Introduction

The research paper by Ratti and Vespignani (2013), "Liquidity and crude oil prices: China's influence over 1996–2011", published in Economic Modelling, explores the dynamism between liquidity measures and the price of crude oil, with a particular focus on the role of China. The paper is particularly significant given China's emergence as a major player in global energy markets. This analysis aims to summarize, critique, and provide insights into the methodologies and findings of Ratti and Vespignani's work, considering its implications for both the academic community and policymakers.

Literature Review

The relationship between liquidity and commodity prices has been a topic of considerable interest. Previous studies (for instance, Frankel, 2006; Hamilton, 2009) have pointed to various macroeconomic factors affecting oil prices. However, the unique contribution of Ratti and Vespignani (2013) lies in the explicit consideration of China's liquidity measures and their impact on crude oil prices, thereby filling a notable gap in the literature.

Methodology

Ratti and Vespignani employ a Vector AutoRegression (VAR) model to analyze the interactions between various forms of liquidity (global liquidity, China's liquidity, and OECD liquidity) and crude oil prices from January 1996 to October 2011. The VAR model is particularly apt for such analysis due to its ability to capture the linear interdependencies among multiple time series.

Key variables under consideration include:

• Crude oil prices
• China's liquidity (represented by China's M2 money supply)
• Global liquidity
• OECD liquidity

The study uses monthly data, which allows for the examination of both short-term and long-term dynamics.

Key Findings

Ratti and Vespignani find that:

1. China’s Liquidity: China's liquidity has a significant impact on crude oil prices. An increase in China's money supply leads to an increase in oil prices. This finding underscores China's growing influence in global commodity markets.
2. Global and OECD Liquidity: Both global liquidity and OECD liquidity also have significant impacts on oil prices, although the effect of global liquidity is more pronounced than that of OECD countries.
3. Impulse Response Functions: The impulse response functions indicate that a shock to China's liquidity results in a substantial and persistent increase in oil prices, reinforcing the role of Chinese monetary policy in global commodity markets.
4. Variance Decomposition: Variance decomposition analysis shows that changes in China's liquidity account for a significant proportion of the forecast error variance of oil prices, more so than the liquidity from OECD countries.

Critical Analysis

While the paper provides valuable insights, some areas warrant further discussion. Firstly, the choice of VAR models assumes linearity, which might oversimplify the complex nature of the relationship between liquidity and oil prices. Nonlinear models or regime-switching models (as used in the recent academic paper by Bjørnland et al., 2017) might capture the dynamics more effectively.

Secondly, while the timeframe (1996–2011) is robust, an extension or comparison with more recent data could update the findings, considering that China's economic policies and global oil market conditions have evolved significantly post-2011.

Implications

For Academicians: The study by Ratti and Vespignani provides a strong foundation for further research on the economic influence of emerging markets on commodity prices. It also adds to the methodological literature by demonstrating the application of VAR models in understanding macroeconomic variables' interplay.

For Policymakers: The findings suggest that global oil prices are sensitive to changes in China's monetary policy. Hence, policymakers in oil-producing and consuming countries should closely monitor Chinese liquidity measures as part of their economic strategy.

Conclusion

Ratti and Vespignani's (2013) paper makes a significant contribution by highlighting the impact of China's liquidity on global crude oil prices. The study's robust use of VAR models to analyze the data provides clear evidence of China's growing economic influence. Nonetheless, future research could extend these findings by incorporating more recent data and exploring nonlinear relationships.

References

Ratti, R.A., & Vespignani, J.L. (2013). Liquidity and crude oil prices: China's influence over 1996–2011. Economic Modelling, 33, 517-525.