Corporate Cash Holdings and Acquisitions

We find that acquirers’ announcement returns decline with their cash holdings, but only when at least part of the payment is in the form of stock. We further find evidence that acquirers that use stock payment are overvalued, especially when they have excess cash that they could have used instead. Collectively, our results suggest that investors interpret announcements of stock acquisitions as a signal that the acquirers’ equity is overvalued and that high cash holdings intensify this signal. However, our results are inconsistent with the common belief that cash holdings induce value‐destroying acquisitions.     

The rise of defensive engineering: how personal liability considerations impact decision-making

Abstract

Based on a survey of Australian engineers (n = 275) this paper examines the impact of personal liability considerations on engineering decision-making. Almost all respondents who make high-stakes decisions saw questions of liability as having both positive (90%) and negative (87%) impacts. Our analysis shows that awareness of personal liability acts to focus the attention of many engineers on the moral dimension of their work. However, it also encourages more expensive decision-making, inhibition of innovation and professional paralysis. We argue that while personal legal liability is a legitimate way to focus engineers’ attention on the potential impact of their work, a problem arises when decision-makers are held responsible for disasters over which they had little control. The focus then shifts to ‘defensive engineering’ practices that are aimed at limiting individual liability rather than disaster prevention. Legal processes that are seen to unfairly allocate blame do not encourage practices that support future disaster prevention.     

Mean–variance and mean–semivariance portfolio selection: a multivariate nonparametric approach

While univariate nonparametric estimation methods have been developed for estimating returns in mean-downside risk portfolio optimization, the problem of handling possible cross-correlations in a vector of asset returns has not been addressed in portfolio selection. We present a novel multivariate nonparametric portfolio optimization procedure using kernel-based estimators of the conditional mean and the conditional median. The method accounts for the covariance structure information from the full set of returns. We also provide two computational algorithms to implement the estimators. Via the analysis of 24 French stock market returns, we evaluate the in-sample and out-of-sample performance of both portfolio selection algorithms against optimal portfolios selected by classical and univariate nonparametric methods for three highly different time periods and different levels of expected return. By allowing for cross-correlations among returns, our results suggest that the proposed multivariate nonparametric method is a useful extension of standard univariate nonparametric portfolio selection approaches.     

Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.     

Exploring business process modelling paradigms and design-time to run-time transitions

The business process management literature describes a multitude of approaches (e.g. imperative, declarative or event-driven) that each result in a different mix of process flexibility, compliance, effectiveness and efficiency. Although the use of a single approach over the process lifecycle is often assumed, transitions between approaches at different phases in the process lifecycle may also be considered. This article explores several business process strategies by analysing the approaches at different phases in the process lifecycle as well as the various transitions.     

Effectiveness of independent boards of UCITS funds

In order to protect fund investors against conflicts of interest with fund management companies, US funds have mandatory independent directors, but this obligation is not required under the European Union Undertakings for Collective Investment in Transferable Securities (UCITS) Directive. Nevertheless, a considerable number of UCITS funds do have independent directors. Whether independent directors should also be mandatory in Europe has been a topic of ongoing debate. Using a sample of Luxembourg UCITS, we test the hypothesis that more independent boards add value for investors through lower costs and/or better investment performance, but we fail to find supporting evidence, even for funds with a higher risk of conflicts of interest. Oversight by independent depositaries and institutional shareholders does not seem to be effective either. It appears that board attitude and the sponsor distribution model are more important since we find evidence that boards that prioritise cost monitoring have lower costs and that independent sponsor funds have better performance. These results question the effectiveness of self-regulation or formal regulation requiring independent board members.     

Heuristic learning and the discovery of specialization and exchange

I develop and calibrate an agent-based model of boundedly rational, adaptive agents in a two-good production and exchange economy to replicate human-subject outcomes in the same eight-person experimental economy. To test agents’ ability to capture human behavior, I extend the model and use its output to make predictions about a second experimental environment in which the group of eight agents is slowly constructed by merging smaller groups. This environment improves human-subject performance in the specialization and exchange task, and commensurate improvement emerges for some parameterizations of the agent-based model. This iterative process yields incremental improvement of decision-level theories about economic discovery.     

Timing the Start of Material Substitution Projects: Creating Switching Options under Volatile Material Prices

Firms developing new products often face the challenge of making investment decisions under uncertain input–cost conditions due to the price volatilities of the materials they use. These decisions need to be made long before the final products are launched on the market. Therefore, firms that invest in the opportunity to switch materials in a timely manner will have the flexibility to react to material price changes and realize competitive advantages. However, volatile material prices may also cause a firm to delay investment. Using real‐options reasoning, this paper studies the influence of input‐cost fluctuations on the timing decision to start new product development (NPD) and thus create the follow‐on opportunity to later replace an existing product. A model that combines waiting and switching options to derive influencing factors of the flexibility value that triggers the investment is developed and tested on a sample of material substitution projects from manufacturing firms. The results show how price uncertainty of the new and the old material, their joint price development, the expected project duration, and competitive preemption are related to the propensity to delay the start of NPD. The findings provide new insights on how timing in adopting materials can be used to hedge exposure to volatile material prices. The insights are relevant for adopters and producers of new materials, as well as for policy makers who strive for supporting the diffusion of new materials.     

Cannabis use and mental health problems

This paper investigates whether cannabis use leads to worse mental health. To do so, we account for common unobserved factors affecting mental health and cannabis consumption by modeling mental health jointly with the dynamics of cannabis use. Our main finding is that using cannabis increases the likelihood of mental health problems, with current use having a larger effect than past use. The estimates suggest a dose–response relationship between the frequency of recent cannabis use and the probability of currently experiencing a mental health problem. Copyright © 2010 John Wiley & Sons, Ltd.