Students’ knowledge of emerging technology and sustainability through a design activity in technology education

International Journal of Technology and Design Education - The purpose of this study is to explore whether, and if so how, a design activity could encourage students to express and develop...     

Vox Populi,Vox Dei? Tacit collusion in politics

We study competition between political parties in repeated elections with probabilistic voting. This model entails multiple equilibria, and we focus on cases where political collusion occurs. When parties hold different opinions on some policy, they may take different policy positions that do not coincide with the median voter's preferred policy platform. In contrast, when parties have a mutual understanding on a particular policy, their policy positions may converge (on some dimension) but not to the median voter's preferred policy. That is to say, parties can tacitly collude with one another, despite political competition. Collusion may collapse, for instance, after the entry of a new political party. This model rationalizes patterns in survey data from Sweden, where politicians on different sides of the political spectrum take different positions on economic policy but similar positions on refugee intake—diverging from the average voter's position, but only until the entry of a populist party.     

Deep empirical risk minimization in finance: Looking into the future

Many modern computational approaches to classical problems in quantitative finance are formulated as empirical loss minimization (ERM), allowing direct applications of classical results from statistical machine learning. These methods, designed to directly construct the optimal feedback representation of hedging or investment decisions, are analyzed in this framework demonstrating their effectiveness as well as their susceptibility to generalization error. Use of classical techniques shows that over-training renders trained investment decisions to become anticipative, and proves overlearning for large hypothesis spaces. On the other hand, nonasymptotic estimates based on Rademacher complexity show the convergence for sufficiently large training sets. These results emphasize the importance of synthetic data generation and the appropriate calibration of complex models to market data. A numerically studied stylized example illustrates these possibilities, including the importance of problem dimension in the degree of overlearning, and the effectiveness of this approach.     

Neither market nor hierarchy—coordination costs in the allocation of track capacity in the Swedish railway network

Transaction costs have been an issue since the advent of the deregulation of the European railway markets in the 1990s. Transaction cost economics received renewed attention in research on the deregulated railway markets in the EU after the publications of two influential reports in the early 2010s. In this article, we develop a model that enables classification and measurement of transaction costs and other coordination costs in deregulated markets. This model is then used to analyze the costs of path allocation in the Swedish railway sector and to compare the results with findings in previous research. We also discuss the economic rationale of the distribution of coordination costs among the involved parties. Our key empirical findings are that the total coordination costs in the Swedish market-mimicking path allocation process are as low as or lower than the most cost-efficient market coordination processes studied in railway markets, and that the state administrations take on nearly all the coordination costs in order to minimize the effects of opportunism, rent-seeking and information impactedness. Another finding is that the size of the coordination costs found by different studies seems to be dependent on whether a bottom-up or a top-down approach is used.