创建有效的学校文化提高学校效能

本文在解析有效学校文化结构的基础上,提出了创建有效学校文化的＂DIEP＂路径模式,并从建设精神文化、制度与行为文化和物质文化三个方面提出了相应的策略。     

基于有效治理的复合民主:中国民主成长的可能方式

既要顺应民主的潮流,落实民主的普适价值,又要切实应对巨型国家治理的种种现实难题,政治发展的特殊境遇,决定了有效治理乃是中国民主政治建设合乎逻辑的现实目标和基本准则.基于有效治理的民主实践不会拘泥于现有的民主制度形式,而很可能会在长期的试错性探索过程中,将各种有效的民主实现形式吸纳和整合到国家治理过程之中,形成一种复合型的民主政治体系.     

Monetary policy,trade-offs and the transmission of UK Monetary Policy

We provide a new method to model changes in monetary policy of the Bank of England (BoE) as well as the impact of these changes on UK economy. This is important as central bankers have widened the range of instruments in their monetary policy toolbox. Specifically, we estimate a proxy for the monetary policy stance and then analyse a time-varying parameter vector autoregressive with stochastic volatility model to explain the BoE’s trade-offs when making policy decisions and as well as to demonstrate dynamic impacts of monetary policy on inflation and economic growth. The empirical results show that our estimated monetary policy proxy is better at capturing the BoE’s policy when the interest rate lower bound becomes binding.     

外商在华投资的独资化倾向及对策研究

近年来,跨国公司在华企业呈现出明显的独资化倾向。本文在对海外直接投资进入模式影响因素进行分析的基础上,从宏观和微观两个层面探讨了跨国公司在华企业的独资化发展的成因,分析了这种倾向对我国经济技术发展与企业成长所带来的机遇及挑战,并提出了相应的策略和政策建议。     

扩大消费需求的障碍因素及有效途径分析

中国经济连续十几年保持高速的增长,但从总需求的角度进行分析,需求结构不尽合理,经济持续增长受到影响。随着美国引发的次贷危机和世界性金融危机的逐渐漫延和加深,全球经济正在步入衰退,中国经济增长受到一定程度的影响,因此,研究扩大消费需求的障碍因素,探讨扩大消费需求的有效途径十分必要。     

On learning strategies for evolutionary Monte Carlo

The real-parameter evolutionary Monte Carlo algorithm (EMC) has been proposed as an effective tool both for sampling from high-dimensional distributions and for stochastic optimization (Liang and Wong, 2001). EMC uses a temperature ladder similar to that in parallel tempering (PT; Geyer, 1991). In contrast with PT, EMC allows for crossover moves between parallel and tempered MCMC chains. In the context of EMC, we introduce four new moves, which enhance its efficiency as measured by the effective sample size. Secondly, we introduce a practical strategy for determining the temperature range and placing the temperatures in the ladder used in EMC and PT. Lastly, we prove the validity of the conditional sampling step of the snooker algorithm, a crossover move in EMC, which extends a result of Roberts and Gilks (1994).     

Data-driven smooth tests for the extreme value distribution

In this paper we present data-driven smooth tests for the extreme value distribution. These tests are based on a general idea of construction of data-driven smooth tests for composite hypotheses introduced by Inglot, T., Kallenberg, W. C. M. and Ledwina, T. [(1997). Data-driven smooth tests for composite hypotheses. Ann. Statist., 25, 1222–1250] and its modification for location-scale family proposed in Janic-Wróblewska, A. [(2004). Data-driven smooth test for a location-scale family. Statistics, in press]. Results of power simulations show that the newly introduced test performs very well for a wide range of alternatives and is competitive with other commonly used tests for the extreme value distribution.     

Starting Values for EM Estimation of Latent Class Joint Model

Latent class model is one of the important latent variable methods for joint modeling longitudinal and survival data. Latent class joint model can handle underlying heterogeneous population, discover subpopulation structure, and incorporate correlated non normally distributed outcomes. The maximum likelihood estimates of parameters in latent class joint model are generally obtained by the EM algorithm. Finding the starting values is one of the major issues to implement the EM algorithm successfully. In this article, initial value formulas are provided, a simulation study is conducted to show that the proposed starting values perform very well, and two illustrative examples are presented.     

Confidence Intervals for Survival Probabilities: A Comparison Study

The confidence interval of the Kaplan–Meier estimate of the survival probability at a fixed time point is often constructed by the Greenwood formula. This normal approximation-based method can be looked as a Wald type confidence interval for a binomial proportion, the survival probability, using the “effective” sample size defined by Cutler and Ederer. Wald-type binomial confidence interval has been shown to perform poorly comparing to other methods. We choose three methods of binomial confidence intervals for the construction of confidence interval for survival probability: Wilson's method, Agresti–Coull's method, and higher-order asymptotic likelihood method. The methods of “effective” sample size proposed by Peto et al. and Dorey and Korn are also considered. The Greenwood formula is far from satisfactory, while confidence intervals based on the three methods of binomial proportion using Cutler and Ederer's “effective” sample size have much better performance.     

A Note on Sufficient Conditions for Valid Unmodified t Testing in Correlation Analysis with Autocorrelated and Heteroscedastic Sample Data

Traditionally, sphericity (i.e., independence and homoscedasticity for raw data) is put forward as the condition to be satisfied by the variance–covariance matrix of at least one of the two observation vectors analyzed for correlation, for the unmodified t test of significance to be valid under the Gaussian and constant population mean assumptions. In this article, the author proves that the sphericity condition is too strong and a weaker (i.e., more general) sufficient condition for valid unmodified t testing in correlation analysis is circularity (i.e., independence and homoscedasticity after linear transformation by orthonormal contrasts), to be satisfied by the variance–covariance matrix of one of the two observation vectors. Two other conditions (i.e., compound symmetry for one of the two observation vectors; absence of correlation between the components of one observation vector, combined with a particular pattern of joint heteroscedasticity in the two observation vectors) are also considered and discussed. When both observation vectors possess the same variance–covariance matrix up to a positive multiplicative constant, the circularity condition is shown to be necessary and sufficient. “Observation vectors” may designate partial realizations of temporal or spatial stochastic processes as well as profile vectors of repeated measures. From the proof, it follows that an effective sample size appropriately defined can measure the discrepancy from the more general sufficient condition for valid unmodified t testing in correlation analysis with autocorrelated and heteroscedastic sample data. The proof is complemented by a simulation study. Finally, the differences between the role of the circularity condition in the correlation analysis and its role in the repeated measures ANOVA (i.e., where it was first introduced) are scrutinized, and the link between the circular variance–covariance structure and the centering of observations with respect to the sample mean is emphasized.