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Asymmetric Effects of Financial Conditions on GDP Growth in Korea: A Quantile Regression Analysis

Author

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  • Noh-Sun Kwark

    (Department of Economics, Sogang University, Seoul)

  • Changhyun Lee

    (Department of Economics, Sogang University, Seoul)

Abstract

With growing interest in the construction and application of a financial conditions index since the global financial crisis, this study constructs a Korean financial conditions index and examines the impact of the Korean financial conditions on future Korean GDP growth using quantile regression models. Considering that Korea is a small open economy, we also examine the spillover effects of the US financial conditions on the Korean GDP growth by including a US financial conditions index in the quantile regression model. The main empirical findings are as follows. First, the impact of Korean financial conditions on the future GDP growth of Korea is asymmetric in quantiles. The deterioration of financial conditions expands the left tail of the GDP growth distribution, while its impact on the right tail of the distribution is relatively weak. More interestingly, tight financial conditions make the distribution of next quarter’s GDP growth bimodal, implying a mixture of bank runs and no bank runs distributions. Second, the extended quantile regression model with US variables shows that the deterioration of US financial conditions expands both of the left and right tails of the distribution of the Korean GDP growth, increasing its variance. These results are robust with alternative financial conditions indexes and out-of-sample predictions.

Suggested Citation

  • Noh-Sun Kwark & Changhyun Lee, 2020. "Asymmetric Effects of Financial Conditions on GDP Growth in Korea: A Quantile Regression Analysis," Working Papers 2005, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
  • Handle: RePEc:sgo:wpaper:2005
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    3. Wei, Lu & Jing, Haozhe & Huang, Jie & Deng, Yuqi & Jing, Zhongbo, 2023. "Do textual risk disclosures reveal corporate risk? Evidence from U.S. fintech corporations," Economic Modelling, Elsevier, vol. 127(C).
    4. Yoosoon Chang & Yong-gun Kim & Boreum Kwak & Joon Y. Park, 2024. "Using Density Forecast for Growth-at-Risk to Improve Mean Forecast of GDP Growth in Korea," CAEPR Working Papers 2024-005 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    5. Xu, Qifa & Xu, Mengnan & Jiang, Cuixia & Fu, Weizhong, 2023. "Mixed-frequency Growth-at-Risk with the MIDAS-QR method: Evidence from China," Economic Systems, Elsevier, vol. 47(4).
    6. Zeng, Hongjun & Abedin, Mohammad Zoynul & Wu, Ran & Ahmed, Abdullahi D., 2024. "Asymmetric dependency among US national financial conditions and clean energy markets," Global Finance Journal, Elsevier, vol. 63(C).
    7. Lin Zhu & Jian He, 2024. "China financial stability and asymmetric implications for economic stability," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-29, February.
    8. Mohsin, Muhammad & Taghizadeh-Hesary, Farhad & Shahbaz, Muhammad, 2022. "Nexus between financial development and energy poverty in Latin America," Energy Policy, Elsevier, vol. 165(C).

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    Keywords

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    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

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