Uncovering Heterogeneous Regional Impacts of Chinese Monetary Policy

Andrew Tsang

MPRA Paper from University Library of Munich, Germany

Abstract: This paper applies causal machine learning methods to analyze the heterogeneous regional impacts of monetary policy in China. The method uncovers the heterogeneous regional im-pacts of different monetary policy stances on the provincial figures for real GDP growth, CPI inflation and loan growth compared to the national averages. The varying effects of expansionary and contractionary monetary policy phases on Chinese provinces are highlighted and explained. Subsequently, applying interpretable machine learning, the empirical results show that the credit channel is the main channel affecting the regional impacts of monetary policy. An imminent conclusion of the uneven provincial responses to the “one size fits all” monetary policy is that different policymakers should coordinate their efforts to search for the optimal fiscal and monetary policy mix.

Keywords: China; monetary policy; regional heterogeneity; machine learning; shadow banking (search for similar items in EconPapers)
JEL-codes: C54 C61 E52 R11 (search for similar items in EconPapers)
Date: 2021-07-28
New Economics Papers: this item is included in nep-big, nep-cba, nep-cmp, nep-cna, nep-geo, nep-mac, nep-mon and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:110703

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