Top pay transparency in Europe: codes,convergence and clichés

Following the waves of corporate scandals and the increasing attention to corporate governance, the transparency of reporting on director-level pay has increased across Europe. This article examines the extent of convergence in laws, codes and corporate reporting practices in regard to director-level pay in France, Germany, Switzerland and the UK. The paper analyses annual reports and the websites of 23 companies, using institutional theory to discuss the coercive, normative and mimetic pressures for convergence that are revealed, not just in the laws and codes in each country, but also in the standardized wording in the relevant sections of reports which have become clichés.     

Testing time series data compatibility for benchmarking

Compatibility testing determines whether two series, say a sub-annual and an annual series, both of which are subject to sampling errors, can be considered suitable for benchmarking. We derive statistical tests and discuss the issues with their implementation. The results are illustrated using the artificial series from Denton (1971) and two empirical examples. A practical way of implementing the tests is also presented.     

Whose constituency? Representativeness of the Finnish Paper Workers' Union,innovation strategies,and outsourcing in the Finnish paper industry between 1980 and 2008

Outsourcing has been a conflictual issue in the Finnish paper industry, which reached a temporary solution in 2005. This article analyses the Paper Workers' Union's stance on outsourcing, arguing that it has been defending acquired rights and perhaps deliberately narrowed its representation of diverse constituencies over time.     

Hyperbolic Efficiency and Parametric Distance Functions: With Application to Spanish Savings Banks

Distance functions are gaining relevance as alternative representations of production technologies, with growing numbers of empirical applications being made in the productivity and efficiency field. Distance functions were initially defined on the input or output production possibility sets by Shephard (1953, 1970) and extended to a graph representation of the technology by Färe, Grosskopf and Lovell (1985) through their graph hyperbolic distance function. Since then, different techniques such as non parametric-DEA and parametric-SFA have been used to calculate these distance functions. However, in the latter case we know of no study in which the restriction to input or output orientation has been relaxed. What we propose is to overcome such restrictiveness on dimensionality by defining and estimating a parametric hyperbolic distance function which simultaneously allows for the maximum equiproportionate expansion of outputs and reduction of inputs. In particular, we introduce a translog hyperbolic specification that complies with the conventional properties that the hyperbolic distance function satisfies. Finally, to illustrate its applicability in efficiency analysis we implement it using a data set of Spanish savings banks.     

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

Innovation and the circular economy: A systematic literature review

The circular economy emerged as an alternative model to the linear system, which now appears to be reaching its physical limitations. To transition to a circular economy, companies must not only be aware of but also engage in more sustainable practices. For such a transition, companies must rethink and innovate their business models and the ways they propose value to their clients while simultaneously considering environmental and social facets. This systematic literature review sought to map out from the company perspective the key topics interrelated with innovation and the circular economy, describing the internal and external factors to consider in such transition processes. Key lines of research were identified, and suggestions for future research and for facilitating movement toward a circular economy are provided. This work contributes to deepening the literature by identifying the priority areas concerning the circular economy and encouraging future research that meets international standards of excellence.     

Barriers to women entrepreneurship. Different methods,different results?

Building on research by Akehurst et al. (Serv Ind J 32:2489–2505, 2012), this study analysed internal and external factors in women entrepreneurship and linked these factors to the barriers that women face when starting businesses. To do so, two contrasting statistical techniques were used: PLS and QCA. After analysing results from each of these techniques, we observed that family duties and difficulties in obtaining financing (both internal and external) were the main factors related to barriers faced by women entrepreneurs.