Introducing the q-Theil index

TL;DR

This paper introduces the q-Theil index, a nonlinear transformation of the Theil index inspired by Tsallis' non-extensive entropy, and applies it to analyze GDP data of 20 rich countries to detect globalization patterns and economic deviations over time.

Contribution

It develops the q-Theil index based on Tsallis entropy and demonstrates its application to economic time series for detecting globalization and economic divergence.

Findings

Identifies the emergence of globalization around 1970.

Uses the q-Theil index to measure data distribution characteristics.

Detects the beginning of economic deviations in recent years.

Abstract

Starting from the idea of Tsallis on non-extensive statistical mechanics and the {\it q-entropy} notion, we recall the Theil index $Th$ and transform it into the $Th_q$ index. Both indices can be used to map onto themselves any time series in a non linear way. We develop an application of the $Th_q$ to the GDP evolution of 20 rich countries in the time interval [1950 - 2003] and search for a proof of globalization of their economies. First we calculate the distances between the "new" time series and to their mean, from which such data simple networks are constructed. We emphasize that it is useful to, and we do, take into account different time "parameters": (i) the moving average time window for the raw time series to calculate the $Th_q$ index; (ii) the moving average time window for calculating the time series distances; (iii) a correlation time lag. This allows us to deduce optimal conditions to measure the features of the network, i.e. the appearance in 1970 of a globalization process in the economy of such countries and the present beginning of deviations. The $q$ value hereby used is that which measures the overall data distribution and is equal to 1.8125.