WHY MERGERS REDUCE PROFITS AND RAISE SHARE PRICES–A THEORY OF PREEMPTIVE MERGERS

We provide a possible explanation for the empirical puzzle that mergers often reduce profits, but raise share prices. If being an “insider” is better than being an “outsider”, firms may merge to preempt their partner merging with a rival. The insiders' stock market value is increased, since the risk of becoming an outsider is eliminated. These results are derived in an endogenous‐merger model, predicting the conditions under which mergers occur, when they occur, and how the surplus is shared. (JEL: L13, L41, G34, C78)     

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.     

Is the Precautionary Principle Really Incoherent?

The Precautionary Principle has been an increasingly important principle in international treaties since the 1980s. Through varying formulations, it states that when an activity can lead to a catastrophe for human health or the environment, measures should be taken to prevent it even if the cause‐and‐effect relationship is not fully established scientifically. The Precautionary Principle has been critically discussed from many sides. This article concentrates on a theoretical argument by Peterson (2006) according to which the Precautionary Principle is incoherent with other desiderata of rational decision making, and thus cannot be used as a decision rule that selects an action among several ones. I claim here that Peterson's argument fails to establish the incoherence of the Precautionary Principle, by attacking three of its premises. I argue (i) that Peterson's treatment of uncertainties lacks generality, (ii) that his Archimedian condition is problematic for incommensurability reasons, and (iii) that his explication of the Precautionary Principle is not adequate. This leads me to conjecture that the Precautionary Principle can be envisaged as a coherent decision rule, again.     

Dynamic Pricing to Minimize Maximum Regret

We consider a dynamic pricing problem that involves selling a given inventory of a single product over a short, two‐period selling season. There is insufficient time to replenish inventory during this season, hence sales are made entirely from inventory. The demand for the product is a stochastic, nonincreasing function of price. We assume interval uncertainty for demand, that is, knowledge of upper and lower bounds but not a probability distribution, with no correlation between the two periods. We minimize the maximum total regret over the two periods that results from the pricing decisions. We consider a dynamic model where the decision maker chooses the price for each period contingent on the remaining inventory at the beginning of the period, and a static model where the decision maker chooses the prices for both periods at the beginning of the first period. Both models can be solved by a polynomial time algorithm that solves systems of linear inequalities. Our computational study demonstrates that the prices generated by both our models are insensitive to errors in estimating the demand intervals. Our dynamic model outperforms our static model and two classical approaches that do not use demand probability distributions, when evaluated by maximum regret, average relative regret, variability, and risk measures. Further, our dynamic model generates a total expected revenue which closely approximates that of a maximum expected revenue approach which requires demand probability distributions.     

The Role of Shocks in Employee Turnover*

This paper reports the findings from a recent study of nurse leavers at eight large hospitals in the National Health Service (NHS) of England and Wales. The study develops and extends an influential theory of employee turnover by describing how for some leavers a single, jarring event or shock triggers the decision to quit. By elaborating on the nature of shocks for this sample of 352 nurse leavers, the paper allows for improved understanding of nursing turnover and thus offers an example of relevant management research. The analysis of shock illustrates how conventional research methodologies can lead to a distorted picture of turnover. This has wider implications, both for any organization wishing to manage turnover effectively and for future research. The paper adds to the limited body of empirical analysis on actual leavers, thereby contributing to an ongoing methodological debate concerning the use of proxy variables. By highlighting flaws in the dominant methodology used to study turnover, the paper offers an example of management research that is also rigorous, and thus ‘pragmatic’.     

An Empirical Investigation of Corporate Citizenship in Australia and Turkey *

This paper describes a study of corporate citizenship practices and its relationship to dimensions of internal and external corporate culture, customer loyalty and organizational commitment. Empirical data was collected from a cross‐industry sample in Turkey and Australia using a questionnaire form developed and validated for other cultures. It was shown that Australian and Turkish firms' practices differed significantly on a number of important variables, but also that it is possible to compare corporate citizenship practices in a way that is not culture‐specific.     

A General Formula for Valuing Defaultable Securities

Previous research has shown that under a suitable no‐jump condition, the price of a defaultable security is equal to its risk‐neutral expected discounted cash flows if a modified discount rate is introduced to account for the possibility of default. Below, we generalize this result by demonstrating that one can always value defaultable claims using expected risk‐adjusted discounting provided that the expectation is taken under a slightly modified probability measure. This new probability measure puts zero probability on paths where default occurs prior to the maturity, and is thus only absolutely continuous with respect to the risk‐neutral probability measure. After establishing the general result and discussing its relation with the existing literature, we investigate several examples for which the no‐jump condition fails. Each example illustrates the power of our general formula by providing simple analytic solutions for the prices of defaultable securities.     

Polarization: Concepts,Measurement, Estimation

We develop the measurement theory of polarization for the case in which income distributions can be described using density functions. The main theorem uniquely characterizes a class of polarization measures that fits into what we call the “identity‐alienation” framework, and simultanously satisfies a set of axioms. Second, we provide sample estimators of population polarization indices that can be used to compare polarization across time or entities. Distribution‐free statistical inference results are also used in order to ensure that the orderings of polarization across entities are not simply due to sampling noise. An illustration of the use of these tools using data from 21 countries shows that polarization and inequality orderings can often differ in practice.     

Asymptotic Distributions of Quasi‐Maximum Likelihood Estimators for Spatial Autoregressive Models

This paper investigates asymptotic properties of the maximum likelihood estimator and the quasi‐maximum likelihood estimator for the spatial autoregressive model. The rates of convergence of those estimators may depend on some general features of the spatial weights matrix of the model. It is important to make the distinction with different spatial scenarios. Under the scenario that each unit will be influenced by only a few neighboring units, the estimators may have ‐rate of convergence and be asymptotically normal. When each unit can be influenced by many neighbors, irregularity of the information matrix may occur and various components of the estimators may have different rates of convergence.