How do US investors perceive the risk of local political corruption? Evidence from acquisition announcement

This study examines the impact of local political corruption on investors’ evaluation of firms’ mergers and acquisitions (M&As) in the US. Using the number of corruption convictions of government officials reported by the US Department of Justice, we find that acquirers in more corrupt court districts experience lower acquirer announcement returns, lower combined acquirer and target announcement returns, and are less likely to complete acquisitions. We further find that the relation between local political corruption and acquirer announcement returns is worsened when acquirers operate primarily in the headquarters state. Overall, the results suggest that local political corruption has an adverse impact on investors’ evaluation of a firm’s M&A profitability.     

A Unifying Framework for Marginalised Random‐Intercept Models of Correlated Binary Outcomes

We demonstrate that many current approaches for marginal modelling of correlated binary outcomes produce likelihoods that are equivalent to the copula‐based models herein. These general copula models of underlying latent threshold random variables yield likelihood‐based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data with exchangeable correlation structures. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalised random‐intercept models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts. Copyright © 2013 John Wiley & Sons, Ltd.     

观察中国市场转型的一个新角度:地方政府与老字号企业的“伞式”关系

从"伞式关系"的视角探讨"市场转型"中政府与老字号企业的关系,认为在市场转型过程中,尽管未来"全面深化改革"的目标和方向是市场或市场主体起决定性作用,政府主要充当"裁判员"的角色。但是,在"官本位"和属地经济体制下,政府与老字号企业的关系模式特征依然是原有的"庇护"与"被庇护"的伞式关系。这种关系是一种重要的资源配置方式,在一定程度上,可能比企业的市场开拓能力还重要。如何更科学地认识这种"伞式"关系,既要看到它的现实合理性,也要看到它的历史局限性,以便进一步优化各项社会资源的配置。地方政府与企业之间的这种"伞式"关系,是一个亟待认真研究和解决的重大问题,需要政府、老字号企业以及其他相关方面深入思考,探寻有价值的对策。     

Local Action Groups and Rural Sustainable Development. A spatial multiple criteria approach for efficient territorial planning

Rural Sustainable Development is a very important topic under the European Union policy, and it is currently promoted through the European Agricultural Fund for Rural Development 2014–2020. This fund is managed at sub-regional level by the Community-Led Local Development approach that involves Local Action Groups in order to promote the objectives of Rural Sustainable Development within rural municipalities. Each Local Action Group applies the Strengths, Weaknesses, Opportunities and Threats analysis in order to identify for its own rural municipalities the strategic elements to which it will allocate the European Agricultural Fund for Rural Development budget. Nevertheless, this analysis has some general shortcomings, including difficulties in managing a large number of Strength and Weakness factors. In addition, the importance of each factor cannot be measured quantitatively, and the same factor may be characterized both as a Strength and a Weakness. Further difficulties may occur in the case of partnerships between different Local Action Groups, such as disagreement about whether a given factor is a Strength or a Weakness, lack of information about the relationships between Strength and a Weakness factors and decision alternatives, as well as impossibility of ranking the decision alternatives.Thus, this research aims to overcome the drawbacks of the Strengths, Weaknesses, Opportunities and Threats analysis and to support Local Action Group partnerships in the sustainability evaluation of their rural municipalities, and therefore to aid the identification of a common Rural Sustainable Development strategy to allocate the European Agricultural Fund for Rural Development budget. This decision problem was tackled by applying a Multiple Criteria Spatial Decision Support System that integrates a Geographic Information System with the Multiple Criteria Decision Aiding methods “Technique for Order Preference by Similarity to Ideal Solution” and “Dominance-based Rough Set Approach”.In order to demonstrate the validity of this methodological approach, this Multiple Criteria Spatial Decision Support System was applied to a study area of thirteen rural municipalities located in Apulia Region (Southern Italy); these municipalities belong to the same landscape unit, but they are managed by five different policy makers that represent the Local Action Groups. The results provided the maps of environmental, economic and social sustainability rankings of rural municipalities as well as their overall sustainability value. Based on these rankings, a specific Rural Sustainable Development strategy was identified for the allocation of the European Agricultural Fund for Rural Development. This methodology provided a common decision making framework that can also be applied to Local Action Group partnerships within the European Union.     

政府安全管制有效吗?——基于2002—2009年省级面板数据的实证分析

基于2002—2009年省级面板数据，构建模型分析了政府罚款、检查单位数、使用执法文书等政府安全管制工具对抑制生产安全事故以及死亡率的影响，这些安全管制执法指标存在随机缺失值，为提高预测精度和统计效力，利用极大似然法(Maximum Likelihood,ML)处理缺头值，得到参数无偏估计量。实证结果表明：政府安全执法对于遏制事故起数和死亡率均无显著效果。而职工素质对事故起数和死亡率都具有显著抑制作用，工人素质每提高1％，事故起数平均下降超过1％，亿元GDP死亡人数降低约0.008人。安全投入仅有助于减少事故发生频率，但对于死亡率没有显著影响，安全投入每增加1％，事故起数平均下降0.4％。此文的政策启示在于：为了有效降低安全事故和死亡率，政府的安全管制重点应转变为促进企业提高职工素质、激励企业增加安全投入及提高技术水平、监督企业切实发挥工会作用等。     

Pricing of the currency risk in the Canadian equity market

Based on a three-factor international capital asset pricing model, we examine whether the world market, the local market and the currency risks are priced in the Canadian equity market. The analysis presented in this paper is based on data collected from 2003 to 2010. As the dataset also includes the period of global financial crisis, we examine the issue of risk pricing in the full sample as well as in before and after global financial crisis periods. Unlike most existing studies, the empirical results presented in this paper are based on (i) the quasi maximum likelihood estimation (QMLE) based multivariate GARCH-in-Mean specification and (ii) the generalized method of moments (GMM) techniques. Our empirical analysis based on weekly data on 58 largest Canadian firms indicates that the currency as well as the local and the world market risks are priced in the Canadian equity market. This result holds for all exchange currency rates proxies and in all sample periods. We find that the price of the world market, the local market and the currency risks is time-varying and the Canadian equity market is partially segmented.     

Using the Fraction of Missing Information to Identify Auxiliary Variables for Imputation Procedures via Proxy Pattern‐mixture Models

In many surveys, imputation procedures are used to account for non‐response bias induced by either unit non‐response or item non‐response. Such procedures are optimised (in terms of reducing non‐response bias) when the models include covariates that are highly predictive of both response and outcome variables. To achieve this, we propose a method for selecting sets of covariates used in regression imputation models or to determine imputation cells for one or more outcome variables, using the fraction of missing information (FMI) as obtained via a proxy pattern‐mixture (PMM) model as the key metric. In our variable selection approach, we use the PPM model to obtain a maximum likelihood estimate of the FMI for separate sets of candidate imputation models and look for the point at which changes in the FMI level off and further auxiliary variables do not improve the imputation model. We illustrate our proposed approach using empirical data from the Ohio Medicaid Assessment Survey and from the Service Annual Survey.     

On the Efficiency of Conditional Heteroskedasticity Models

This paper discusses how conditional heteroskedasticity models can be estimated efficiently without imposing strong distributional assumptions such as normality. Using the generalized method of moments (GMM) principle, we show that for a class of models with a symmetric conditional distribution, the GMM estimates obtained from the joint estimating equations corresponding to the conditional mean and variance of the model are efficient when the instruments are chosen optimally. A simple ARCH(1) model is used to illustrate the feasibility of the proposed estimation procedure.