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What Causes China's High Inflation? A Threshold Structural Vector Autoregression Analysis

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  • Fang Guo

Abstract

China's astonishing economic growth implies a necessity to understand its inflation. The present paper employs threshold nonrecursive structural vector autoregression analysis to explore the asymmetric effects of macro-variables on inflation in low and high inflation regimes. The empirical evidence demonstrates, first, that the reactions of inflation to various shocks are inflation-regime-dependent and asymmetric. Second, monetary policy influences China's high inflation and adjusting the domestic interest rate in China may be an effective way to control inflation in a high inflation regime, but not in a low inflation regime. In a high inflation regime, a high inflation rate may cause the macro-policy authorities to increase the domestic interest rate, in an attempt to stabilize high inflation. Third, contrary to expectations, the world oil price is not a strong cost-push factor in a low inflation regime. Oil price increases may increase inflation in a high inflation regime, but there is no such obvious effect in a low inflation regime. Finally, China's nominal effective exchange rate influences inflation in both low and high inflation regimes. A nominal effective exchange rate appreciation might be effective in controlling domestic inflation in both regimes.

Suggested Citation

  • Fang Guo, 2013. "What Causes China's High Inflation? A Threshold Structural Vector Autoregression Analysis," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 21(6), pages 100-120, November.
  • Handle: RePEc:bla:chinae:v:21:y:2013:i:6:p:100-120
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    File URL: http://hdl.handle.net/10.1111/j.1749-124X.2013.12048.x
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    2. Yuko Kinoshita & Fang Guo, 2015. "What Can Boost Female Labor Force Participation in Asia?," IMF Working Papers 2015/056, International Monetary Fund.
    3. Bradley Jones & Joel Bowman, 2019. "China's Evolving Monetary Policy Framework in International Context," RBA Research Discussion Papers rdp2019-11, Reserve Bank of Australia.

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