Management earnings forecasts and other forward-looking statements

We identify forward-looking statements (FLS) in firms’ disclosures to distinguish between “forecast-like” (quantitative statements about earnings) and “other”, or non-forecast-like, FLS.  We show that, like earnings forecasts, other FLS generate significant investor and analyst responses. Unlike earnings forecasts, other FLS are issued more frequently when uncertainty is higher. We then show that earnings-related FLS are more sensitive to uncertainty than quantitative statements, suggesting that managers are more likely to alter the content than the form of FLS when uncertainty is higher.  Our study indicates that incorporating other FLS into empirical measures provides a more comprehensive proxy for firms’ voluntary disclosures.     

Chebyshev interpolation for parametric option pricing

Recurrent tasks such as pricing, calibration and risk assessment need to be executed accurately and in real time. We concentrate on parametric option pricing (POP) as a generic instance of parametric conditional expectations and show that polynomial interpolation in the parameter space promises to considerably reduce run-times while maintaining accuracy. The attractive properties of Chebyshev interpolation and its tensorized extension enable us to identify broadly applicable criteria for (sub)exponential convergence and explicit error bounds. The method is most promising when the computation of the prices is most challenging. We therefore investigate its combination with Monte Carlo simulation and analyze the effect of (stochastic) approximations of the interpolation. For a wide and important range of problems, the Chebyshev method turns out to be more efficient than parametric multilevel Monte Carlo. We conclude with a numerical efficiency study.     

The potential of integrated reporting to enhance sustainability reporting in the public sector

This paper examines the influence of integrated reporting (IR) on the sustainability reporting practices of a state-owned enterprise through a content analysis of their reports and interviews with report preparers. The findings show a steady increase in the quantity and quality of sustainability disclosures. In 2012, the organization chose to adopt the IR framework in order to enhance sustainability reporting for all stakeholders. The IR process resulted in a more balanced disclosure of material aspects of sustainability. However, while IR has the potential to enhance public sector sustainability reporting, inter-generational equity issues were ignored.     

The interactive effects of organizational and leadership career management support on job satisfaction and turnover intention

In the organizational career management literature, scholars have focused on career management policies, with little attention given to practices that can vary within organizations. And despite its recognized importance, research on the role of leaders in the career management process is also scant. In this study, we investigate the effects of career management practices (OCPs) and leadership career support (LCS) on employee attitudes. Grounded on coping theory, we propose that career support received from line managers can be particularly consequential when OCPs are lacking. We analyze the moderating effects of LCS on the relationship between OCPs and both job satisfaction and turnover intention in a sample of employees from a large Brazilian organization, applying multiple regression analyses. Results showed that OCPs and LCS are positively related to job satisfaction and that OCPs are negatively related to turnover intention. In addition, we confirmed that LCS moderates the relationship between OCPs and both job satisfaction and turnover intention. Finally, we observed that the relationship between OCPs and turnover intention is mediated by job satisfaction. Theoretical and practical implications are discussed.     

Inequality and Income Distribution in Global Value Chains

Global value chains (GVCs), led by transnational corporations (TNCs), have reshaped the world division of labor over the past two decades. GVCs are pervasive in low technology manufacturing, such as textile and apparel, as well as in more advanced industries like automobiles, electronics, and machines. This hierarchical division of labor generates wild competition at the lower value-added stages of production, where low wages and low profit margins prevail for workers and contract manufacturers in developing countries. At the top of the hierarchy another kind of competition prevails, centered on the ability to monitor and control intellectual property rights related to innovation, finance, and marketing. We argue that GVCs have had crucial effects on income inequality and the appropriation of rents in modern capitalism.     

POSTERIOR‐PREDICTIVE EVIDENCE ON US INFLATION USING EXTENDED NEW KEYNESIAN PHILLIPS CURVE MODELS WITH NON‐FILTERED DATA

Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended New Keynesian Phillips curve (NKPC) models. It is shown that mechanical removal or modeling of simple low‐frequency movements in the data may yield poor predictive results which depend on the model specification used. Basic NKPC models are extended to include structural time series models that describe typical time‐varying patterns in levels and volatilities. Forward‐ and backward‐looking expectation components for inflation are incorporated and their relative importance is evaluated. Survey data on expected inflation are introduced to strengthen the information in the likelihood. Use is made of simulation‐based Bayesian techniques for the empirical analysis. No credible evidence is found on endogeneity and long‐run stability between inflation and marginal costs. Backward‐looking inflation appears stronger than forward‐looking inflation. Levels and volatilities of inflation are estimated more precisely using rich NKPC models. The extended NKPC structures compare favorably with existing basic Bayesian vector autoregressive and stochastic volatility models in terms of fit and prediction. Tails of the complete predictive distributions indicate an increase in the probability of deflation in recent years. Copyright © 2014 John Wiley & Sons, Ltd.     

Extending the enterprise evolution contextualisation model

Enterprise engineering (EE) emerged as a new discipline to encourage comprehensive and consistent enterprise design. Since EE is multidisciplinary, various researchers study enterprises from different perspectives, which resulted in a plethora of applicable literature and terminology, but without shared meaning. Previous research specifically focused on the fragmentation of knowledge for designing and aligning the information and communication technology (ICT) subsystem of the enterprise in order to support the business organisation subsystem of the enterprise. As a solution for this fragmented landscape, a business-IT alignment model (BIAM) was developed inductively from existing business-IT alignment approaches. Since most of the existing alignment frameworks addressed the alignment between the ICT subsystem and the business organisation subsystem, BIAM also focused on the alignment between these two subsystems. Yet, the emerging EE discipline intends to address a broader scope of design, evident in the existing approaches that incorporate a broader scope of design/alignment/governance. A need was identified to address the knowledge fragmentation of the EE knowledge base by adapting BIAM to an enterprise evolution contextualisation model (EECM), to contextualise a broader set of approaches, as identified by Lapalme. The main contribution of this article is the incremental development and evaluation of EECM. We also present guiding indicators/prerequisites for applying EECM as a contextualisation tool.