The Effect of the Moscow Theatre Siege on Expectations of Well-Being in the Future

Abstract

We employ the Russia Longitudinal Monitoring Survey–Higher School of Economics (RLMS-HSE), a survey of 6,000 individuals, and a difference-in-differences estimation strategy to examine the effect of the 2002 Moscow theatre siege on the level of self-reported expectations of life in the future of the Russian population. The longitudinal nature of the data allows us to explore both the short- and long-term effects of terrorism on this population as well as contribute to the limited number of quasi-experimental studies in this area. By focusing on expectations of life in the future, we broaden our understanding of the social consequences of terrorism. Controlling for a range of sociodemographic variables including self-assessed relative income, our findings suggest that the well-being effects of terrorism are complex and the net effect of a terrorism incident on well-being may not necessarily be negative. This can be explained, at least in part, by the theory of posttraumatic growth—a theory that refers to the positive psychological change experienced as a result of adversity, with terrorism incidents inadvertently promoting more meaningful interpersonal relationships, new views of the self and new views of the world. That is not to suggest that terrorism is a positive phenomenon—rather, that individuals have a lifelong plasticity rendering them capable of recovery from adversity. The primary objectives of terrorists, therefore, are unlikely to be fully achieved. It is hoped that our research allows for the development of more refined policies that aim to encourage posttraumatic growth while simultaneously attempting to minimize posttraumatic stress disorder. This may involve engaging with the psychological community to devise policies and programs that target those in the population who are most vulnerable and for these groups devise strategies to enhance their psychological resilience following a terrorist (or other traumatic) event.

Keywords

hate crimes violence exposure war

The consequences of terrorism have been, and continue to be, felt by citizens of countries across the globe. Since 2000, the number of deaths from terrorism has increased fivefold, from over 3,000 in the year 2000 to almost 18,000 in the year 2013 (Institute for Economics and Peace, 2014). Terrorism is a concentrated phenomenon, with over 80% of the lives lost to terrorist activity in 2013 occurring in only five countries (Iraq, Afghanistan, Pakistan, Nigeria and Syria). Another 55 countries, however, recorded one or more deaths from a terrorism incident (Institute for Economics and Peace, 2014).

In a European context, there have been a number of high profile terrorism incidents in recent years. Incidents include the string of terrorist attacks across Paris on Friday, November 13, 2015, with an estimated death toll in excess of 130 people and a further 350 wounded; the attack on the headquarters of satirical weekly newspaper Charlie Hebdo on January 7, 2015, in which 11 people were killed and 11 others injured; the London bombings on July 7, 2005, in which 52 people were killed and more than 700 injured; the 2004 Madrid bombings, in which 191 people were killed and 2,050 wounded; and the 2002 Moscow theatre siege. The theatre siege is the subject of inquiry of this article.

The Moscow theatre siege was organized by terrorists from the Islamist militant separatist movement in Chechnya. Approximately 40 armed Chechens took 850 hostages in the Dubrovka Theatre. The motive of the siege was to demand the withdrawal of Russian forces from the region and the end to the second Chechen war. During the siege, a videotape was released to the media, with the following statement:

Every nation has the right to their fate. Russia has taken away this right from the Chechens and today we want to reclaim these rights, which Allah has given us, in the same way he has given it to other nations. Allah has given us the right of freedom and the right to choose our destiny. And the Russian occupiers have flooded our land with our children’s blood. And we have longed for a just solution. People are unaware of the innocent who are dying in Chechnya: the sheikhs, the women, the children and the weak ones. And therefore, we have chosen this approach. This approach is for the freedom of the Chechen people and there is no difference in where we die, and therefore we have decided to die here, in Moscow. And we will take with us the lives of hundreds of sinners. If we die, others will come and follow us—our brothers and sisters who are willing to sacrifice their lives, in Allah’s way, to liberate their nation. Our nationalists have died but people have said that they, the nationalists, are terrorists and criminals. But the truth is Russia is the true criminal. (Cable News Network [CNN], 2002)

The siege lasted from October 23 to October 26, 2002, and ended when Russian Special Forces raided the theatre. All 40 terrorists were killed, as were more than 130 hostages. In total, more than 170 people died and more than 700 people were injured.

This article employs longitudinal household panel data for more than 6,000 individuals to estimate the effect of the Moscow theatre hostage siege on the self-reported expectations of life in the future of the Russian population. The Moscow attack was exogenous to the timing of the household survey and could, therefore, be described as an exogenous shock to the randomly sampled population. This allows us to employ the difference-in-differences approach to test the effect of the attack on self-reported expectations of life in the future (Metcalfe, Powdthavee, & Dolan, 2011). This extends our current understanding of the effect of a terrorist event on the well-being of a population, which to date has received very little attention in the literature. The longitudinal nature of the data allows us to explore both the short- and long-term effects of terrorism on this population as well as contribute to the limited number of quasi-experimental studies in this area (Metcalfe et al., 2011). By focusing on expectations of life in the future, we broaden our understanding of the social consequences of terrorism. Our research allows for the development of more refined policies that aim to encourage posttraumatic growth while attempting to minimize posttraumatic stress disorder. To achieve this, however, policy makers require evidence on the net effect of a terrorist incident on well-being and if, and to what degree, the impact is distributed equally over the population. Policymakers also need evidence on helping the population to cope with terrorism. This may involve engaging with the psychological community to devise policies and programs that target those in the population who are most vulnerable and for these groups devise strategies to enhance their psychological resilience following a terrorist (or other traumatic) event. In this article, we provide evidence as to who these vulnerable populations may be.

The article is structured as follows: The related theoretical and empirical literature is provided in the Section “Literature.” Data, method, and variables employed are described in the Section “Data and Method.” This is followed by the “Results” and finally the “Discussion.”

Literature

The Economic and Psychological Impacts of Terrorism

The impact of terrorism can be measured in a number of ways including its effect on Gross Domestic Product (Gaibulloev & Sandler, 2008, 2009, 2011), national consumption (Eckstein & Tsiddon, 2004; Fielding, 2003a), national investment (Fielding, 2003b; Frey, Luechinger, & Stutzer, 2007), stock markets (Drakos, 2010; Essaddam & Karagianis, 2014), foreign direct investment (Enders & Sandler, 1996), and foreign trade (Mirza & Verdier, 2008; Nitsch & Schumacher, 2004). A more thorough review of this literature is provided by Vorsina, Manning, Fleming, Ambrey, and Smith (2017).

The psychological and emotional negative effects of terrorism have also been studied, with an extensive body of literature exploring the influence of the 2001 9/11 terrorist attacks on the mental health of citizens of the United States (Galea et al., 2002; Schlenger et al., 2002; Schuster et al., 2001; Silver, Holman, McIntosh, Poulin, & Gil-Rivas, 2002). Results consistently show that the effect of the 9/11 attacks were substantial during the first week. For example, Silver et al. (2002) show that 90% of interviewees displayed at least one symptom of stress for 3 to 5 days following the event; symptoms significantly subsided, however, after 2 months. Likewise, the effect of the attack on sadness (Ford, Udry, Gleiter, & Chantala, 2003) and emotional distress (DeLisi et al., 2003) lasted for 4 to 6 weeks and 3 to 6 weeks, respectively. With regard to the terrorist attack that occurred in Madrid in 2004, Miguel-Tobal et al. (2006) report that 8% of respondents had symptoms of depression 1 to 3 months after the attack, and 2.3% of respondents reported symptoms of posttraumatic stress disorder. Similarly, Salguero, Fernández-Berrocal, Iruarrizaga, Cano-Vindel, and Galea (2011) report that 8% of citizens interviewed in Madrid had major depressive disorder symptoms 1 month after the attack. The population of the United Kingdom had a similar emotional reaction after the 2005 London terrorist attacks. Rubin, Brewin, Greenberg, Simpson, and Wessely (2005) find that substantial stress symptoms were reported by 31% of respondents interviewed 11 to 13 days after the attacks. Further, 45% of the population feared catching public transport and more than 70% of the directly affected victims displayed symptoms of mental disorder (Handley, Salkovskis, Scragg, & Ehlers, 2009).

A small body of literature also considers the negative relationship between terrorism and various measures of self-reported well-being. For example, Frey, Luechinger, and Stutzer (2009) use combined cross-section time-series data to estimate the costs of terrorism for France and the British Isles, finding large negative effects of terrorism on life satisfaction. Similarly, Romanov, Zussman, and Zussman (2012) employ data from Israel’s Social Survey for the years 2002 to 2004 to investigate the relationship between terrorism and the life satisfaction of Israelis during the second Palestinian Intifada. They find that terrorism has a limited impact on the life satisfaction of Jewish Israelis, while the life satisfaction of Arab citizens of Israel is negatively affected. In terms of inter-country affects, Metcalfe et al. (2011) examine the influence of the 9/11 attacks on the happiness of residents of the United Kingdom. The authors find that the attack led to a significant increase in mental distress among the population. This effect, however, was short, lasting for only approximately 3 months. In a cross country study, Vorsina et al. (2017) employ data from 117 countries over the period 2006 to 2011 to estimate a macroeconomic cross-country system of equations that examines the association between terrorism, self-reported life satisfaction, and national income. The authors find that terrorism is negatively associated with life satisfaction, whereas no such association is found between terrorism and real Gross Domestic Product per worker, suggesting that the subjective well-being costs of terrorism are potentially much higher than the economic costs.

Coping With Terrorism

When a terrorist attack occurs, people look for ways to cope with the associated stress and trauma. This sets off a chain of psychological events culminating in helplessness, vulnerability, and grief. It often leads to xenophobia, which can become a danger to both individuals and society at large (Tedeschi & Calhoun, 2004).

There is also, however, a growing body of empirical evidence that suggests that many survivors of traumatic events experience positive psychological changes. Posttraumatic growth is defined as “. . . the subjective experience of positive psychological change reported by an individual as a result of the struggle with trauma” (Zoellner & Maercker, 2006, p. 628). Examples of positive psychological change are an increased appreciation of life, setting of new life priorities, a sense of increased personal strength, identification of new possibilities, improved closeness of intimate relationships, or positive spiritual change (Tedeschi, Park, & Calhoun, 1998). Posttraumatic growth describes the experience of individuals who do not only recover from trauma, that is, return back to pre-trauma functioning after a period of emotional distress, but use it as an opportunity for further individual development. Those individuals overcome trauma with improved psychological functioning in specific domains (Zoellner & Maercker, 2006).

A number of researchers have applied posttraumatic growth theory to examine psychological outcomes from terrorist attacks. For example, Fredrickson, Tugade, Waugh, and Larkin (2003) measured emotion, symptoms of depression, and resilience resources before and after the 9/11 terrorist attacks. They find that the event increased sadness, anger, and fear of future terrorist attacks. Respondents reported that they had problems with concentration on their studies and had concerns about friends or relatives living in and around New York City. Positive emotions such as gratitude, interest, and love, however, were also reported. Fredrickson et al. (2003) suggest that these emotions helped individuals cope with stress and the negative consequences of the terrorist event. In particular, people who experienced positive emotions after the attacks showed higher resilience and were less likely to develop depressive symptoms. In a subsequent study to examine the impact of the 9/11 attacks, Ai, Cascio, Santangelo, and Evans-Campbell (2005) examine how respondents changed their views about themselves, their behavior, relations, worldviews, spiritual beliefs, and purpose in life. They find that stronger faith, hope, and spiritual meaning is negatively correlated with depression and anxiety. This is consistent with Fischer, Greitemeyer, Kastenmüller, Jonas, and Frey (2006), who find that on the day of a terrorist attack in Istanbul, nonreligious participants reported a higher degree of negative emotions and reduced positive emotions, while religious participants did not. Similarly, Val and Linley (2006) find that residents of Madrid experienced posttraumatic growth and other positive changes as a result of indirect exposure to the March 11, 2004, terrorist attack. In addition, Bhat and Rangaiah (2015) found that young adults directly exposed to armed conflict in Kashmir experienced high levels of posttraumatic growth and social support.

Vazquez, Hervas, and Perez-Sales (2008) provide a review of the literature on positive effects of terrorism and show that terrorist attack may have positive consequences at individual and community levels. The authors suggest six directions for future research: (a) assess the positive effects of terror, (b) estimate the effect in the general population, (c) analyze the effects of different types of terrorism, (d) conduct more longitudinal studies on the dynamics of the changes induced by terrorist threats, (e) analyze whether some apparently positive effects could have collateral negative effects, and (f) estimate whether positive reactions generated by terrorist attacks are adaptive or somehow associated with positive health outcomes.

In this study, we explore the positive emotions of the Russian population developed as a result of a terrorist attack. The data allow us to contribute to the existing literature by addressing three of the six points mentioned above. First, we directly focus on positive reactions; second, we estimate the effect of the attack on the general population; and finally, we apply longitudinal data to study the long-term effects of terror.

Data and Method

Data

Data are obtained from the Russia Longitudinal Monitoring Survey—Higher School of Economics (RLMS-HSE).¹ RLMS-HSE is a series of nationally representative surveys designed to monitor the effects of Russian reforms on the health and economic welfare of households and individuals in the Russian Federation. These effects are measured by a variety of means including detailed monitoring of individuals’ health status and dietary intake, precise measurement of household-level expenditures and service utilization, and collection of relevant community-level data. To qualify as a quasi-experiment, the timing of the siege needs to be exogenous and largely randomly assigned in terms of the survey interviews. In this case, respondents are interviewed between October and December each year, with the particular day and month of the interview allocated randomly. Thus, the siege is clearly exogenous to the survey.

To test for the presence of post-traumatic growth among the Russian population following the Moscow Theatre Siege, we employ a measure of self-reported expectations of life in the future. This measure is obtained from individuals’ responses to the question, “Do you think that in the next 12 months you and your family will live better than today or worse?”² This variable is also scored from 1 to 5, where 1 is the highest score. In particular, the categories are as follows: (a) You will live much better, (b) You will live somewhat better, (c) Nothing will change, (d) You will live somewhat worse, and (e) You will live much worse. The translations of the question and scores are drawn from the English version of the RLMS-HSE questionnaire. For ease of interpretation and consistency with the wider literature, we reorder the responses to both questions so that 5 is the highest measure and 1 is the lowest.

We consider an unbalanced sample for two different geographic regions.³ Sample 1 includes only residents of Moscow and its surrounds, and Sample 2 includes residents of Russia excluding the Moscow region. Individual characteristics such as age, education, income, marital status, and gender are included in the analysis as control variables. Self-assessed relative income was employed as a proxy for household income due to a lack of reliable actual income data.⁴

We separate all of our samples into two groups—the first (control) group consists of individuals who, in 2002, were interviewed before the siege (i.e., were interviewed before October 23, 2002), the second (treatment) group consists of individuals who, in 2002, were interviewed after the siege (i.e., from October 24 to December 31 2002). Descriptive statistics are provided in the appendix.

Empirical Strategy

Similar to the estimation strategy employed by Metcalfe et al. (2011), we use a difference-in-differences approach. This method assumes that the Moscow theatre siege affects only the treatment (post-siege) group, which leads to a change in the expectations of life in the future of this group, and in the absence of the siege, the differences in expectations of life in the future between the treatment and control groups would be approximately the same each year. The approach then calculates the “normal” level of expectations of life in the future, which would have been associated with the treatment group if the siege had not occurred. Thus, the effect of the siege is the difference between the observed level in expectations of life in the future and the predicted “normal” level of expectations of life in the future for the treatment group.

We begin by estimating Equation 1:

\begin{array}{l} E L F_{i t} = α + β_{1} P o s t 10 | 23_{i t} + β_{2} {(Y e a r = 2002)}_{t} \\ + β_{3} [P o s t 10 | 23_{i t} * {(Y e a r = 2002)}_{t}] + \sum_{j = 4}^{k} β_{j} Z_{i t} + ε_{i t}, \end{array}

where $E L F_{i t}$ is the self-reported expectations of life in the future of individual i in time t; $P o s t 10 | 23$ is a dummy variable denoting 1 if the individual was interviewed post October 23 in 2002 and 0 otherwise; $Y e a r = 2002$ is a dummy variable representing the year of the attack; $Z_{i t}$ is vector of individual characteristics; and $ε_{i t}$ is an error term.

The parameter $β_{3}$ of Equation 1 represents the effect of the siege on expectations of life in the future of people interviewed post October 23 in 2002. In the absence of the siege, $β_{3}$ would not be statistically significantly different from zero, since $E L F_{i t}$ would have changed similarly in both the treatment and control groups in each year. Thus, the unbiased estimate of $β_{3}$ could be specified as Equation 2:

\begin{array}{l} {\hat{β}}_{3} = Δ {\bar{E L F}}_{2001 - 2002}^{p o s t 23 | 10} - Δ {\bar{E L F}}_{2001 - 2002}^{p r e 23 | 10} = \\ ({\bar{E L F}}_{2002}^{p o s t 23 | 10} - {\bar{E L F}}_{2001}^{p o s t 23 | 10}) - ({\bar{E L F}}_{2002}^{p r e 23 | 10} - {\bar{E L F}}_{2001}^{p r e 23 | 10}), \end{array}

where ${\bar{E L F}}_{2002}^{p o s t 23 | 10}$ is the mean level of self-reported expectations of life in the future of the treatment group in 2002; ${\bar{E L F}}_{2001}^{p o s t 23 | 10}$ is the mean level of self-reported expectations of life in the future of the treatment group in 2001; ${\bar{E L F}}_{2002}^{p r e 23 | 10}$ is the mean level of self-reported expectations of life in the future of the control group in 2002; and ${\bar{E L F}}_{2001}^{p r e 23 | 10}$ is the mean level of self-reported expectations of life in the future of the control group in 2001.

Results

Table 1 reports the results of the difference-in-differences model using ordinary least squares (OLS). Consistent with the literature on the measurement of subjective well-being (MacKerron, 2012), control variables such as age, gender, marital status, labor force status, being a student, level of education, and self-estimated relative income are included. The research questions that require linked macro and micro data are ones that postulate variation between the macro units either in the distributions of some of the macro variables or in the patterns of association between micro variables (Fisher, 2016). However, we were unable to obtain reliable regional-level data on gross regional product or unemployment, and the inclusion of national level gross domestic product data did not improve model results.

Table 1.

Self-Reported Expectations of Life in the Future, 2001-2002.

Expectations of Life in the Future	Sample 1Moscow Region	Sample 2Russia Without Moscow Region
Post October 23	−0.085 (0.077)	0.003 (0.026)
Year = 2002	−0.081 (0.084)	0.040** (0.019)
Post October 23 × Year = 2002	0.213** (0.101)	0.069** (0.035)
Constant	3.435*** (0.235)	3.529*** (0.082)
Controls	Yes	Yes
Observations	1,189	9,246
R-squared	.152	.190
Number of individuals	806	5,506

Note. Random effects, ordered probit random effects, and fixed effects models were also estimated, with inconsequential differences across models. All model results are available on request. Standard errors in brackets.

Significant at the 10% level, **significant at the 5% level, ***significant at the 1% level.

We can see from the interaction coefficients between “Post October 23” and “Year = 2002” reported in Table 1 that for Sample 1, the Moscow Theatre Siege had a positive and statistically significant effect on self-reported expectations of life in the future with an average treatment effect (ATE) of 0.213. For Sample 2, we also find a positive and statistically significant effect, with an ATE of 0.069.

It is important to also check the underlying trends in self-reported expectations of life in the future between the treatment and control groups across a number of years. To satisfy one of the difference-in-differences conditions, it is necessary to show that, in the absence of treatment, the differences between the treatment and control groups would have remained constant over time (Meyer, 1995). We can check whether this is the case for the siege by plotting expectations of life in the future trends for the control and treatment groups from 2000 to 2005. From Figure 1, for Sample 1, we can see that the difference between expectations of a better life in the future for the two groups is larger in all years. For Sample 2, this is also true, except for 2005, where there is a considerable divergence between the two groups. Results from this sample, therefore, should be interpreted with this in mind.

Figure 1.

Self-reported expectations of life in the future, 2000-2005.

As a test of robustness, Table 2 incorporates multiple time periods and treated groups into the analysis by estimating Equation 1 on an extended sample including respondents from the years 2000 to 2005. All estimations in Table 2 include dummy variables for interview months November and December to control for any well-being effects of the holiday season (i.e., the possibility that people feel happier around the Christmas period). As with the results reported in Table 1, sociodemographic controls are included.

Table 2.

Self-Reported Expectations of Life in the Future, 2000-2005.

Dependent Variable:	Moscow Region				Russia Without Moscow Region
Better Life	RE	FE	AR(1)	Collapsed	RE	FE	AR(1)	Collapsed
Post October 23	−0.094 (0.074)		−0.099(0.074)	−0.138* (0.074)	0.015(0.026)		0.014(0.026)	0.019(0.024)
Year = 2000	−0.182* (0.105)	−0.277* (0.152)	−0.182* (0.105)		−0.131*** (0.018)	−0.124*** (0.024)	−0.131*** (0.017)
Year = 2002	−0.094(0.073)	−0.041(0.131)	−0.105(0.072)	−0.044(0.080)	0.033** (0.0162)	0.019(0.024)	0.032** (0.016)	0.086*** (0.015)
Year = 2003	−0.018(0.078)	0.085(0.226)	−0.036(0.081)		0.008(0.017)	−0.003(0.038)	0.008(0.018)
Year = 2004	−0.142* (0.082)	0.062(0.328)	−0.158* (0.085)		−0.024(0.018)	−0.044(0.053)	−0.024(0.019)
Year = 2005	−0.113(0.095)	0.125(0.429)	−0.137(0.099)		0.017(0.019)	−0.0062(0.069)	0.018(0.019)
Post October 23 × Year = 2000	−0.020(0.127)	0.040(0.134)	−0.031(0.127)		0.014(0.034)	0.024(0.035)	0.010(0.032)
Post October 23 × Year = 2002	0.234*** (0.088)	0.223** (0.093)	0.244*** (0.086)	0.225** (0.096)	0.068** (0.031)	0.065** (0.032)	0.067** (0.030)	0.064** (0.029)
Post October 23 × Year = 2003	0.116(0.093)	0.117(0.099)	0.126(0.096)		0.070** (0.032)	0.067** (0.033)	0.071** (0.033)
Post October 23 × Year = 2004	0.035(0.098)	0.011(0.104)	0.045(0.102)		0.022(0.034)	0.007(0.035)	0.021(0.035)
Post October 23 × Year = 2005	0.145(0.114)	0.136(0.121)	0.162(0.119)		0.047(0.035)	0.047(0.036)	0.044(0.037)
Constant	3.674*** (0.200)	3.934(4.847)	3.680*** (0.197)	3.412*** (0.247)	3.627*** (0.064)	3.247*** (0.759)	3.644*** (0.065)	3.523*** (0.085)
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	2,569	2,569	2,569	1,220	23,445	23,445	23,445	9,696
R-squared		.042				.047
Number of individuals	897	897	897	817	5,781	5,781	5,781	5,616

Note. Standard errors in brackets.

Significant at the 10% level, **significant at the 5% level, ***significant at the 1% level.

RE = Random Effects, FE = Fixed Effects, AR = Autoregressive.

We also explore the possibility that the estimation of Equation 1 is subject to serial correlation, which could potentially bias the standard error of the estimate upward (Bertrand, Duflo, & Mullainathan, 2004). To account for potential serial correlation, we estimate a generalized least squares with random effects that also accounts for an AR(1) disturbance. This does not materially change our results across the two samples. Allowing only for an AR(1) disturbance in the estimation of Equation 1, however, may not be enough to counter the serial correlation problem (Metcalfe et al., 2011). Bertrand et al. (2004) propose that the solution is to ignore the time-series data when computing the standard error. Therefore, we simply average the data in the 2 years before the date of the siege and rerun Equation 1 on this averaged outcome variable and self-reported expectations of life in the future reported in 2002 in a panel of time length equal to two. Results presented in the “collapsed” columns are consistent with Table 1 for both samples. This implies that our results continue to hold even when serial correlations in the dependent variable have been taken into account.

Given the robustness of results to alternative specifications, we now focus on the type of individual most affected by the siege. Tables 3 and 4 show the results from re-estimating Equation 1 with our samples further split according to gender, age, and income.⁵ Male and younger respondents are more (positively) affected by the siege (Tables 3 and 4, Columns 1 and 3). For the Moscow sample only, poorer respondents are also more (positively) affected by the siege (Table 3, Column 5).

Table 3.

Self-Reported Expectations of Life in the Future (Sample 1—Moscow Region) 2001-2002 by Gender, Age, and Income (OLS).

Dependent Variable:	(1)	(2)	(3)	(4)	(5)	(6)
Expectations	Male	Female	Young	Old	Poor	Rich
Post October 23	−0.096(0.119)	−0.060(0.101)	−0.244** (0.120)	0.063(0.101)	−0.027(0.098)	−0.300(0.295)
Year = 2002	−0.032(0.124)	−0.119(0.112)	−0.015(0.131)	−0.099(0.109)	−0.094(0.105)	−0.218(0.328)
Post October 23 × Year = 2002	0.263* (0.152)	0.183(0.135)	0.283* (0.156)	0.147(0.133)	0.217* (0.129)	0.086(0.382)
Constant	3.377*** (0.371)	3.482*** (0.302)	2.755*** (0.171)	2.748*** (0.126)	3.797*** (0.290)	4.897*** (0.668)
Controls	Yes	Yes	Yes	Yes	Yes	Yes
Observations	465	724	436	753	811	100
R-squared	.156	.169	.135	.096	.071	.163

Note. Standard errors in brackets.

Significant at the 10% level, **Significant at the 5% level, ***Significant at the 1% level.

Table 4.

Self-Reported Expectations of Life in the Future (Sample 2—Russia Without Moscow Region) 2001-2002 by Gender, Age, and Income (OLS).

Dependent variable	(1)	(2)	(3)	(4)	(5)	(6)
Expectations	Male	Female	Young	Old	Poor	Rich
Post October 23	−0.056(0.040)	0.045(0.034)	−0.034(0.045)	0.020(0.032)	0.051(0.034)	−0.111(0.082)
Year = 2002	0.037(0.029)	0.041* (0.024)	−0.017(0.032)	0.068*** (0.023)	0.056** (0.024)	0.083(0.057)
Post October 23 × Year = 2002	0.098* (0.053)	0.051(0.046)	0.102* (0.059)	0.056(0.044)	0.0433(0.045)	0.067(0.108)
Constant	3.832*** (0.135)	3.363*** (0.103)	2.706*** (0.052)	2.301*** (0.035)	4.275*** (0.100)	4.195*** (0.228)
Controls	Yes	Yes	Yes	Yes	Yes	Yes
Observations	3,882	5,364	3,229	6,017	6,097	1,052
R-squared	.191	.186	.099	.125	.082	.087

Note. Standard errors in brackets.

Significant at the 10% level, **significant at the 5% level, ***significant at the 1% level.

Table 5 provides information on whether the effect of the attack on self-reported expectations of life in the future was most keenly felt immediately after the attack or in the weeks following the event. To do this, we split the post October 23 group into four subsamples according to the date the respondent was surveyed. We then re-estimate Equation 1.

Table 5.

Self-Reported Expectation of Life in the Future, 2001-2002 by Weeks (OLS).

Dependent Variable:Expectations	Sample 1Moscow Region	Sample 2Russia Without Moscow Region
October 24–November 6	0.0481(0.105)	0.0042(0.029)
November 7–November 20	0.035(0.110)	−0.001(0.053)
November 21–December 4	−0.234** (0.114)	−0.023(0.128)
December 5–December 31	−0.194* (0.101)	0.086(0.227)
Year = 2002	−0.081(0.084)	0.040** (0.019)
October 24–November 6 × Year = 2002	0.180(0.137)	0.060(0.038)
November 7–November 20 × Year = 2002	−0.053(0.145)	0.108(0.071)
November 21–December 4 × Year = 2002	0.334** (0.149)	0.047(0.163)
December 5–December 31 × Year = 2002	0.357*** (0.133)	0.110(0.276)
Constant	3.393*** (0.235)	3.528*** (0.082)
Controls	Yes	Yes
Observations (October 24–November 6)	224	2021
Observations (November 7–November 20)	183	488
Observations (November 21–December 4)	169	91
Observations (December 5–December 31)	241	34
Total observations	1,189	9,246
R-squared	.162	.190

Note. Standard errors in brackets.

Significant at the 10% level, **significant at the 5% level, ***significant at the 1% level.

Results presented in Table 5 show that for Sample 1 (Moscow), expectations of life in the future are higher for those interviewed in the third and fourth time periods. For Sample 2 (Russian Without Moscow region), expectations of life in the future are close to being significant at the 10% level for those interviewed in the first and second time periods (p values of .118 and .129, respectively). In unreported results we re-estimate Equation 1 with 2003 as the base year to control for any well-being effects of the holiday season. No significant changes are found, suggesting that the increase in expectations of life in the future reported in Table 5 cannot be attributed to the Christmas or New Year holidays.

Discussion

This study uses RLMS-HSE data to estimate the effect of the 2002 Moscow theatre hostage siege on self-reported expectations of life in the future. Employing a difference-in-differences approach, we find that the siege had a positive effect on expectations of life in the future for residents of Moscow and the Russian population more broadly.

These results may seem counter-intuitive. At the very least, they suggest that the well-being effects of terrorism are complex, and the net effect of a terrorism incident on well-being is not necessarily negative. This can be explained, at least in part, by the theory of posttraumatic growth—a theory that refers to the positive psychological change experienced as a result of adversity, with terrorism incidents inadvertently promoting more meaningful interpersonal relationships, new views of the self and new views of the world. This is somewhat consistent with the findings of Ai et al. (2005) who show that post the 9/11 attacks, students of U.S. universities changed their views about their purpose in life. This result may also be partly explained by the relative frequency of terrorism events in Russia. As noted by Romanov et al. (2012), once terrorism becomes part of everyday life, the negative well-being effects are reduced. Given the dramatic increase in the level of terrorism activity in recent years, it is, therefore, plausible that the effectiveness (in terms of instilling fear and hopelessness in the targeted society) of any single incident is diminished. In fact, in our case, it would appear that, in many instances, the positive changes in well-being outweigh the obvious negative effects of the Moscow theatre siege.

This is most certainly not to suggest that terrorism is a positive phenomenon. It is important to note that our sample is for the population as a whole, not for those directly affected. It is self-evident that those directly affected are harmed by a terrorism incident—we are not questioning this. Rather, these results serve to highlight the fact that individuals have a lifelong plasticity that renders them capable of dramatic recovery from significant adversity. This suggests that the primary objectives of terrorists are unlikely to be fully achieved in either the short- or long-run.

In terms of diversity, splitting the samples by gender, age, and income yields further insights. The general finding is that the association between the siege and self-reported expectations of life in the future is stronger for young, male, and poor respondents.

In terms of age, our results are consistent with Ramos and Leal (2013), who show that younger people are generally more likely to experience posttraumatic growth after a traumatizing event. These findings may be explained by the fact that younger individuals prioritize future-oriented goals and reflect hopeful and positive expectations of the future (Boyle, Stanton, Ganz, & Bower, 2017). According to Tedeschi and Calhoun (2004, p. 1), posttraumatic growth manifests itself in ways including “. . . an increased appreciation for life in general, more meaningful interpersonal relationships, an increased sense of personal strength, changed priorities, and a richer existential and spiritual life.”

With regard to gender, Akbar and Witruk (2016) show higher posttraumatic growth among women compared with men—our findings sometimes show an opposite relationship, where men, on occasion (e.g., expectations of the future for both the overall Russian sample and the Moscow sample—see Tables 3 and 4), reveal higher posttraumatic growth than women. A plausible explanation for our findings may be due to a distance variable, where women are more likely to be psychologically affected by an event when someone they know (e.g., family member) is involved. Conversely, when an event occurs, but the female respondent does not know anyone involved, then her psychological state is less affected. This latter scenario has the potential to manifest lower levels of posttraumatic growth (Akbar & Witruk, 2016). The results also could be partially explained by the fact that women are more likely than men to develop negative emotions such as depression or posttraumatic stress disorder (Galea et al., 2002). Our results are consistent with Metcalfe et al. (2011), who show that females and older people experienced a decrease in life satisfaction after the 9/11 terrorist event. In addition, there is some speculation in the literature that terrorism has generally been conceptualized as a masculine-dominated phenomena such that females do not identify as strongly as their male counterparts with the consequences of terrorist acts (Grisard, 2014).

With respect to socioeconomic status, for poorer respondents, we find a weakly positive association between the Moscow siege and expectations of life in the future. However, the only statistically significant results are for Moscow (Table 3). This may be explained by the poor perceiving the attack to be focused on the established elite, as most of the hostages in the Moscow theatre siege were from higher socioeconomic backgrounds.

When we further disaggregate the results into discrete time periods (Table 5), we find a delayed response to the siege. Specifically, for the Moscow sample, the strongest positive association appears 1 to 2 months after the event. There are two plausible explanations for this. First, it might take time for individuals to process the event and for posttraumatic growth to develop. Second, individuals may perceive the risk of future attacks to be lower as time passes. An alternative explanation is that this is a seasonal effect, whereby individuals reflect positively on their life and future plans during the Christmas and New Year holiday season. As discussed above, however, this argument can be discounted as we examine responses from subsequent years and find no such seasonal effect.

We suggest that the use of self-reported measures of well-being is a promising means for increasing our understanding of the costs of terrorism. Well-being, however, is best understood as a multifaceted phenomenon that can be assessed by measuring a wide array of subjective and objective constructs. Future research may address the effect of terrorism on other domains of well-being not explored in this study such as happiness, positive emotion, engagement, meaning and purpose, relationships and social support, and accomplishment and competence (Forgeard, Jayawickreme, Kern, & Seligman, 2011). Further, much of the current literature focusses on terrorist events that occur in developed countries. A useful exercise may be to test whether our findings can be replicated in developing countries where most of the world’s terrorist attacks take place, and societal norms, context, and culture are likely to differ.

Footnotes

Appendix

Descriptive Statistics.

Variable	Sample 1Moscow Region			Sample 2Russia Without Moscow Region
Variable	All	Pre Oct 23	Post Oct 23	All	Pre Oct 23	Post Oct 23
Observations	1,189	485	817	9,246	6,612	2,634
Better life	3.29	3.23	3.32	3.12	3.10	3.17**
	[3.24, 3.34]	[3.13, 3.33]	[3.27, 3.38]	[3.1, 3.14]	[3.08, 3.12]	[3.14, 3.2]
Age	44.35	45.47	43.84	44.57	45.10	43.22**
	[43.28, 45.42]	[43.49, 47.45]	[42.56, 45.11]	[44.18, 44.95]	[44.64, 45.57]	[42.54, 43.91]
Male (%)	39.11	40.59	38.43	41.99	41.17	44.04**
	[36.33, 41.89]	[35.58, 45.60]	[35.09, 41.78]	[40.98, 42.99]	[39.98, 42.35]	[42.14, 45.94]
Single (%)	21.45	24.19	20.20	20.81	20.70	21.07
	[19.11, 23.78]	[19.82, 28.57]	[17.44, 22.95]	[19.98, 21.64]	[19.73, 21.68]	[19.51, 22.63]
Divorced (%)	12.45	12.10	12.61	6.68	6.59	6.91
	[10.57, 14.33]	[8.77, 15.43]	[10.33, 14.89]	[6.17, 7.19]	[6, 7.19]	[5.94, 7.88]
Widowed (%)	11.77	11.29	12.00	13.35	13.99	11.73**
	[9.94, 13.61]	[8.06, 14.52]	[9.76, 14.23]	[12.65, 14.04]	[13.15, 14.83]	[10.5, 12.96]
Unemployed (%)	43.31	46.51	41.86	53.64	55.73	48.41**
	[40.49, 46.13]	[41.41, 51.60]	[38.47, 45.25]	[52.63, 54.66]	[54.53, 56.93]	[46.5, 50.32]
Student (%)	9.84	9.95	9.79	11.41	10.84	12.83**
	[8.14, 11.54]	[6.89, 13]	[7.75, 11.83]	[10.76, 12.06]	[10.09, 11.59]	[11.55, 14.11]
University degree (%)	26.58	26.08	26.81	15.44	13.69	19.86**
	[24.06, 29.09]	[21.59, 30.56]	[23.76, 29.85]	[14.71, 16.18]	[12.86, 14.52]	[18.33, 21.38]
Self-estimated income	3.75	3.62	3.80**	3.83	3.82	3.88
	[3.67, 3.82]	[3.48, 3.77]	[3.71, 3.89]	[3.8, 30.86]	[3.78, 3.85]	[3.82, 3.93]

Note. 95% confidence intervals in brackets.

Pre and Post October 23 subsamples are statistically different from each other at the 5% level.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Margarita Vorsina is a doctoral student in the department of Accounting, Finance and Economics, Griffith University, Australia. Her thesis applies economic methods to estimate reasons for and consequences of terrorism. In particular, Margarita is examining (a) the association between ethnic inequality and terrorism, (b) the effect of terrorism on life satisfaction, and (c) a population’s willingness-to-pay for a reduction in terrorism. Her interest lies in economic analysis of crime, public choice models, and cost–benefit analysis for crime-reduction programs.

Matthew Manning is an applied micro-economist who focuses predominantly on the economics of crime and enforcement. His research involves using economic methods for measuring outcomes associated with situational and developmental crime-prevention programs and policies. He also adapts economic methods for analysing complex problems for the development of better policy. Over the last 10 years, he has conducted a number of economic analyses (e.g. cost–benefit analysis) for government and nongovernment organizations. He has published in areas such as juvenile justice, crime prevention (e.g., situational and developmental/life-course prevention), drug and alcohol prevention, police legitimacy, and well-being/life satisfaction.

Christopher M. Fleming is an associate professor and MBA Director at Griffith Business School, a founding member of the Griffith Centre for Sustainable Enterprise and a member of Griffith University’s Cities Research Institute. An applied micro-economist with teaching, consulting, and public policy experience, his research and consulting interests include social and economic project/program evaluation, natural resource and environmental economics, economic development, the economic determinants of subjective well-being, the economics of crime, and the sustainable management of natural resources.

Christine Smith is a professor of economics at Griffith University. She has a PhD and masters from Cornell University, and masters and bachelor degrees from University of Queensland. She is the author (or coauthor) or editor of seven books as well as numerous book chapters and journal articles in the areas of regional science, economic growth, and regional development, peace studies and conflict management, evaluation of government programs, and crime prevention. She has acted as an advisor to federal and state governments and ministers in Australia as well as to private sector organizations and the U.S. National Academy of Science.

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