Shareholder Value Creation in European M&As

This paper looks at the value generated to shareholders by the announcement of mergers and acquisitions involving firms in the European Union over the period 1998–2000. Cumulative abnormal shareholder returns due to the announcement of a merger reflect a revision of the expected value resulting from future synergies or wealth redistribution among stakeholders. Target firm shareholders receive on average a statistically significant cumulative abnormal return of 9% in a one‐month window centred on the announcement date. Acquirers’ cumulative abnormal returns are null on average. When distinguishing in terms of the geographical and sectoral dimensions of the merger deals, our main finding is that mergers in industries that had previously been under government control or that are still heavily regulated generate lower value than M&A announcements in unregulated industries. This low value creation in regulated industries becomes significantly negative when the merger involves two firms from different countries and is primarily due to the lower positive return that shareholders of the target firm enjoy upon the announcement of the merger. This evidence is consistent with the existence of obstacles (such as cultural, legal, or transaction barriers) to the successful conclusion of this type of transaction, which lessen the probability of the merger actually being completed as announced and, therefore, reduce its expected value.     

Analysing Perceived Downside Risk: the Component Value‐at‐Risk Framework

Multinational companies face increasing risks arising from external risk factors, e.g. exchange rates, interest rates and commodity prices, which they have learned to hedge using derivatives. However, despite increasing disclosure requirements, a firm's net risk profile may not be transparent to shareholders. We develop the ‘Component Value‐at‐Risk (VaR)’ framework for companies to identify the multi‐dimensional downside risk profile as perceived by shareholders. This framework allows for decomposing downside risk into components that are attributable to each of the underlying risk factors. The firm can compare this perceived VaR, including its composition and dynamics, to an internal VaR based on net exposures as it is known to the company. Any differences may lead to surprises at times of earnings announcements and thus constitute a litigation threat to the firm. It may reduce this information asymmetry through targeted communication efforts.     

中小企业股票市场化发行定价的半参数自组织模型与实证

随着深圳交易所中小企业板块的正式启动，我国中小企业新股发行的市场化定价方式必将启用。本文采用基于自组织数据挖掘GMDH算法的半参数模型的定价方法，将GMDH算法与半参数模型方法结合起来。不仅利用计算机的自动拟合优选最优复杂度模型，从而大大简化了非参数部分估计。创造了半参数模型崭新的实现方式，并达到了理想的定价效果，而且可以发挥半参数模型的特有优势。进行模型结构分析。经过实证和检验证明了这种模型用于我国股票发行定价的有效性和合理性。为完全市场化股票发行方式下确定股票的发行价格提供了新的方法。     

Use of Statistics in the Monetary Policy of the Czech National Bank: The Case of a Country in Transition

In the presented text the authors judge the importance of statistics in the monetary policy of the Czech National Bank (CNB) over the course of the economic transformation process, with particular consideration of changing statistical needs and the possibilities and limits of statistical data exploitation in the monetary analyses. The importance of statistics lies on the level of collection and processing of statistical information and on the level of use of statistical methods to analyse data. Since the start of the 1990s the requirements for statistics were significantly influenced by monetary policy. In the period 1990–1997, monetary targeting was the primary influential factor. Since 1998, the monetary policy is influenced by inflation targeting. Statistical priorities switched from monetary data to economy and financial market data. Much progress has been made in the use of statistical methods for analysing data. Statistics available at present cover the CNB's standard monetary-policy requirements and are on par with those in developed countries. Its further development will reflect the standard changes taking place in the more advanced countries.     

Aspects of statistical analysis in DEA-type frontier models

In Grosskopf (1995) and Banker (1995) different approaches and problems of statistical inference in DEA frontier models are presented. This paper focuses on the basic characteristics of DEA models from a statistical point of view. It arose from comments and discussions on both papers above. The framework of DEA models is deterministic (all the observed points lie on the same side of the frontier), nevertheless a stochastic model can be constructed once a data generating process is defined. So statistical analysis may be performed and sampling properties of DEA estimators can be established. However, practical statistical inference (such as test of hypothesis, confidence intervals) still needs artifacts like the bootstrap to be performed. A consistent bootstrap relies also on a clear definition of the data generating proces and on a consistent estimator of it: The approach of Simar and Wilson (1995) is described. Finally, some trails are proposed for introducing stochastic noise in DEA models, in the spirit of the Kneip-Simar (1995) approach.     

The Measurement of Consumption Efficiency Considering the Discrete Choice of Consumers

In this study we propose a mathematical definition of the consumption efficiency of multi-attribute products in the price–quality space. A new model, the discrete Range Adjusted Measure (RAM) model, is suggested as an empirical tool to measure the level of consumption efficiency. We further discuss the effect of consumption efficiency on the innovation incentive. Empirical work is made for the mobile phone market. We expect that the consumption efficiency concept will contribute to the extension of the traditional framework of production efficiency analysis on the one hand and to the understanding of the nature of innovation in a technology-intensive market on the other hand.JEL Classification: C67, D11, D12, D21     

Blocked-Error-R 2: A Conceptually Improved Definition of the Proportion of Explained Variance in Models Containing Loops or Correlated Residuals

Bentler and Raykov (2000, Journal of Applied Psychology 85: 125–131), and Jöreskog (1999a, http://www.ssicentral.com/lisrel/column3.htm, 1999b http://www.ssicentral. com/lisrel/column5.htm) proposed procedures for calculating R ² for dependent variables involved in loops or possessing correlated errors. This article demonstrates that Bentler and Raykov’s procedure can not be routinely interpreted as a “proportion” of explained variance, while Jöreskog’s reduced-form calculation is unnecessarily restrictive. The new blocked-error-R ² (beR ²) uses a minimal hypothetical causal intervention to resolve the variance-partitioning ambiguities created by loops and correlated errors. Hayduk (1996) discussed how stabilising feedback models – models capable of counteracting external perturbations – can result in an acceptable error variance which exceeds the variance of the dependent variable to which that error is attached. For variables included within loops, whether stabilising or not, beR ² provides the same value as Hayduk’s (1996) loop-adjusted-R ². For variables not involved in loops and not displaying correlated residuals, beR ² reports the same value as the traditional regression R ². Thus, beR ² provides a conceptualisation of the proportion of explained variance that spans both recursive and nonrecursive structural equation models. A procedure for calculating beR ² in any SEM program is provided.     

企业资产结构的影响因素及模式研究

资产结构是指企业资本在不同资产形态上分布状况及分配比例。资产结构一般具有整体性、封闭性、动态性等特征;资产结构的形成受到诸多内外部因素的影响。本文研究了影响企业资产结构的因素,分析了资产结构的类型,并根据资产变现性的特征,将资产结构模式分为三种类型。     

The relationship between major-league sports’ official sponsorship announcements and the stock prices of sponsoring firms

This study presents analysis of the impact of “official product” sports sponsorships with the National Football League (NFL), Major League Baseball (MLB), the National Hockey League (NHL), the National Basketball Association (NBA), and the Professional Golfers Association (PGA) on the stock prices of sponsoring firms. The primary finding of the study is that, in the main, announcements were accompanied by increases in shareholder wealth. The 53 sponsors analyzed experienced mean increases in stock valuations of about $257 million. A multiple regression analysis of firm-specific stock price changes and selected corporate and sponsorship attributes indicates that official product sponsorships with the NBA, NHL, and PGA and those with smaller market shares were associated with the largest gains in share prices. Although corporate cashflow (a proxy for agency conflicts) is statistically unrelated to shareholder approval, sponsorships by high-technology companies were associated with stronger stock price reactions than otherwise. Finally, product congruence with the sponsored sport was positively related to changes in stock prices. T. Bettina Cornwell (b.cornwell@business.uq.edu.au) is Professor of Marketing and Leader of the Marketing cluster in the UQ Business School at the University of Queensland, Australia. She was formerly Professor of Marketing in the Fogelman College of Business and Economics at the University of Memphis. She received her Ph.D. from the University of Texas. Her research focuses on promotion and consumer behavior, especially with regard to international and public policy issues. Other articles on the topic of sponsorship-linked marketing have recently appeared in theJournal of Advertising, the Journal of Advertising Research, theJournal of Business Research, andPsychology & Marketing. Stephen W. Pruitt (pruittst@umkc.edu) is the holder of the Arvin Gottlieb/Missouri Endowed Chair of Business Economics and Finance in the Henry W. Bloch School of Business and Public Administration at the University of Missouri-Kansas City. He received his Ph.D. from Florida State University. He has published more than 45 articles, most of which employ event study methodologies, in journals such as theJournal of Finance, theJournal of Political Economy, Financial Management, theJournal of Public Policy and Marketing, and theJournal of Advertising Research. John M. Clark (clarkj@cba.usm.edu) is an assistant professor of finance at the University of Southern Mississippi. He received his Ph.D. from the University of Alabama. His research interests include options and other derivatives, investments, and the impact of real events upon the stock prices of corporations. His work has appeared in scholarly outlets such as theJournal of Advertising Research, theFinancial Review, and theJournal of Business Ethics.     

应用期权方法构建商业银行贷款利率模型

以分析公司普通股所具有的看涨期权特性为出发点，以Black—Scholes看涨期权定价模型为基础，根据不同企业资本结构和资产回报风险的差别，构造了一个商业银行基本贷款利率模型。从期权角度来设计贷款利率模型，除考虑了企业的经营风险因责外，还同时考虑了企业融资结构所带来的财务风险，能更加全面地反映出商业银行贷款的保障程度。