The Impact of Power Distance and Uncertainty Avoidance on Real Options Exercise: Potential for Suboptimal Time Delays and Value Destruction

Real options (RO) valuation has been promoted as a way to evaluate investment opportunities and make investment decisions that takes into account the value of managerial flexibility in the face of uncertainty. Although RO enjoys a substantial body of literature considering its application and suitability in different situations, the impact of national culture on the application of RO has received little attention. Values embedded in national culture affect the behavior of managers. In particular, these values play a role in how managers frame information, communicate, and make decisions, directly and indirectly affecting behavior through cultural layers such as organizational culture. National culture, therefore, can systematically affect the application of RO, potentially leading to suboptimal outcomes. In this article, we hypothesize how 2 particularly relevant dimensions of culture, power distance and uncertainty avoidance, affect RO exercise, and estimate the magnitude suboptimality of these effects using a model we develop for the case of a put option. Our estimates suggest RO may not always be a superior valuation approach to net present value for national cultures with certain characteristics.     

审计师地理距离对客户公司股价信息含量的影响

从地理经济学视角分析审计师的地理区位特征对上市公司股价信息含量的可能影响，利用2004—2013年中国A股上市公司的数据，实证检验了审计师与客户间的地理距离对客户公司股价信息含量的经验影响关系，并进一步考察了证券分析师与审计监督两种中介组织间的交互效应。研究发现：（1）审计师与客户公司间的地理距离越小，客户公司的股价信息含量越低，因为在中国当前经济社会背景下，地理邻近对审计师独立性的消极影响要强于其对审计师专业胜任能力的积极影响，这导致审计师审计质量降低，影响客户公司股价信息含量；（2）证券分析师对客户公司的关注程度越高，审计师的地理邻近性对客户公司股价信息含量的负面影响越弱，表明证券分析师与外部审计之间主要呈现一种相互替代的关系，证券分析师可以作为一种有效的补充监督机制。     

Migration decisions under ambiguity: Migration distance effects revisited

There is ample evidence that distance has a strong negative effect on migration. Despite its significance in migration decisions, scholars rarely explore the migration distance effect deeper than the first level of interpretation derived from the simple neoclassical theory of migration. This study revisits the migration distance effect in the spirit of Knightian distinction between risk and uncertainty. To this end, this study attempts to construct estimates of the risk premium migrants are willing to pay to avoid the risk associated with migration distance. The results show that the magnitude of the distance effect is not rationalized by risk aversion in the Arrow–Pratt sense (Arrow, 1965, The theory of risk aversion, Yrjo Jahnssonin Saatio, Helsinki, Finland, 90; Pratt, 1964, Econometrica, 32, 122). In particular, the risk premium demanded by distant rural residents is unjustifiably higher compared with that of those living closer to urban areas in their migration decisions. The results suggest that the migration distance effect is analogous to the equity home bias puzzle and the Ellsberg paradox in that the assumption of subjective expected utility can lead to seemingly irrational human behaviors. Some of the findings in this study shed light on the role of subjective aspects such as perception, confidence, and pessimism in migration decisions, which have been neglected in the literature.     

Interorganisational project dynamics: A longitudinal study of perceptual distance and client-contractor collaborative relationships

Despite the importance of good collaborative relationships in interorganisational projects, clients and contractors often develop adversarial relationships due to perceptual distance about key project issues. In this case study research, we investigated how perceptual distance emerges and changes over time, and how the collaborative relationship between client and contractor develops alongside these dynamics. In this exploration, we built upon agency theory and stewardship theory as complementary perspectives for understanding client-contractor collaborative relationships. We gathered quantitative and qualitative data in two projects, conducting three assessments in about one year. We found that perceptual distance increased and decreased over time, and that a reduction was typically associated with the collaborative relationship being characterized by stewardship rather than agency. These findings suggest that a regular assessment and evaluation of partners’ perceptions of critical project issues is warranted to timely detect and counteract perceptual distance. Moreover, partners would best adopt a stewardship orientation to reduce perceptual distance, although this may take considerable effort given the distributive nature of many pre-project negotiations.     

MODELING SOVEREIGN RISKS: FROM A HYBRID MODEL TO THE GENERALIZED DENSITY APPROACH

Motivated by the European sovereign debt crisis, we propose a hybrid sovereign default model that combines an accessible part taking into account the evolution of the sovereign solvency and the impact of critical political events, and a totally inaccessible part for the idiosyncratic credit risk. We obtain closed‐form formulas for the probability that the default occurs at critical political dates in a Markovian setting. Moreover, we introduce a generalized density framework for the hybrid default time and deduce the compensator process of default. Finally, we apply the hybrid model and the generalized density to the valuation of sovereign bonds and explain the significant jumps in long‐term government bond yields during the sovereign crisis.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Targeting Conservation Investments in Heterogeneous Landscapes: A Distance-Function Approach and Application to Watershed Management

To achieve an environmental objective at least cost, decision makers must integrate information about spatially variable biophysical and economic conditions. Although the biophysical attributes that contribute to an environmental outcome are often known, the way in which these attributes interact to produce the outcome is often unknown. We introduce a nonparametric conservation targeting approach that relies on distance functions to cost-efficiently allocate conservation funds. We apply the approach empirically to the case of conservation contracting for water-quality objectives. The contract portfolios derived from the application have many desirable properties, including intuitive appeal and robust performance across plausible parametric scoring measures.