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Citizen Information, Electoral Incentives, and Provision of Counter-Terrorism: An Experimental Approach

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Abstract

How does incomplete information about counter-terror provisions influence the strategic interaction between a government, terrorist groups, and the citizenry? We investigate this research question using a laboratory experiment and present two key findings. (1) Public counter-terror spending leads citizens to overly frequent “protected” targets such that it makes them easier targets for terrorists. (2) Additionally, we show that citizens over-estimate government counter-terror spending when they are unable to observe it. These findings suggest that asymmetric information and the small probability of a successful terrorist attack may lead to the inefficient provision of counter-terror. We also connect the findings to the larger literature on the principal-agent relationship between citizens and elected officials.

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Notes

  1. From a methodological standpoint, it would be ideal to directly observe and/or manipulate citizens’ and terrorists’ level of incomplete information (from 100 % incomplete to 100 % complete) and observe subsequent counter-terror dynamics. Yet from an ethical standpoint (thankfully), this is not feasible, nor practical. Thus, we accept the artificiality of a laboratory.

  2. For a complete review of the game-theoretical approaches to terrorism, see Sandler and Arce (2003) and Sandler and Siqueira (2009).

  3. Looking more closely at partisanship, Berrebi and Klor (2006) finds that terrorists react strategically by attacking left-wing governments more than right-wing. Both Berrebi and Klor (2008) and Getmansky and Zeitzoff (2014) show that terrorism shifts voters to the right.

  4. With regards to the plausibility of citizens switching transportation methods, Blalock et al. (2009) finds an increase in driving fatalities after 9/11 that can be attributed to travelers substituting road trips in place of air travel. Furthermore, Cox et al. (2011) find a reduction in subway and bus trips after the 2005 London bombings.

  5. Further evidence of this dynamic can be found in Iraq, when American forces pulled back in Iraq behind the heavily fortified ‘Green Zone’, and insurgents stepped up their attacks–even though the area was fortified http://www.nytimes.com/2010/09/30/world/middleeast/30iraq.html.

  6. While empirical work on how protecting a site affects the probability of attack there is difficult to come by, Berman and Laitin (2005) suggest that terrorists change tactics in response to site hardening, with more hardened sites being more likely to attract a suicide attack.

  7. This logic is similar to that of bounded rationality commonly exhibited in the beauty contest game. In the game, a pool of subjects choose an integer [0,100]. An individual who guesses closest to \(\dfrac{2}{3}\) the average of the responses receives a monetary prize.If subjects completely backwardly induct, then they should guess 0 (the Nash Equilibrium). However, observed responses vary between 15 and 40, suggesting that humans have, or believe others have, a limited ability (“level-k”) to reason backward and act fully strategic (Nagel 1995; Stahl and Wilson 1995).

  8. Camerer et al. (2004) estimate that an average person can reason through about one and a half steps of strategic interaction.

  9. We denote Government, Citizen, and Terrorist with capital letters in the experiment. Lowercase government, terrorist, and citizen should be thought of as a more general argument.

  10. In reality, citizens may be less informed about target vulnerability than terrorists—who actively conduct surveillance and planning for attacks http://www.nytimes.com/2012/09/11/opinion/the-bush-white-house-was-deaf-to-9-11-warnings.html. Yet, we show in our experiment that even when the Terrorist and the Citizen have the same incomplete information, the Citizen still does not react as strategically as the Terrorist. This suggests that the dynamic of Citizens behaving less strategic than the Terrorists in our experiment is likely to be even stronger in real life, where terrorists have an informational advantage.

  11. For instance, see the failed plots of the so-called “Shoe Bomber” and the “Underwear Bomber” http://articles.cnn.com/2009-12-25/justice/richard.reid.shoe.bomber_1_terror-attacks-american-airlines-flight-qaeda?_s=PM:CRIME.

  12. In the experiment these were referred to as Players 1, 2, or 3. See Online Appendix for a full list of instructions.

  13. On one hand, the assumption the Government keeps the points not spent on counter-terrorism spending may serve as a model of corruption. However, we find it more realistic that the Government shifts the counter-terrorism funds to another area of policy that helps it stay in power, rather than that the Government is personally appropriating the funds. In this way, the Government faces a trade-off between spending on counter-terrorism and on other policies. For example, see Chapter 3 of the 9/11 Commission Report on the low priority of counter-terrorism spending in the mid-1990s, even after the first World Trade Center Bombing (Kean 2011).

  14. We are agnostic as to what a terrorist “success” represents. It could be the terrorist seeking to inflict maximum casualties against a citizenry. Or it could be the terrorist seeking to strike a high value target. All that is required for our game is that the Terrorist and Citizen have opposing preferences.

  15. The small probability of a successful Terrorist attack when both the Citizen and the Terrorist choose C can be thought of as an event targeted at a particular citizen, such as a kidnapping, whose victims tend to be middle class locals (Forest 2012). Santifort and Sandler (2013) find that, conditional on a successful kidnapping, in only 27.5 hostage incidents do terrorist achieve even some of their goals.

  16. These treatment blocks include Public Harden One, Public Harden Both, and Government Choice in which the Government chose to make hardening public. The results do not change substantially when we exclude the Government Choice treatment.

  17. Throughout the paper we use random effects panel regression. Given that we randomly assigned individuals to groups and treatments, we assume that any baseline differences are orthogonal to the treatment (Greene 2008)—thus random effects is preferable. However, there may be a concern that in some models the use of a lagged dependent variable biases the estimates and random effects. The Online Appendix presents the results from Table 4 and Fig. 5 (Model 3) using fixed effects. The results there are nearly identical to those in Table 4 and Fig. 5 (Model 3), alleviating any concerns about the use of random effects.

  18. A discussion of learning during the experiment and public hardening appears in the Online Appendix.

  19. These are to account for learning in subjects’ behavior both within treatment blocks and across time.

  20. For instance in Private treatment, Visible Harden could only take on zero, whereas in Public Both treatment Visible Harden would take on the value \(I_{G}\). In the Public One treatment, only the investment in option A counts toward the Visible Harden variable

  21. Governments invested on average 3.875 points, so from Model 3 the main effect on the latent \(Bonus = 1.505 \times 3.875+-8.286=-2.454125\)

  22. The Government invested an average of 3.50, 3.875, and 4.60 points in hardening in the Public One, Public Both, and Choice Public treatments, respectively.

  23. Bonuses in the Public Both are on average 1.4 points lower than in the Public One treatment (two-tailed p value=0.07). It should be emphasized that treatment order was randomized across groups.

  24. In fact, when we reformulate the dependent variables \(I_{G}\) and \(B_{Z}\) as binary variables—1 right censored for \(B_{Z}\), 0 otherwise and 1 left censored for \(I_{G}=0\), 0 otherwise, the results are even stronger (see Online Appendix).

  25. See the Online Appendix for a discussion of the expected increase in the Citizen’s payoff per point of hardening, which is calculated to be between .5 and .9.

  26. Powell (2007b) makes a similar point in arguing why strategic defense does not necessarily make targets uniformly safer due to strategic behavior on the part of terrorists.

  27. We argue that a terrorist defeating the government at its strongest may instill fear in the citizenry, making attacks at protected sites even more valuable to the terrorist.

  28. This could also be a high value target, whereby hardening the target signals that it is high value to terrorists (Powell 2007b).

  29. For instance, both Getmansky and Sinmazdemir (2013) (terror attacks) and Johnston (2012) (drone strikes) use the quasi-random success of terror attacks and drone strikes, comparing successes to failures, to estimate their causal effect.

  30. 1 point spent by the government reduced the probability of a successful terrorist attack by 2 percentage points if the terrorist guessed correctly.

  31. I.e., the size of the bonus the Citizen can give the Government does not depend on the success of a Terrorist attack.

  32. The recent uproar over the disclosure by former US intelligence contractor Eric Snowden of secret US surveillance programs run by the National Security Agency (NSA) on ordinary Americans suggests an interesting alternative http://www.theguardian.com/world/the-nsa-files. In our model, the government can shirk by simply not investing in private hardening. However, as the Snowden revelations suggest, they may use secrecy to as a cover for far more invasive surveillance. Modeling this would be an interesting extension.

References

  • Abramson, Paul R., Aldrich, John H., Rickershauser, Jill, & Rohde, David, W. (2007). Fear in the voting booth: The 2004 presidential election. Political Behavior, 29(2), 197–220.

    Article  Google Scholar 

  • Achen, C. H., Bartels, & L. M. (2004). Blind retrospection. Electoral responses to drought, flu, and shark attacks. Estudios/Working Papers (Centro de Estudios Avanzados en Ciencias Sociales), (199), 1.

  • Arce, D. G., & Sandler, T. (2005). Counterterrorism: A game-theoretic analysis. Journal of Conflict Resolution, 49(2), 183–200.

    Article  Google Scholar 

  • Arce, D. G., Croson, R. T. A., & Eckel, C. C. (2011). Terrorism experiments. Journal of Peace Research, 48(3), 373–382.

    Article  Google Scholar 

  • Bagues, M., & Esteve-Volart, B. (2011). Politicians Luck of the Draw: Evidence from the Spanish Christmas Lottery. Working Paper.

  • Berman, E., & Laitin, D. (2005). Hard targets: Theory and evidence on suicide attacks. NBER Working Paper, 11740.

  • Berrebi, Claude, & Klor, Esteban F. (2006). On terrorism and electoral outcomes theory and evidence from the Israeli-Palestinian conflict. Journal of Conflict Resolution, 50(6), 899–925.

    Article  Google Scholar 

  • Berrebi, Claude, & Klor, Esteban F. (2008). Are voters sensitive to terrorism? Direct evidence from the Israeli electorate. American Political Science Review, 102(03), 279–301.

    Article  Google Scholar 

  • Blalock, Garrick, Kadiyali, Vrinda, & Simon, Daniel H. (2009). Driving fatalities after 9/11: A hidden cost of terrorism. Applied Economics, 41(14), 1717–1729.

    Article  Google Scholar 

  • Bueno de Mesquita, E. (2007). Politics and the suboptimal provision of counterterror. International Organization, 61(1), 9.

    Article  Google Scholar 

  • Cadigan, J., & Schmitt, P. M. (2010). Strategic entry deterrence and terrorism: Theory and experimental evidence. Public Choice, 143(1), 3–22.

    Article  Google Scholar 

  • Camerer, Colin. (2003). Behavioral game theory: Experiments in strategic interaction. Princeton: Princeton University Press.

    Google Scholar 

  • Camerer, Colin F., Ho, Teck-Hua, & Chong, Juin-Kuan. (2004). A cognitive hierarchy model of games. The Quarterly Journal of Economics, 119(3), 861–898.

    Article  Google Scholar 

  • Cole, S., Healy, A., & Werker, E. (2012). Do voters demand responsive governments? Evidence from Indian disaster relief. Journal of Development Economics, 97, 167–181.

    Article  Google Scholar 

  • Cox, Andrew, Prager, Fynnwin, & Rose, Adam. (2011). Transportation security and the role of resilience: A foundation for operational metrics. Transport Policy, 18(2), 307–317.

    Article  Google Scholar 

  • de Rugy, V. (2006). Spending too much the wrong way on the wrong things. CATO Unbound.

  • Enders, W., & Sandler, T. (1993). The effectiveness of antiterrorism policies: A vector-autoregression-intervention analysis. American Political Science Review, 87, 829–844.

    Article  Google Scholar 

  • Enders, W., & Sandler, T. (2002). Patterns of transnational terrorism, 1970–1999: Alternative time-series estimates. International Studies Quarterly, 46(2), 145–165.

    Article  Google Scholar 

  • Faria, J. R. (2006). Terrorist innovations and anti-terrorist policies. Terrorism and Political Violence, 18(1), 47–56.

    Article  Google Scholar 

  • Forest, James J. F. (2012). Global trends in kidnapping by terrorist groups. Global Change, Peace and Security, 24(3), 311–330.

    Article  Google Scholar 

  • Gasper, J. T., & Reeves, A. (2011). Make It Rain? Retrospection and the attentive electorate in the context of natural disasters. American Journal of Political Science, 55(2), 340–355.

    Article  Google Scholar 

  • Gassebner, M., Jong-A-Pin, R., & Mierau, J. O. (2008). Terrorism and electoral accountability: One strike, you’re out!. Economics Letters, 100(1), 126–129.

    Article  Google Scholar 

  • Getmansky, A. (2011a). Protection politics: The effect of Government’s counter terrorism policy on terrorists’ choice of targets. Working Paper.

  • Getmansky, A. (2011b). Whose life is worth more? Domestic politics, counterterrorism, and terrorists selection of targets. Working Paper.

  • Getmansky, A., & Zeitzoff, T. (2014). Terrorism and voting: The effect of rocket threat on voting in Israeli elections. American Political Science Review, Forthcoming.

  • Getmansky, A., & Sinmazdemir, T. (2013). Success breeds failure: The effect of terrorist attacks on land seizures in the Israeli-Palestinian conflict. Working Paper.

  • Goeree, J.K., & Holt, C.A. (2001). Ten little treasures of game theory and ten intuitive contradictions. American Economic Review, 1402–1422.

  • Goeree, J. K., Holt, C. A., & Palfrey, T. R. (2003). Risk averse behavior in generalized matching pennies games. Games and Economic Behavior, 45(1), 97–113.

    Article  Google Scholar 

  • Greene, William H. (2008). Econometric analysis (6th ed.). Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Hamman, J. R., Weber, R. A., & Woon, J. (2011). An experimental investigation of electoral delegation and the provision of public goods. American Journal of Political Science, 55(4), 738–752.

    Article  Google Scholar 

  • Healy, A., & Malhotra, N. (2009). Myopic voters and natural disaster policy. American Political Science Review, 103(03), 387–406.

    Article  Google Scholar 

  • Healy, A. J., Malhotra, N., & Mo, C. H. (2010). Irrelevant events affect voters’ evaluations of government performance. Proceedings of the National Academy of Sciences, 107(29), 12804–12809.

    Article  Google Scholar 

  • Huber, A., Hill, Seth J., & Lenz, Gabriel S. (2012). Sources of bias in retrospective decision-making: Experimental evidence on voters limitations in controlling incumbents. American Political Science Review, 106(04), 720–741.

    Article  Google Scholar 

  • Jindapon, P., & Neilson, W. S. (2009). The impact of societal risk attitudes on terrorism and counterterrorism. Economics and Politics, 21(3), 433–451.

    Article  Google Scholar 

  • Johnston, Patrick B. (2012). Does decapitation work? Assessing the effectiveness of leadership targeting in counterinsurgency campaigns. International Security, 36(4), 47–79.

    Article  Google Scholar 

  • Kahneman, Daniel. (2011). Thinking, fast and slow. New York: Macmillan.

    Google Scholar 

  • Kean, Thomas. (2011). The 9/11 commission report: Final report of the national commission on terrorist attacks upon the United States. Washington, DC: Government Printing Office.

    Google Scholar 

  • Kibris, A. (2011). Funerals and elections: The effects of terrorism on voting behavior in Turkey. Journal of Conflict Resolution, 55(2), 220–247.

    Article  Google Scholar 

  • Landes, W. M. (1978). An economic study of US aircraft hijacking, 1961–1976. Journal of Law and Economics, 21(1), 1–31.

    Article  Google Scholar 

  • Lipton, E. (2010). Officials regret curbs on adding to terror watch list. New York: The New York Times.

    Google Scholar 

  • McDermott, R. (2011). New directions for experimental work in international relations. International Studies Quarterly, 55, 503–520.

    Article  Google Scholar 

  • Morton, R. B., & Williams, K. C. (2010). Experimental political science and the study of causality: From nature to the lab. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Nagel, R. (1995). Unraveling in guessing games: An experimental study. The American Economic Review, 85, 1313–1326.

    Google Scholar 

  • Ochs, J. (1995). Games with unique, mixed strategy equilibria: An experimental study. Games and Economic Behavior, 10(1), 202–217.

    Article  Google Scholar 

  • Powell, R. (2007a). Allocating defensive resources with private information about vulnerability. American Political Science Review, 101(04), 799–809.

    Article  Google Scholar 

  • Powell, R. (2007b). Defending against terrorist attacks with limited resources. American Political Science Review, 101(03), 527–541.

    Article  Google Scholar 

  • Sandler, T., & Arce, D. G. (2003). Terrorism and game theory. Simulation and Gaming, 34(3), 319–337.

    Article  Google Scholar 

  • Sandler, T., & Siqueira, K. (2006). Global terrorism: Deterrence versus pre-emption. Canadian Journal of Economics, 39(4), 1370–1387.

    Article  Google Scholar 

  • Sandler, T., & Siqueira, K. (2009). Games and terrorism. Simulation and Gaming, 40(2), 164–192.

    Article  Google Scholar 

  • Santifort, Charlinda, & Sandler, Todd. (2013). Terrorist success in hostage-taking missions: 1978–2010. Public Choice, 156(1–2), 125–137.

    Article  Google Scholar 

  • Shapiro, Jacob N., & Cohen, Dara Kay. (2007). Color bind: Lessons from the failed homeland security advisory system. International Security, 32(2), 121–154.

    Article  Google Scholar 

  • Stahl, Dale O., & Wilson, Paul W. (1995). On players models of other players: Theory and experimental evidence. Games and Economic Behavior, 10(1), 218–254.

    Article  Google Scholar 

  • Wolfers, J. (2002). Are voters rational? Evidence from gubernatorial elections. Working Paper.

  • Woon, J. (2012). Democratic accountability and retrospective voting: A laboratory experiment. American Journal of Political Science, 56, 913–930.

    Article  Google Scholar 

  • Wright, John R. (2012). Unemployment and the democratic electoral advantage. American Political Science Review, 106(04), 685–702.

    Article  Google Scholar 

Download references

Acknowledgments

Funding for this research was provided by NSF award number 0905044.

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Authors and Affiliations

  1. Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, USA

    Andrew W. Bausch

  2. American University, Washington, DC, USA

    Thomas Zeitzoff

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Correspondence to Andrew W. Bausch.

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Bausch, A.W., Zeitzoff, T. Citizen Information, Electoral Incentives, and Provision of Counter-Terrorism: An Experimental Approach. Polit Behav 37, 723–748 (2015). https://doi.org/10.1007/s11109-014-9289-x

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