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The implication of extreme events onpolicy responsesUrs Steiner Brandt aa Department of Business and Environmental Economics ,University of Southern Denmark , Esbjerg , DenmarkPublished online: 28 May 2013.

To cite this article: Journal of Risk Research (2013): The implication of extreme events on policyresponses, Journal of Risk Research, DOI: 10.1080/13669877.2013.794151

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The implication of extreme events on policy responses

Urs Steiner Brandt*

Department of Business and Environmental Economics, University of Southern Denmark,Esbjerg, Denmark

(Received 26 March 2012; final version received 3 April 2013)

This paper considers a situation where a real risk exists that requiresprecautions, but the public mostly experiences the risk through infrequentlyoccurring extreme events; this type of risk includes risk from climate change,international terrorism, natural calamities or financial crises. The analysis showsthat if a risk-mitigating policy is based on the perceived riskiness of that risk, itwill call for disproportionate responses (compared to what the ‘real’ risk sug-gests) by either under- or over-investing in risk-reducing policies, depending onthe characteristics of the problem, implying significant volatility in the policyresponse. This type of response provides at least three challenges to society:policy cycles where implementation lags behind the actual change in risk, alock-in to inefficient technologies and additional costs. Finally, this paperaddresses the question of how the above-mentioned challenges can be managedthrough proper risk communication.

Keywords: risk perception; climate change adaptation; comparative risk

1. Introduction

In the wake of the incident at the Fukushima nuclear power plant in 2011, a nuclearpower security expert concluded that the incident effectively showed how securenuclear energy actually is. The incident involved a major earthquake and an unprec-edentedly high tsunami, and yet it was not severe.1 For a nuclear sceptic, however,this incident provides additional proof that nuclear power is dangerous. Many indi-viduals, regardless of the expert testimony, feel increasingly uncomfortable withnuclear power. In several countries, the incident affected decisions on the future ofnuclear power policy (e.g. in Germany and Switzerland, where the latter reacted tothe Japanese disaster by suspending plans to build and replace nuclear plants).2 Thisevent is, however, not a unique example of an extreme event having real policyimplications: the 9/11 incident triggered major changes in US foreign policy andincreased the public fear of terrorism in many areas of the world. In the aftermathof 9/11, tremendous amounts of additional precautions and resources were devotedto mitigate the threat of terrorism (Enders and Sandler 2006a; Sunstein 2006).

The present work focuses on concerns where the riskiness of the underlyingproblem is visible to the public because of the occurrence of extreme events.3 Forsuch problems, this paper seeks to discover the consequences of allowing the public

*Email: usb@sam.sdu.dk

Journal of Risk Research, 2013http://dx.doi.org/10.1080/13669877.2013.794151

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perception of a risk to influence decisions about the resource allocation for reducingthat risk.

An extreme event is a low-probability, high-impact event. Extreme events can,more generally, be defined by maxima/minima, magnitude, rarity and/or impact/losses. E.g. for climate change, IPCC (2012) defines an extreme climate event as‘the occurrence of a value of a weather or climate variable above (or below) athreshold value near the upper (or lower) ends of the range of observed values ofthe variable’ (IPCC 2012, 3). For most types of events, the likelihood and the size/impact are negatively correlated (e.g. of the 100 terror attacks with highest numberof fatalities, only 17 had a death toll of over 200, 8 of over 300 and 1 of over 510,which is the 9/11 attack with 2993 death, see Johnson 2013). For the purpose ofthis paper, an extreme event is defined as one that significantly changes public per-ception over a period of time.

A central theme of the present research is that the level of resources spent toreduce a specific risk is at least partially shaped by the public’s perception of thecurrent risk. According to Salanié and Treich (2009) and Wagner and Zenkhauser(2012), the risk regulators typically respond to the citizens’ beliefs. More generally,for many political issues, it is essential that the (affected) public support the pro-posed project, which Heaney (1993) calls the socio-political feasibility test. Coenen(2010) identifies several perspectives through which a policy-maker can incorporatethe information possessed by the relevant groups, thereby making competent deci-sions (and, for the purposes of this paper, the policy-maker can decide if and howto include citizens’ beliefs). According to the above-mentioned author, the pluralistapproach appears to be the most appropriate for describing risk management poli-cies on the governmental/state level.

The idea of the current paper is related to Salanié and Treich (2009), who ana-lyse two polar cases of how a policy-maker could respond to citizens’ beliefs: thepopulist approach to risk regulation, where all citizens’ beliefs are important, and apaternalistic approach, where the decision-maker is assumed to know what is goodfor the citizens better than they do (analogous to the managerial perspective). Theapproach adopted in this work is more general, in that it considers the policies tobe determined by both the publicly perceived risk and a scientific, evidence-basedestimate of the risk.

The second observation that is employed in the analysis is that the public’s per-ceived risk is very sensitive to the occurrence of extreme events that can be relatedto a specific risk. The psychological mechanism known as the availability heuristicstates that if an extreme event occurs, the availability bias leads individuals to tem-porarily overvalue the threat from the risk and thereby take temporarily excessiveprecautions (Tversky and Kahneman 1973). Recent disasters or heavy media cover-age are likely to ‘distort’ perceptions of risk (Siegrist, Gutscher, and Earle 2005).However, if relevant events are not available, the unavailability bias will predomi-nate, leading to inaction in taking the necessary precautions.4 Burns, Peters, andSlovac (2012) conducted a time series study on how public risk perception respondsto the current economic crisis. These authors detected a dynamic pattern where riskperception first responds very quickly but then peaks and decreases, despite anongoing crisis. According to the psychometric paradigm (e.g. see Slovic, Fischhoff,and Lichtenstein 1982), not all events will create the same ‘availability.5 Multivari-ate factor analysis techniques reveal that two factors dominate: dread anduncertainty (Slovic 1987). In the application section of this paper, these results are

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used to argue that for climate change, society is likely to be underprotecting itselfdue to the lack of availability of the extreme events that trigger the above factors,while for terror, there will be a tendency toward overprotection. For both problems,because risk-reducing policy measures are assumed to depend on both public per-ceptions and scientific estimates of the prevailing risk, if the citizens’ perceptionsare affected by extreme events, resource allocation will tend to be volatile.

The final observation for the analysis in this paper is a significant divergencebetween objective (scientifically based) risk analysis and subjective (emotionallyand affect based) risk perception (Slovic and Weber 2002; Slovic et al. 2004).6 Spe-cifically, the emotionally based system provides an explanation for the large fearsand emotional reactions that we have towards media-transmitted pictures of terror-ism and how this reaction affects both our revised assessment of present risk(threat) and our demand for immediate action in the face of the perceived increasein the threat.

Combining the above observations, it can be concluded that a policy aimed atcontrolling risks to society is likely to be affected by perceived risk. Perceived risk,in turn, is affected not solely by an analytical estimation of the risk but also to avarying degree by its availability, which is determined by the occurrence of extremeevents that can be related to that risk. Because the perceived risk does not necessar-ily match the true risk faced by the public, the consequence will be an investmentin risk-reducing measures that do not reflect the optimal investment given the actualrisk.

The analysis reveals three areas where these types of policy procedures implychallenges. For policies that are easily adjustable, risk-reducing measures (might)exhibit cycles where the policy implementation lags behind the changes in risk (e.g.in counterterrorism policies, see Feichtinger and Novak 2008; Faria 2003). Forpolices that are not easily adjustable, e.g. due to high sunk costs, hysteresis andpath dependencies might result in a lock-in to inefficient technologies (Acemogluet al. 2012) or in periods with high vulnerability if the polices cannot be adjustedrapidly enough. Finally, the high volatility in public risk perceptions relative tomore evidence-based risk estimates produces additional costs, e.g. if large invest-ments in one period are more expensive than the same investment divided over twoor more periods.

The paper is organised as follows. Following this introduction, a model is pre-sented that formalises how extreme events affect public policy. In Section 3, themodel is applied to terrorism and climate change and the conditions under whichthese effects appear in counterterrorism measures and climate policy are discussed.Section 4 builds on the preceding sections to propose the appropriate risk communi-cation strategies. The last section concludes the paper.

2. The model

Consider a society (e.g. a country) that is vulnerable to a risk-generating natural orhuman-induced problem (climate change, terrorism, a financial crisis, etc.). The coun-try has the means to reduce its vulnerability to the given problem j by invoking/employing a risk-reducing policy. The level of this policy is measured by q j. Thispolicy variable is treated as a one-dimensional policy measure, although risk-reducingpolicies consist of a variety of possible policy initiatives. q j is here interpreted as theincrease in the policy measures necessary to reduce the vulnerability (the risk from

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the problem) by q j units. Moreover, it is assumed that a country always uses the pol-icy that is most effective first, effectiveness being measured by the most effect per unitcost. It is assumed that costs are convex increasing in q j.

The population is negatively affected by the expected damage that the problemin question might cause. The population in this country has preferences between theexpected damage from the problem and the costs of implementing the risk-reducingpolicies.

Let the (identical) individuals be equipped with the following utility function:

u ¼ uðED q jð Þ;C qjð ÞÞ ð1Þ

Assume further that u′ED < 0, u′′ = 0 and u′c < 0, u′′c = 0. (The linearity assump-tion is only for simplicity.) Let the preferences be unaffected by the changes in per-ceived damages.

If the policy-maker’s goal is to implement the policy to maximise the citizens’utility (as described by (1)), he or she should select the level of q j that maximises(1). The solution implicitly defines qj ¼ qPj, the optimal level of risk-reducing pol-icy, for a given level of risk perceived by the public regarding the risk generatingissue, only taking the citizens’ preferences into account.

The first-order condition for utility maximisation by maximising (1) with respectto q j yields the following:

qpj :u0Cu0ED

¼ �ED0q j

C0q j

ð2Þ

Given (2), it is possible to derive the optimal level of protection (risk-reducingpolicies). The implication of higher marginal damage (an increase in ED0

q j ) is thatq j needs to be increased to restore the optimality condition. Intuitively, when themarginal expected damage increases (and when the perceived risk increases), then itis optimal (from the perspective of maximising public utility) to employ more q j.Essentially, the public is willing to pay more (in terms of reduced consumption) tohave the risk reduced.

The model presented here is intended to incorporate both the difference in riskperception between the (relevant) scientists and the public and the changes in per-ceived risk as described above. Consider that the scientists produce the best esti-mate of the current risk that a given problem presents, based on the bestinformation available. Such an estimate is denoted EBG

t (The exact nature of suchan estimate is not considered here.) Now, at time t, the best estimate is normalised

to zero, EBGjt ¼ 0, and let E

PRjt 2 ½�1; 1� be the public perceived risk such that a

higher EPRjt implies a greater perceived risk (the scientific and public perceptions of

the risk align when EBGjt ¼ E

PRjt ¼ 0). An example of how E

PRjt develops after a

single extreme event (EE j) is depicted in Figure 1.The notion here is that while E

BGjt is unaffected by the occurrence of an extreme

event (or affected to the extent that it contains information that will alter the bestestimate by, e.g. applying a Bayesian approach), the public perception of the risk ofthe problem underlying the extreme event (or perceived to be underlying) isaffected. Formally, allow

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EPRjt ¼ E

PRjt ðI jt ; I jt�1; � � � ; I jt�kÞ ð3Þ

I jt is an index of the number and strength of the extreme events related to (orconsidered to be related to) problem j in period t. If no events occur in period t,then I jt ¼ 0 . As noted in the literature, public perception reacts to extreme eventsto a greater extent than evidence-based, scientific estimates; in this model, thisimplies the following:

dEPRjt

dI jt

�����

�����[

dEBGjt

dI jt

�����

�����

ð4Þ

After an extreme event related to problem j (EE j), people tend to ‘over-react’,while after periods with no experiences of the risk generating issue, people tend tounderestimate the probability, as indicated in Figure 1.7 The perceived risk is trans-lated into expected damage according to

ED jt ¼ ED j

t ðEPRjt Þ ð5Þ

with @ED jt

@EPRJt

[0.

Combining (5) with (2), it follows that changes in EPRjt translate into

(monotonic) changes in qBRjt . In other words, the variation in E

PRjt is reflected in a

(monotonic transformed) variation in qBRjt .

The pluralist approach is used here to integrate the perspectives of both thepublic and the scientists. Therefore, the decision-maker selects the level of riskmitigation according to the following:

q jt ¼ qj

t ðEBGjt ;E

PRjt Þ ð6Þ

with @q jt

@RP jt[0 and @q j

t

@BG jt[0.

The policy-maker still maximises (1) but is assumed to consider both the inputof the scientific community and the risk perceived by the population; in particular,the scientific and public judgments of the expected risk presented by problem j.The relative importance of the risk perceived by the public and the best estimate ofthe scientific community depends on many factors, e.g. the political position of the

Figure 1. A possible evolution of the perceived risk after extreme events.

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government. Different governments might assign different weights to these twotypes of policy influences. Finally, (4–6) result in

dqpjt

dI jt[0 ð7Þ

When an extreme event occurs, the decision-maker responds by increasing theintensity of the risk-reducing policy, even in situations where E

BGjt is unaffected by

the occurrence of the extreme event.A linear version of (6), the politically optimal level of risk regulation for issue j,

can be described as

qjt ¼ c j�qPRj

t þ ð1� c jÞ�qBGjt ð8Þ

Here, 06 γ j6 1 measures the relative weight of the public perceptions, and qBGjt

is the chosen policy if EPRjt ¼ E

BGjt . The implication of this policy is depicted in

Figure 2. Here, it is shown that given (2), in cases where the decision-makers basetheir risk estimate on a lower value that the scientific evidence suggests, the societyis undersecured; if they conversely base their estimate on a higher value, then thesociety is oversecured.

The final analysis in this paper is to determine how an extreme event related toproblem j at time t (EE j

t ) affects the selection of a risk-reducing policy. As the liter-ature reports, the public’s perception is much more volatile than the scientific, evi-dence-based estimates. This tendency is captured in the model by the followingexpression (which follows directly from (4)):8

dqPRjt

dI jt

�����

�����[

dqBGjt

dI jt

�����

�����

ð9Þ

Although our model is mostly static, dynamics are introduced through (3). Thedynamics described in (3) and their influence on policy decisions is best presentedin figures. Consider that, on average, the scientists’ best estimate and the public’sperception are the same but, as specified in (9), the public’s perception is affectedby individual events to a greater extent than the scientists’. Given (8), the chosenpolicy lies somewhere between q

BGjt and q

PRjt , depending on γj. The temporary

overreaction followed by an underreaction to the perceived risk relative to the best

Figure 2. How the level of security relates to the risk perception of the public.

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estimates translates into a similar temporary overallocation followed by an underal-location of resources to be applied to risk-reducing policies.

This relationship is the basis for the analysis that underlies Figure 3: when citi-zens experience an extreme event that triggers an increase in the perceived risk ofthe problem that generated the extreme event, the citizens’ estimates of the expecteddamage increase. As a consequence, the effect of the risk-reducing policiesincreases (on the margin), which can be observed from (6). An interpretation of (6)is that when an extreme event occurs, the threat of this problem becomes available(through the availability heuristic) and is translated into perceived fear, thus creatinga willingness to sacrifice economic well-being (or in regard to terror, civil liberties,Enders and Sandler 2006a).

The consequences of basing risk-regulation policy in part on the public percep-tion of risk are the cyclic nature of investments in risk-reducing policies shown inFigure 3: periods with overprotection are followed by periods with underprotection.As noted in Salanié and Treich (2009), this populist policy increases well-being butoffers non-optimal protection against the underlying risk from the problem at hand.

In the next section, two case studies will highlight the shortcomings/problematicnature of these policies compared to a situation where less emphasis is placed onpublic perceptions (or at least the volatile component of the public’s perception).Generally, when policies regarding risk-reducing investments are based on bothpublic perceptions and scientific evidence, the policy might be more costly, result inshort-term decisions that have unintended long-term effects or result in underprotec-tion precisely when protection is most needed. The next section provides examplesof these situations.

3. Applying the model: case studies

This section is devoted to applying the model from Section 2 to analyse the policyresponse on two major risk-generating problems: climate change and terrorism.Although the two problems are very dissimilar, a common feature is that the poten-tial threats stem from the extreme events that these two problems generate, eitherextreme weather events or terror attacks.

The polls on climate change and terror in both Europe and the USA show thatthe public on average finds these problems to be serious. Gallup – US (2010) findsthat in 2010, 79% of respondents find terrorism to be a serious threat to the USfuture well-being, thereby being the most worrying threat. For the environment,including global warming, 51% of respondents perceived it to be a threat to futurewell-being, being number 8 on the list. For Europe, the EU conducted a large sur-vey on the public perception of risks in the EU (2009). To the question asked about‘which of the following do you consider to be the most serious problem currently

Figure 3. Dynamics of risk policy decisions around extreme events.

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facing the world as a whole’, 62% of the respondents identified climate change(second on the list) while 53% found international terrorism to be a serious problem(third on the list).

Terror and climate change also have, however, different characteristics, which inparticular affect the public perception of the risk stemming from these problems.The comparison of the problems will be based on the characteristics of the prob-lems and the way that extreme events are understood to be signals about the true‘riskiness’ of the problem.

3.1. Climate change

Climate change is a global environmental problem caused primarily by the burningof fossil fuels, driven by human needs for energy; however, it is also caused byland use changes; in particular, deforestation.

An increase in the global average temperature is expected, and as a conse-quence, the magnitude and likelihood of extreme events is likely to increase.According to IPCC (2012), a changing climate leads to likely changes in the fre-quency, intensity, spatial extent, duration and timing of extreme weather and climateevents and can result in unprecedented extreme weather and climate events. Suchextreme events include intensification in droughts, flooding and the frequency ofheavy precipitation. Due to an increase in the mean sea level, an upward trend inextreme coastal high water is very likely.9 As a direct consequence, extreme eventswill have a greater impact on sectors with closer links to the climate, such as water,agriculture and food security, forestry, health and tourism.

The difficulty in attributing a single extreme event to climate change is thatclimatic extreme events are a natural phenomenon. IPCC (2012) argues that thesignals from projected changes in extreme climate events are relatively small forthe coming two to three decades compared to the natural climate variability overthis time frame. Although statistical methods exist that argue about the probabil-ity that a single events is ‘caused’ by climate change (Peterson, Stott, and Her-ring 2012), it is a well-observed phenomenon that people have difficulty inunderstanding low probabilities (Keller, Siegrist, and Gutscher 2006) and oftenpredict the frequency of an event based on the availability of the event (accord-ing to the availability heuristics, see, e.g. Sunstein and Zeckhauser 2011). Morespecifically, over time, the signals are assessed to become clearer indicators of achanging climate.10

Climate change is a so-called stock pollution problem. Greenhouse gases slowlyaccumulate in the atmosphere due to human-caused releases of primarily CO2 andmethane. Due to the slow warming of oceans, there is a considerable delay fromthe time that emissions accrue until the effect on the climate can be observed (IPCC2007).

This delay has serious implications for the public perception of climate change.As a natural consequence, basing the estimates of riskiness on extreme events sys-tematically underestimates the threat of climate change (see also Weber 2010).Given the characteristics of the climate change problem, the public’s perception ofthe risks of climate change is low because, as discussed in the introduction, the lackof availability implies inaction (Weber 2010). As forcefully noted by Sunstein(2006), thus far, no salient event has heighted public concern. In fact, most peoplelack personal experiences that would make the relevant risks appear immediate or

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real as opposed to speculative and hypothetical; hence, climate change does not cur-rently trigger strong emotions.

PCAP (2012) presents the result of polls performed by seven poll institutes overthe period 2006–2012 regarding the question: is global warming occurring? By sim-ple visual inspections, up to 2010 all polls uniformly show a decreasing trend inthe percentage of those who believe that global warming is happening, while from2010 on the trend is reversed and all polls show an increasing trend. Moreover,over the period 2006–2012, there was no overall increase in the percentage andfinally, in 2012 50–80% believed that global warming is occurring. Several impor-tant lessons can be drawn from these percentages. First, public perception has beenvolatile even though no event or new knowledge from a scientific point of viewsupports the trends in the public perception. Secondly, according to Anderegg et al.(2010), the percentage of climate experts that support the hypothesis that climatechange is anthropocentrically induced is significantly higher than the percentage ofthe public that believes that global warming is occurring.11

How would a climate policy based only on scientific knowledge develop overtime? This question has been investigated by Nordhaus (2010, 2011). For three rele-vant policy scenarios, Nordhaus calculates the optimal trajectory of a carbon priceover time (a uniform tax equal to the carbon price would then be an appropriatechoice of climate policy). For all scenarios, the carbon price is (continuously)increasing up to 2085.12

As a consequence, it can be expected that EDCCt is very low; extreme events

related to climate change are generally local and very temporary at present. Whenthis information is placed in the model described in Section 2, the resources that asociety spends to combat the risks associated with climate change can be repre-sented graphically as in Figure 4. This figure depicts how the average awareness(publically perceived risk) is lower than the best estimates except after extremeevents. On average, this trend in awareness results in a sub-optimal level of invest-ment in climate-related polices, but a temporary large change might be expected.13

What is the possible consequence of a situation such as that depicted inFigure 4? One means of limiting climate change is to reduce emissions, primarilyCO2 (countries have national reduction plans, despite the fact that the problemneeds to be addressed globally), by reducing the CO2 content in energy consump-tion and from traffic.14 Such policies can include transitioning from coal-firedpower plants to renewable energy production. A distinctive feature of investmentsin energy systems is the large up-front investment costs and the long lives of theinvestments (Stern 2006). These investments are, moreover, often to a large extent‘sunk’. The expansion of coal-fired power plants or the construction of a powerplant or large off-shore wind farm will exhibit economic, if not technological, path

Figure 4. A possible dynamic of policy decisions for controlling risks related to climatechange.

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dependence, being either extremely expensive or technologically complex to adjustsignificantly within several years or even decades.

This tendency is reinforced by the presence of technological ‘lock-in’. Acemogluet al. (2012) analyse the presence of path-dependence in the area of technologicaldevelopment. The article demonstrates that if a company produces an innovation ina relatively dirty technology, it will also find it more profitable to do so in the subse-quent periods and will respond less to price effects (e.g. taxes or quota regulationsaimed at providing a price signal for more innovation in clean technologies). Theconclusion is that this technological lock-in leads to technological path-dependence,which complicates the possibilities for correcting a temporary, non-optimal climatepolicy.

Although the climate problem needs to be addressed globally on a country level,security can be increased by investing in adaptation measures such as increasing theheight of dams. It can be expected that investment over a series of periods is lesscostly than the same amount of investment in a single period. The implication isthat if a policy based solely on the scientific evidence suggests that climate changewill materialise slowly but at an accelerating pace, the optimal investment path overtime will be one of smoothly increasing adaptation levels over time.15 However,investments that follow this optimal path are distorted by the risk perceptions of thepublic. In periods when there is a series of extreme events, public preferences shifttowards increased protection despite the lack of scientific evidence to suggest theneed for an increase in adaptations. These increased costs can be considered to bethe costs of risk management (Brandt 2012).

3.2. Terror

A uniformly agreed-upon definition of terror does not exist. The UN defines terroras ‘criminal acts, including against civilians, committed with the intent to causedeath or serious bodily injury, or taking of hostages, with the purpose to provoke astate of terror in the general public or in a group of persons or particular persons,intimidate a population or compel a government or an international organisation todo or to abstain from doing any act’ (UN 2004).16 Major recent terror attacks inNew York, London, Madrid and Mumbai fall into this category.17 Terror attacks areinfrequent and mostly unpredictable events, and they quite naturally fall into thecategory of extreme events.

What is the likely impact of terror attacks on risk perception? First of all, terroris intentional because its most frequent main characteristic is to deliberately andintentionally create fear. According to the psychometric paradigm, intentionally isthe main driving force in perceiving the risk as a dread risk.18 Moreover, terrorattacks are easily understood signals because terror by its very nature is intentionaland generally designed to spread and maximise fear among a much larger groupthan that directly affected by the attack. Finally, the signals are often carried byforceful images that are repeatedly shown in the mass media (e.g. the smoking twintowers in Manhattan), which, therefore, according to the availability heuristicshypothesis, elevates the immediate fear and prolongs the state of fear.

These suggestions are supported by observations. A time series study conductedby Gallup (presented in Block-Elkon 2011) includes both major terror events andmediated threats, for example, after 9/11,after the invasion of Iraq (beginning inMarch 2003), the London terror attack (July 2005) and the 10 year ‘anniversary’ of

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9/11. On all of these occasions, the perceived risk of terror increased significantly.Not surprisingly, terrorism possesses most of the characteristics that increase percep-tions of fear. Therefore, although we may not directly experience suffering from aterror attack, the underlying fear (often mediated though the press) is pervasive.19

The second consequence of being intentional is that terror is unpredictable anddifficult to prevent. The terror prevention measures that are employed create what isknown as a ‘weakest link public good’; that is, the terrorist organisation can exam-ine a country’s defence strategy and evaluate the most effective way to successfullylaunch a terror attack (Sandler 1997; Arce, Kovenock, and Roberson 2012, and ref-erences herein). These measures presume that every segment of society can be pro-tected equally, which appears to be unrealistic particularly because the risk acountry faces is unknown (Beck 2006). Another characteristic of terror preventionis, as noted by Arce, Kovenock, and Roberson (2012), that ‘For the target govern-ment, success is defined in terms of security against all possible attacks; whereasfor terrorists one success is often enough to alter the political landscape, airways,etc.’

Is it possible to describe (predict) how experts will judge the threat of terrorafter a major terror attack? For various reasons, the information that a terror attackcarries and its consequences for future attacks is not straightforward. The insightsof the above-mentioned papers suggest the following:

• Major terror attacks might provide new information about threats unknownbeforehand or the capabilities of known groups that were underestimated.

• A terror organisation also exposes itself, and anti-terror measures and intelli-gence can be directed against that group.

• By its very nature, a terror attack costs many resources to launch. It also takestime to recruit, train and plan terror attacks, and the terror organisationrequires time to find the weakest link in the defences.

• A rational terrorist organisation will not find it optimal to invest in anotherterror attack in the short term. After periods with no terror activities, terrorismpreparedness weakens, while the terror organisation requires time to find theweakest link in the defences.

Because of the complex interaction between the above factors, it is not possibleto provide a uniform formula for how the experts are likely to re-evaluate the threatof terrorism after an attack, nor how experts are likely to assess the risk of terror insubsequent years. However, Figure 5 intends to show two likely possibilities. Thefirst extreme event (EE1) implies that both experts and the public perceive the riskfrom terror to be more imminent. For the expert, the attack can change the estimatesof the capabilities of a specific terror organisation or movement (a situation not

Figure 5. Possible dynamics of policy decisions for controlling the risks related to terror.

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unlike 9/11).20 Over time, public perception falls, as explained by the availabilityheuristics. For the experts, as new measures are put in place and a new understand-ing of the threats develops, the perceived risk might fall, but as already discussed,rational terror originations could regroup and consider new targets.

However, the figure indicates that the overall resources spent to combat terror arefalling over time, while the threat is increasing. The logic of this, which is denotedas a terror cycle, has been described in several papers. Enders and Sandler (2006a)argue that after a terrorist attack, public pressure results in more safeguards, implyingthat there is less terror followed by less pressure and fewer safeguards and, therefore,a higher probability of another terror attack. Feichtinger et al. (2001) analyse amodel of terror cycles in the context of the tourism industry. As a country invests intourism, it attracts an increasing number of tourists, making the industry a morelikely target for terrorism, which scares away tourists, which then reduces the interestof terrorists. As terrorist incidents decline, the government again begins to invest intourism, and the cycle continues. Feichtinger and Novak (2008) observe cyclicalbehaviour in the sense that when counterterrorism policies continue to increase, thecosts of launching terror attacks also increase so that terror attacks decline; con-versely, when counterterrorism policies are reduced again (due to their limited bene-fits), terror activity increases due to the now decreased cost of this activity. There isa lag in the response through the counterterrorism policies, which the authors attri-bute to the government’s reaction to terrorist activities.21

In the model presented in the current paper, these effects are reinforced by theway in which public risk perception enters the policy decision-making process, cre-ating even longer lags between terror activity and the proper investments in risk-reducing policies. In Figure 6, this type of situation is shown.

In the model presented in the current paper, these effects are reinforced by theway in which public risk perception enters the policy decision-making process, cre-ating even longer lags between terror activity and the proper investments in risk-reducing policies. In Figure 6, this type of situation is shown. After the secondextreme event, the experts perceive that the risk is falling because they know thatthe terror organisation has exhausted its resources or that the organisation has beenexposed and even neutralised. Still, the public perceived risk can be expected toincrease due to the renewed availability of the terror threat.

The main conclusion of this analysis of the perceived threat of terror is that ifpolicy is focused too heavily on public perceptions and public perceptions are pri-marily based on experience as described in Section 2, then the unfortunate situationoccurs that when security is most needed, it is the most difficult to implement. Thissituation is portrayed in Figures 5 and 6.

Figure 6. An example of a ‘terror cycle’.

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4. Risk communication

A natural means of aligning the risk assessments of the public and the scientificcommunity is through risk communication. As noted by Smillie and Blissett (2010),communicating risk is complex and involves different types of communicators, fromscientists, the media, government agencies, industry and consumer groups, each ofwhich has its own agendas to pursue. Traditionally, risk communication focuses onproviding information to the public. In Figure 7, the possible information exchangechannels in risk communication are presented.

The solid line reflects that the primary communication is between the risk com-municator and the public, with the potential for feedback from the public. This viewof risk communication is expressed by the WHO (2009), for example, where riskcommunication is defined as an interactive process of the exchange of informationand opinions between those who assess risk (the relevant scientists), risk managers(politicians and businesses) and other interested parties. It is a process that will cre-ate a mutual understanding between the governing and the regulated to align inter-ests and goals.

However, the flow of information is complex. Macnaghten and Jacobs (1997)(in the context of sustainability) state that a widely used method of information pro-vision uses indicators as tools for communication.22 Not all indicators communicateequally well, however. These authors identify two types of indicators: cold indica-tors, which serve the managerial purpose of technological accuracy, and hot indica-tors, which resonate with the public because they strike an emotive chord in termsof recognition and concern. However, using hot indicators will only be useful if therisk perception does not sufficiently reflect the ‘real’ risk. Here, the scientific com-munity is the primary information provider (and also the risk communicator).

We adhere to the notion that, in essence, the government is the risk communica-tor but might receive information from various sources. The main lesson fromMacnaghten and Jacobs (1997) in this context is that risk communication should beintelligent, in that all information (identified by the arrow pointing to the riskcommunicator) should be taken into account. This requirement will be discussed forthe two cases presented here: climate change and terrorism.

Figure 7. Channels for information exchange in risk communication.

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4.1. Risk communication and climate change

A recurring conclusion in the literature is that, on average, the public focusestoo little on the risk of climate change. A strategy to increase public awarenessabout the threat of climate change is to increase fear. According to Visscherset al. (2012), affect has a central role in people’s risk perception and decision-making. It is, therefore, important that the risk communicators know how riskcommunication can influence affect or more specific emotions. Scare campaignscan have some effect on, e.g. health promotion. Scare campaigns are based onappealing to anxiety or fear. The mechanism is to stimulate a sense of dangerin the target audience by attempting to produce fear with the aim of promotingprecautionary measures and self-protective actions (O’Neill and Nicholson-Cole2009). According to O’Neill and Nicholson-Cole (2009), the experiences fromhealth and marketing-related disciplines cannot, however, be directly transferredto climate change. Personal experience and thus the identification with the prob-lem are missing in the case of climate change because the consequences of cli-mate change are often perceived to be impersonal and distant. Moser andDilling (2004) note that when an individual is confronted with fear, it initiatesthe desire to control this fear. Because individuals cannot be expected to controlclimate change by changing their behaviour, these fears must be controlled inter-nally, resulting in denial and apathy. Therefore, intimidation on the climatechange issue may have the opposite effect of that intended in the longer run ifscare campaigns are used.

In marketing, the importance of raising awareness has long been recognisedwithin what is called ‘attention economics’ (Davenport and Beck 2001). A well-planned communication strategy to disseminate the potential risks of climatechange would take advantage of the insight from this strand of the literature.The information may be ‘framed’ by the relevant decision-makers, such that it isperceived more clearly by the receiver and thus produces the conditions for theimplementation of effective climate policies. Moser and Dilling (2004) draw onthe well-known prospect theory (Kahneman and Tversky 1979) and its resultsregarding the difference in how we perceive gains and losses. They argue thatthe policies that have a high success rate, for example adaptation investments,are best framed in a way that highlights the benefits of the policy. The reasonis that we often choose the certain result compared to the risky one in the pres-ence of potential, but uncertain, larger gains (i.e. the gain from doing nothing ifclimate change is not occurring). Less certain choices (i.e. where the successrate is lower) should be framed so that the losses are highlighted. In this way,the decision-maker can use proper framing to improve the potential for imple-menting the desired policies.

A second mechanism for intelligent risk communication in this area is to pro-vide the public with a sense of control by describing the options available for indi-vidual actions and thereby improving the identification and local commitment toclimate change. A key objective of this process is to make the regulated party a partof the process and provide a sense of ownership over the project. The governmentcan create incentives such that it is in the consumer's best interest to be climate-friendly or can provide grants for ‘proper climate conduct’ or disincentives for sub-optimal climate solutions.

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4.2. Risk communication for terrorism

Major terror attacks generate huge psychological distress among a potentially verylarge number of individuals. Using the policy model derived in this paper, this dis-proportionate reaction relative to the actual changes is unfortunate. This disconnectsuggests that a proper risk communication strategy regarding terrorism shouldattempt to reduce this affect-driven fear.

The literature offers different means for effective risk communication in thepresence of this persistently high level of public fear. The provision of better infor-mation regarding the real risks is one option. Slovic (1987) mentions attempts toeducate the public by providing quantitative risk estimates for a variety of hazards(such as comparing the death toll from 9/11 to fatalities from road accidents) andthereby improve people’s intuition about risk. However, according to, e.g. Sunsteinand Zeckhauser (2011), fear leads to probability neglect, and it is by no meansguaranteed that this strategy would reduce the fear felt by the public. These authorsare consistent with Slovic (1987), who finds that riskiness means more to peoplethan probabilities and the number of fatalities. Sunstein and Zeckhauser (2011)advocate a more systematic investigation into how to communicate risk in these cir-cumstances. The government should, according to these authors, determine whichmeans are the most effective for reducing fear. They propose measures that arehighly visible, low in cost and perceived to be effective. Greenberg and Babcock-Dunning (2012) conducted a survey to better understand why some people worry(and why some groups systematically worry more) about terrorism, and they pro-pose ways to reduce this worrying. Their finding is that a (relatively) large minority(the study is of the USA) hold a continuously high level of terror-related worry,while in general (overall), the immediate distress from 9/11 has declined gradually.This minority has a disproportionately multi-ethnic composition. The authors arguethat one reason for this high level of worry is that this group in particular feels vul-nerable because they have fewer personal resources to secure themselves againstterrorism and, therefore, feel that they lack control over the problem. This argumentsuggests that one means for reducing the disproportionate terror-related concern isto allow the most worried individuals to regain their feeling of control over theproblem.

5. Conclusion

This paper demonstrates the potential for a number of problematic consequenceswhen the risk perceived by the public partly determines a country’s risk and secu-rity policy. Because any democratic process needs to address the public’s reactionto policies, this paper also provides means for communicating risk to the public.

For the risk of terror, this paper described and explained the likely policyreaction after a terror attack, which results in ‘response overshooting’. For climatechange, however, the analysis identified the reasons behind ‘response undershoot-ing’, the generally too low level of resources devoted to reduce the risk of climatechange. The consequences of these policies are economic (in the sense of moreexpensive policies) and periodically too high and too low protection. For both terrorand climate change, it is possible to identify likely situations where relatively highprotection is achieved in periods with relatively low risk and relatively lowprotection in periods with relatively high risk.

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A well-planned communication strategy is necessary. This communication needsto be tailored towards the specific characteristics of the problem. For climatechange, scare campaigns will most likely result in more neglect of the problembecause individuals lack the means to control the consequences of the problem. Abetter strategy is to provide the public with a feeling of control by suggesting areaswhere individuals can behave in a more climate friendly manner. For terror, whichintends to provoke dread risk, the best strategy appears to be the application offear-reducing measures by e.g. providing individuals with a sense of self-protection.A lesson that can be drawn from the analysis is that public involvement in risk-reducing policies appears to be a universal strategy for providing the public with amore realistic sense of the potential risks stemming from a given problem.

The general nature of the analysis comes, however, at a price because it buildson a number of simplifying assumptions. One issue is that the public is treated as asingle individual, while in reality, public risk perceptions might very well vary sub-stantially between individuals. The current model is designed to take an averageview because this is assumed to indicate the general pressure that public perceptionshave on the overall political direction of a country. Moreover, policy is a complexinterplay between multiple factors and stakeholders, including lobbying organisa-tions. These special interests attempt to exploit extreme events to progress their par-ticular agenda, which can have either positive or negative feedback for the chosenpolicy after an extreme event. Finally, there is interplay between the risk perceptionof one problem and the occurrence of extreme events related to another problem(through the availability heuristics). It is reasonable that the occurrence of a finan-cial crisis might reduce focus on both climate change and terror issues.

However, the general results of this paper are valid if the logic that the analysisbuilds upon is valid: public perceptions are systematically influenced by extremeevents, while scientific, evidence-based estimates are not influenced to the sameextent. Finally, risk and security policy is influenced by inputs from both.

Notes1. According to Nakahara and Ichikawa (2013), nearly 20,000 died as a consequence of

the 9.0 earthquake and tsunami in Japan in 2011. These consequences can be comparedwith the Fukushima accident, which carried with it enormous economic damage withoutsignificant human casualties. The economic damage was largely due to the mandatoryand voluntary evacuations in the radioactively contaminated communities (Hayashi2012).

2. Evidence of this claim can be found in Wittneben (2012), who attributes the outcome ofregional elections in Baden-Württemberg and Rheinland-Pfalz to the Fukushima incidentbecause the election was held two weeks after the incident and put more anti-nuclearparties in power. According to Wittneben (2012), the voters came out against nuclearpower, primarily driven by extensive media coverage.

3. Examples where the public becomes aware of potential risks through extreme eventsinclude climate change (Lorenzoni and Pidgeon 2006; Lorenzoni et al. 2006), interna-tional terrorism (Sunstein 2006), natural calamities (Slovic and Weber 2002) or financialsystem vulnerability (e.g. the collapse of the US housing market, [Blankenburg andPalma 2009]).

4. Sunstein and Zeckhauser (2011) analyse the effect of the (un)availability bias withrespect to climate change and (Sunstein 2006) for a comparison of the availability of ter-ror and climate change.

5. Ropeik (2010) lists 13 such factors; among these, the important characteristics arewhether a person has control, whether the problem is natural or man-made, whether it is

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uncertain, if it is possible to personify the problem (or the mechanisms that create theproblem), and whether it is catastrophic or the person thinks it could happen to him/her.

6. Slovic and Weber (2002) present an ordering of the perceived risks from 30 activitiesand technologies. Although ‘experts’ rank nuclear power as number 20, the ‘League ofWomen Voters’ and ‘Active College Students’ rank it as having the highest perceivedrisk. Their explanation for this deviation is that experts base their estimates on technicalestimates of annual fatalities, whereas laypeople base their judgments on other hazardcharacteristics.

7. There is, however, no guarantee that, on average, the expected publicly perceived riskequals the scientific estimates; systematic biases might exist. As an example, Weber(2010) concludes that the public’s perceptions of climate change over time appear gener-ally to reflect a reduced concern and greater volatility than warranted by the scientificevidence. This issue is discussed more thoroughly in Section 3.

8. The numerical results also indicate that extreme events that reduce the perceived risk(cold winters for the perception of climate risk, the killing of Bin Laden for the percep-tion of terror risk) are more volatile than the scientifically verifiable risk.

9. For a precise definition of the various probability terms, see IPCC (2012). An extremeweather event is an event that is rare within its statistical reference distribution at a par-ticular place. The IPCC assessments are based on the assumption that no effective cli-mate agreement is implemented.

10. Whether or not an extreme climate event becomes more likely over time depends on thechoice of reference. If we, however, also define extreme events in terms of magnitude(damage caused), then extreme events are likely to increase over time.

11. Note that only a subset of respondents that believe that global warming is occurring alsoconsider the causes for global warming to be human activity. E.g. Gallup – USA (2010)reports that in 2010, 50% were answering that global warming was due to human activi-ties while 46% answered natural causes.

12. The three policy scenarios are as follows: not allowing the global average temperature toincrease by over 2 °C, implementing the pledges from the Copenhagen accord andfinally, the optimal path (from an economic point of view). This is not to say that thesepaths are independent of the occurrence of new information about the costs and damagesfrom climate change.

13. In Denmark, it has long been recognised that the drainage capacity of the major citiescannot handle the extreme rain that is expected as a result of climate change, but invest-ments to increase this capacity have been almost non-existent. This policy, however,changed dramatically after the massive flooding in parts of Copenhagen in the summerof 2011. See, e.g. EEA (2012).

14. Brandt (2003) considers the notion of unilateral actions – the fact that some countrieshave reduction targets – to be ‘leadership by example’ and to affect the overall reductioneffort.

15. The current scientific understanding is that the probability of extreme events related toclimate change (flooding, droughts and storms) is expected to be positively correlatedwith the magnitude of the temperature increase (IPCC 2007).

16. Further definitions; see Enders and Sandler (2006a).17. Several databases exist that report all terror incidents, see, e.g. http://www.start.umd.edu/

gtd/.18. The intentionality of terror is associated with the fact that terrorist organisations are

regarded as rational (see, e.g. Enders and Sandler 2006a; Feichtinger and Novak 2008;Shughart 2011) and that they exhibit maximising behaviour by balancing the costs andbenefits of terror attacks (Enders and Sandler 2006a). According to Shughart (2011), ter-rorists are rational in two important means–ends senses. Every terrorist faces a budgetconstraint and must deploy resources cost-effectively, allocating the available resourcesover time and space so as to maximise terrorism’s net returns, in whatever form thosereturns are expected to materialise. Second, terrorists respond rationally to the measurestaken to counter them.

19. Fear is particularly pervasive after massive terror attacks such as those that affected thecities of New York, Madrid, London or Mumbai.

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20. According to Enders and Sandler (2006b), even though there was a general recognitionfrom experts that the threat of fundamental terrorism was raising up until 9/11, there wasonly minimal evidence that a major attack would hit a high-income country. Therefore,9/11 was unexpected, and before it occurred, most experts did not consider that its dev-astating consequences were possible. The view about the potential scale obviously hadto be revised after 9/11.

21. According to Pillar (2011, 2), US policy has been distorted due to high fear and traumaafter 9/11: ‘high disproportionate share of US resources has been directed to this (AlQaeda) one group’.

22. Examples of frequently applied indicators are as follows: GDP as an indicator of eco-nomic performance, the ecological footprint for environmental performance, the HumanDevelopment Index as a proxy for social performance, or the number of killings in ter-rorist incidents.

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