Absolute And Conditional Convergence And Divergence In India And China: A Comparative Panel Data Regressions Analysis

Abstract

A debate on absolute and conditional convergence and divergence between the per capita GDP of the emerging economies (India and China- the global south economies) and the United States- the dominant global north economy and four global north economies (the United Kingdom, Germany, Norway, and Russian Federation) during 2010-2020 is discussed in this paper.  The descriptive analysis and panel regressions are used for testing the convergence and divergence. This paper has four significant results: (i) there is no significant difference between the GDP per capita of India and China reflecting an absolute convergence among the global south economies; (ii) an absolute divergence between China and the Russian Federation;  (iii)  an absolute divergence between the per capita GDP of China and the GDP per capita of the US, the UK, Germany and Norway and (iv) Norway has the highest GDP per capita as compared to other six economies -empirically testing by using the panel regression of the random effect - a conditional divergence between the global south economies (India and China) and the global north economies. The results have two policy implications: (1) there is a need to expand public funding in social sectoral investment, mainly in education, health, and research and development for creating a knowledge economy in developing economies, like India and (2) there is a crucial role of the welfare by the state in the recession times of Covid-19 era as both absolute and conditional divergences are significantly tested in this paper.