Spillovers from China's Growth Slowdown and Rebalancing to the ASEAN-5 Economies

Abstract

After many years of rapid expansion, China's growth is slowing to more sustainable levels and is rebalancing, with consumption becoming the main growth driver. This transition is likely to have negative effects on its trading partners in the near term. This paper studies the potential spillovers to the ASEAN-5 economies through trade, commodity prices, and financial markets. It finds that countries with closer trade linkages with China (Malaysia, Singapore, and Thailand) and net commodity exporters (Indonesia and Malaysia) would suffer the largest impact, with growth falling between 0.2 and 0.5 percentage points in response to a decline in China's growth by 1 percentage point depending on the model used and the nature of the shock. The impact could be larger if China's slowdown and rebalancing coincides with bouts of global financial volatility. There are also opportunities from China's rebalancing, both in merchandise and services trade, and there is preliminary evidence that some ASEAN-5 economies are already benefiting from these trends.

Propagation of changes in demand through international trade: A case study of China

“…Furthermore, effects are stronger for countries more integrated into the regional supply chain (Dizioli et al, 2016;Hong et al, 2016), commodity exporters, and export-dependent countries (Inoue et al, 2015). Effects are also stronger when global financial volatility is higher (Dizioli et al, 2016;Cashin et al, 2016). Cesa-Bianchi et al (2011) find that due to the stronger integration of China into the world economy, the long-term impact of a GDP shock in China has tripled since 1990.…”

“…Some key elements, such as private consumption and investment, are modeled based on micro-foundations, while others elements, such as trade, labor supply, and inflation, have reduced-form representations. Estimations based on FSGM can be found in Anderson et al (2015) or Dizioli et al (2016), among others. As expected, the size of the effects in the two papers is very similar, although Anderson et al (2015) focus on Sub-Saharan Africa and Dizioli et al (2016) on ASEAN countries.…”

“…Most of these models include variables such as real GDP growth, inflation, real exchange rates, and short-and long-term interest rates. Additionally, some authors such as Cesa-Bianchi et al (2011), Dreger andZhang (2013) and Dizioli et al (2016) include equity prices. Dizioli et al (2016) and Cashin et al (2016) include financial variables, such as a financial stress index, along with the oil price.…”

“…Additionally, some authors such as Cesa-Bianchi et al (2011), Dreger andZhang (2013) and Dizioli et al (2016) include equity prices. Dizioli et al (2016) and Cashin et al (2016) include financial variables, such as a financial stress index, along with the oil price. The estimated effects for a demand shock of -1% of GDP in China vary between -0.05% and -0.12% of GDP for the EU, although the effects might not be exactly comparable.…”

“…Ahuja and Myrvoda (2012), or global vector autoregressive (GVAR) models, e.g. Dizioli et al (2016), Dreger and Zhang (2013), Hong et al (2016), Cesa-Bianchi et al (2011), Cashin et al (2016), or Inoue et al (2015 (see Table 1). Most of these models include variables such as real GDP growth, inflation, real exchange rates, and short-and long-term interest rates.…”