Left-Wing Extremism From the Indian Perspective: An Econometric Interpretation

Left-Wing Extremism From the Indian Perspective: An Econometric Interpretation

Sovik Mukherjee (St. Xavier's University, Kolkata, India)
Copyright: © 2020 |Pages: 15
DOI: 10.4018/978-1-5225-9715-5.ch006

Abstract

The article tries to geographically locate the pockets where such forms of crime are the most prevalent and do a trend analysis for these states over a period of five years. In addition to this, the article models left wing extremist activities across 12 severely affected states in India for a period of nine years from 2008-2017 in a generalized method of moments (GMM) set-up to take care of the endogeneity problem which are quite likely to arise in case of such analysis. In conclusion, the results highlight that while economic growth has a definite positive role in abating such violent forms of left-wing extremist crime, the development strategy should give high priority to literacy, internal security, and human development.
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Key Terms in this Chapter

Poverty Head Count Ratio: The poverty head count ratio (PHCR) is the proportion of a population that exists, or lives, below the poverty line.

Gini Coefficient: In economics, the Gini coefficient sometimes called Gini index, or Gini ratio, is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation's residents, and is the most commonly used measurement of inequality.

Maoists: Maoists, also known as Naxalites or Naxals, are the group of people who believe in the political theory derived from the teachings of the Chinese political leader Mao Zedong. It is a doctrine to capture State power through a combination of armed insurgency, mass mobilization and strategic alliances. Also, these Maoists use insurgency doctrine based on use of propaganda and disinformation against State institutions. Herein, the author has used Maoists, left-wing extremists, and Naxalites interchangeably.

Monte Carlo Simulations: Monte Carlo simulation is a mathematical technique that generates random variables for modeling risk or uncertainty of a certain system. The random variables or inputs are modelled on the basis of probability distributions such as normal, log normal, etc. Different iterations or simulations are run for generating paths and the outcome is arrived at by using suitable numerical computations.

Police Force: A body of trained officers entrusted by a government with maintenance of public peace, law and order, enforcement of laws, and prevention and detection of crime.

Panel Data: Also called longitudinal data, represents cross-sectional time series data i.e. data on multi-dimensional cross-sections (comprising of individuals, firms and countries) over a period of time.

Economic Growth: It can be defined as the increase in the capability of an economy to produce goods and services from one period to another. It can be measured either in nominal terms or in inflation adjusted real terms. Typically, GDP or GNP is taken as a measure of economic growth. In notational terms, GDP growth rate, g t , AU54: Mathtype 7 where, t indicates the particular time point.

Generalized Method of Moments (GMM Estimation): It is a common method for estimation of the parameters in statistical models. Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable. Using the moment conditions, the true parameter values are estimated. The GMM method then minimizes a certain norm of the sample averages of the moment conditions. It is applied in case when there can be a chance of endogeneity problem.

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