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Real Exchange Rate and GDP Growth: A Regression Analysis Considering Multiple Economic Indicators

In: Management Information Systems in a Digitalized AI World

Author

Listed:
  • Zhewen Meng

    (University of Bristol)

  • Ruichen Tang

    (University of Toronto)

  • Jieya Yang

    (Jinan University)

  • Jiale Tan

    (Jinan University)

  • Liyan Zhang

    (Jincheng College of Sichuan University)

Abstract

This paper examines the relationship between the real exchange rate and GDP growth in both developing and developed countries under the Balassa-Samuelson effect, incorporating various economic indicators. Based on Purchasing Power Parity Theory, the sensitivity of real exchange rate undervaluation to GDP fluctuation is analysed. This study employs panel regression analysis, stepwise regression, and predictive model to assess the impact of the exchange rate on economic growth. The results reveal a positive correlation between the exchange rate and GDP growth, particularly in developing countries, while also highlighting the significance of other factors such as consumption, investment, and trade openness. Additionally, a time series forecasting model is utilized to predict future GDP growth rate and exchange rate trend. The applicability of the model is validated using actual data from China and Britain, revealing that undervaluation can stimulate economic growth, especially during periods of high economic openness. The robustness of the model, including its goodness of fit and multicollinearity, is also discussed. Furthermore, this research suggests that the government should comprehensively regulate exchange rate policy, trade policy, and foreign investment policy to achieve a more flexible and integrated policy mix that promotes economic growth.

Suggested Citation

  • Zhewen Meng & Ruichen Tang & Jieya Yang & Jiale Tan & Liyan Zhang, 2025. "Real Exchange Rate and GDP Growth: A Regression Analysis Considering Multiple Economic Indicators," Springer Proceedings in Business and Economics, in: Eric Tsui & Montathar Faraon & Kari Rönkkö (ed.), Management Information Systems in a Digitalized AI World, pages 187-210, Springer.
  • Handle: RePEc:spr:prbchp:978-981-96-6526-6_13
    DOI: 10.1007/978-981-96-6526-6_13
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