We analyze a principal-agent model with moral hazard where the principal is risk neutral while the agent is risk averse or risk neutral. The agent is free to choose any probability distribution over outcomes, where some distributions require more effort than others. The agent's effort-cost function is of "Legendre type" and satisfies an axiom of invariance under mergers of outcomes that are equally paid by the principal. We analyze a family of such effort-cost functions. For a canonical subclass of these, and arbitrary outcome spaces, the principal's contract problem allows for closed-form solutions. Optimal contracts then combine debt with a monotonic sharing rule for the surplus above a threshold chosen by the principal. When the agent is risk neutral, the contract boils down to a pure debt contract. For agents with unit degree of relative risk aversion, the surplus is divided in fixed shares.

A modified version of Lazear’s model (in American Economic Review, 94, 208-211, 2004, Journal of Labor Economics, 23, 649–680, 2005) for occupational choice is formulated. It includes a utility adjustment factor that captures the combined effect of nonpecuniary benefits and uncertainty associated with entrepreneurship. We show that the counterfactual income returns to entrepreneurship are lower than the market value of entrepreneurial talent and higher than the inverse of the utility adjustment factor. Moreover, if the skill profiles in the population are Fréchet-distributed, the ratio between the expected incomes of entrepreneurs and observationally similar wage employees is lower than the inverse of the utility adjustment factor. Thus, entrepreneurs will on average earn less than wage employees if the utility adjustment factor is greater than or equal to one. It is also shown that the self-selection bias related to this income ratio or returns measure increases with the observed percentage of entrepreneurs. Swedish employment data are used to calibrate the modified Lazear model. The empirical results indicate that uncertainty considerations might be more important for the occupational choices than nonpecuniary benefits.

The connected autonomous vehicle (CAV) will never be completely autonomous; on the contrary, it will be heavily dependent on so-called vehicular ad hoc networks (VANETs) for its function. To deserve the trust of the general public, the vehicles as well as the intelligent transport system (ITS) infrastructure must be able to handle not only natural disturbances but also attacks of malicious nature. In this paper, we discuss the effects of antagonistic attacks using intentional electromagnetic interference (IEMI) and how the antagonistic nature of the threat renders probabilistic risk analysis inadequate for the defense of the vehicles and the infrastructure. Instead, we propose a shift toward resilience engineering and vulnerability analysis to manage antagonistic threats. Finally, we also give two examples of possible scenarios to illustrate the type of situations a CAV must be able to handle.

The development of Self-Driving Vehicles (SDVs) is fast, and SDVs are predicted to have the potential to change mobility, human life, and society. Several positive and negative effects of SDVs are listed in the literature, but as the effects can be both counteracting and reinforcing depending on actions taken by different stakeholders, it is difficult to predict the outcome. In this chapter a scenario planning method is used to identify certain and uncertain trends, and to draw four different but plausible future scenarios for the development of SDVs. The four scenarios create a platform for policy discussions, development of regulations, and decision-making of different stakeholders. Most importantly, it shows that the development of SDVs depends on decisions made today.

Many models in economics involve discrete choices where a decision-maker selects the best alternative from a finite set. Viewing the array of values of the alternatives as a random vector, the decision-maker draws a realization and chooses the alternative with the highest value. The analyst is then interested in the choice probabilities and in the value of the best alternative. The random vector has the invariance property if the distribution of the value of a specific alternative, conditional on that alternative being chosen, is the same, regardless of which alternative is considered. This note shows that the invariance property holds if and only if the marginal distributions of the random components are positive powers of each other, even when allowing for quite general statistical dependence among the random components. We illustrate the analytical power of the invariance property by way of examples.

Modern infrastructures are becoming increasingly dependent on electronic systems, leaving them more vulnerable to electrical surges or electromagnetic interference. Electromagnetic disturbances appear in nature, e.g., lightning and solar wind; however, they may also be generated by man-made technology to maliciously damage or disturb electronic equipment. This article presents a systematic risk assessment framework for identifying possible, consequential, and plausible intentional electromagnetic interference (IEMI) attacks on an arbitrary distribution network infrastructure. In the absence of available data on IEMI occurrences, we find that a systems-based risk assessment is more useful than a probabilistic approach. We therefore modify the often applied definition of risk, i.e., a set of triplets containing scenario, probability, and consequence, to a set of quadruplets: scenario, resource requirements, plausibility, and consequence. Probability is replaced by resource requirements and plausibility, where the former is the minimum amount and type of equipment necessary to successfully carry out an attack scenario and the latter is a subjective assessment of the extent of the existence of attackers who possess the motivation, knowledge, and resources necessary to carry out the scenario. We apply the concept of intrusion areas and classify electromagnetic source technology according to key attributes. Worst-case scenarios are identified for different quantities of attacker resources. The most plausible and consequential of these are deemed the most important scenarios and should provide useful decision support in a countermeasures effort. Finally, an example of the proposed risk assessment framework, based on notional data, is provided on a hypothetical water distribution network.

The original version of this article unfortunately contains an error in Appendix A.

This paper investigates the income return to entrepreneurship and wage employment by means of Lazear's model of occupational choice. The paper has two major aims. The first is to develop a new theoretical framework for analyzing the income return to entrepreneurship by combining the Lazear model with the assumption that the skill profiles in a population are Frechet-distributed. The second is to demonstrate that the resulting theoretical derivations can be used for a new type of regional analysis of the income return to entrepreneurship and wage employment. The empirical analysis is based on data for individuals with a Master of Science degree in Electrical Engineering. We compute their income return to self-employment and wage employment in three parts of Sweden: the Stockholm region, the combined Gothenburg and Malmo region, and the Rest of Sweden. The results show that the average return to self-employment is less than 5% in all regions and smaller in the Gothenburg and Malmo region than in the other two regions. The regional differences are explained by the differential supply curves and market values of entrepreneurial talent. The theoretical derivation of the income return to entrepreneurship is the main contribution of the paper. Another contribution is the derivation of regional supply curves for entrepreneurs.

The development of Self-Driving Vehicles (SDVs) is fast, and new pilots and tests are released every week. SDVs are predicted to have the potential to change mobility, human life and society.

In literature, both negative and positive effects of SDVs are listed (Litman 2015; Fagnant and Kockelman 2015). Among the positive effects are increased traffic throughput leading to less congestion, improved mobility for people without a driver’s license, decreased need for parking spaces, and SDV as an enabler for shared mobility. On the other hand, SDVs are expected to increase the consumption of transport which leads to an increase in total vehicle kilometers travelled. This effect is further reinforced by empty vehicles driving around. This will increase the number of vehicles on the streets and lead to more congestion and increased energy usage. Since the SDV technology is expensive, segregation may be a consequence of the development. In addition there are several challenges related to for example legislation, standardization, infrastructure investments, privacy and security. The question is not if, but rather when SDVs will be common on our streets and roads, and if they will change our way of living, and if so, how?

As we are in a potential mobility shift, and decisions made today will affect the future development, understanding possibilities and challenges for the future is important for many stakeholders. To this end a scenario-based future study was performed to derive a common platform for initiation of future research and innovation projects concerning SDVs in Sweden. This study will also be used in the ongoing governmental investigation about future regulations for SDVs on Swedish roads (Bjelfvenstam 2016). A third motivation for the study is to shed light on how demography, geography and political landscape can affect the development of new mobility services.

Since there are many different forces that drive the development, often uncertain and sometimes in conflict with each other, a scenario planning approach was chosen. In previous studies, different types of predictions have been derived. Most of them are made by US scholars and are therefore naturally focused on the development in the US. The culture, both with respect to urban planning and public transport is different in Europe compared to the US.

The work has been performed by an expert group and a smaller analysis team. The expert group has involved nearly 40 persons from 20 transport organizations, including public authorities, lawyers, city planners, researchers, transport service suppliers, and vehicle manufacturers. The expert group met three times, each time focusing on a specific theme: 1) trend analysis, 2) defining scenario axes of uncertainty, and 3) consequence analysis. The analysis team, consisting of the present three authors and two future strategists, has analyzed, refined and condensed the material from the expert group.

During the project certain trends and strategic uncertainties were identified by the expert group. The uncertainties that were identified as most important for the development of SDVs in Sweden are: 1) whether the sharing economy becomes a new norm or not, and 2) whether city planners, authorities and politicians will be proactive in the development of cities and societies or not, especially regarding the transportation system. This led to four scenarios: A) “Same, same but all the difference” – a green, individualistic society, B) “Sharing is the new black” – a governmentally driven innovation society based on sharing, C) “Follow the path” – an individualistic society based on development in the same direction as today, and D) “What you need is what you get” – a commercially driven innovation society where sharing is a key.

In the paper, we describe the scenarios and the process to derive them in more detail. We also present an analysis of the consequences for the development of SDVs in the four scenarios, including predictions concerning pace of development, level of self-driving, fleet size, travel demand and vehicle kilometers travelled. The paper also includes a discussion and comparison with other studies on the development of SDVs in the US, Europe and Asia.