Concept‐Based Bayesian Model Averaging and Growth Empirics

In specifying a regression equation, we need to specify which regressors to include, but also how these regressors are measured. This gives rise to two levels of uncertainty: concepts (level 1) and measurements within each concept (level 2). In this paper we propose a hierarchical weighted least squares (HWALS) method to address these uncertainties. We examine the effects of different growth determinants taking explicit account of the measurement problem in the growth regressions. We find that estimates produced by HWALS provide intuitive and robust explanations. We also consider approximation techniques which are useful when the number of variables is large or when computing time is limited.     

Corporate Responsibility and the Collegial Field

This article is based on 21 interviews of informants actively engaged with corporate responsibility in Sweden. The article introduces a new concept—the “collegial field”—which is helpful in understanding the course of events. With systems that are more open to other organizations, horizontal groupings with common interests become more influential. Collegial fields can also be relevant for understanding other activities in organizations than corporate responsibility.     

Prospect Theory in the Heterogeneous Agent Model

Using the Heterogeneous Agent Model framework, we incorporate an extension based on Prospect Theory into a popular agent-based asset pricing model. This extension covers the phenomenon of loss aversion manifested in risk aversion and asymmetric treatment of gains and losses. Using Monte Carlo methods, we investigate behavior and statistical properties of the extended model and assess how our extension is manifested in different strategies. We show that, on the one hand, the Prospect Theory extension keeps the essential underlying mechanics of the model intact, but on the other hand it considerably changes the model dynamics. Stability of the model is increased and fundamentalists may be able to survive in the market more easily. When only the fundamentalists are loss-averse, other strategies profit more.

     

Jensen's alpha and the market‐timing puzzle

Theory predicts that market‐timing activities bias Jensen's alpha (JA). However, empirical studies have failed to find consistent evidence of this bias. We tackle this puzzle in a nested model analysis and show that the bias contains an exogenous market component that is unrelated to market‐timing skill. In a comprehensive empirical analysis of US mutual funds, we find that the timing‐induced bias in JA is mainly driven by this market component, which is uncorrelated with measured timing activities. Measures of total performance that allow for timing activities are virtually identical to JA, even if timing activities are present in the evaluated fund. Hence, we conclude that JA is a sufficient measure of total performance.     

Disentangling types of liquidity and testing limits-to-arbitrage theories in the CDS–bond basis

We disentangle asset-specific, market, and funding liquidity in the CDS–bond basis outside and during the 2007–9 global financial crisis. Our findings stress the importance of separating different types of liquidity, since all three measures have independently negative impacts on the basis. Funding liquidity emerges as the economically most important liquidity metric. While asset-specific liquidity is cross-correlated in both the cash and derivative markets, funding and market liquidity only matter for the cash market. We exploit the decomposition of the basis to test predictions of limits-to-arbitrage theories. We find strong evidence in favor of margin-based asset pricing and flight-to-quality effects.     

Identifying business opportunities for sustainable development: Longitudinal and experimental evidence contributing to the field of sustainable entrepreneurship

Which factors facilitate the identification of business opportunities for sustainable development? To answer this question, we develop a process model of sustainable opportunity identification. We argue that sustainable opportunity identification is a process with transitions from problem to solution identification and from solution to sustainable opportunity identification. Moreover, the transitions are facilitated by two factors—awareness of adverse consequences and entrepreneurial attitude—providing motivation and direction in the process. We tested our model in a field study (N = 107) and two experiments (N = 53 and N = 69). Our findings show that awareness of adverse consequences and entrepreneurial attitude influence the process of sustainable opportunity identification, explaining under which conditions people are more likely to identify business opportunities for sustainable development. Our study thus contributes to the field of sustainable entrepreneurship.     

Organizational characteristics explaining participation in sustainable business models in the sharing economy: Evidence from the fashion industry using conjoint analysis

Environmental and social challenges require new sustainable business models, like sharing platforms. However, sharing platforms differ widely in their contribution to a more sustainable society. Whereas idealistic sharing platforms have dominant social goals, other sharing platforms are, or became, commercial. We explore the attractiveness of the typical organizational characteristics of idealistic sharing platforms in the fashion industry context, an industry with negative environmental and social impacts. Based on a literature review and exploratory focus groups, we conduct an online survey using conjoint analysis, completed by 1,512 respondents. Our results reveal that potential users prefer clothes sharing platforms to be small, to not partner with large clothing retailers, to have the possibility to participate in decision‐making, but to not require shareholding.     

A unified framework for robust modelling of financial markets in discrete time

Finance and Stochastics - We unify and establish equivalence between the pathwise and the quasi-sure approaches to robust modelling of financial markets in finite discrete time. In particular, we...