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We investigate the dynamic evolution of the price discovery function in Chinese agricultural futures markets using a newly developed rolling window cointegration approach. The results show that, compared with wheat and rice, the futures-spot cointegration relationship in the soybean and corn markets tends to be more durable and frequent. Dynamic cointegration analysis indicates that the recent market-oriented reforms in China have boosted the price discovery function of soybean and corn futures markets, whereas price stabilization policies tend to weaken the price discovery function of futures markets. The difference in price discovery function is attributed to differences in market mechanisms and Chinese agricultural policies.

Type-II censored data is an important scheme of data in lifetime studies. The purpose of this paper is to obtain E-Bayesian predictive functions which are based on observed order statistics with two samples from two parameter Burr XII model. Predictive functions are developed to derive both point prediction and interval prediction based on type-II censored data, where the median Bayesian estimation is a novel formulation to get Bayesian sample prediction, as the integral for calculating the Bayesian prediction directly does not exist. All kinds of predictions are obtained with symmetric and asymmetric loss functions. Two sample techniques are considered, and gamma conjugate prior density is assumed. Illustrative examples are provided for all the scenarios considered in this article. Both illustrative examples with real data and the Monte Carlo simulation are carried out to show the new method is acceptable. The results show that Bayesian and E-Bayesian predictions with the two kinds of loss functions have little difference for the point prediction, and E-Bayesian confidence interval (CI) with the two kinds of loss functions are almost similar and they are more accurate for the interval prediction.

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