Terrorism and India: an economic perspective

Abstract

This study seeks to evaluate the terrorism and economic performance of the economy of India from the year 2004 to the year 2013. The analysis of the study is based on the model of Economics of Terrorism Monitoring Model (ETM-Model) introduced by Khan et al. (Qual Quant, 2015). The main objective of this research study is to scrutinize the terrorism situation in the economy of India. The effects of terrorism on the economic performance is measured by economic desgrowth. The economic desgrowth generated from economic growth rate due to terrorism in the year 2004 for the Indian economy is −0.91 %, while the economic desgrowth for the year 2013 of the same economy is −2.05 %. The study concludes that terrorism is one of the main issue of the Indian economy from the economic perspective. Indian government may work with Pakistan to resolve the issue of Jammu and Kashmir to overcome the terrorism issue. It is also needed for the Indian economy to make harmony between Muslims and Hindu with in the territory of India.

Appendix

1.1 The national terrorism vulnerability rate (µ_T)

In order to measure national terrorism vulnerability rate, one should estimate the total terrorism frequency rate (β_i) which is the ratio of a particular terrorism incident in an explicit year divided by the total terrorism frequency rate cumulatively (Eq. 1).

$$ \beta_{i} = \frac{{\beta_{i,t = T} }}{{\sum\nolimits_{t = T - 9}^{t = T} {\beta_{i,t = T} } }}$$

(1)

The value of terrorism frequency rate will be in between zero and one. As given in Eq. 2 as below

$$ 0 \le \beta_{i} \ge 1$$

(2)

We take into account that terrorism incident and attacks can take place at any place and any time because these incidents are unpredictable and uncertain. The frequency rates of nominated twelve different terrorism activities and types of terrorist attacks are as follow, suicide (β ₁), assassination (β ₂), hijacking (β ₃), kidnapping (β ₄), barricade (β ₅), bombing (β ₆), unknown (β ₇), armed assaults (β ₈), unarmed assaults (β ₉), infrastructure (β ₁₀), number of killed (β ₁₁) and number of wounded (β ₁₂). The various terrorism incidents and types of terrorist attacks have different intensity depending on their nature, magnitude and location. The hypothesis of the ETM-Model states that the terrorism incidents cannot be examined with precision as their nature is irregular and uncertain.

To find the national terrorism vulnerability rate, the common formula to measure is as below.

There are three different levels of vulnerability rate to examine the terrorism vulnerability rate (µ_T) (see Eq. 3).

$$ \mu_{T} = \left( {Ln\sqrt {1 - \beta } } \right)$$

(3)

The first level is the high vulnerability rate whose value lies between 1 and 0.75. The second level is the average vulnerability rate which between 0.74 and 0.34 and third level is the low vulnerability rate with value from 0.33 to 0.

There are three types of relationship between national terrorism vulnerability rate (µ_T) and economic desgrowth. On one side, when the national terrorism vulnerability rate is very high the economic desgrowth will be high. On other side, when the terrorism vulnerability rate (µ_T) is low the economic desgrowth will also be low. The application of “The Dynamic Imbalanced State (DIS)”, which is presented by Ruiz Estrada and Yap (2012) explains that it is dynamic and changes continuously.

1.2 The terrorism devastation magnitude (λ)

Capital devastation and human capital devastation are used as a variables to calculate terrorism devastation magnitude rate. The capital devastation magnitude rate is measured as the total number of incidence of terrorism and types of terrorist attacks in a certain area in a geographical locality divided by the total area of the same specific locality. The human capital devastation magnitude rate measures as the number of killing or missing persons in a specific location divided by the total population of the same geographical locality. By multiplying both the results of capital and human capital devastation magnitude rate measure the value of terrorism devastation magnitude rate (λ).

$$ \lambda = Ln\left[ {(\phi k) \times (\psi L)} \right]$$

(4)

1.3 The economic desgrowth

The economic desgrowth is a novel concept and macroeconomic indicator that reveals the final impact of any natural hazards on the GNP. This elucidates that how final GNP-post violence hazards depend on the terrorism devastation magnitude rate (λ). Along with that, terrorism devastation magnitude rate (λ) is directly linked to the national terrorism vulnerability rate (µ _T). So the economic desgrowth is measured by the combination of the rates of product of terrorism devastation magnitude rate and national terrorism vulnerability rate. The general formula for the measurement of economic desgrowth is as below:

$$ \delta = (\mu_{T} )(\lambda )$$

(5)

Equation (5) explains that the economic desgrowth value will be negative. The analysis scrutinizes that when both national vulnerability rate and terrorism devastation magnitude rate are moving upward, the economic desgrowth will also change in the same course (se expression 6).

$$ \uparrow \delta = \left( { \uparrow \mu_{T} } \right)\left( { \uparrow \lambda } \right)$$

(6)

$$ \downarrow \delta = \left( { \downarrow \mu_{T} } \right)\left( { \downarrow \lambda } \right)$$

(7)

Therefore, economic desgrowth is directly proportional to magnitude rate, national vulnerability rate, and terrorism devastation.

1.4 The terrorism vulnerability surface (VV-Surface)

The plotting of vulnerability surface (VV-Surface) depends on the mega-surface coordinate space and terrorism frequency rate (B). In this case of the research study, the VV- surface is plotted through three by four matrix (single value of all 12 variables). All the 12 variables of terrorism incidents and types of terrorist attacks values are plotted into four rows and three columns on the VV-Surface. The VV-Surface describes the visual representation of the terrorism incidents and types of terrorist attacks of any economy or country. The VV-Surface can be shown as bellow.

$$ \eta = (\beta_{1} ,\beta_{2} ,\beta_{3} ,\beta_{4} ,\beta_{5} ,\beta_{6} ,\beta_{7} ,\beta_{8} ,\beta_{9} ,\beta_{10} ,\beta_{11} ,\beta_{12} )$$

(8)

The VV-Surface depends on the divergence that happened due to any terrorism incident or any type of terrorist attack during a given time period.