The low-intensity bombs that blew up in Ahmedabad and Bangalore have thrown light on the challenges before India’s intelligence agencies. Not only are the agencies unsure of who is behind the attack, the terrorists remain faceless. The obvious question to ask is: why has there been a spate of low-intensity bombings in small markets as opposed to say, the high-intensity bombing of a strategic location?
Let us try to answer this question using simple economics. First, the cost of planning a low-intensity operation is much lower. Second, the cost of executing it by placing ammonium nitrate inside a tiffin box atop a cycle is also very small. Third, the benefit gained by the terrorists through media coverage of the destruction and accompanying terror is relatively significant and contributes to creating distrust between communities. Fourth, the extremely low risk of getting caught makes engaging in terrorism more lucrative for a few local people and organisations funding such activities.
This means that there are broadly only three ways in which we can reduce bombings in low-intensity attacks and not compromise the security of strategic locations:
To raise the costs for terrorists of planning and executing low-intensity attacks.
To reduce the “benefit” the terrorists obtain from such attacks.
To increase their risk of getting caught.
Figure 1 illustrates the equilibrium number of bombings terrorists execute. The two black diagonal lines represent marginal cost and marginal benefit curves, i.e., the planned cost or benefit of bombing one more location in a single terrorist attack. Equilibrium is reached where these two curves intersect. Here, implementing (a) would mean a parallel upward shift of the marginal cost curve and implementing (b) would lead to a shift of the marginal benefit curve leftward. These have not been shown on the diagram. Acting on (a) and (b) by interfering with efficient market mechanisms like putting controls on use of fertilizers or on free media is not advisable as it can have negative spillovers.
The only convincing way of dealing with terrorism of this nature is to increase a terrorist’s risk of getting caught on camera in at least one of the locations. This not only raises the costs of planning an attack (making the curve move upward), but also makes the marginal cost curve steeper than before as chances of getting caught increase exponentially. The marginal cost curve now becomes the red line and the equilibrium number of bombings carried out in one attack comes down dramatically. By exponentially raising the costs of carrying out one extra bombing, two effects may take place. First, there would be a decline in the number of bombings per terrorist incident (as shown in the graph). Second, there would be a greater incentive to go in for one high-intensity blast at a strategic location. This would work like a substitution effect, whereby a worker tends to reduce the amount of work if marginal tax rate increases. However, it would be a preferable situation for India if we consider this a zero-sum game, whereby raising the costs for terrorists works in the same manner as increasing benefits for India.
Installing Closed Circuit Television (CCTV) cameras in susceptible places like markets, shrines, hospitals and colleges would help garner information on terrorists, should they decide to attack. These cameras may be visible or hidden. These can also be used to detect traffic violations, violence, drug abuse, shoplifting and property theft. Britain had started using CCTV cameras to combat IRA terrorism during the 1970’s and today has the highest amount of camera surveillance in the world. In London, there is a good chance that one will be captured by over 300 cameras in a single day. The only dilemma facing the authorities should be whether to install fixed cameras or Wi-fi enabled cameras. The latter are more expensive, but give the option of higher mobility and thus may indeed be the better option since terrorism seems to be a long-run issue. There are also costs of maintenance and staff to monitor the pictures that must be taken into account in any cost-benefit analysis.
Although studies show a decline in vandalism in London buses and reduced robberies in London Underground stations when they are equipped with CCTV cameras, there is very little quality evidence to suggest the extent of their achievement. This is mainly because of the problem of lack of randomisation when the cameras are installed.
For instance, in order to quantify the degree of success of a drug, a pharmaceutical company will undertake randomised trials, in which a random sample of people is given the drug and others are not. Everything else remains the same for these two groups. This is helpful in finding the true extent of potency of a drug. Similarly, to find out if smaller class groups increase learning ability, a randomised solution has been carried out by economists in Israel. In another experiment, a bank in South Africa lent money at different rates to randomly selected individuals, in order to find its effect on non-performing assets.
Therefore, in order to judge the efficacy of cameras, the police would need to install these cameras at pre-planned locations in randomly selected cities (“treated” cities). The difference in terrorism and crime between the treated and the control cities would be monitored. If the difference changes significantly after the introduction of cameras, it would imply that surveillance is having an effect and, more importantly, the quantitative effect can be found. Furthermore, dummy cameras (which are readily available online) can be used in half the cities and real cameras in others to distinguish the effect of deterrence from just the perception of being under-watch and deterrence from actual catching and punishment.
The problem lies in implementing such an experiment on a large enough scale. In order to give policy recommendations, it is of great importance to delineate causal impacts of policies. Carrying out randomised social experiments will give a fillip to finding out “clean” effects of surveillance on terrorist activities.
Generally the police would like to set these cameras in cities where crime is expected to be high, but this would rule out a way to find the causal impact of CCTV on crime as there would be a selection bias. Moreover, it would be a multi-pronged approach (increased policing, hiring more personnel, etc.) to tackling crime and terrorism, and thus to isolate the impact of CCTV on crime would be impossible.
CCTV is also likely to change the behaviour of people who are not potential offenders. In a survey carried out in Germany to assess perceptions of people to CCTV, it was found that a majority of people like to have cameras installed in malls, banks, railway platforms, and along motorways. However, there is displeasure at placing them at the entrance of residential buildings, in public toilets and in changing or dressing rooms. There is a general concern that being constantly under inspection will adversely affect civil liberties.
Between 1996 and 1998, more than three quarters of the UK government spending on crime prevention went towards CCTV installation and monitoring. It has been shown that effects of CCTV on deterrence are short-lived and not persistent. For instance, the underlying patterns of car thefts in British cities re-emerged after three quarters of low-crime.
The Indian police are waking up to the yawning gap in their surveillance infrastructure. In a recent news article, it was predicted that by 2010, all NCR towns of Haryana would come under hi-tech CCTV surveillance through Wi-fi, hi-band and fiber based surveillance systems covering all major sensitive locations such as the expressway, malls and MNC offices, bus stands and railway stations. Even though there are no randomised studies on the benefits of installing these and several concerns on their use remain, there seems to be a consensus emerging on advantages of having “someone watching over us”.
Will CCTV Technology Deter Terrorists?
More from the author
The low-intensity bombs that blew up in Ahmedabad and Bangalore have thrown light on the challenges before India’s intelligence agencies. Not only are the agencies unsure of who is behind the attack, the terrorists remain faceless. The obvious question to ask is: why has there been a spate of low-intensity bombings in small markets as opposed to say, the high-intensity bombing of a strategic location?
Let us try to answer this question using simple economics. First, the cost of planning a low-intensity operation is much lower. Second, the cost of executing it by placing ammonium nitrate inside a tiffin box atop a cycle is also very small. Third, the benefit gained by the terrorists through media coverage of the destruction and accompanying terror is relatively significant and contributes to creating distrust between communities. Fourth, the extremely low risk of getting caught makes engaging in terrorism more lucrative for a few local people and organisations funding such activities.
This means that there are broadly only three ways in which we can reduce bombings in low-intensity attacks and not compromise the security of strategic locations:
Figure 1 illustrates the equilibrium number of bombings terrorists execute. The two black diagonal lines represent marginal cost and marginal benefit curves, i.e., the planned cost or benefit of bombing one more location in a single terrorist attack. Equilibrium is reached where these two curves intersect. Here, implementing (a) would mean a parallel upward shift of the marginal cost curve and implementing (b) would lead to a shift of the marginal benefit curve leftward. These have not been shown on the diagram. Acting on (a) and (b) by interfering with efficient market mechanisms like putting controls on use of fertilizers or on free media is not advisable as it can have negative spillovers.
The only convincing way of dealing with terrorism of this nature is to increase a terrorist’s risk of getting caught on camera in at least one of the locations. This not only raises the costs of planning an attack (making the curve move upward), but also makes the marginal cost curve steeper than before as chances of getting caught increase exponentially. The marginal cost curve now becomes the red line and the equilibrium number of bombings carried out in one attack comes down dramatically. By exponentially raising the costs of carrying out one extra bombing, two effects may take place. First, there would be a decline in the number of bombings per terrorist incident (as shown in the graph). Second, there would be a greater incentive to go in for one high-intensity blast at a strategic location. This would work like a substitution effect, whereby a worker tends to reduce the amount of work if marginal tax rate increases. However, it would be a preferable situation for India if we consider this a zero-sum game, whereby raising the costs for terrorists works in the same manner as increasing benefits for India.
Installing Closed Circuit Television (CCTV) cameras in susceptible places like markets, shrines, hospitals and colleges would help garner information on terrorists, should they decide to attack. These cameras may be visible or hidden. These can also be used to detect traffic violations, violence, drug abuse, shoplifting and property theft. Britain had started using CCTV cameras to combat IRA terrorism during the 1970’s and today has the highest amount of camera surveillance in the world. In London, there is a good chance that one will be captured by over 300 cameras in a single day. The only dilemma facing the authorities should be whether to install fixed cameras or Wi-fi enabled cameras. The latter are more expensive, but give the option of higher mobility and thus may indeed be the better option since terrorism seems to be a long-run issue. There are also costs of maintenance and staff to monitor the pictures that must be taken into account in any cost-benefit analysis.
Although studies show a decline in vandalism in London buses and reduced robberies in London Underground stations when they are equipped with CCTV cameras, there is very little quality evidence to suggest the extent of their achievement. This is mainly because of the problem of lack of randomisation when the cameras are installed.
For instance, in order to quantify the degree of success of a drug, a pharmaceutical company will undertake randomised trials, in which a random sample of people is given the drug and others are not. Everything else remains the same for these two groups. This is helpful in finding the true extent of potency of a drug. Similarly, to find out if smaller class groups increase learning ability, a randomised solution has been carried out by economists in Israel. In another experiment, a bank in South Africa lent money at different rates to randomly selected individuals, in order to find its effect on non-performing assets.
Therefore, in order to judge the efficacy of cameras, the police would need to install these cameras at pre-planned locations in randomly selected cities (“treated” cities). The difference in terrorism and crime between the treated and the control cities would be monitored. If the difference changes significantly after the introduction of cameras, it would imply that surveillance is having an effect and, more importantly, the quantitative effect can be found. Furthermore, dummy cameras (which are readily available online) can be used in half the cities and real cameras in others to distinguish the effect of deterrence from just the perception of being under-watch and deterrence from actual catching and punishment.
The problem lies in implementing such an experiment on a large enough scale. In order to give policy recommendations, it is of great importance to delineate causal impacts of policies. Carrying out randomised social experiments will give a fillip to finding out “clean” effects of surveillance on terrorist activities.
Generally the police would like to set these cameras in cities where crime is expected to be high, but this would rule out a way to find the causal impact of CCTV on crime as there would be a selection bias. Moreover, it would be a multi-pronged approach (increased policing, hiring more personnel, etc.) to tackling crime and terrorism, and thus to isolate the impact of CCTV on crime would be impossible.
CCTV is also likely to change the behaviour of people who are not potential offenders. In a survey carried out in Germany to assess perceptions of people to CCTV, it was found that a majority of people like to have cameras installed in malls, banks, railway platforms, and along motorways. However, there is displeasure at placing them at the entrance of residential buildings, in public toilets and in changing or dressing rooms. There is a general concern that being constantly under inspection will adversely affect civil liberties.
Between 1996 and 1998, more than three quarters of the UK government spending on crime prevention went towards CCTV installation and monitoring. It has been shown that effects of CCTV on deterrence are short-lived and not persistent. For instance, the underlying patterns of car thefts in British cities re-emerged after three quarters of low-crime.
The Indian police are waking up to the yawning gap in their surveillance infrastructure. In a recent news article, it was predicted that by 2010, all NCR towns of Haryana would come under hi-tech CCTV surveillance through Wi-fi, hi-band and fiber based surveillance systems covering all major sensitive locations such as the expressway, malls and MNC offices, bus stands and railway stations. Even though there are no randomised studies on the benefits of installing these and several concerns on their use remain, there seems to be a consensus emerging on advantages of having “someone watching over us”.
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