Structural changes in EC trade intensities

The European Economic Community has now been in existence for about 20 years. Five years have elapsed since it was enlarged. What progress have the member countries made in the integration of their foreign trade? What would be the repercussions of a southward extension of the EC to take in Greece, Portugal and Spain?     

Consumer inventory sensitivity and the postpromotion dip

We summarize and critique seven theories that might explain the lack of a postpromotion dip in sales in the weeks following a promotion. We then propose and provide empirical support for a new explanation. We argue that in markets where the consumer category purchase decision is not strongly influenced by inventory levels, the displacement effect of accelerated sales will tend to be distributed fairly uniformly into the future such that clearly defined dips are not observed. We utilize a simulation based on real data to investigate this explanation. The simulation shows that given the degree to which inventory influences the purchase decision, we would not expect to see postpromotion dips, even though promotion influences the purchase decision. However, the simulation shows that if inventory had a greater influence on the purchase decision, we would expect to see postpromotion dips. We conclude with implications for both researchers and managers.     

Sampling Procedures for Coordinating Stratified Samples: Methods Based on Microstrata

The aim of sampling coordination is to maximize or minimize the overlap between several samples drawn successively in a population that changes over time. Therefore, the selection of a new sample will depend on the samples previously drawn. In order to obtain a larger (or smaller) overlap of the samples than the one obtained by independent selection of samples, a dependence between the samples must be introduced. This dependence will emphasize (or limit) the number of common units in the selected samples. Several methods for coordinating stratified samples, such as the Kish & Scott method, the Cotton & Hesse method, and the Rivière method, have already been developed. Using simulations, we compare the optimality of these methods and their quality of coordination. We present six new methods based on permanent random numbers (PRNs) and microstrata. These new methods have the advantage of allowing us to choose between positive or negative coordination with each of the previous samples. Simulations are run to test the validity of each of them.     

On the stability of nonsunspot equilibria

This paper analyzes the stability of the (Pareto efficient) nonsunspot equilibria as a function of the constraints faced by consumers in their ability to transfer wealth between states of nature. Equilibria that are stable for the certainty economy define nonsunspot equilibria that are stable in the following two polar cases: 1) All consumers are unconstrained; 2) All consumers are fully constrained. Furthermore, the stable certainty equilibria with small trade vectors define nonsunspot equilibria that are also stable independently of the constraint levels. Instability can develop only at intermediate constraint levels and for nonsunspot equilibria that feature sufficiently large trade vectors.     

Making real options work for practitioners: a generic model for valuing R&D projects

We propose a generic valuation framework for the appraisal of R&D projects based on real option theory. The added value of this approach is the presentation of a model that was implemented in a manner that allows corporate decision makers to use real options in an intuitive and standardized way. The project valuation procedure is separated into three main phases: project modeling, data and input collection, and result generation and analysis. The project model represents the structure of the real world R&D project with its investments, expected results, and decisions that need to be taken conditionally on the outcomes of research activities. The project model is represented in the form of a decision tree, where different research results or taken decisions lead to new branches. In this way, every possible situation the project can pass through can be represented. Uncertainties are separated into market uncertainties (e.g., market prices) and project specific, private uncertainties (e.g. uncertainty of research results). For both uncertainties, event trees are constructed which are then combined and merged with the above mentioned decision tree in order to represent the value evolution of the R&D project under given decisions and uncertainties. For every possible state of the project the real option value is calculated. By creating multidimensional trees, a multitude of decision steps and various kinds of real options (e.g., continue, expansion, switch, abandonment) can be modeled. The calculation complexity for the decision trees is given. From the tree structure we can calculate the real option value of starting an R&D project, i.e., the value of undertaking the first investment and thus acquiring the subsequent decision opportunities given by the completion of the first research effort. Furthermore, the optimal exercise strategy is derived from the decision tree. The exercise strategy gives the manager the possibility to have an a priori overview of where an R&D project may lead to, which decisions need to be taken in which circumstances, and when the project needs to be stopped in order not to generate losses. In an in‐depth case study we use an illustrative R&D project to set up and discuss the three phases of project modeling in the real options framework: building the multidimensional decision tree, input generation, and calculation of the real option value as well as the optimal strategy for the R&D project.