DUAL DYNAMICS OF SAVINGS IN GLOBAL CONSUMPTION DISPARITIES

Abstract

This paper examines global consumption inequality through empirical and theoretical approaches. To provide a clear perspective on the magnitude of consumption inequality globally, the study utilizes the Penn World Tables 10.01 dataset covering the period from 1960 to 2019. To do this, countries are grouped into five categories based on their consumption levels. The analysis based on the categorization reveals a significant rigidity in these groups, with lower-tier countries facing challenges in moving to higher consumption categories. In contrast, top-tier countries consistently retain their positions over decades. Moreover, the proportion of the global population residing in the lowest consumption group has remained remarkably high in the past six decades, further emphasizing global inequality’s entrenched and severe nature. The paper broadens the theoretical framework by extending Solow’s (1956) perspective on how savings rates influence economic disparities among countries. While the Solow-Swan model traditionally highlights the role of higher savings in fostering economic growth and decreasing economic inequalities, this study incorporates Pasinetti’s (1962) perspective, which argues that increased savings among lower-income groups may disproportionately benefit wealthier groups, potentially intensifying inequality. Using Gillman’s (2011) general equilibrium model, the paper bridges these theoretical insights to examine how class-based economic differences shape the outcomes of savings behavior. Empirical results derived from the theoretical model show that the impact of savings rates on global consumption patterns varies significantly depending on the economic structures of different countries. This analysis underscores the importance of designing economic policies sensitive to each country's unique characteristics and structural realities rather than applying uniform, one-size-fits-all solutions.

Keywords

• Consumption-Saving
• Solow Growth Model
• Demand-led Growth Models
• Dynamic Panel Data Models.

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