The impact of corporate social performance on the cost of debt and access to debt financing for listed European non-financial firms

This study addresses the controversial issue of how non-financial performance affects the cost of debt capital and access to it. The relationship between corporate social performance and two measures of debt cost (accounting-based and market-based) and the measure of debt access are analysed by means of a multi-theoretical framework combining economics with social theories. By observing a sample of listed European non-financial firms over an 8-year period from 2005 to 2012, we find a negative relationship between corporate social performance and interest rate. Consistent with this result, we find a positive relationship between corporate social performance and debt rating. Thus, corporate social performance has a positive role in reducing the cost of debt capital. Moreover, firms with better corporate social performance are more attractive to lenders in terms of leverage allowance. Overall, our findings provide deeper insight into the reasons why companies should improve their corporate social performance.     

LEGAL STANDARDS,ENFORCEMENT, AND CORRUPTION

Stricter laws require more incisive and costlier enforcement. Because enforcement activity depends both on available tax revenue and the honesty of officials, the optimal legal standard of a benevolent government is increasing in per capita income and decreasing in officials' corruption. In contrast to the “tollbooth view” of regulation, the standard chosen by a self‐interested government is a non‐monotonic function of officials' corruption, and can be either lower or higher than that chosen by a benevolent regulator. International evidence on environmental regulation shows that standards correlate positively with per‐capita income, and negatively with corruption, consistent with the model's predictions for benevolent governments. (JEL: D73, K42, L51)     

Firms,Destinations, and Aggregate Fluctuations

This paper uses a data base covering the universe of French firms for the period 1990–2007 to provide a forensic account of the role of individual firms in generating aggregate fluctuations. We set up a simple multisector model of heterogeneous firms selling to multiple markets to motivate a theoretically founded decomposition of firms' annual sales growth rate into different components. We find that the firm‐specific component contributes substantially to aggregate sales volatility, mattering about as much as the components capturing shocks that are common across firms within a sector or country. We then decompose the firm‐specific component to provide evidence on two mechanisms that generate aggregate fluctuations from microeconomic shocks highlighted in the recent literature: (i) when the firm size distribution is fat‐tailed, idiosyncratic shocks to large firms directly contribute to aggregate fluctuations, and (ii) aggregate fluctuations can arise from idiosyncratic shocks due to input–output linkages across the economy. Firm linkages are approximately three times as important as the direct effect of firm shocks in driving aggregate fluctuations.     

A note about calibrated prediction regions and distributions

In this work we address the problem of the construction of prediction regions and distribution functions, with particular regard to the multidimensional setting. Firstly, we define a simple procedure for calculating the predictive distribution function which gives improved prediction limits. Secondly, with a multivariate generalization of a result presented in Ueki and Fueda (2007), we propose a method for correcting estimative prediction regions, to reduce their coverage error to the third-order accuracy. The improved prediction regions and the associated distribution functions are easy to calculate using a suitable bootstrap procedure. Examples of application are included, showing the good performance of the proposed method, even if we consider an approximated model for prediction purposes.     

Gender wage differentials in Italy: a structural estimation approach

This paper studies gender wage differentials by providing a maximum likelihood structural estimation of the frictional parameters of an equilibrium search model with on-the-job search and firm heterogeneity. In a second step, I also consider the role of discrimination. Results indicate higher level of search frictions for women; this result is confirmed by various robustness checks and by different specification and estimation strategies. I also find that the resulting mapping from productivity to wages for men is highly non-linear, while for women it is almost linear. Search, productivity and discrimination play different roles in shaping the gender differential depending on the specification and estimation of the model.     

Infants' Individuation of Rigid and Plastic Objects Based on Shape

Recent research suggests that 12‐month‐old infants use shape to individuate the number of objects present in a scene. This study addressed the question of whether infants would also rely on shape when shape is only a temporary attribute of an object. Specifically, we investigated whether infants realize that shape changes reliably indicate identity changes only in the case of rigid objects, but not in the case of deformable plastic objects. Twelve‐month‐old infants observed how either a rigid or a plastic object was placed in a box. When searching the box, they retrieved either an object with the same (no‐switch event) or with a different shape (switch event). Infants correctly inferred two distinct objects in the switch event in the case of rigid objects, but not in the case of plastic objects. A control experiment confirmed that this result was not due to a lack of salience of the shape transformation. Thus, infants' re‐searching behavior indicated that they viewed shape as being diagnostic in the individuation process of rigid objects only.     

Beyond the “silo view” of strategic management and corporate governance: evidence from Fiat,Telecom Italia and Unicredit

While corporate governance and strategic management have for a long time suffered from artificial separation and, therefore, generally been tackled in a secluded manner, their combined organizational impact makes them stringently related to one another in the firms’ evolution. In this paper, we argue that, transcending the “silo view” of corporate governance and strategic management, time has come to acknowledge that, depending on circumstances and time periods, within a firm is possible to detect the relative dominance of corporate governance over strategic management, rather than the leadership of strategic management over corporate governance. Drawing on a contingency approach, we dissect the relationships (and the mechanisms that control it) between the strategic function (i.e., which defines the firms’ strategy and supervisions its implementation) and the governance function (i.e., the congruence assessment between the firm strategy selected and the interests of the ownership and of other relevant stakeholders represented in the board of directors and the effectiveness appraisal of the entrepreneurial action). Then, by performing a thorough retrospective qualitative analysis of three relevant case-histories of Italian firms (Fiat, Telecom Italia and Unicredit) operating in three different industries (automobile, banking and telecommunications), we surmise that, either in corporate governance (board) oriented or in strategic management (CEO) oriented companies, the ‘real’ problems arise when the quality of corporate governance or strategic management is poor. Interestingly, we eventually suggest to adopt a value-based approach to the relationship between corporate governance and strategy that may fruitfully complement the contingency perspective taken at the onset of the work.     

Least Squares Sparse Principal Component Analysis: A Backward Elimination Approach to Attain Large Loadings

Sparse principal components analysis (SPCA) is a technique for finding principal components with a small number of non‐zero loadings. Our contribution to this methodology is twofold. First we derive the sparse solutions that minimise the least squares criterion subject to sparsity requirements. Second, recognising that sparsity is not the only requirement for achieving simplicity, we suggest a backward elimination algorithm that computes sparse solutions with large loadings. This algorithm can be run without specifying the number of non‐zero loadings in advance. It is also possible to impose the requirement that a minimum amount of variance be explained by the components. We give thorough comparisons with existing SPCA methods and present several examples using real datasets.     

DEA-Like Model and Common Weights Approach for the Construction of a Subjective Community Well-Being Indicator

A growing literature assesses the quality of life and well-being in geographically and/or politically divided areas. The paper proposes a new subjective well being (SWB) indicator based on residents’ satisfaction with environment and community, personal life and leisure activities. Our approach is a novel construction and new application of the well-being index, specifically, a DEA-like model with common weights under the benefit of the doubt (BoD) approach. This approach is very interesting in the SWB framework, allowing us to differentiate efficient individuals or estimate the relative importance of each domain in the SWB indicator. The results state that Personal life is the domain that most profoundly affects SWB index; it also differs in groups of individuals and geographic spaces.