Classical convergence versus Zipf rank approach: Evidence from China’s local-level data

Abstract

This paper applies Zipf rank approach to measure how long it will take for the individual economy to reach the final state of equilibrium by using local-level data of China’s urban areas. The indicators, the gross domestic product (GDP) per capita and the market capitalization (MCAP) per capita of 150 major cities in China are used for analyzing their convergence. Besides, the power law relationship is examined for GDP and MCAP. Our findings show that, compared to the classical approaches: β-convergence and σ-convergence, the Zipf ranking predicts that, in approximately 16 years, all the major cities in China will reach comparable values of GDP per capita. However, the MCAP per capita tends to follow the periodic fluctuation of the economic cycle, while the mean-log derivation (MLD) confirms the results of our study. Moreover, GDP per capita and MCAP per capita follow a power law with an average value of α=0.41 which is higher than α=0.38 obtained based on a large number of countries around the world.