition remote areas of Pakistan
and minor cities have also been targeted.
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15. Background and context for Pakistan
• There are several terrorist organisations operating in
Pakistan and Afghanistan that have declared war on
the government of Pakistan. Some of these include
Tehreek-e-Taliban Pakistan (TTP), LashkareJhangvi (LeJ), Sipah-e-Muhammad Pakistan
(SMP) , Lashkar-e-Toiba (LeT) and the Balochistan
Liberation Army (BLA). Most of these organisations
are religious extremist organizations. Some of them
receive internal funding, while some of them receive
funding from overseas.
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16. Background and context for Pakistan
• This paper chooses NFDI for three reasons:
• Firstly, analysing NFDI gives this paper a base point
to compare with the growing literature on terrorism
and foreign direct investment (FDI) (Muckley, 2010,
Abadie and Gardeazabal, 2008, Enders and
Sandler, 1996, Enders et al., 2006, Bandyopadhyay
et al., 2011, Sandler and Enders, 2004, Mancuso et
al., 2010).
• Secondly, FDI is likely to be sensitive to terrorism.
• Data availability.
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17. Data
• For a database of terrorist attacks this paper uses
Global Terrorism Database (GTD).
• For NFDI this paper uses CPEIC database, using
the US GDP deflator to convert nominal NFDI into
real values, with 2009 used as the base year. This is
monthly data and the sample period is between July
2001 and December 2011.
• To capture terrorism I created a causality list
which was the number of people killed plus
number of people wounded in a terrorist attack.
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19. Data: structural break and stationarity
• Structural break in NFDI series, using Chow test.
The null hypothesis is that there are no structural
breaks in the data. The F-statistic is based on the
comparison of the restricted and unrestricted sum
of squared residuals.
• DF and Phillip-Perrson confirm that all series are
stationary.
Chow Break Point Test
Null Hypothesis: No breaks at specified breakpoints
F-statistic
13.67
Prob. F(3,119)
0.00
Chow Breakpoint Test: 2008M08
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20. Data: Regions
• Terrorist attacks were disaggregated by geography
into three categories as following:
• i) major cities which included Karachi, Lahore,
Islamabad and Rawalpindi. These are the main
cities of Pakistan, as well as the financial hubs and
government centres;
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21. • ii) remote areas included Khyber Pakhtunkhwa (KP),
Balochistan, the Pakistani part of Kashmir, GilgitBaltistan and tribal agencies on the Pakistan-Afghan
border in the North-West of Pakistan. Based on
contribution by GDP, these regions add very little to
the Pakistan’s economy and are considered remote;
and
• iii) medium zones consisted of the remainder of i
and ii.
• There were a total of 14199 casualties due to
terrorism between July 2001 and December 2011 for
Pakistan, of which 9213 were in major cities, 3431
were in remote areas and the remainder in the
medium zone.
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23. Methodology: Vector Autoregression
• Reasons:
• i) It can take into account reverse causality between
variables and is widely used in the literature;
• ii) by using impulse response functions (IRF) we
can evaluate how a shock in one variable impacts
other variables, and whether this impact is long
lasting, i.e. look at long term and short effects; and
• iii) it can be used to calculate total reductions on
NFDI caused by terrorism
(Enders and Sandler, 1996).
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25. Methodology: Vector Autoregression
• Likelihood ratio (LR) was used to get lag length. It
chose 12 lags, which takes account of seasonality.
• Results robust to AIC. These criteria have better
small sample properties.
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26. Results: Impulse response functions
A. Terrorism in Remote Areas and NFDI
order1, remote, NFDI
40
0
-40
0
1
2
3
4
5
6
7
8
step
95% CI
orthogonalized irf
Graphs by irfname, impulse variable, and response variable
26
27. Results: Impulse response functions
B. Terrorism in Major Cities and NFDI
order1, major_city, NFDI
40
0
-40
0
1
2
3
4
5
6
7
8
step
95% CI
orthogonalized irf
Graphs by irfname, impulse variable, and response variable
27
28. Results: Impulse response functions
• A standardised attack in a major city decreases
NFDI by around $40.94 million 2009 US dollars in
one months’ time. This result is statistically
significant at the 95 per cent level.
• All other impacts are statistically insignificant at 95
per cent level.
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29. Results: Impulse response functions
C. Terrorism in Medium Zone areas and NFDI
order1, medium_zone, NFDI
40
0
-40
0
1
2
3
4
5
6
7
8
step
95% CI
orthogonalized irf
Graphs by irfname, impulse variable, and response variable
29
30. Results: Impulse response functions
Terrorism reaction to NFDI
order1, NFDI, major_city
40
20
0
-20
0
1
2
3
4
5
6
7
8
step
95% CI
orthogonalized irf
Graphs by irfname, impulse variable, and response variable
30
31. Results: Impulse response functions
• Another interesting dynamic between terrorism and
NFDI is that terrorism reacts to increased NFDI in
major cities. A one standard deviation increase in
NFDI in major cities results in terrorist attacks in
one, four and five months on average after the
increase.
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32. Results: Robustness test
• As a robustness test this paper uses two methods.
In the first method we see if our results are sensitive
to the ordering of the variables. Secondly we
combine data from terrorist attacks in all regions into
one regression and examine whether the results are
sensitive to specification.
• Our results remain robust to these two tests.
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35. Results: Accumulated effect
• Over the entire sample, this paper finds that
terrorism in major cities of Pakistan caused a
decline of $3.0 billion in 2009 US dollars, or about
10.7 per cent. These results are similar to Enders
and Sandler’s (1996) results on the effect of
terrorism in Spain and Greece.
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36. Conclusion and policy implications
• There are two main policy implications from this
research and they are as following: i) terrorists gain
more media coverage and impose a bigger cost on
the state by attacking the financial hubs of the
country. Given this, financial hubs are more
vulnerable to terrorism and should be better
protected; and
• ii) terrorists react to foreign presence. In particular
this paper demonstrates that terrorists had the
tendency to increase attacks in major cities due to
increased FDI in Pakistan.
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37. Conclusion and policy implications
• It would be incorrect to conclude from this research
that security apparatus should focus on the financial
hubs only and ignore remote areas of the country. If
this happens, then the terrorists can use the vacuum
to launch attacks on the main sectors of the
economy. The example of how terrorists in a
remote-land-locked country managed to use the
vacuum in Afghanistan to launch attack on the main
financial hub of the world is still prominent in every
one’s memory.
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