COMPUTER-AIDED CONSTRUCTION OF SMALL (M, S)-OPTIMAL INCOMPLETE BLOCK DESIGNS

A new exchange algorithm for the construction of (M, S)-optimal incomplete block designs (IBDS) is developed. This exchange algorithm is used to construct 973 (M, S)-optimal IBDs (v, k, b) for v= 4,…,12 (varieties) with arbitrary v, k (block size) and b (number of blocks). The efficiencies of the “best” (M, S)-optimal IBDs constructed by this algorithm are compared with the efficiencies of the corresponding nearly balanced incomplete block designs (NBIBDs) of Cheng(1979), Cheng & Wu (1981) and Mitchell & John(1976).     

The impact of labor unionization on monitoring costs

This paper analyzes the impact of labor unionization on monitoring costs. Our findings show that monitoring costs are significantly higher for unionized firms. We demonstrate that the more complex, industrial relations structures that characterize unionized firms increase monitoring risks and corporate costs. We further show that monitoring agents consider political ideology supportive to labor unions as a parameter that enhances relevant costs. Additionally, we demonstrate that monitoring costs are lower in the presence of employee share ownership. We conclude that labor unionization increases the costs of monitoring agents, a burden which is amplified or mitigated depending on the structure of industrial relations.     

Living with zombie companies: Do we know where the threat lies?

This paper shows the existence of extreme types of zombie firm, i.e. companies with negative equity that continue to do business despite having lost their entire equity. We explain how these firms are measured and how the riskier ones are defined with different determinants. Using a Spanish sample from 2010 to 2014 an index called the EZIndex is developed that includes four dimensions of the extreme zombie problem: extension, contagion, recovery signs and immediacy. The paper contributes to zombie theory on the one hand by developing a method for ranking zombie firms based on risks and changes over time, and on the other hand by using a log-linear model to detect the riskiest corporate profiles out of all these risky firms. It demonstrates significant implications that need to be considered by the competent authorities not only in terms of their impact as a whole but also in regard to the particular profile of extreme zombie firms: they are less regulated, large and located in regions with large business fabrics.     

Modelling the role of anticipated emotions in blood donor behaviour: A cross-sectional study

For blood transfusion centres, studying anticipated emotions (AEs) related to blood donation is essential, since these variables influence donation decision. For this reason, this work addresses the need to identify the antecedents and consequences of AEs, which will help explain their origin and their role in donation behaviour. Our purpose is to make further progress with the application of the AE framework in a non-profit context, by analysing how AEs are generated and how they influence decision-making. This study aims to design and validate an explanatory model of donation intention, where motivations and attitude towards donation are direct antecedents of AEs, while AEs, motivations and attitude towards donation act as direct antecedents of intention. Moreover, it has been also considered how the type of donor influences the proposed model as a moderating factor. The final sample is comprised of 35,982 active donors, inactive donors and non-donors. Data was obtained through an online questionnaire, with the collaboration of 14 of the 17 Spanish blood transfusion centres, as well as some universities. Results indicate that (1) AEs, motivations and attitude towards donation are direct antecedents of donation intention, (2) motivations and attitude towards donation are direct antecedents of AEs, and (3) donation experience moderates the relationships between motivations, attitude towards donation, AEs, and donation intention. These results indicate several operational implications that will enable blood transfusion centres to better design and target donation promotion campaigns according to type of donor. Furthermore, the results will let centres assess whether placing value on donation motivation and attitude towards donation can bolster positive AEs, diminish negative AEs and have a direct effect on donation intention.     

On testing for independence between the innovations of several time series

Test statistics for checking the independence between the innovations of several time series are developed. The time series models considered allow for general specifications for the conditional mean and variance functions that could depend on common explanatory variables. In testing for independence between more than two time series, checking pairwise independence does not lead to consistent procedures. Thus a finite family of empirical processes relying on multivariate lagged residuals are constructed, and we derive their asymptotic distributions. In order to obtain simple asymptotic covariance structures, Möbius transformations of the empirical processes are studied, and simplifications occur. Under the null hypothesis of independence, we show that these transformed processes are asymptotically Gaussian, independent, and with tractable covariance functions not depending on the estimated parameters. Various procedures are discussed, including Cramér–von Mises test statistics and tests based on non‐parametric measures. The ranks of the residuals are considered in the new methods, giving test statistics which are asymptotically margin‐free. Generalized cross‐correlations are introduced, extending the concept of cross‐correlation to an arbitrary number of time series; portmanteau procedures based on them are discussed. In order to detect the dependence visually, graphical devices are proposed. Simulations are conducted to explore the finite sample properties of the methodology, which is found to be powerful against various types of alternatives when the independence is tested between two and three time series. An application is considered, using the daily log‐returns of Apple, Intel and Hewlett‐Packard traded on the Nasdaq financial market. The Canadian Journal of Statistics 40: 447–479; 2012 © 2012 Statistical Society of Canada     

理论的张力：在史观与方法之间——重读普实克《抒情与史诗：中国现代文学论集》

捷克汉学家普实克之于海外中国现代文学研究具有开创性与典范性的意义。重读普实克,可见其以结构主义方法为马克思主义史观救弊的努力,但某种悖论性面貌也由此生成。在＂主观＂与＂客观＂的辩证结构之上,普实克显示出一种以现实主义理论为依托的整体性视野,并力图实现文学内外的打通与勾连,表现出其理论的丰富性与张力。     

Likelihood-based inference for a class of multivariate diffusions with unobserved paths

This paper presents a Markov chain Monte Carlo algorithm for a class of multivariate diffusion models with unobserved paths. This class is of high practical interest as it includes most diffusion driven stochastic volatility models. The algorithm is based on a data augmentation scheme where the paths are treated as missing data. However, unless these paths are transformed so that the dominating measure is independent of any parameters, the algorithm becomes reducible. The methodology developed in Roberts and Stramer [2001a. On inference for partial observed nonlinear diffusion models using the metropolis-hastings algorithm. Biometrika 88(3); 603–621] circumvents the problem for scalar diffusions. We extend this framework to the class of models of this paper by introducing an appropriate reparametrisation of the likelihood that can be used to construct an irreducible data augmentation scheme. Practical implementation issues are considered and the methodology is applied to simulated data from the Heston model.     

Asymptotic distributions of statistics and parameter estimates for mixed Poisson processes

Mixed Poisson processes have been used as natural models for events occurring in continuous or discrete time. Our main result is the derivation of the joint asymptotic distributions of statistics, including parameter estimators, computed in different time intervals from data generated by mixed Poisson processes. These distributions can be used, for example, to test the hypothesis about the adequacy of the mixed Poisson process against data. We provide some simulation results and test the model on actual market research data.     

Do nonprofessional investors value the assurance of integrated reports? Exploratory evidence

Using an experimental design, this explorative study provides unique empirical evidence of the effects of an integrated reporting assurance (IRA) on nonprofessional investors’ (NPIs) financial decision-making in a laboratory experiment. For this purpose, two independent experiments were carried out, one relying on a sample of Master’s students, and one focusing on managers of large corporations. In line with our agency theoretical reasoning, we find that students value an IRA positively, evidenced through significantly higher investments, while, contrary to expectations, an IRA has the opposite effect for managers. The results reveal that, dependent on the empirical model, an IRA has either no, or even an investment-decreasing, impact on executives. In order to assess the sense-making process underlying this conundrum, subsequent interviews with the managers were carried out which revealed three dimensions that shape practitioners’ critical attitudes towards assurance engagements. First, managers expressed a general disbelief in the decision usefulness of integrated reporting (IR) to (nonprofessional) investors. Second, interlocutors referred to negative practical experiences with audit and assurance engagements and had technical doubts specific to IRA. Third, managers voiced emotional caveats regarding the audit and assurance profession. These findings indicate a prevailing divergence between the extolled theoretical contribution of an IRA to report credibility and its actual nature in practice. In the further course of the investigation, we also find that the assurance provider (Big 4 auditor versus specialized consultant) does not affect investment decisions, but that a higher assurance level leverages investments among students. The results of this study add to the growing, albeit still small, IRA research body and deliver valuable insights for research, regulators, and practice.     

Estimation in M/Er /1 queueing systems

In this paper, the maximum likelihood estimates of the parameters for the M/E_r /1 queueing model are derived when the queue size at each departure point is observed. A numerical example is generated by simulating a finite Markov chain to illustrate the methodology for estimating the parameters with variable Erlang service time distribution. The problem of hypothesis testing and simultaneous Confidence regions of the parameter is also investigated.0