Terrorism and stock market development: Causality evidence from Pakistan
ABSTRACT Purpose– The aim of this paper is to explore the relationship between terrorist activities in Pakistan and the stock market development.
Design/methodology/approach– Using Terrorism Impact Factor (TIF), a unique score developed for this paper, an insight is provided into the causal relationship that exists between terrorism and Karachi Stock Exchange (KSE) index. Quantitative significance of the impact of terrorist activities on stock index is also discussed in the paper.
Findings– Through the empirics of the study, it is analyzed that terrorism negatively impacts stock market returns in the long run; whereas no significant relationship between stock market returns and terrorism is estimated in the short run.
Research limitations/implications– A potential limitation of the study was the constraint related to the available yearly economic growth and other economic variables’ data. The TIF created for the study was based on the terrorist activities from 2001 to mid-2011 on an incident-to-incident basis. A yearly measure would have provided 11 data points for the study, which are considered insufficient for econometric analysis.
Practical implications– It is recommended that governments pay particular attention to economic recovery in the aftermath of terrorist attacks. Policies aimed at combating terrorism must be the priority of the government, so that its harm can be reduced, if not exterminated. Social implications– Terrorism, with its all kinds of impacts, affects the society and its activities and therefore must be eliminated if an economy needs to prosper.
Originality/value– This study envisions the overall impact of terrorist activities, not just a single activity, on the health of the economy. For studying this impact, a Terrorism Impact Factor (TIF) scale has been developed for this study, based on the impact of each terrorist activity in the country.
- SourceAvailable from: Javier Gardeazabal[Show abstract] [Hide abstract]
ABSTRACT: This article investigates the economic effects of conflict, using the terrorist conflict in the Basque Country as a case study. We find that, after the outbreak of terrorism in the late 1960's, per capita GDP in the Basque Country declined about 10 percentage points relative to a synthetic control region without terrorism. In addition, we use the 1998-1999 truce as a natural experiment. We find that stocks of firms with a significant part of their business in the Basque Country showed a positive relative performance when truce became credible, and a negative relative performance at the end of the cease-fire.American Economic Review 02/2003; 93(1):113-132. · 2.69 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: [eng] Transportation costs and monopoly location in presence of regional disparities. . This article aims at analysing the impact of the level of transportation costs on the location choice of a monopolist. We consider two asymmetric regions. The heterogeneity of space lies in both regional incomes and population sizes: the first region is endowed with wide income spreads allocated among few consumers whereas the second one is highly populated however not as wealthy. Among the results, we show that a low transportation costs induces the firm to exploit size effects through locating in the most populated region. Moreover, a small transport cost decrease may induce a net welfare loss, thus allowing for regional development policies which do not rely on inter-regional transportation infrastructures. cost decrease may induce a net welfare loss, thus allowing for regional development policies which do not rely on inter-regional transportation infrastructures. [fre] Cet article d�veloppe une statique comparative de l'impact de diff�rents sc�narios d'investissement (projet d'infrastructure conduisant � une baisse mod�r�e ou � une forte baisse du co�t de transport inter-r�gional) sur le choix de localisation d'une entreprise en situation de monopole, au sein d'un espace int�gr� compos� de deux r�gions aux populations et revenus h�t�rog�nes. La premi�re r�gion, faiblement peupl�e, pr�sente de fortes disparit�s de revenus, tandis que la seconde, plus homog�ne en termes de revenu, repr�sente un march� potentiel plus �tendu. On montre que l'h�t�rog�n�it� des revenus constitue la force dominante du mod�le lorsque le sc�nario d'investissement privil�gi� par les politiques publiques conduit � des gains substantiels du point de vue du co�t de transport entre les deux r�gions. L'effet de richesse, lorsqu'il est associ� � une forte disparit� des revenus, n'incite pas l'entreprise � exploiter son pouvoir de march� au d�triment de la r�gion lEconometrica 01/1981; 49(4):1057-72. · 3.82 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: The event study methodology is used to assess the effects of terrorism on global capital markets. We examine the U.S. capital market's response to 14 terrorist/military attacks dating back to 1915 and global capital markets' response to two recent events—Iraq's invasion of Kuwait in 1990 and the September 11, 2001 terrorist attacks. U.S. capital markets are more resilient than in the past and recover sooner from terrorist attacks than other global capital markets. Evidence suggests that this increased market resilience can be partially explained by a stable banking/financial sector that provides adequate liquidity to promote market stability and minimize panic.European Journal of Political Economy. 01/2004;
Journal of Financial Crime
Emerald Article: Terrorism and stock market development: causality
evidence from Pakistan
To cite this document: Abdullah Alam, (2013),"Terrorism and stock market development: causality evidence from Pakistan", Journal
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Terrorism and stock market
development: causality evidence
Department of Management Sciences,
International Islamic University Islamabad, Islamabad, Pakistan
Purpose – The aim of this paper is to explore the relationship between terrorist activities in Pakistan
and the stock market development.
Design/methodology/approach – Using Terrorism Impact Factor (TIF), a unique score developed
for this paper, an insight is provided into the causal relationship that exists between terrorism and
Karachi Stock Exchange (KSE) index. Quantitative significance of the impact of terrorist activities on
stock index is also discussed in the paper.
Findings – Through the empirics of the study, it is analyzed that terrorism negatively impacts stock
market returns in the long run; whereas no significant relationship between stock market returns and
terrorism is estimated in the short run.
Research limitations/implications – Apotentiallimitationofthestudywastheconstraintrelatedto
based on the terrorist activities from 2001 to mid-2011 on an incident-to-incident basis. A yearly measure
Practical implications – It is recommended that governments pay particular attention to economic
recovery in the aftermath of terrorist attacks. Policies aimed at combating terrorism must be the
priority of the government, so that its harm can be reduced, if not exterminated.
Social implications – Terrorism, with its all kinds of impacts, affects the society and its activities
and therefore must be eliminated if an economy needs to prosper.
Originality/value – This study envisions the overall impact of terrorist activities, not just a single
activity, on the health of the economy. For studying this impact, a Terrorism Impact Factor (TIF) scale
has been developed for this study, based on the impact of each terrorist activity in the country.
Keywords Pakistan, Stock markets, Terrorism, Terrorism Impact Factor (TIF),
Stock market development
Paper type Research paper
After the 9/11 attacks, Pakistan, being one of the foremost allies in the “war on terror”,
paid a high price. For the last decade or so, Pakistan has been the major target of
terrorist attacks. The number of terrorist activities in the country has risen from two in
2001 to 163 in 2010. Number of deaths and injuries owing to these terrorist activities in
Pakistan are graphed in Figure 1.
Not much work has been done in order to investigate the root causes of terrorism and
The current issue and full text archive of this journal is available at
JEL classification – C22, K42, O16, O53
Journal of Financial Crime
Vol. 20 No. 1, 2013
q Emerald Group Publishing Limited
has been suffering and people of the country are being hard-pressed against inflation,
unemployment, power losses and security concerns. At present, the news of a terrorist
activity does not worry the un-affected people much because they are so used to such
This paper analyzes the impact ofterrorism (through terrorism impact factor) on the
country’s stock market development, as stock market outlook presents a measure of
the health of an economy. Using co-integration and causality tests, the short and
long-run relationship between terrorism and stock prices has been investigated. Unlike
Gaibulloev and Sandler (2009), this study incorporates terrorist activities that have
taken place over the past decade. This provides us with an expanded range of time
period to check if the impact of terrorist activities is consistent on the stock market
development. Many past studies have used an event-study methodology to uncover the
impact of terrorism on the stock markets (see, for example, Burch et al. (2003)
considering 9/11 attacks on US; Johnston and Nedelescu (2005) considering 9/11 US
attacks and 2004 Madrid attacks). The present study envisions the overall impact of
terrorist activities, not just a single activity, on the health of the economy. For studying
this impact, a terrorism impact factor (TIF) scale has been developed for this study,
based on the impact of each terrorist activity in the country. Using this unique dataset
of terror attacks, this study aims at answering the following questions:
Number of injuries and
deaths owing to terrorism
in Pakistan (2001-2010)
Notes: A major structural change can be seen between 2006 and 2007; the
major reason for this change has been the extension of terrorist attacks into
the major cities of the country; previously, terrorists mainly focused on tribal
areas, Balochistan and Khyber Pakhtunkhwa provinces; but by 2007, the
attack's focus was widened to Karachi, Lahore, Rawalpindi, Multan and other
major cities of the country
. Do terrorist attacks impact the stock market?
. Is the impact present in the short-run or the long-run?
. What is quantitative importance of the results obtained?
. What are the policy related lessons for the government in this regard?
The rest of the paper is structured as follows: Section II gives review of the literature.
Section III aims at theoretical considerations and hypotheses development. Section IV
details. Section VI provides the empirical analysis while Section VII concludes the paper.
II. Literature review
Terrorist activities impact the infrastructure and systems of a country. Also, investor
moods and interests are diverted by such activities. In turn, stock markets, measuring
the health of an economy, are also affected. Johnston and Nedelescu (2005) studied
two cases of terrorism, 9/11 attacks on the US and 2004 Madrid attacks; and concluded
that terrorist activities cause heavy damage to property and other systems including
communication. This, in turn, forces investors into a defensive mood where they are
reluctant to invest due to the prevailing uncertainty. Terrorism affects economic
prosperity, whereas, economic prosperity and increasing development levels in a
country may hamper terrorist activities (Lai, 2007; Freytag et al., 2012). This
motivation leads into a two-way analysis for this study where the bi-directional
relationship between terrorism and stock market development needs to be looked at.
There is also a growing body of literature which, arguably, points out that terrorist
activities do not impact developed countries much. Gaibulloev and Sandler (2009) used
one-year panel analysis and indicated that terrorism significantly retards growth in the
short-run for Asian developing countries. They also noted that this effect is not present
for the Asian developed countries. Abadie and Gardeazabal (2003) approximated a
10 percent decline in per capita income for Basque region of Spain due to ETA’s
terrorist movement. According to Sandler and Enders (2008), stable and developed
economies exhibit lesser reactions to terrorist activities. Karolyi and Martell (2005)
examined the long-term impact of terrorism on stock prices and found that the impact
was not consistent. They indicated that wealthier and democratic countries show
greater reaction in their share prices in response to terrorist activities.
Eldor and Melnick (2004) researched Israeli stock and foreign exchange markets’
response towards the 639 terror attacks during 1990-2003. Their findings suggest that
terrorism has a negative impact on stock markets. However, they did not find support
for the effect of terrorism on foreign exchange markets; due to the efficient nature of
these markets in incorporating news about such violent episodes. Based on the
findings of Eldor and Melnick (2004), this study is also motivated of the negative
relationship between stock market development and terrorism.
According to Shiller (2003), terrorism potentially affects investors’ sentiment and
thereby generates a negative impact on the stock prices. Burch et al. (2003) considered
310 US based closed-end funds and tried to analyze the investors’ reaction to the 9/11
attacks. An over-reaction was recorded in the first week after the attacks but it then
converted into under-reaction in the next two weeks. A similar pattern of investor
behavior has been documented by Kallberg et al. (2008) who studied the response of
New York real estate investment trusts to the 9/11 attacks. A positive trend to begin
with, converts into a downward trend in the weeks to follow. Cummins and Lewis
(2003) found a significant negative reaction to the 9/11 attacks for 43 property-casualty
insurers, by analyzing their returns. Overall, there is a general consensus that a
negative relation holds between stock market returns, through investors’ reaction, and
terrorist activities. These reactions directly impact the stock prices and with the
passage of time, their impact diminishes.
The above literature (studying the impact of terrorist activities on stock market)
indicates a strong impact of terrorism on stock market development, where most of the
researchers find a definite shift in the investors’ moods due to a terrorist activity
creating a negative reaction as recorded in the above studies. The present study adds
to the above strand of literature by examining the results of, for example, Gaibulloev
and Sandler (2009) who were convinced of the short-run impact of terrorism on growth
for Asian developing countries. Also, this paper investigates the reverse impact of
stock market development on terrorist attacks, i.e. the reverse causality.
III. Theoretical consideration and hypotheses
Our basic study model is given in the equation (A) below:
xt¼ xt21þ yt21þ mt
Where, xtrepresents the logarithmic function of stock market Karachi Stock Exchange
confirms the I(1) nature of both the series. Residual term mtis the white noise innovation.
A shock to the system impacts all the agents interacting in it. A terrorist activity, by
impacting the moods and behaviors of the people, creates a realistic hype in the general
investors who do not find it safe to invest further, at least for some period of time. This,
in turn, impacts the stock index. Therefore, there exists a relationship between terrorist
activities and the stock market. The study is motivated of the existence of a negative
relationship between the TIF and stock market development; the higher the TIF score
is, lower would be the stock market returns. For equation (A), if the coefficient of the
independent variable is significant, we can assume that there exists a relationship
between the stock markets and terrorist activities. To test the short-run and long-run
causal relationship between the two variables, equation (A) is first-differenced and
transformed into equation (B) as:
Dxt¼ Dxt21þ Dyt21þ mt
Error correction mechanism is adopted in this study to unleash the short and long-run
causalities between the two variables.
Our main hypotheses for the study are:
There exists a relationship between stock index and TIF.
There is a short as well as long-run relationship between terrorism and the
The impact of terrorism on stock index is quantitatively relevant and
IV. Terrorism impact factor
Literature contains numerous studies on terrorism in which researchers adopt
event-study methodology (Abadie and Gardeazabal, 2003; Chen and Siembs, 2004) to
study the impact of terrorist activities on stock market development. In such studies,
the impact of a terrorist activity is considered by analyzing the deviations of returns
from their previous values. In the present study, the conventional event-study
methodology was not preferred; instead an index was constructed called the terrorism
impact factor. This index, different in attributes from other existing terrorism
databases, considers the impact of each terrorist incident in the country and based
on the intensity of the event awards a score to it. Also this methodology allows for the
time-series analysis of terrorism and stock prices. Previous attempts at forming an
index for the terrorist activities do not focus on a comprehensive list of “impact factors”
(TIF1-TIF9 in this study) that are directly related to a terrorist activity. Also, prior
attempts in this regard have not awarded scores to each terrorist activity based on the
impact it created (e.g. in the case of Eldor and Melnick (2004)).
For the purpose of constructing an index, all (major) terrorist activities that have
taken place from 1 January 2001 to 30 June 2011 are listed. 452 events are recorded for
the mentioned time period. Sources of data for these incidents are leading newspapers
of Pakistan (Daily Jang, The News and Dawn). These newspapers are reliable sources of
information in Pakistan and to ensure consistency only those events are reported
which were included in all the three major newspapers mentioned above. These events
are also counterchecked for accuracy of figures from world wide web sources. After
listing all the terrorist events, each event is checked on nine different sub-scores
(factors). Following table lists the nine areas for sub-scores of each event.
Factors TIF1-TIF9 are expected to capture the major impacts of a terrorist activity.
A terroristactivityresulting inthe deathorinjuryofa politicalfigureheadmay incite the
followerstostart riots, etc. (eventlike thedeath offormer PrimeMinisterBenazirBhutto)
a sense of insecurity among the general public and people start avoiding indulging in
purchasing and other outside activities; thereby creating a major setback to the financial
activity. All other factors are also relevant and are anticipated to have a strong impact in
nine factor scores are constructed for each event. All these factors covering the whole
time period are then entered into a principal component analysis (PCA) in order to get a
unique index score for each factor. PCA is a multivariate statistical analysis technique
which shrinks large number of variables into some reduced dimension(s). Generally,
for variables ranging from a1to an, the following equation represents the estimation of
the principal component:
PC1¼ a11a1þ a12a2þ a13a3þ ··· þ a1nan
PCk¼ ak1a1þ ak2a2þ ak3a3þ ··· þ aknan
where, aknrepresents the weight for the kth principal component and the nth variable.
The ordering of the components is adjusted in a manner that the first principal
component PC1explains the maximum amount of variation in the data. All subsequent
principal components show lesser variation than the first one.
Based on the index scores for each factor by using first extracted principal
component method, following equation is estimated for establishing a TIF score for
TIF ¼ 0:613254*TIF1 þ 0:636135*TIF2 2 0:091349*TIF3 2 0:023802*TIF4
2 0:079329*TIF8 2 0:067681*TIF9
TIF5 þ 0:010304*TIF6 þ 0:288032*TIF7
This forms a “Daily TIF Index”, which gives a unique score to each day on which the
terrorist activity took place. The TIF index includes the domestic terrorist activities as
well as attacks on foreigners (transnational) that have taken place during the time
period under consideration.
V. Methodology and data
of establishing the relationship between terrorism and stock market development,
causality evidence was studied between them. Engle-Granger method (Engle and
ADF (Dickey and Fuller, 1981) tests. Because the study employs daily data, therefore,
there may have been instances of structural breaks. In order to check for this issue,
TIF1 Deaths1 point for every ten dead
1 point for every 20
0 for no and 1 for yes
TIF3 Assassination of a Pakistani high-profile figure (politician, high-
rank officer, religious leader, etc.)
TIF4 Attack on a Pakistani high-profile figure but not killed
TIF5 Suicide attack
TIF6 Attack in a major city (Karachi, Lahore, Islamabad, Peshawar,
TIF7 A major attack on forces (army, navy, air force, police, etc.)
TIF8 Attack on foreigners/consulate/embassy
TIF9 Attack on foreign delegate (large scale) especially sports delegate 0 for no and 1 for yes
0 for no and 1 for yes
0 for no and 1 for yes
0 for no and 1 for yes
0 for no and 1 for yes
0 for no and 1 for yes
Notes: These factors TIF1-TIF9 are considered on the basis of their direct relationship with a terrorist
attack; these factors directly influence the people’s reaction to such events; factors like capital flight,
government destabilization and market disruption, etc. are inarguably, relevant to a terrorist activity;
but are not directly conceived by a common man because of their indirect impact; lives of people are
(10:1) than the number of injuries (20:1); since, it has been observed that the injuries carried due to
casualty); therefore, a compatible score has been awarded to injuries as compared to deaths
Terrorism impact factor
this study also utilizes the Clemente-Montanes-Reyes unit root test with additive (AO)
and innovative outliers (IO) models for the presence of two structural breaks. The
direction of causality was estimated using error correction model as follow:
DS Pricet¼ A11ðLÞDS Pricet2kþ A12ðLÞDTIFt2kþ dS PriceECTt21þ 11t
DTIFt¼ A21ðLÞDTIFt2kþ A22ðLÞDS Pricet2kþ dTIFECTt21þ 12t
. SPricet and TIFt correspond to stock prices and terrorism impact factor,
. D represents the difference operator and k is the lag length.
. Aijrepresents polynomials in the lag operator (L).
. ECT refers to the lagged error correction term derived from long-run
. 1trepresents the error correction terms (uncorrelated and random with a zero
. d represents the deviation of the dependent variable from long-run equilibrium.
If the variables are co-integrated, then at least one or both of the error correction terms
should be non-zero. Causality was checked by using simple t test of d, joint Wald F-test
of the significance of each explanatory variable’s sum of lags and a joint Wald F-test of
(dSPriceand A12) and (dTIFand A22).
Daily time-series data was used (1 January 2001 to 30 June 2011) for TIF index and
stock prices. Stock prices are of KSE 100 index (closing prices) and are used in
logarithmic form. The graph of stock price index is shown in Figure 2.
However, a specific day’s TIF score should be compared to the following day’s stock
price. Therefore, the stock prices variable was used in a lead. Descriptive analysis of
the variables used in the study is presented in Table II.
Stock price index
VI. Empirical findings
VI.A. Unit root tests
The results of ADF test performed for unit root specification indicates that both the
variables are integrated of the order I(1) at 1 percent significance level. Results of the
Clemente-Montanes-Reyes unit root test also confirmed the I(1) nature of the two series.
Tables III and IV represent the results of the two unit root tests.
VI.B. Co-integration tests
Since both the variables are integrated of the order I(1), therefore there may exist a case
of co-integration. This co-integration was tested by using Johansen’s procedure
(Johansen, 1988; Johansen and Juselius, 1990) as shown in Table V.
VariablesMean SDMinimum Maximum
Augmented Dickey-Fuller test
Critical values (%)
Notes:*Rejection of the null hypothesis of non-stationarity at 1 percent level; lag length was
determined using Akaike information criterion (AIC)
Unit root test results
t-stat.TB2 Decision t-stat.TB1 Decision
SPrice 25.36 7 October
2 June 2008*
22.4529 July-4 August
Notes: Significance at:*5 percent level
Reyes unit root test
Null hypothesis (no. of CE)EigenvalueTest statisticsa
5% critical value
At most 1
Notes: Significance at:*5 percent level;atest statistics are maximum eigen-statistics
Results of Johansen
For both the variables, the null hypothesis of no co-integration is clearly rejected at
5 percent level against the alternative of the existence of two co-integration
relationships between the two variables. Hence, our H1 is validated that there exists a
relationship between terrorism (TIF) and stock index. This indicates that causality can
now be studied between the variables.
VI.C. Error correction mechanism and direction of causality
For finding the direction of causality between the variables, error correction terms were
included in the respective equations. This error correction mechanism allows us to find
short and long-run causalities between the variables.
impact factor has no short-run causality associated with stock market returns in either
Our H2 was partially validated as there is a long-run relationship between stock index
and terrorism only. This asserts the point that in the short-run, terrorism might not
are clearly noteworthy. Our finding of the negative association of terrorism with stock
returns are consistent with the findings of Eldor and Melnick (2004), Johnston and
Nedelescu (2005) and Shiller (2003) who also reported similar results.
VI.D. Quantitative importance of the long-run impact
From Table VII, it is clear that terrorist attacks in the country had significant impact
on the stock index; validating the H3 of our study. Eight major terrorist incidents are
reported in the table where huge losses of lives (along with injuries) were sustained.
The greatest slump in the index, that is 210.21 percent, is recorded for the attack on
Benazir Bhutto (two time prime minister of Pakistan) convoy in Karachi that saw
139 deaths and 450 injuries. The decline in the index continued for a period of about
one month. Second most significant downward trend was observed for a period of
22 days on the assassination of Benazir Bhutto where the intensity of the decline
was measured to be 21.45 percent. Suicide attack in Lahore recorded a slump of
24.60 percent in the index, followed by decrease of 22.76 percent as a result of the car
bomb attack in Peshawar. Lowest decline in the index was reported for the twin blasts
in Karachi in 2010 where the downward trend continued for five days and the intensity
of the trend was recorded to be 20.77 percent.
The main purpose of the study was to establish a relationship between terrorism and
stock market development. Pakistan was chosen as the study-case because of the
Vector error correction model (VECM) estimation
Notes: Significance at:*1 percent level;aECT refers to the error correction term; lag length was
selected using AIC
increasing number of terrorist activities in the country and Pakistan’s significant role
in the war against terrorism. Co-integration and causality evidence was recorded for
the relationship between the variables.
No short-term impact of terrorism on stock market returns (or vice-versa) was
recorded in the analysis. However, terrorism was found to negatively influence stock
returns in the long-run. This indicates that terrorist activities change the investor
moods to a large extent in particular and shift the economic outlook of the country in
general. Therefore, it can be said that terrorist activities are major set-backs to the
health and development of the economy. Pakistan has been a major subject of terrorist
activities in the last decade or so. Enormous number of such activities has now reduced
its impact on the minds of the people and their behavior is not much affected by these
activities in the short-run. However, in the long-run, these activities impact the overall
and foreign). In order to ascertain the participation of all the agents, it is necessary that
the government must provide security to businesses and should improve on the overall
well-being of the general public.
The empirical findings of this research can have useful policy implications for
Pakistan and its policy makers. More sincere efforts are needed to combat terrorism
and associated activities on the part of the government elites, since such activities
induce vulnerability in stock market prices in specific and stock market development
in general. Having shown with systematic evidence that terrorism has negative
economic externalities, and based on the literature showing that poor economic
conditions are linked to a wide array of socio-political problems (including terrorist
activities); it is recommended that governments pay particular attention to economic
recovery in the aftermath of terrorist attacks. Policies aimed at combating terrorism
must be the priority of the government so that its harms can be reduced, if not
exterminated. Terrorism, with its all kinds of impacts, affects the society and its
activities and therefore must be eliminated if an economy needs to prosper.
Event Deaths InjuriesEvent date
Attack on Benazir Bhutto’s
convoy in Karachi
assassination in Rawalpindi
Suicide attack near CCPO
and ISI offices in Lahore
Car bomb attack in a
market in Peshawar
Suicide attack on ISI
headquarters in Peshawar
Attack on friday
congregation in Rawalpindi
Twin planted blast
Twin suicide attacks
139 450 18 October
27 May 2009
14 June 2009
27 326 19 days
118 20028 October
21 March 2010
of terrorist attacks
Future research should be directed at finding the impact of government
expenditure, budgetary allocations, financial borrowings, inequality and inflation on
terrorism in Pakistan in order to evaluate the roots of terrorism. Also the impact of
terrorism on the economic growth, foreign direct investment and inflation may be
studied in the Pakistani context. Using natural disasters as a control in future studies
may enhance the understanding of terrorism and its role in financial development.
A potential limitation of the study was the constraint related to the available yearly
economic growth and other economic variables’ data. The TIF created for the study
was based on the terrorist activities from 2001 to mid-2011 on an incident-to-incident
basis. A yearly measure would have provided 11 data points for the study which are
considered insufficient for econometric analysis.
1. ITERATE and GTD terrorism databases are two of the main data stores of terrorism
incidents. Global terrorism database (GTD), one of the most comprehensive database on
terrorist events around the world, provides information about the date and location of the
incident, weapons used in the attack, nature of the target, the number of casualties and
the responsible group/individual. GTD contains more than 80,000 cases of terrorism between
the years 1970 and 2007. ITERATE data base, another comprehensive source of terrorist
incidents, also records fields like type of attack, location, casualties, fatalities, etc. This
paper’s proposed TIF is different from ITERATE and GTD in the sense that it is not just a
database of terrorist events in Pakistan but itawards a score (the impact factor) to each event
based on the analysis of the impact that a terrorism event has created.
2. The world wide web sources included: http://en.wikipedia.org/wiki/List_of_terrorist_
3. For reference, see www.telegraph.co.uk/news/worldnews/1573789/Pakistan-faces-horror-of-
4. Researchers like Filmer and Pritchett (2001) and McKenzie (2003) have used additional
component is justified, where its results are also robust to including additional components.
5. The above weights can be justified for their indicated signs. A terrorist attack (a planted or a
suicide attack) causing deaths and/or injuries is considered as a major set-back by the
general public and thereby receive higher scores in the TIF (TIF1, TIF2 and TIF5). The
miseries of the general public, in relation to these terrorist attacks, are considered (by general
public) to be the outcomes of wrong (thought to be) policies of the government and military
officials and therefore, an attack launched on them may not raise many eye-brows. This is
the reason for the negative weights for TIF3 and TIF4. Attack in a major city and attack on
forces (mostly low raked personnel) also receive sympathetic response and induce people
into a defensive mood thereby validating the positive weights for TIF6 and TIF7.
Foreigners, especially, Americans, etc. are not welcomed by the masses in Pakistan in
relation to their government’s stance on drone attacks and their policies related to Pakistan
and Afghanistan; therefore an attack on a foreigner may not highly impact the general
public of the country, thereby indicating a negative weights for TIF8 and TIF9.
6. For a terrorist activity to continue for more than one day, the average of stock prices of all
the days of the activity was taken.
7. Lag length was selected using AIC.
Abadie, A. and Gardeazabal, J. (2003), “The economic cost of conflict: a case study of the Basque
country”, American Economic Review, Vol. 93, pp. 113-32.
fund discounts and investor sentiment?”, Financial Review, Vol. 38 No. 4, pp. 515-29.
Chen, A. and Siembs, T. (2004), “The effects of terrorism on global capital markets”, European
Journal of Political Economy, Vol. 20, pp. 349-66.
Cummins, D.J. and Lewis, C.M. (2003), “Catastrophic events, parameter uncertainty and the
breakdown of implicit long-term contracting: the case of terrorism insurance”, Journal of
Risk and Uncertainty, Vol. 26, pp. 153-78.
Dickey, D.A. and Fuller, W.A. (1981), “Likelihood ratio statistics for autoregressive time series
with a unit root”, Econometrica, Vol. 49 No. 4, pp. 1057-72.
Eldor, R. and Melnick, R. (2004), “Financial markets and terrorism”, European Journal of Political
Economy, Vol. 20, pp. 367-86.
Engle, R.F. and Granger, C.W.J. (1981), “Cointegration and error-correction: representation,
estimation and testing”, Econometrica, Vol. 55 No. 2, pp. 251-76.
Filmer, D. and Pritchett, L.H. (2001), “Estimating wealth effect without expenditure data – or
tears: an application to educational enrollments in states of India”, Demography, Vol. 38,
Freytag, A., Kru ¨ger, J., Meierrieks, D. and Schneider, F. (2012), “The origins of terrorism:
cross-country estimates on socio-economic determinants of terrorism”, European Journal
of Political Economy, Vol. 27, S1, pp. S5-S16.
Gaibulloev, K. and Sandler, T. (2009), “The impact of terrorism and conflicts on growth in Asia”,
Economics and Politics, Vol. 21, pp. 359-83.
Johansen, S. (1988), “Statistical analysis of cointegrating vectors”, Journal of Economic Dynamics
and Control, Vol. 12, pp. 231-54.
with approach”, Oxford Bulletin of Economics and Statistics, Vol. 52 No. 2, pp. 169-210.
Johnston, B.R. and Nedelescu, O.M. (2005), The Impact of Terrorism on Financial Markets,
International Monetary Fund, Washington, DC.
Kallberg, J., Liu, C.H. and Pasquariello, P. (2008), “Updating expectations: an analysis of
post-9/11 returns”, Journal of Financial Markets, Vol. 11 No. 4, pp. 400-32.
Karolyi, A.G. and Martell, R. (2005), “Terrorism and the stock market”, Working Paper Series
2005-19, The Ohio State University, Columbus, OH.
Lai, B. (2007), “Draining the swamp: an empirical investigation of the production of
transnational terrorism, 1968-1998”, Conflict Management and Peace Science, Vol. 24
No. 4, pp. 297-310.
McKenzie, D.J. (2003), “Measure inequality with asset indicators”, BREAD Working Paper
No. 042, Bureau for Research and Economic Analysis of Development, Center for
International Development, Harvard University, Cambridge, MA.
Sandler, T. and Walter, E. (2008), “Economic consequences of terrorism in developed and
developing countries: an overview”, in Philip, K. and Norman, L. (Eds), Terrorism,
Economic Development, and Political Openness, Cambridge University Press, Cambridge,
Shiller, R.J. (2003), “From efficient markets theory to behavioral finance”, Journal of Economic
Perspectives, Vol. 17 No. 1, pp. 83-104.
Abadie, A. and Gardeazabal, J. (2007), “Terrorism and the world economy”, European Economic
Review, Vol. 57, pp. 1-27.
Blomberg, B.S. and Mody, S. (2005), “How severely does violence deter international
investment?”, Claremont Colleges Economics Departments Working Paper No. 2005-01.
Crain, N.V. and Crain, W.M. (2006), “Terrorized economies”, Public Choice, Vol. 128, pp. 317-49.
Enders, W. and Sandler, T. (1996), “Terrorism and foreign direct investment in Spain and
Greece”, Kyklos, Vol. 49 No. 3, pp. 331-52.
Gassebner, M. and Luechinger, S. (2011), “Lock, stock and barrel: a comprehensive assessment of
the determinants of terror”, Public Choice, Vol. 149, pp. 235-61.
Koh, W.T.H. (2007), “Terrorism and its impact on economic growth and technological
innovation”, Technological Forecasting and Social Change, Vol. 74 No. 2, pp. 129-38.
Mihalache, A. (2010), “Who’s afraid of political violence? Evidence from industry level FDI
flows”, paper presented at the Annual Meeting of the Theory vs Policy? Connecting
Scholars and Practitioners, New Orleans Hilton Riverside Hotel, The Loews New Orleans
Hotel, New Orleans, USA.
Schneider, F. and Frey, B. (1985), “Economic and political determinants of foreign direct
investment”, World Development, Vol. 13 No. 2, pp. 161-75.
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