Global Macroeconomic Performance: A Comparative Study Based on Composite Scores

Somnath Chattopadhyay, Suchismita Bose

Abstract


This paper proposes a composite indicator designed to summarise in a single statistic a variety of different facets of macroeconomic performance and assesses relative performances of countries with respect to six macroeconomic variables, viz., the growth rate of real GDP, real per capita GDP, unemployment rate, fiscal balance, rate of inflation, and current account balance. An appropriate mathematical model to aggregate these variables to form composite scores has been implemented by adopting the MCDM (Multiple Criteria Decision Making) technique of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). This allows a parsimonious representation of a variety of different facets of macroeconomic performance and its inter-temporal comparison across countries. The distinctive features of the indicator relate to the domains covered, the normalisation methodology and the weights used for aggregation. Some existing indices like the Okun index and the Calmfors index turn out to be special cases of our proposed index. The data comprising a wide spectrum of countries and spanning the pre- and post- crisis years allow us to capture the effect of the recent global financial and economic crisis on the overall macroeconomic performance of countries relative to others. Not only do the relative performance scores show tremendous variability during the post-crisis years, but the measures of disarray are also at their highest, despite there being overall stability in the country rankings in terms of indicators, which are traditionally relied on, like GDP growth or per-capita GDP. A single graphical plot easily identifies countries that have performed consistently over time, and those whose overall macroeconomic performances have deteriorated sharply relative to others during the post-crisis years.

Keywords


Macroeconomic Performance, Correspondence Analysis, Composite Scores, Country Rankings, Measures of Disarray, TOPSIS, Entropy.

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ISSN: 1929-7092