工业企业提高能源统计数据质量的方法浅析

在当前的国民经济核算中,能源统计是非常重要的组成部分,能源统计数据的质量将直接影响对我国国民经济的核算,对制定宏观调控政策及相关的能源政策都会产生不同程度的影响。所以,针对我国的能源统计工作需要不断强化落实并完善有关的管理办法。论文在介绍加强能源统计管理的重要性的基础上,分析了工业企业能源统计管理的成效和问题,提出了提升工业企业能源统计数据质量的方法,以期提升能源统计工作的质量。     

我国纳米压印光刻技术专利态势分析

由于具有高分辨率、高产量、低成本等特点,纳米压印光刻技术被IC业界认为是最具发展前景的下一代光刻技术之一。本文旨在通过对纳米压印光刻技术中国专利申请进行统计分析,为我国进行具有自主知识产权的纳米压印光刻技术研发和制定有效的专利战略提供参考。     

How to Construct a Random Probability Measure

This article presents an overview of several constructive methods for generating random probability measures. Applications of random probability measures include Bayesian statistics, average optimal control problems, average error bounds for numerical equation solving methods, and models for random distributions of mass in space.     

Tendency to Infer Bribery and Corrupt Intent in Social and Business Situations: Comparing Chinese and Singaporean Employees

The present paper investigates the differences in ethicalperceptions between Chinese and Singaporean employees. Twocontrasting predictions based on socialization theory are testedusing 142 Chinese and 141 Singaporean employees as subjects. Results show that Chinese employees tend to infer a greaterdegree of unethical (bribery and corrupt) intent than Singaporeanemployees in 17 of the 25 ethical vignettes. The converse isfound in only two and no significant differences are found in therest of the vignettes. Implications for international managersand assignees and researchers in international business workingon or in China are discussed.     

Methods for Default and Robust Bayesian Model Comparison: the Fractional Bayes Factor Approach

In the Bayesian approach to model selection and hypothesis testing, the Bayes factor plays a central role. However, the Bayes factor is very sensitive to prior distributions of parameters. This is a problem especially in the presence of weak prior information on the parameters of the models. The most radical consequence of this fact is that the Bayes factor is undetermined when improper priors are used. Nonetheless, extending the non-informative approach of Bayesian analysis to model selection/testing procedures is important both from a theoretical and an applied viewpoint. The need to develop automatic and robust methods for model comparison has led to the introduction of several alternative Bayes factors. In this paper we review one of these methods: the fractional Bayes factor (O'Hagan, 1995). We discuss general properties of the method, such as consistency and coherence. Furthermore, in addition to the original, essentially asymptotic justifications of the fractional Bayes factor, we provide further finite-sample motivations for its use. Connections and comparisons to other automatic methods are discussed and several issues of robustness with respect to priors and data are considered. Finally, we focus on some open problems in the fractional Bayes factor approach, and outline some possible answers and directions for future research.     

Proposals for a Minimum Programme for Statistics in Developing Countries

Statistical offices in developing countries are confronted with the challenge of introducing, with limited means, methods and tools ensuring the production of durable statistics satisfying regional, national and international requirements. Taking into account the evolution, over the last years, in the attitude of national authorities, funding partners and statisticians themselves regarding the building up of relevant and durable statistics, the present paper's proposal is to have, in each developing country, a Minimum Programme for Statistics (MPS) and that this programme be centred on four domains: coordination, national accounts, economic and social short term analysis, and dissemination.     

Bayesian modeling of joint and conditional distributions

In this paper, we study a Bayesian approach to flexible modeling of conditional distributions. The approach uses a flexible model for the joint distribution of the dependent and independent variables and then extracts the conditional distributions of interest from the estimated joint distribution. We use a finite mixture of multivariate normals (FMMN) to estimate the joint distribution. The conditional distributions can then be assessed analytically or through simulations. The discrete variables are handled through the use of latent variables. The estimation procedure employs an MCMC algorithm. We provide a characterization of the Kullback–Leibler closure of FMMN and show that the joint and conditional predictive densities implied by the FMMN model are consistent estimators for a large class of data generating processes with continuous and discrete observables. The method can be used as a robust regression model with discrete and continuous dependent and independent variables and as a Bayesian alternative to semi- and non-parametric models such as quantile and kernel regression. In experiments, the method compares favorably with classical nonparametric and alternative Bayesian methods.     

Governance, Democracy and Poverty Reduction: Lessons Drawn from Household Surveys in Sub-Saharan Africa and Latin America

Public statistics face quite a challenge when it comes to measuring new dimensions of development (institutions, governance, and social and political participation). To take up this challenge, modules on Governance, Democracy and Multiple Dimensions of Poverty have been appended to household surveys by National Statistics Institutes in twelve African and Latin American developing countries. This paper presents the issues addressed and the methodological lessons learnt along with a selection of findings to illustrate this innovative approach and demonstrate its analytic potential. We investigate, for instance, the population's support for democratic principles, the respect for civil and political rights and the trust in the political class; the ‘need for the State’, particularly of the poorest; the extent of petty corruption; the reliability of expert surveys on governance; the perception of decentralization policies at local level; the level and vitality of social and political participation, etc. The conclusive appraisal made opens up prospects for the national statistical information systems in the developing countries. The measurement and tracking of this new set of objective and subjective public policy monitoring indicators would benefit from being made systematic.     

THEORY AND PRACTICE OF DECENTRALIZED PLANNING PROCEDURES

Abstract. The paper surveys the theory of decentralized planning procedures, dealing with price-guided, quantity-guided and mixed procedures. Informational and incentive properties of the various procedures are dealt with, as is the problem of public goods. The practice of planning in the USSR, Hungary and India is also discussed.     

The use of logit and probit models in strategic management research: Critical issues

The logit and probit models have become critical parts of the management researcher's analytical arsenal, growing rapidly from almost no use in the 1980s to appearing in 15% of all articles published in Strategic Management Journal in 2005. However, a review of three top strategy journals revealed numerous areas in their use and interpretation where current practice fell short of ideal. Failure to understand how these models differ from ordinary least squares can lead researchers to misunderstand their statistical results and draw incorrect conclusions regarding the theory they are testing. Based on a review of the methodological literature and recent empirical papers in three leading strategy journals, this paper identifies four critical issues in their use: interpreting coefficients, modeling interactions between variables, comparing coefficients between groups (e.g., foreign and domestic firms), and measures of model fit. For each issue, the paper provides a background, a review of current practice, and recommendations for best practice. A concluding section presents overall implications for the conduct of research with logit and probit models, which should assist both authors and readers of strategic management research. Copyright © 2007 John Wiley & Sons, Ltd.