Income Shifting in Italian Business Groups and some Governance Implications

This paper explores the relationship among group control, financial reporting strategies and governance implications in the pursuit of domestic tax planning. A very large number of papers deals with international tax planning in multidivisional enterprises, but very few are devoted to exploring significant incentives for national business groups to engage in tax planning strategies. In this paper we propose a one-period model relating to the tax incentives of income shifting in Italian business groups. We show that, given the total amount of expected earnings before taxes and the dividends received by the firms belonging to a business group, an optimal solution to the problem of minimizing the group tax burden exists. The optimal solution involves a gain in value for the group as a whole; nevertheless, since in business groups ownership is often differentiated among shareholders (often because of the separation between ownership and control), income shifting may determine wealth transfers, often in favor of the controlling shareholder. We therefore analyze the management and governance implications of such income shifting, for both shareholders and stakeholders (i.e. managers). This revised version was published online in July 2006 with corrections to the Cover Date.     

A study of search algorithms’ optimization speed

Search algorithms are often compared by the optimization speed achieved on some sets of cost functions. Here some properties of algorithms’ optimization speed are introduced and discussed. In particular, we show that determining whether a set of cost functions F admits a search algorithm having given optimization speed is an NP-complete problem. Further, we derive an explicit formula to calculate the best achievable optimization speed when F is closed under permutation. Finally, we show that the optimization speed achieved by some well-know optimization techniques can be much worse than the best theoretical value, at least on some sets of optimization benchmarks.     

Estimating a sensitive proportion through randomized response procedures based on auxiliary information

Randomized response techniques are widely employed in surveys dealing with sensitive questions to ensure interviewee anonymity and reduce nonrespondents rates and biased responses. Since Warner’s (J Am Stat Assoc 60:63–69, 1965) pioneering work, many ingenious devices have been suggested to increase respondent’s privacy protection and to better estimate the proportion of people, π _A , bearing a sensitive attribute. In spite of the massive use of auxiliary information in the estimation of non-sensitive parameters, very few attempts have been made to improve randomization strategy performance when auxiliary variables are available. Moving from Zaizai’s (Model Assist Stat Appl 1:125–130, 2006) recent work, in this paper we provide a class of estimators for π _A , for a generic randomization scheme, when the mean of a supplementary non-sensitive variable is known. The minimum attainable variance bound of the class is obtained and the best estimator is also identified. We prove that the best estimator acts as a regression-type estimator which is at least as efficient as the corresponding estimator evaluated without allowing for the auxiliary variable. The general results are then applied to Warner and Simmons’ model.     

Physical activity is inversely related to drug consumption in elderly patients with cardiovascular events

Elderly patients with cardiovascular events are characterized by high drug consumptions. Whether high drug consumptions are related to physical activity is not known. In order to examine whether physical activity is related to drug consumption in the elderly, patients older than 65 years (n?=?250) with a recent cardiovascular event were studied. Physical activity was analyzed according to the Physical Activity Scale for the Elderly (PASE) score and related to drug consumption. PASE score was 72.4?±?45.0 and drug consumption was 8.3?±?2.2. Elderly patients with greater comorbidity took more drugs (8.7?±?2.1) and are less active (PASE?=?64.4?±?50.6) than patients with Cumulative Illness Rating Scale severity score higher than 1.8 than those with a score lower than 1.8 (76.3?±?41.4, p?<?0.05, and 8.0?±?2.0, p?=?0.006, respectively). Multivariate analysis correlation confirmed that PASE score is negatively associated with drug consumption (β?=??0.149, p?=?0.031), independently of several variables including comorbidity. Thus, physical activity is inversely related to drug consumption in elderly patients with cardiovascular events. This inverse relationship may be attributable to the high degree of comorbidity observed in elderly patients in whom poor level of physical activity and high drug consumption are predominant.     

Optimal use of two auxiliary variables in double sampling

Double sampling scheme is used when cheap auxiliary variables may be measured to improve the estimation of a finite population parameter. Several estimators for population mean, ratio of means and variance are available, when two dependent samples are drawn. However, there are few proposals for the case of independent samples. In this paper both cases of dependent and independent samples are dealt with. A general approach for estimating a finite population parameter is given, showing that all the proposed estimators are particular cases of the same general class. The minimum variance bound for any estimator in this class is provided (at the first order of approximation). Furthermore, an optimal estimator which reaches this minimum is found.     

克拉多·帕塞拉：领导变革

迄今为止，很少有执行官能够成功地在一家陷入困境的大型组织内部实现变革，克拉多·帕塞拉就是为数不多的成功者之一，不仅如此，他还先后成功地领导两家大型企业完成了变革。     

Multi-phase sampling under cost constraints

Multi-phase sampling (M-PhS) scheme is useful when the interest is in the estimation of the population mean of an expensive variable strictly connected with other cheaper (auxiliary) variables. The MSE is an accuracy measure of an estimator. Usually it decreases as the sample size increases. In practice the sample size cannot become arbitrarily large for possible cost constraints. From a practical point of view it would be useful to know the sample sizes which guarantee the best accuracy of the estimates for fixed costs. These “optimum” sample sizes can be, in some cases, computable but not admissible. In other cases, they can be neither admissible nor computable. The main goal of this paper is to propose a solution for both these situations. It will be clear that in both situations the solution is to consider a M-PhS scheme with one or more phases less.