In this paper, 13 different types of composite indices are constructed by linear combination of indicator variables (with and without outliers/data corruption). Weights of different indicator variables are obtained by maximizing the sum of squared (and, alternatively, absolute) correlation...

Structural change which is inherent in an evolving economy refers to a long-term widespread transformation of the fundamental relationships among different parts and organic constituents of it, rather than micro scale or short-term change in output and employment. Short-term economic challenges...

This paper aims at locating the practice of micro-credit system into a larger theoretical canvas of economic theory and philosophy. A systems theoretic approach has been adopted. Emergence of the ‘excluded' class has been explained with the help of the theory of feedback. Individuals have been...

This paper proposes a method to construct composite index, which is a linear combination of several variables, by deriving weights on the criterion of Shapley value (from cooperative game theory) that a constituent variable has in making the composite index. In practice it is found oftentimes...

In this paper we construct thirteen different types of composite indices by linear combination of indicator variables (with and without outliers/data corruption). Weights of different indicator variables are obtained by maximization of the sum of squared (and, alternatively, absolute)...

Multicollinearity in empirical data violates the assumption of independence among the explanatory variables in a linear regression model and by inflating the standard error of estimates of the estimated regression coefficients leads to failure in rejecting a false null hypothesis of...

This paper proposes a novel method of global optimization based on host-parasite co-evolution. It also develops a Fortran-77 code for the algorithm. The algorithm has been tested on 100 benchmark functions (of which the results of 32 relatively harder problems have been reported). In its search...

The nearest correlation matrix problem is to find a valid (positive semidefinite) correlation matrix, R(m,m), that is nearest to a given invalid (non-positive semidefinite) or pseudo-correlation matrix, Q(m,m); m larger than 2. In the literature on this problem, 'nearest' is invariably defined...