Political pressures and the credibility of regulation: can profit sharing mitigate regulatory risk?

When price-cap rules determine the structure of prices for a long period, they suffer a credibility problem and introduce an element of risk especially if a firm’s profits are “too large”. Profit sharing may be seen as a device to pre-determine price adjustments and thus to decrease regulatory risk. We analyse the effects of profit sharing on the incentives to invest, using a real option approach. Absent credibility issues, a well designed profit sharing system may be neutral relative to a pure price cap. With regulatory risk, profit sharing is preferable to a pure price-cap one, if it intervenes for high enough profit levels.

The deregulation of international trucking in the European Union: form and effect

We describe the regulatory regime under which international trucking operated in Western Europe until the mid-1980s, the deregulatory process that followed, and the effect of this deregulation. We find that deregulation had a large positive effect on the growth of international trucking. We also find that shippers shifted toward more outsourcing of their trucking needs, but this occurred to an even greater extent in local and national road transport. We conclude that other factors beside the deregulation of international trucking affected the organization of the industry at the time. Finally, despite concerns voiced by member countries, we find no evidence that deregulation disproportionately favored carriers of countries that were initially more (or less) involved in international trucking, nor that it has favored low-wage countries.      

An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.     

Existence of optimal strategies in linear multisector models with several consumption goods

In this paper, we give a sufficient and almost necessary condition for the existence of optimal strategies in linear multisector models when time is continuous.