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Dynamics of Optimal Growth and Overlapping Generations Models in Economic Convergence and Inequality: A Review Cover

Dynamics of Optimal Growth and Overlapping Generations Models in Economic Convergence and Inequality: A Review

Open Access
|Nov 2023

Abstract

This study explains the dynamics in the Optimal Growth [OGR] and Overlapping Generations [OGE]models and their implications for (real) GDP per capita [RGDPPC] in different countries, short-run and long-run. This analysis uses RGDPPCs for ten countries consisting of five per each developed and developing category for 116 years. Sri Lanka is used as the favourite destination and calculated the RGDPPC ratios. Data on RGDPPC for ten countries explains that the relative differences between RGDPPC ratios and the baseline are varying over time. Also, it demonstrates a high variation in the short-run dynamics between countries. Both models predict a convergence of economies into a steady-state having the same amount of RGDPPCs in the long run. This prediction appears to be acceptable in the analysis. Having Sri Lanka as the benchmark, Japan exhibits low RGDPPC values at the initial stage and eventually gets closer to the RGDPPCs of developed countries. This is not a direct convergence to the steady-state but convergence to the RGDPPC level of developed countries. Also, the concept of efficient contributions by generations in the OGE model was considered and it reflects a more realistic reasoning as per the short-run dynamics, but that resulted in making differences across countries per capita GDP in the long run. The long-run dynamics revealed that growing inequality is a common issue in developing nations as a very low percentage of populations enjoys a high proportion of national output.
Language: English
Page range: 125 - 130
Published on: Nov 28, 2023
Published by: General Sir John Kotelawala Defence University
In partnership with: Paradigm Publishing Services

© 2023 D. I. J. Samaranayake, published by General Sir John Kotelawala Defence University
This work is licensed under the Creative Commons Attribution 4.0 License.