CREATE Research Archive Published Articles & Papers 1-1-2010 e Adverse Effect of Transnational and Domestic Terrorism on Growth in Africa Khusrav Gaibulloev University of Texas at Dallas Todd Sandler University of Texas at Dallas, [email protected]Follow this and additional works at: hp://research.create.usc.edu/published_papers is Article is brought to you for free and open access by CREATE Research Archive. It has been accepted for inclusion in Published Articles & Papers by an authorized administrator of CREATE Research Archive. For more information, please contact [email protected]. Recommended Citation Gaibulloev, Khusrav and Sandler, Todd, "e Adverse Effect of Transnational and Domestic Terrorism on Growth in Africa" (2010). Published Articles & Papers. Paper 152. hp://research.create.usc.edu/published_papers/152
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CREATE Research Archive
Published Articles & Papers
1-1-2010
The Adverse Effect of Transnational and DomesticTerrorism on Growth in AfricaKhusrav GaibulloevUniversity of Texas at Dallas
Follow this and additional works at: http://research.create.usc.edu/published_papers
This Article is brought to you for free and open access by CREATE Research Archive. It has been accepted for inclusion in Published Articles & Papersby an authorized administrator of CREATE Research Archive. For more information, please contact [email protected].
Recommended CitationGaibulloev, Khusrav and Sandler, Todd, "The Adverse Effect of Transnational and Domestic Terrorism on Growth in Africa" (2010).Published Articles & Papers. Paper 152.http://research.create.usc.edu/published_papers/152
Running Title: Terrorism Impact on African Growth Word Count: 8,349 *This study was funded by the US Department of Homeland Security through the Center for Risk and Economic Analysis of Terrorism Events (CREATE) at the University of Southern California, grant number 2007-ST-061-000001. However, any opinions, findings, and conclusions or recommendations are solely those of the authors and do not necessarily reflect the view of the Department of Homeland Security or CREATE. Gaibulloev is a Postdoctoral Researcher and Sandler is the Vibhooti Shukla Professor of Economics and Political Economy.
The Adverse Effect of Transnational and Domestic Terrorism on Growth in Africa
Abstract
With panel estimates, this paper investigates the neoclassical determinants of income per capita
growth for 51 African countries for 1970–2007, while accounting for cross-sectional (spatial)
dependence and conflict (i.e., terrorism, internal conflicts, and external wars). For the entire
sample, fixed-effects panel estimates find that transnational terrorism has a significant, but
modest, marginal impact on income per capita growth. These results hold for two different
terrorism event data sets. However, domestic terrorist events do not affect income per capita
growth. This suggests that an earlier growth study, which did not include domestic terrorist
events for a different sample and time period, provided an accurate picture for Africa. The paper
contains a host of robustness checks that find virtually identical results. Alternative terrorist
variables are also used, with little qualitative change in the findings. The absence of a domestic
terrorism impact is surprising because there were generally many more domestic than
transnational terrorist incidents in Africa. To promote growth, host and donor countries must
direct scarce counterterrorism resources to protect against transnational terrorism in particular.
Keywords: growth in Africa, transnational terrorism, domestic terrorism, conflict, fixed-effects
panel
The Adverse Effect of Transnational and Domestic Terrorism on Growth in Africa
Introduction
In their bid to force governments to concede to their demands, terrorists plan attacks that have
adverse consequences on targeted countries’ economies. Thus, Euskadi ta Askatasuna (ETA)
targeted tourist sites and commerce centers in Spain, while Jemaah Islamiyah bombed a popular
nightclub in Bali and a tourist hotel in Jakarta. Modern-day terrorists have damaged
infrastructure – e.g., train stations, bus stations, airports, and stock exchanges – not only to create
anxiety in a targeted audience, but also to disrupt the economy. Terrorists hope that economic
costs when combined with human losses from economic-damaging attacks will pressure
besieged governments to concede to their political demands. In Africa, terrorist groups have also
sought out economic targets – e.g., the Islamic Group staged the Luxor massacre of tourists on
17 November 1997 at Hatshepsut’s Temple in Egypt. This armed attack murdered 62 and
injured 24 (Mickolus & Simmons, 2002). The car bombing of the Israeli-owned Paradise Hotel
in Mombasa, Kenya on 28 November 2002 by an al-Qaida affiliated Somali group killed 16
(including 3 suicide terrorists) and injured 80 (Mickolus & Simmons, 2006). Two surface-to-air-
missiles on this same day narrowly missed hitting an Israeli-chartered airline taking off from
Mombasa airport.
Terrorism can negatively influence a targeted country’s economic growth through a
number of channels.1 First, terrorist attacks may enhance uncertainty which limits investments
and diverts foreign direct investment to safer venues, as documented by a number of studies
terrorism: Data, decomposition, and dynamics. Unpublished manuscript, Center for
Global Collective Action, University of Texas at Dallas.
Enders, Walter; Todd Sandler & Gerald F. Parise (1992) An econometric analysis of the impact
of terrorism on tourism. Kyklos 45(4): 531–554.
Gaibulloev, Khusrav & Todd Sandler (2008) Growth consequences of terrorism in Western
Europe. Kyklos 61(3): 411–424.
Gaibulloev, Khusrav & Todd Sandler (2009) The impact of terrorism and conflicts on growth in
Asia. Economics and Politics 21(3): 359–383.
Heston, Alan; Robert Summers & Bettina Aten (2006) Penn World Table Version 6.2.
Philadelphia, PA: Center for International Comparisons of Production, Income and Prices
at the University of Pennsylvania.
Hoechle, Daniel (2007) Robust standard errors for panel regressions with cross-sectional
dependence. Stata Journal 7(3): 281–312.
Hoeffler, Anke (2002) The augmented Solow model and the African growth. Oxford Bulletin of
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Economics and Statistics 64(2): 135–158.
International Monetary Fund (IMF) (2009) World Economic Outlook (WEO) Database, April
(http://www.imf.org). Accessed 1 July 2009.
Ito, Harumi & Darin Lee (2005) Assessing the impact of the September 11th terrorist attacks on
US airline demand. Journal of Economics and Business 57(1): 75–95.
Keefer, Philip & Norman Loayza (eds.) (2008) Terrorism, Economic Development, and Political
Openness. Cambridge: Cambridge University Press.
Lyman, Princeton N. & J. Stephen Morrison (2004) The terrorist threat in Africa. Foreign
Affairs 83(1): 75–86.
Marshall, Monty G., 2009. Major Episodes of Political Violence (MEPV), 1946–2008. Fairfax,
VA: Center for Systemic Peace, George Mason University
(http://www.systemicpeace.org). Accessed 1 July 2009.
Marshall, Monty G. & Keith Jaggers, 2009. Polity IV Dataset Version 2007 and Dataset Users’
Manual. Fairfax, VA: Center for Systemic Peace and the Center for Global Policy,
George Mason University (http://www.systemicpeace.org). Accessed 1 July 2009.
Mickolus, Edward F (1989) What constitutes state support to terrorists? Terrorism and Political
Violence 1(3): 287–293.
Mickolus, Edward F.; Todd Sandler, Jean M. Murdock & Peter Flemming (2008) International
Terrorism Attributes of Terrorism Events (ITERATE), 1968–2007. Dunn Loring, VA:
Vinyard Software.
Mickolus, Edward F. & Susan L. Simmons (2002) Terrorism, 1996–2001: A Chronology, 2 vols
Westport, CT: Greenwood Press.
Mickolus, Edward F. & Susan L. Simmons (2006) Terrorism, 2002–2004: A Chronology.
Westport, Ct: Praeger Security International.
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Murdoch, James C. & Todd Sandler (2002a) Civil wars and economic growth: A regional
comparison. Defence and Peace Economics 13(6): 451–464.
Murdoch, James C. & Todd Sandler (2002b) Economic growth, civil wars, and spatial
spillovers. Journal of Conflict Resolution 46(1): 91–110.
Murdoch, James C. & Todd Sandler (2004) Civil wars and economic growth: Spatial spillovers.
American Journal of Political Science 48(1): 138–151.
National Consortium for the Study of Terrorism and Responses to Terrorism (START) (2009)
Global Terrorism Database, CD-Rom. College Park, MD: University of Maryland.
Pesaran, M. Hashem (2004) General diagnostic tests for cross section dependence in panels.
Cambridge Working Papers in Economics No. 0435, Faculty of Economics, University of
Cambridge.
Tavares, Jose (2004) The open society assesses its enemies: Shocks, disasters, and terrorist
attacks. Journal of Monetary Economics 51(5): 1039–1070.
United Nations Statistics Division (UNSD) (2008) National Accounts Main Aggregates
Database (http://unstats.un.org/unsd/snaama/Introduction.asp). Accessed 1 July 2009.
World Bank (2009) World Development Indicators (WDI) (http://www.worldbank.org/data).
Accessed 1 July 2009.
0
20
40
60
80
100
120
140
160
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006
Figure 1. Annual Number of Transnational Terrorist Incidents, 1970-2007
Num
ber
of in
cide
nts
ITERATE
GTD_trans
0
20
40
60
80
100
120
140
160
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006
Figure 2. Annual Number of Transnational Terrorist Incidents Using Adjusted GTD Data
Num
ber
of in
cide
nts
ITERATE
GTD_trans1
GTD_trans2
Table I. Fixed-effects estimation of growth model with cross-sectional dependence, 1970–2007
Model 1 Model 2 Model 3 Model 4 ln yit–1 –0.042*** –0.040*** –0.041*** –0.040*** (0.013) (0.013) (0.013) (0.013) I/GDPit–1 0.161*** 0.161*** 0.158*** 0.161*** (0.032) (0.031) (0.031) (0.031) trans_terror_iterit –0.013** (0.006) trans_terror_gtdit –0.020*** –0.020*** (0.005) (0.005) dom_terror_gtdit –0.002 –0.0004 (0.002) (0.0013) internalit –0.016*** –0.013*** –0.016*** –0.013*** (0.003) (0.003) (0.003) (0.003) externalit –0.018** –0.019** –0.018** –0.019** (0.008) (0.008) (0.008) (0.008) Sample size 1751 1751 1751 1751 R-squared 0.14 0.15 0.13 0.15 CD test –1.72 –1.75 –1.43 –1.76 p-value 0. 085 0.080 0.154 0.078 Notes: CD test is Pesaran’s (2004) test of cross-sectional independence and p-value is the probability value of the null. Constant and time dummies are suppressed. Driscoll and Kraay’s standard errors are in parentheses. These standard errors are robust to general forms of heteroskedasticity, autocorrelation, and cross-sectional (spatial) dependence. R-squared (within) is computed after removing country effects. Significance levels: *** is .01, ** is .05, and * is .10.
Table II. Robustness of estimates to inclusion of additional variables, 1970–2007
Model 1 Model 2 Model 3 Model 4 ln yit–1 –0.051*** –0.049*** –0.051*** –0.049*** (0.012) (0.012) (0.012) (0.012) I/GDPit–1 0.082** 0.084** 0.079** 0.084** (0.035) (0.033) (0.036) (0.033) G/GDPit–1 –0.105*** –0.101*** –0.103*** –0.101*** (0.036) (0.035) (0.036) (0.036) TRADE/GDPit–1 0.070*** 0.068*** 0.071*** 0.068*** (0.014) (0.013) (0.015) (0.013) trans_terror_iterit –0.013** (0.005) trans_terror_gtdit –0.019*** –0.019*** (0.004) (0.004) dom_terror_gtdit –0.002 –0.001 (0.002) (0.001) internalit –0.011*** –0.009*** –0.012*** –0.009*** (0.003) (0.003) (0.003) (0.003) externalit –0.015** –0.017** –0.016** –0.017** (0.007) (0.007) (0.007) (0.007) polityit –0.0002 –0.0002 –0.0002 –0.0002 (0.0003) (0.0004) (0.0003) (0.0003) population growthit 0.478 0.466 0.473 0.465 (0.357) (0.343) (0.372) (0.342) Sample size 1744 1744 1744 1744 R-squared 0.18 0.18 0.17 0.18 CD test –2.33 –2.31 –2.11 –2.32 p-value 0.020 0.021 0.035 0.021 Notes: CD test is Pesaran’s (2004) test of cross-sectional independence and p-value is the probability value of the null. Constant and time dummies are suppressed. Driscoll and Kraay’s standard errors are in parentheses. These standard errors are robust to general forms of heteroskedasticity, autocorrelation, and cross-sectional (spatial) dependence. R-squared (within) is computed after removing country effects. Significance levels: *** is .01, ** is .05, and * is .10.
Table III. Re-estimation of Table II by using unadjusted GTD data and alternative specifications of terrorism variables
Model 1 Model 2 Model 3 Model 4 Using unadjusted GTD data
Using number of terrorist incidents trans_terror_iterit –0.002** (0.001) trans_terror_gtdit –0.001*** –0.002*** (0.0005) (0.001) dom_terror_gtdit 0.00003 0.00008 (0.00003) (0.00005)
Using dummy variable for terrorism trans_terror_iterit –0.011** (0.005) trans_terror_gtdit –0.012** –0.011** (0.004) (0.005) dom_terror_gtdit –0.008** –0.005 (0.004) (0.004)
Using lagged value of the number of terrorist incidents per million population trans_terror_iterit-1 –0.002 (0.003) trans_terror_gtdit-1 –0.009** –0.009*** (0.004) (0.003) dom_terror_gtdit-1 –0.001 –0.001 (0.001) (0.001) Notes: See Models in Table II for specification. Driscoll and Kraay’s standard errors are in parentheses. These standard errors are robust to general forms of heteroskedasticity, autocorrelation, and cross-sectional (spatial) dependence. Significance levels: *** is .01, ** is .05, and * is .10.
APPENDIX Table IA. Raw data and sources Data Sources GDP per capita (PPP at current international dollars, LCU at constant prices)
World Bank (2009), IMF(2009), Heston, Summers & Aten (2006), UNSD (2008)
Investment share in GDP UNSD (2008) Government spending share in GDP UNSD (2008) Import share in GDP UNSD (2008) Export share in GDP UNSD (2008) Transnational terrorist incidents (ITERATE) Mickolus et al. (2008) Transnational terrorist incidents and domestic terrorist incidents (GTD)
Enders, Sandler & Gaibulloev (2010), START (2009)
Internal conflicts (MEPV) Marshall (2009) External conflicts (MEPV) Marshall (2009) Polity2 (Polity IV dataset) Marshall and Jaggers (2009) Population World Bank (2009)
Table IIA. Number of terrorist incidents by country and ranking of countries in terms of the number of terrorist incidents for 1970–2007
Country ITERATE GTD transnational GTD domestic Number Rank Number Rank Number Rank