A new approach to the identification of regional clusters: hierarchical clustering on principal components

This study focuses on the identification of regional business clusters as a primary step in the design and implementation of cluster-based development strategies. A methodology that has not been used previously to identify clusters is applied to data on inter-industry linkages from the input–output table of a region in northern Spain. The first advantage of this approach, hierarchical clustering on principal components (HCPC), over the use of factorial analysis alone, is that it involves the application of objective clustering techniques to the principal components analysis results, which leads to a better cluster solution. A second advantage is derived from using a mixed algorithm for the clustering process – a combination of the Ward’s classification method with the K-means algorithm – which improves the robustness of the final results.     

Exchangeability, Correlation, and Bayes' Effect

We examine the difference between Bayesian and frequentist statistics in making statements about the relationship between observable values. We show how standard models under both paradigms can be based on an assumption of exchangeability and we derive useful covariance and correlation results for values from an exchangeable sequence. We find that such values are never negatively correlated, and are generally positively correlated under the models used in Bayesian statistics. We discuss the significance of this result as well as a phenomenon which often follows from the differing methodologies and practical applications of these paradigms – a phenomenon we call Bayes' effect.     

Environmental–Economic Accounting: Progress and Digression in the SEEA Revisions

The 1992 Earth Summit and its message of sustainable development drove the launching of a System for integrated Environmental and Economic Accounting, the SEEA. Since then, sustainable development and the SEEA have given way to green growth and green economy indicators in the latest 2012 Summit. A lengthy revision process has now produced a curtailed “SEEA central framework.” The new framework focuses on expenditures for environmental protection and resource management, and stocks and flows of “economic” resources; both are covered by the conventional national accounts. Environmental degradation, notably from pollution, is left to “experimental” ecosystem accounts. Further revision of the SEEA should reverse this retrenchment from integrative environmental–economic accounting. A comprehensive satellite system, rather than a limited statistical standard, might put the SEEA back on the policy agenda.     

民间统计组织管理模式

最近几年,民间统计组织在中国已取得了快速的发展,它具有三种管理模式：完全不管、完全管制和适当管制。随着民间统计组织的发展、成熟和完善,政府应转变自己的角色和功能,应从“管理者”转变成“服务者”,并用“服务”模式取代“管制”模式。     

Decomposition of new venture growth into firm age,survey period and vintage effects

Firm data are accumulated on a yearly basis. In view of the linear relationship of firm age?+?foundation year?=?survey year, the fluctuations of firm data classified by age and period cannot be decomposed into age, period and cohort (foundation year) effects. Three decomposition methods are briefly reviewed and applied to Japanese data on new ventures founded since 1995. Regarding sales and employment growth, the age effect is the largest with a downward trend, and the cohort effect is negligible. Regarding labour productivity, the age effect indicates upward movements, and the cohort effect is negligible. The reason of the negligible cohort effect is discussed.     

Bayesian–Walrasian equilibria: beyond the rational expectations equilibrium

In general rational expectations equilibrium (REE), as introduced in Radner (Econometrica 47:655–678, 1978) in an Arrow–Debreu–McKenzie setting with uncertainty, does not exist. Moreover, it fails to be fully Pareto optimal and incentive compatible and is also not implementable as a perfect Bayesian equilibrium of an extensive form game (Glycopantis et al. in Econ Theory 26:765–791, 2005). The lack of all the above properties is mainly due to the fact that the agents are supposed to predict the equilibrium market clearing price (as agent’s expected maximized utility is conditioned on the information that equilibrium prices reveal), which leads inevitably to the presumption that agents know all the primitives in the economy, i.e., random initial endowments, random utility functions and private information sets. To get around this problematic equilibrium notion, we introduce a new concept called Bayesian–Walrasian equilibrium (BWE) which has Bayesian features. In particular, agents try to predict the market-clearing prices using Bayesian updating and evaluate their consumption in terms of Bayesian price estimates, which are different for each individual. In this framework agents maximize expected utility conditioned on their own private information about the state of nature, subject to a Bayesian estimated budget constraint. Market clearing is not an intrinsic part of the definition of BWE. However, both in the case of perfect foresight and in the case of symmetric information BWE leads to a statewise market clearing; it then becomes an ex post Walrasian equilibrium allocation. This new BWE exists under standard assumptions, in contrast to the REE. In particular, we show that our new BWE exists in the well-known example in Kreps (J Econ Theory 14:32–43, 1977), where REE fails to exist. This work was done in the Spring of 2005, when EJB was a visiting professor at the University of Illinois.     

基于贝叶斯网络方法的客户忠诚研究

提高客户忠诚是企业的核心原则。在与传统的数据挖掘及决策分析方法比较的基础上,提出了用贝叶斯网络方法来对客户忠诚进行研究。用贝叶斯网络方法对客户数据进行分析,确定影响客户忠诚的各因素之间的贝叶斯网络结构,得出这些因素之间的相互决定关系,为采取有效措施提高客户忠诚提供了理论依据。     

Modeling Disinterest and Dislike: A Bounded Bayesian Mixed Logit Model of the UK Market for GM Food

Mixed logit models represent a powerful discrete choice analytical model but require assumptions about the functional form of the parameter distributions. The use of unbounded distributions, such as the normal distribution, may be regarded as unsuitable where theory indicates that all are negatively affected by increases in an attribute, such as price. Bounded distributions such as the triangular and log-normal are unable to model the case where a section of the population is indifferent towards an attribute, while the remainder are negatively disposed toward it. Train and Sonnier’s bounded mixed logit model accommodates these features and is employed in this paper. A censored normal and Johnson’s S_b distribution are used to model preferences in the UK for food attributes, including price and GM technology. Bi-modal distributions are identified regarding GM food: some are unlikely to ever consume it, some are close to indifference and willing to consume at relatively small discounts while the remainder are fairly unresponsive to further price reductions.     

Simultaneous versus sequential information processing

Subjects update prior information simultaneously versus sequentially. The mean prediction is remarkably close to the correct Bayesian estimate with simultaneous information, but differs significantly conditional on whether good news precedes bad news or vice versa.