Use of Derivatives and Analysts’ Forecasts: New Evidence from Non‐financial Brazilian Companies

This study investigates whether market analysts’ forecasts are influenced by the presence of derivative financial instruments in listed firms. From a sample of firms comprising 1173 derivative users and 7797 non‐users for the 2006–14 period, the results indicate the existence of less error behaviour (bias) on earnings per share forecasts for derivative user firms compared to non‐user firms. This finding suggests that these instruments may be used to protect businesses and provide greater stability in the results of companies that use them. The presence of derivative financial instruments is increasing among listed firms, and management can use them for hedging or speculation (thus mitigating or increasing risk). The literature contains few studies on this issue, and the general understanding relies on the assumption that derivative financial instruments provide relevant information for decision making.     

The Quality of Smallholder Coffee in South Sumatra: The Production of Low-Quality Coffee as a Response to World Demand 1

Improving the quality of Indonesia's coffee exports has been a priority of government and the Association of Indonesian Coffee Exporters for some years. Efforts to achieve this objective have, however, been hampered by misconceptions about the reasons why coffee producers and traders at each point in the marketing network do not deliver a higher quality product. The research reported here shows that price premia for higher quality coffee are not large enough to encourage greater quality enhancement. The world market for low to medium grades, used in the production of instant coffee, is much larger than that for high-quality coffee, and this preference is transmitted in the form of low incentives to improve the product. Failure to understand this has led to government policies which at best do not solve the quality problem and at worst exacerbate it.     

Interpreting IS alignment: A multiple case study in professional organizations

This paper centers on the interpretation attributed by organizational members to the information systems (IS) alignment concept. Its objective is to study IS alignment in professional organizations. Specifically, it reports on an interpretive study conducted in five Chilean organizations; four professional and one entrepreneurial, of which two are private and three are public. The theoretical background of our study is derived from three IS strategic alignment conceptualizations: managerial, emergent and critical. These concepts formed our theoretical framework that guided data collection and analysis. The study centers on the meanings organizational members assigned to IS strategic alignment, as well as their views on the barriers that hinder achieving this level of organizational integration. The analysis results are summarized in seven hermeneutic themes that point out the different connotations the organizations assigned to IS alignment. The significance of the findings are summarized in four insights that formulate theoretical and practical implications. These insights refer to: (1) the difficulties of achieving alignment for professional organizations, particularly public ones, (2) the limitations these organizations have in being agile, (3) the rationale for acquiring technology and determining IT skills, and (4) the imperative meaning that CIOs attribute to IS alignment. The paper concludes with a reflection on the limitations and relevance of the research.     

Cardinality-based equality of opportunities

We study possible rankings of opportunity profiles. An opportunity profile is a list of opportunity sets, one for each agent in the society. We compare profiles on the basis of the notion of “equality of opportunities”. Our main results show the necessary and sufficient conditions for this comparison to be made using exclusively the information provided by two cardinal measures: the number of common alternatives in all sets of a given profile and the difference between the number of alternatives in the individual sets. We also show that, under additional axioms, we can combine these criteria only in a weighted procedure or in some lexicographic refinements of a weighted procedure.      

A note on forecasting international tourism demand in Spain

This paper considers the extent to which price and income proxy variables help in forecasting tourist demand in Spain. Contrary to some recent studies, we found that the inputs' contribution in terms of fitting and forecasting is nil when compared with alternative univariate models. Whether these findings are the results of the restrictions embedded in building the proxy inputs or in a poor specification of the dynamics of these models remains to be seen. We also contend that when dealing with medium, long-term forecasting comparisons, the use of the traditional aggregate accuracy measures like RMSE and MAPE help very little in discriminating among competing models. In these situations, predicted annual growth rates may be a better alternative.     

Risk-based classification of supplier relationships

The management and exploitation of external resources has increased and become a new source of business success. This has given rise to various new risks and therefore increased the need for collaborative risk management and learning. The objective of this paper is to explore the differences in risk management and learning across supplier relationships classified through network risks. The paper provides a theoretical review of supplier relationships and risk management, as well as a survey-based empirical study conducted in one case company's supply network. A set of network risks and risk-management measures is developed by means of factor analysis, and a supplier classification by means of cluster analysis. According to the results, the exploitation of collaborative risk management and learning is highest among the most strategic supplier relationships. A classification typology based on suppliers’ opinions helps both parties in the relationship and enables the efficient exploitation of mutual risk management with collaborative learning as one of its keystones.     

LIQUIDITY,MONEY CREATION AND DESTRUCTION,AND THE RETURNS TO BANKING*

We build on our earlier model of money in which bank liabilities circulate as a medium of exchange. We investigate optimal bank behavior and the resulting provision of liquidity under a range of central bank regulations. In our model, banks issue inside money under fractional reserves, facing the possibility of excess redemptions. Banks consider the float resulting from money creation and make reserve‐management decisions that affect aggregate liquidity conditions. Numerical examples demonstrate positive bank failure rates when returns to banking are low. Central bank interventions may improve banks' returns and welfare through a reduction in bank failure.     

Accelerators as start-up infrastructure for entrepreneurial clusters

ABSTRACT

Infrastructure is commonly conceptualized as a set of facilities that play a critical role in facilitating activities by individuals and organizations. Conventionally, infrastructure is tightly linked to publicly funded projects that facilitate access to key resources and enable diverse activities. Within entrepreneurial clusters research, infrastructure includes universities, research institutions and telecommunication technologies that facilitate entrepreneurial activities. These capital-intensive investments seek to facilitate start-ups emergence by aiding access to markets and development of ideas. Accelerators facilitate the same activities and have only recently been conceptualized as start-up infrastructure. This study builds upon this research stream by elaborating on how accelerators can play this meaningful role at the cluster level. Specifically, and by relying on the analysis of empirical evidence from three distinct studies, we uncover how accelerators provide tangible and intangible dimensions of start-up infrastructure to form a positively reinforcing cycle of entrepreneurial activities. Additionally, our findings allow us to push further the idea that start-up infrastructure development can be an endogenous process involving multiple actors within the cluster. Our empirical findings and the theoretical insights derived from them have meaningful implications for the aforementioned literature, as well as start-up practitioners and policymakers linked to the funding of entrepreneurial clusters.     

A critical overview of privacy-preserving approaches for collaborative forecasting

Cooperation between different data owners may lead to an improvement in forecast quality—for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in collaborative privacy-preserving forecasting is thus increasing. This paper analyzes the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing vector autoregressive models. The methods are divided into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as (i) the necessary trade-off between privacy and forecasting accuracy, empirically evaluated through simulations and real-world experiments based on solar data; and (ii) iterative model fitting processes, which reveal data after a number of iterations.