OPTIMAL EMPLOYEE OWNERSHIP CONTRACTS UNDER AMBIGUITY AVERSION

The aim of this paper is to compute and describe the conditions of an optimal employee ownership contract between an employer and an ambiguity‐averse employee. We then introduce ambiguity aversion in the baseline model of Aubert et al. (2014) using the multiple prior preferences of Gilboa and Schmeidler (1989) and its extension proposed by Maccheroni et al. (2006). This model offers solutions that reconcile labor and financial economics and behavioral economics research findings on employee ownership. The paper focuses on the most common situation where employee ownership has a positive impact on corporate performance, but can also be used as an entrenchment mechanism. We determine the optimal company stock contribution, which corresponds to a perfect subgame Nash equilibrium in the ambiguity framework. Using the framework of Gilboa and Schmeidler (1989), we show that the optimal ownership contract is increasing with respect to the lower bound of the return expectation in the case of a high level of effort, and decreasing with respect to the upper bound of the return expectation in the case of a low level of effort. In the framework of Maccheroni et al. (2006), we prove that if aversion to ambiguity is sufficiently high, then we find the same behavior as in the case of no ambiguity. (JEL G11, G32, G34, J33)     

Pension Schemes Comparison between EEC Countries*

Abstract. A lot of research has been made on macroeconomic spending on the financing of retirement, most of it taking into account demographic evolution. On the other hand, little research has gone into international comparisons that shed more light on the standards of living that are guaranteed after retirement, and on the flexibility and accessibility of public pension schemes. It is a study of this type that we have carried out for 11 member-states of the EEC (Greece having been left out because of its lack of statistics). In this article, we construct an index that reflects the levels of protection that are offered to the aged by the “first pillar” and under the most general conditions. On the basis of a series of important criteria (conditions for access, flexibility, intervention levels, etc.), we calculated an average of the scores for each criterion. These averages are then used to obtain a general score for each country, ranking them against each other relative to the quality of their respective pension schemes.     

Behavioral Identification in Coalitional Bargaining: An Experimental Analysis of Demand Bargaining and Alternating Offers

Alternating‐offer and demand bargaining models of legislative bargaining make very different predictions in terms of both ex ante and ex post distribution of payoffs, as well as in the role of the order of play. The experiment shows that actual bargaining behavior is not as sensitive to the different bargaining rules as the theoretical point predictions, whereas the comparative statics are in line with both models. We compare our results to studies that attempt to distinguish between these two approaches using field data, finding strong similarities between the laboratory and field data regardless of the underlying bargaining process.     

Inference under pivotal sampling: Properties,variance estimation,and application to tesselation for spatial sampling

Unequal probability sampling is commonly used for sample selection. In the context of spatial sampling, the variables of interest often present a positive spatial correlation, so that it is intuitively relevant to select spatially balanced samples. In this article, we study the properties of pivotal sampling and propose an application to tesselation for spatial sampling. We also propose a simple conservative variance estimator. We show that the proposed sampling design is spatially well balanced, with good statistical properties and is computationally very efficient.     

MORM—A Petri Net Based Model for Assessing OH&S Risks in Industrial Processes: Modeling Qualitative Aspects

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.