Country versus sector factors in equity returns: The roles of non-unit exposures

In this paper we disentangle, analytically and empirically, the roles of the unit-exposure restriction in Heston and Rouwenhorst (1994). We show that if the purpose is to construct factors, the unit-exposure variance-analysis model can be viewed as just an algorithm that does not really assume a return-generating process; and in practice the effect of relaxing the restriction is immaterial. The restriction is more important if one wants to estimate whether, for a typical stock, the country factor generates more variance than the sector factor: exposure estimation becomes more important (i) the further the average exposures are from unity; or (ii) the higher the dispersion of the exposures. With respect to (i), the more important the corrections for sector (or geographical) structure in country (or sector) factors are, the more the average exposure falls below unity. Thus, the average exposure provides an alternative indicator of the importance of country versus sector effects. We empirically find that the average sector exposure is low (0.3) compared to the average country exposure (0.9). With respect to (ii) we correct the dispersion of exposures for estimation error in the exposures. We find that in our sample these estimation error corrections are more important for sector factors than for country factors, and that country factors are generating far more variance, in a typical stock's return, than do sector factors.     

Hedging Pressure Effects in Futures Markets

We present a simple model implying that futures risk premia depend on both own-market and cross-market hedging pressures. Empirical evidence from 20 futures markets, divided into four groups (financial, agricultural, mineral, and currency) indicates that, after controlling for systematic risk, both the futures own hedging pressure and cross-hedging pressures from within the group significantly affect futures returns. These effects remain significant after controlling for a measure of price pressure. Finally, we show that hedging pressure also contains explanatory power for returns on the underlying asset, as predicted by the model.     

Are Family Transfers Crowded Out by Public Transfers?

We give an account of an overlapping–generations experiment with multiple families in which voluntary transfers can take the form of support to the elderly or grants to children. Support to the old is a purely intergenerational (intra–family) transfer, whereas grants to children also involve an element of intra–generational (inter–family) redistribution through a compulsory pension system. Our data show that higher compulsory inter–family transfers lead subjects to place relatively more emphasis on support instead of grants: grants are crowded out, but support is not significantly affected. The efficiency of voluntary transfers increases, however. Furthermore, if subjects give transfers, they do not use tokens of direct reciprocity; evidence of indirect reciprocity in transfer behavior can only be obtained for the case where compulsory transfers are high.
JEL classification : C 91; H 55     

Understanding conflicting views of endocrine disruptor experts: a pilot study using argumentation analysis

Abstract

To what extent do substances have the potential to cause adverse health effects through an endocrine mode of action? This question elicited intense debates between endocrine disrupting substances (EDS) experts. The pervasive nature of the underlying differences of opinion justifies a systematic analysis of the argumentation put forward by the experts involved. Two scientific publications pertaining to EDS science were analyzed using pragma-dialectical argumentation theory (PDAT). PDAT’s methodology allowed us to perform a maximally impartial and systematic analysis. Using PDAT, the structure of the argumentation put forward in both publications was reconstructed, main standpoints, and arguments were identified, underlying unexpressed premises were made explicit and major differences in starting points were uncovered. The five differences in starting points identified were subdivided into two categories: interpretative ambiguity about underlying scientific evidence and normative ambiguity about differences in broader norms and values. Accordingly, two differences in starting points were explored further using existing risk and expert role typologies. We emphasize that particularly the settlement of normative ambiguity, through the involvement of broader ethical, social or political values, inherently requires multi-stakeholder approaches. Extrapolation of our findings to the broader discussion on EDS science and further exploration of the roles of EDS experts in policy processes should follow from further research.     

Implementing new business models: What challenges lie ahead?

What strategic choices do business leaders make when implementing new business models? This study tries to answer this question by analyzing the development of several business model innovations that were new to the industry. We find that business model innovators face four strategic trade-offs and accompanying tensions during the implementation of their business model innovation process: (1) the level of independence granted to the developer (independence vs. dependence), (2) the degree to which the roadmap is planned in advance (discovery vs. planned execution), (3) the degree to which the value proposition challenges the status quo (challenging vs. maintaining status quo), and (4) the rigor to which business model innovators preserve the logic of the initial value proposition (solid vs. fluid logic). Our in-depth analysis reveals that business model innovators make pragmatic decisions that may deviate from the guidelines offered by existing literature, and we offer insights into the drivers behind these decisions.     

Seeing the wood for the trees: How machine learning can help firms in identifying relevant electronic word-of-mouth in social media

The increasing volume of firm-related conversations on social media has made it considerably more difficult for marketers to track and analyse electronic word-of-mouth (eWOM) about brands, products or services. Firms often use sentiment analysis to identify relevant eWOM that requires a response to consequently engage in webcare. In this paper, we show that sentiment analysis of any kind might not be ideal for this purpose, because it relies on the questionable assumption that only negative eWOM is response-worthy and it is not able to infer meaning from text. We propose and test an approach based on supervised machine learning that first decides whether eWOM is relevant for the brand to respond, and then—based on a categorization of seven different types of eWOM (e.g., question, complaint)—classifies three customer satisfaction dimensions. Using a dataset of approximately 60,000 Facebook comments and 11,000 tweets about 16 different brands in eight different industries, we test and compare the efficacy of various sentiment analysis, dictionary-based and machine learning techniques to detect relevant eWOM. In doing so, this study identifies response-worthy eWOM based on the content instead of its expressed sentiment. The results indicate that these machine learning techniques achieve considerably higher accuracy in detecting relevant eWOM on social media compared to any kind of sentiment analysis. Moreover, it is shown that industry-specific classifiers can further improve this process and that algorithms are applicable across different social networks.     

Successful New Product Pricing Practices: A Contingency Approach

The purpose of this study is to examine the success of new product pricing practices and the conditions upon which success is contingent. We distinguish three different pricing practices that refer to the use of information on customer value, competition, and costs respectively. Following Monroe's (1990) price discretion, we argue that the success of these practices is contingent on relative product advantage and competitive intensity. The hypotheses are tested on pricing decisions for new industrial products. Our results show that there are no general best or bad practices, but that a contingency approach is appropriate. These results may help reduce the complexity that managers experience in pricing new products.     

Transparency of Corporate Social Responsibility in Dutch Breweries

According to the Dutch Ministry of Economic Affairs (2001), transparency by means of Sustainability Reporting should lead to better Corporate Social Responsibility (CSR) performance of companies. Sustainability Reporting should also give consumers the information they need to purchase the most sustainable products available (Dutch Ministry of Economic Affairs, 2004). This article analyses the driving factors influencing CSR and Sustainability Reporting at seven breweries in the Netherlands. It also gives a better understanding of organizational behaviour with reference to CSR and the reasons breweries have for Sustainability Reporting. The Dutch government has no intention of forcing organizations to publish a sustainability report, since it is trying to diminish the volume of legislation. Rather, the government prefers to rely on the willingness and initiatives of organizations to make CSR a success. In 2006, the Dutch Ministry of Economic Affairs will evaluate the effect of its CSR policy. But is it a success already? During our research, breweries appeared to find CSR more important than Sustainability Reporting. Sustainability reporting is, for most breweries, not the way to reach stakeholders. Most stakeholders have their own means for receiving information e.g. annual reports, meetings, public statements and press releases. Although small breweries think CSR is very important, they feel no pressure from outside to publish a sustainability report. For them it is very complex and expensive to publish a sustainability report. Large breweries feel pressure from many stakeholders to be transparent, but not on a regular basis. We conclude from this research that CSR does not stimulate Sustainability Reporting, but neither does Sustainability Reporting stimulate CSR.