Abstract
As the worlds second-largest economic powerhouse, China stands at the nexus of global trade, investment, and economic policies. Yet, despite its meteoric rise and the subsequent spotlight on its financial milestones, the correlation between its GDP growth and the unemployment rate remains a fertile ground for exploration. Using time-series data as the backbone of this paper, the Granger Causality Test and Vector Autoregression (VAR) methodologies are employed during the research process. These sophisticated approaches are capable of ascertaining the linear interdependencies between these variables, providing a dynamic perspective that goes beyond traditional static analyses. This research aims to answer key questions: Can the historical fluctuations in GDP serve as a reliable predictor for future unemployment trajectories, and if so, to what extent does Okuns Law hold true? Conversely, does a shift in unemployment rates offer insights into potential GDP movements? The conclusions drawn from this comprehensive analysis aim to uncover the relationship between GDP and unemployment and provide possible explanations by integrating the notion of Okuns law.
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More From: Advances in Economics, Management and Political Sciences
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