The effects of stock options accounting regulation on corporate governance: A comparative European study

The use of stock options as executive compensation, after having developed in the United States in the 1980s and 1990s, has spread to continental Europe in the past fifteen years. The increasing weight of stock options in this region of the world raises various issues and feeds a vast literature dealing with the relationship between corporate managers’ pay and performance. A good chunk of that literature is based on agency theory. In this line of thought a principal (the shareholder) delegates the management of the firm to an agent (the manager) and simultaneously sets up a series of control devices to make sure that the agent will act in his (the shareholder’s) interest (Jensen and Meckling, 1976). Agency theory does not limit itself with identifying potential conflicts of interests between managers and shareholders: it also explores the various means through which the firm’s owners try to make sure that managers seek to maximize their (the owners’) objectives. Optimal contracting theory precisely aims at identifying such means. According to that theory, the firm’s compensation policies should contribute to align the managers’ interests on those of the shareholders – to make sure, in other words, that the agent behaves in the interest of the principal (Murphy, 1999). Such a view, applied to executive compensation plans, has been recently exposed to a strong scepticism. The optimal contracting theory has a weak empirical basis, especially when applied to stock options – whose adoption does not seem to lead to a significant improvement of firms’ corporate governance. Several authors have underlined the importance of “pay without performance” (Murphy, 1999). Most empirical studies cannot find a positive relationship between the adoption of stock option plans and a significant improvement in firms’ performance. Several explanations have been proposed to explain that puzzle (such as, for instance, Bebchuk & Fried, 2004), all linked to rent extraction theory. According such theory, managers extract a rent from their position: concretely, they increase their capacity to change their own remuneration. In this scheme, stock-options, by nature, cannot succeed in aligning the agent’s interests on the principal’s; on the contrary, they strengthen or create new agency problems. This discussion can be linked to the theme of stock-options accounting and disclosure, which has been recently transformed by the adoption of international accounting standards in most developed economies. Indeed, according to the IFRS 2, stock-options are to be accounted for as labour costs, implying an increase of net liabilities within a specific reserve, with a value equal to the fair value of the options. This accounting method breaks significantly with the past, when disclosure of stock-options plans were left to the discretion of firms. Such a change in disclosure rules might have an impact on the corporate governance of European firms. Indeed, according to a growing literature (see Verrecchia, 2001, for an exhaustive review), disclosure (which can be defined as the publication of previously private relevant information) mediates the relation between a firm’s owners and managers. When disclosure is failing, corporate governance worsens, in that managers are able to hide the decisions which damage or threaten owners’ interests. In fact, in the current context, characterized by national and international regulatory reforms in favour of a more stringent disclosure, the academic discussion has shifted its focus from the causes to the consequences of disclosure, especially related to corporate governance (see Bushman & Smith, 2001). Turning the previous reasoning on its head, one can argue that, in presence of information asymmetries and agency conflicts between owners and managers, disclosure acquires a strategic value (Healy & Palepu, 2001). In particular, a better disclosure could help reduce contractual problems linked to agency relations (Lo, 2003), through, for instance, corporate reputation. In the (international) context of the adoption of more stringent norms on stock option disclosure (that is their recognition, meaning, as seen above, accounting stock-options as costs in a firm’s financial statement), both discussions are relevant. The new disclosure of stock-options could help reduce the risks of rent extraction tied to that form of compensation and bring them closer to their role as incentives assumed in the optimal contracting theory. The aim of the present work is to understand whether the aforementioned change in stock option accounting regulation has had an impact, and what impact, on the corporate governance of European firms, in the light of the twin literatures cited above. The sample considered here includes all listed Italian and French firms, excluding financial institutions, which have carried out stock option plans in 2005 and 2006, and therefore underwent the change in accounting regulation mentioned above. The analysis relies on qualitative and quantitative data, and focuses on a few key indicators. The findings of the present research suggest that the impact of new accounting rules and more stringent disclosure on listed French and Italian firms is not significant. The firms under study have not shown any substantial change in their management or governance structure, which appear to be still largely driven by the peculiar power distribution proper to each country. Besides, such firms have not received any market premium for introducing executive compensation schemes that theoretically provide incentives for top management to maximize owners’ interests. In any event, those plans remain a minority among listed firms. One could argue, therefore, that in Italy and France, like other countries in the world and the United States in particular, stock options plans have become another instrument used by executive managers to obtain higher remuneration with no link to the true performance of the firm and the interests of its owners. Such a logic is much closer to the rent extraction theory mentioned above (see, for the US, Dechow, Sutton, Sloan, 1996).Stock-options; accounting; corporate governance; pay and performance; disclosure

Identification of candidate regulatory sequences in mammalian 3' UTRs by statistical analysis of oligonucleotide distributions

3' untranslated regions (3' UTRs) contain binding sites for many regulatory elements, and in particular for microRNAs (miRNAs). The importance of miRNA-mediated post-transcriptional regulation has become increasingly clear in the last few years. We propose two complementary approaches to the statistical analysis of oligonucleotide frequencies in mammalian 3' UTRs aimed at the identification of candidate binding sites for regulatory elements. The first method is based on the identification of sets of genes characterized by evolutionarily conserved overrepresentation of an oligonucleotide. The second method is based on the identification of oligonucleotides showing statistically significant strand asymmetry in their distribution in 3' UTRs. Both methods are able to identify many previously known binding sites located in 3'UTRs, and in particular seed regions of known miRNAs. Many new candidates are proposed for experimental verification.Comment: Added two reference

What does it take to evolve behaviorally complex organisms?

What genotypic features explain the evolvability of organisms that have to accomplish many different tasks? The genotype of behaviorally complex organisms may be more likely to encode modular neural architectures because neural modules dedicated to distinct tasks avoid neural interference, i.e., the arrival of conflicting messages for changing the value of connection weights during learning. However, if the connection weights for the various modules are genetically inherited, this raises the problem of genetic linkage: favorable mutations may fall on one portion of the genotype encoding one neural module and unfavorable mutations on another portion encoding another module. We show that this can prevent the genotype from reaching an adaptive optimum. This effect is different from other linkage effects described in the literature and we argue that it represents a new class of genetic constraints. Using simulations we show that sexual reproduction can alleviate the problem of genetic linkage by recombining separate modules all of which incorporate either favorable or unfavorable mutations. We speculate that this effect may contribute to the taxonomic prevalence of sexual reproduction among higher organisms. In addition to sexual recombination, the problem of genetic linkage for behaviorally complex organisms may be mitigated by entrusting evolution with the task of finding appropriate modular architectures and learning with the task of finding the appropriate connection weights for these architectures

A Fast Multilevel Fuzzy Transform Image Compression Method

We present a fast algorithm that improves on the performance of the multilevel fuzzy transform image compression method. The multilevel F-transform (for short, MF-tr) algorithm is an image compression method based on fuzzy transforms that, compared to the classic fuzzy transform (F-transform) image compression method, has the advantage of being able to reconstruct an image with the required quality. However, this method can be computationally expensive in terms of execution time since, based on the compression ratio used, different iterations may be necessary in order to reconstruct the image with the required quality. To solve this problem, we propose a fast variation of the multilevel F-transform algorithm in which the optimal compression ratio is found in order to reconstruct the image in as few iterations as possible. Comparison tests show that our method reconstructs the image in at most half of the CPU time used by the MF-tr algorithm

Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrepresented upstream motifs

BACKGROUND: Transcriptional regulation is a key mechanism in the functioning of the cell, and is mostly effected through transcription factors binding to specific recognition motifs located upstream of the coding region of the regulated gene. The computational identification of such motifs is made easier by the fact that they often appear several times in the upstream region of the regulated genes, so that the number of occurrences of relevant motifs is often significantly larger than expected by pure chance. RESULTS: To exploit this fact, we construct sets of genes characterized by the statistical overrepresentation of a certain motif in their upstream regions. Then we study the functional characterization of these sets by analyzing their annotation to Gene Ontology terms. For the sets showing a statistically significant specific functional characterization, we conjecture that the upstream motif characterizing the set is a binding site for a transcription factor involved in the regulation of the genes in the set. CONCLUSIONS: The method we propose is able to identify many known binding sites in S. cerevisiae and new candidate targets of regulation by known transcription factors. Its application to less well studied organisms is likely to be valuable in the exploration of their regulatory interaction network.Comment: 19 pages, 1 figure. Published version with several improvements. Supplementary material available from the author

A New Geospatial Model Integrating a Fuzzy Rule-Based System in a GIS Platform to Partition a Complex Urban System in Homogeneous Urban Contexts

Here, we present a new unsupervised method aimed at obtaining a partition of a complex urbansysteminhomogenousurbanareas,calledurbancontexts.Ourmodelintegratesspatialanalysis processes and a fuzzy rule-based system applied to manage the knowledge of domain experts; it is implemented using a GIS platform. The area of study is initially partitioned in microzones, homogeneous portions of the urban system, which are the atomic reference elements for the census data. With the contribution of domain experts, we identify the physical, morphological, environmental, and socio-economic indicators needed to identify synthetic characteristics of urban contexts and create the fuzzy rule set necessary for determining the type of urban context. We implement the set of spatial analysis processes required to calculate the indicators for the microzones and apply a Mamdani fuzzy rule system to classify the microzones. Finally, the partition of the area of study in urban contexts is obtained by dissolving continuous microzones belonging to the same type of urban context. Tests are performed on the Municipality of Pozzuoli (Naples, Italy); the reliability of the out model is measured by comparing the results with the ones obtained through a detailed analysis

Fuzzy-Based Spatiotemporal Hot Spot Intensity and Propagation—An Application in Crime Analysis

Cluster-based hot spot detection is applied in many disciplines to analyze the locations, concentrations, and evolution over time for a phenomenon occurring in an area of study. The hot spots consist of areas within which the phenomenon is most present; by detecting and monitoring the presence of hot spots in different time steps, it is possible to study their evolution over time. One of the most prominent problems in hot spot analysis occurs when measuring the intensity of a phenomenon in terms of the presence and impact on an area of study and evaluating its evolution over time. In this research, we propose a hot spot analysis method based on a fuzzy cluster hot spot detection algorithm, which allows us to measure the incidence of hot spots in the area of study. We analyze its variation over time, and in order to evaluate its reliability we use a well-known fuzzy entropy measure that was recently applied to measure the reliability of hot spots by executing fuzzy clustering algorithms. We apply this method in crime analysis of the urban area of the City of London, using a dataset of criminal events that have occurred since 2011, published by the City of London Police. The obtained results show a decrease in the frequency of all types of criminal events over the entire area of study in recent years

A Fuzzy Entropy-Based Thematic Classification Method Aimed at Improving the Reliability of Thematic Maps in GIS Environments

Thematic maps of spatial data are constructed by using standard thematic classification methods that do not allow management of the uncertainty of classification and, consequently, eval uation of the reliability of the resulting thematic map. We propose a novel fuzzy-based thematic classification method applied to construct thematic maps in Geographical Information Systems. An initial fuzzy partition of the domain of the features of the spatial dataset is constructed using triangular fuzzy numbers; our method finds an optimal fuzzy partition evaluating the fuzziness of the fuzzy sets by using a fuzzy entropy measure. An assessment of the reliability of the final thematic map is performed according to the fuzziness of the fuzzy sets. We implement our method on a GIS framework, testing it on various vector and image spatial datasets. The results of these tests confirm that our thematic classification method provide thematic maps with a higher reliability with respect to that obtained through fuzzy partitions constructed by expert users