The role of cross-market linkages in the occurrence of tail events in stock and energy markets has not yet been fully understood in the contagion literature. This paper investigates the contagion from oil prices to Chinese stock sectors by considering differences between extreme positive returns and extreme negative returns. We compute time-varying cutoffs by employing a generalized Pareto distribution (GPD) function to estimate excess returns. We then use a multinomial logit (MNL) model to examine the probability of Chinese stock sector co-exceedances associated with oil price exceedances. Our results indicate that, compared to common domestic factors, the contagion between oil price and stock sectors is relatively weak, but never negligible. We argue that faced with volatile oil prices during turbulent periods, the existence of any contagion weakens the benefits of portfolio diversification related to oil and Chinese stock sector investment. Based on our findings, investors holding a portfolio of oil and Chinese sector stocks should pay special attention to the extreme changes in crude oil prices and adopt hedging measures to protect their portfolio from extreme shocks to oil markets.

This paper estimates augmented versions of the Investment-Saving curve for the People's Republic of China in an attempt to examine the relationship between monetary policy and the real economy. It endeavors to account for any structural break, nonlinearity, or asymmetry in the transmission process by estimating a breakpoint model and a Markov switching model. The Investment-Saving curve equations are estimated using a Monetary Policy Index, which has been calculated using the Kalman filter. This index will account for the various monetary policy tools, both quantitative and qualitative, that the People's Bank of China has used over the period 1991-2014. The results of this paper suggest that monetary policy has an asymmetric affect depending on the level of output in relation to potential, and that the People's Republic of China's exchange rate policy has restricted the effectiveness of the People's Bank of China's monetary policy response.

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This paper models inflation dynamics in China from 1987-2014 using a Phillips curve framework. The Phillips curve is generally estimated under the assumption of linearity and parameter constancy. The existence of structural breaks in China's inflation dynamics make standard linear models inappropriate tools for analysis however. Our results find that the Chinese Phillips curve is characterised by a non-linear relationship. The inflation/output relationship takes the form of a concave curve. This suggests that changes in the level of output effect inflation in China more strongly in periods when output is operating below its potential but the relationship is weaker when output is operating at or above potential. Based on these findings, the People's Bank of China (PBC) could consider output cost and policy response on a case by case basis depending on the level of output in relation to potential.

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This paper estimates a monetary policy rule for the People's Republic of China (PRC) using a standard OLS estimation and a Markov switching model. As the People's Bank of China (PBOC) generally uses a battery of instruments in the conduct of its monetary policy, these models are estimated using a constructed monetary policy index (MPI) in place of the traditional interest rate.This allows for a better understanding of the role the PBOC has played in the PRC's unprecedented economic growth and its relatively low inflation over the last twenty years. This paper will not only examine the unique characteristics of Chinese monetary policy but may also give a more general insight into the dynamics of monetary policy reactions in other emerging markets and economies in transition.

Research in the area of tail dependence between oil prices and the stock market is sparse, particularly at the firm level. This article investigates lower and upper tail dependences between the price of crude oil and China's A‐share market by estimating an empirical copula with a rolling window. Our results show that tail dependence is increasing over time and that there are differences between lower and upper tail dependences in terms of incremental magnitude. We also find that the impulse responses of tail dependences to shocks to variables of interests vary significantly over the sample period. Our results also indicate that lower tail dependence, in particular, is found to have more than one breakpoint, and the break dates are highly associated with financial crises. In addition, we find evidence of asymmetry in tail dependence, which varies across periods. Finally, we find that tail dependence is persistent in the short‐term but deteriorates as the duration increases. These findings have important implications for investors, risk managers and policy makers.

The present study investigates the influence of international oil prices on China's stock market returns across 29 different industries. The paper attempts to account for any structural breaks and nonlinearity in this relationship. The results reveal that the effect of changes in the international price of oil on stock returns differs substantially across industries. The stock returns of the coal, chemical, mining and oil industries are found to be positively affected by crude oil price movements. Conversely, electronics, food manufacturing, general equipment, pharmaceuticals, retail, rubber and vehicle industries are found to be negatively affected by movements in the price of crude oil. The results of the estimations also suggest that the majority of Chinese industries have been significantly affected by oil prices since 2004. The influence of international oil prices on Chinese stocks also has a stronger effect in the presence of high volatility but the effect varies across industries.