We analyse the increasing engagement of business in the creation and application of self-regulatory standards in the area of human rights in the light of an emerging framework of transnational human rights initiatives. The voluntariness of most of these approaches leads to problems that are characteristic of organizational self-regulation initiatives. Our analysis will show that these issues cannot be resolved simply by designing organizational structures. Rather, we argue that organizations need to acquire additional moral, communicative and collaborative capabilities to successfully contribute to the protection of human rights.
A major obstacle for research in international asset pricing and corporate finance has been a lack of reliable and publicly available data on international common risk factors and portfolios. To address this gap, we provide a step-by-step description of how appropriately screened data from Thomson Reuters Datastream and Thomson Reuters Worldscope can be used to construct high-quality systematic risk factors. We provide common risk factors for 23 countries across the globe.
This paper empirically analyzes the effect of the inclusion of German corporations in the Dow Jones STOXX Sustainability Index (DJSI STOXX) and the Dow Jones Sustainability World Index (DJSI World) on stock performance. In order to receive robust estimation results, we apply an event study approach that is based on both a modern asset pricing model, namely the three-factor model according to Fama and French (1993), and additionally on a GARCH model. Our empirical analysis implies that stock markets may penalize the inclusion of a firm in sustainability stock indexes. This result is mainly driven by the negative effect of the inclusion in the DJSI World. While we do not find significant average cumulative abnormal returns for the inclusion in the DJSI STOXX, the inclusion in the DJSI World leads to strong negative impacts. This suggests that the inclusion in a more visible sustainability stock index has larger negative impacts.
This paper analyzes small sample properties of several versions of z-tests in multinomial probit
models under simulated maximum likelihood estimation. OurMonte Carlo experiments show
that z-tests on utility function coefficients provide more robust results than z-tests on variance
covariance parameters. As expected, both the number of observations and the number of random
draws in the incorporatedGeweke-Hajivassiliou-Keane (GHK) simulator have on average
a positive impact on the conformities between the shares of type I errors and the nominal significance
levels. Furthermore, an increase of the number of observations leads to an expected
decrease of the shares of type II errors, whereas the number of random draws in the GHK
simulator surprisingly has no significant effect in this respect. One main result of our study
is that the use of the robust version of the simulated z-test statistics is not systematically
more favorable than the use of other versions. However, the application of the z-test statistics
that exclusively include the Hessian matrix of the simulated loglikelihood function to estimate
the information matrix often leads to substantial computational problems.
The proportion of sustainable property in the total building stock remains small. One reason is that the financial added value resulting from sustainability is not sufficiently taken into account in property valuation due to the tendency of valuations to lag behind market trends. This article presents the development of a new approach that attempts to provide the quantitative information necessary to integrate those aspects of sustainability relating to value into valuations and thereby contribute to reducing the valuation lag. The CCRS Economic Sustainability Indicator ESI measures the risk of property to lose and the opportunity to gain value due to future developments like climate change or rising energy prices. Five groups of value-related sustainability features were identified: flexibility and polyvalence, energy and water dependency, accessibility and mobility, security, health and comfort. By minimizing the risk of loss in value through future developments, those sustainability features contribute to the property value. Their effects on property value were quantified by risk modelling. As an indicator for future-oriented property risk, ESI is integrated in the discount rate of Discounted Cash Flow (DCF ) valuations. The approach has been tested for plausibility and practicability on more than 200 properties.
