由“国美事件”对中国家族式企业管理文化的反思

国美事件是中国家族式企业发展中的一个具有典型意义的事件。国美事件的发生反映了传统家族企业管理文化与现代企业管理文化的矛盾和冲突,揭示了我国传统家族企业管理文化的特征及其存在的种种弊端。家族企业健康、可持续发展必须重构企业文化,实现管理文化创新。     

Random walk and efficiency tests in the Asia-Pacific foreign exchange markets: Evidence from the post-Asian currency crisis data

This paper empirically tests the random walk and efficiency hypothesis for 12 Asia-Pacific foreign exchange markets. The hypothesis is tested using individual as well as panel unit root tests and two variance-ratio tests. The study covers the high (daily) and medium (weekly) frequency post-Asian crisis spot exchange rate data from January 1998 to July 2007. The inferential outcomes do not differ substantially between the unit root tests and the variance-ratio tests when using daily data but differ significantly when using weekly data. With the daily data, both types of unit root tests identify unit root components for all the series and two variance-ratio tests provide the evidence of martingale behavior for majority of the exchange rates tested. With the weekly data, panel unit root tests identify unit root component for the exchange rates and, the unit root tests on a single series basis identify unit root component for 10 foreign exchange markets. However, the variance-ratio tests reject the martingale null for the majority of the exchange rates when using weekly data.     

基于BP神经网络的中、美贸易预测研究

根据中、美贸易的经济研究背景,分析中、美贸易重要影响指标,对其进行线性回归分析,发现中、美贸易额与各指标之间不是简单的线性相关,且各指标之间存在相互关系,所以不能用单一的线性回归模型进行预测。而BP神经网络具有非线性映射、自适应学习和良好的泛化能力等特征,运用BP神经网络模型对中、美贸易进行实证预测,大大提高了预测精度,取得了较好的效果。     

Stochastic Conditional Intensity Processes

In this article, we introduce the so-called stochastic conditionalintensity (SCI) model by extending Russell’s (1999) autoregressiveconditional intensity (ACI) model by a latent common dynamicfactor that jointly drives the individual intensity components.We show by simulations that the proposed model allows for awide range of (cross-)autocorrelation structures in multivariatepoint processes. The model is estimated by simulated maximumlikelihood (SML) using the efficient importance sampling (EIS)technique. By modeling price intensities based on NYSE trading,we provide significant evidence for a joint latent factor andshow that its inclusion allows for an improved and more parsimoniousspecification of the multivariate intensity process.     

Locally Most Powerful and Other Rank Tests for Independence – with a Contaminated Weighted Alternative

Several authors in the literature have attempted the quantification of the concept of stochastic dependence for bivariate distribution. Two weighted rank tests for testing independence against a weighted contamination alternative is proposed and their distributional properties are studied. We also derived a locally most powerful rank test for the alternative setting. The rank tests proposed are shown to be asymptotic locally most powerful for specific distributions.     

Underpricing,Share Overhang,and Insider Selling in Follow‐on Offerings

Prospect and information‐momentum theories predict that insiders can offer fewer shares in an initial public offering (IPO) to create informational momentum and obtain higher prices in follow‐on offerings. I find that dilution and insider participation in the IPO are negatively related to the number and size of follow‐on offerings, consistent with the prediction. However, insider selling in follow‐on offerings is positively related to IPO selling, contrary to the theories. Returns around follow‐on offering announcements are more negative for newly public firms than older firms, but for newly public firms do not differ by whether the announcement comes before or after the lockup expiration date.     

A multivariate Poisson mixture model for marketing applications

This paper describes a multivariate Poisson mixture model for clustering supermarket shoppers based on their purchase frequency in a set of product categories. The multivariate nature of the model accounts for cross-selling effects between the purchases made in different product categories. However, for computational reasons, most multivariate approaches limit the covariance structure by including just one common interaction term, or by not including any covariance at all. Although this reduces the number of parameters significantly, it is often too simplistic as typically multiple interactions exist on different levels. This paper proposes a theoretically more complete variance/covariance structure of the multivariate Poisson model, based on domain knowledge or preliminary statistical analysis of significant purchase interaction effects in the data. Consequently, the model does not contain more parameters than necessary, whilst still accounting for the existing covariance in the data. Practically, retail category managers can use the model to devise customized merchandising strategies.     

Testing Multiple Non-Nested Factor Demand Systems

This article explains how to obtain straightforward extensions of the most popular univariate non‐nested statistics, and of the RESET‐test, to a multivariate context and examines how to use these tests to compare alternative factor demand systems. The empirical application involves the classical Berndt–Khaled KLEM data set. A statistically adequate specification is determined for each competing factor demand system. The empirical results are interpreted for each system, the models are compared on the basis of multivariate paired and joint non‐nested procedures and practical indications about what to expect if these tests are applied to alternative factor demand specifications are provided.     

基于业务事件的网络财务报告披露模式研究

本文研究了网络财务报告披露模式问题。文章首先回顾和评价现有的关于网络财务报告披露模式的观点即经济事项模式、数据库报告模式、交换式按需报告模式以及多层面报告模式,在此基础上提出了业务事件驱动报告模式的基本原理。文章最后比较了业务事件驱动模式与经济事项模式的异同。     

Explaining Growth: A Contest Between Models

Recent contributions to the empirical growth literature show no tendency to convergence in specification, as researchers seek to identify new variables that can account for significant regional effects in earlier work. We conduct non-nested tests between the models of Barro (1997), Easterly and Levine (1997) and Sachs and Warner (1997). The data strongly prefer an encompassing model, but fail to reject any of the candidate models, implying that each model represents a partial truth. We identify a model that includes most (but not all) of the regressors in the candidate models and is robust to the inclusion of regional dummies.