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The concepts of food deficit, hunger, undernourishment and food security are discussed. Axioms and indices for the assessment of nutrition of individuals and groups are suggested. Furthermore a measure for food aid donor performance is developed and applied to a sample of bilateral and multilateral donors providing food aid for African countries.
Revisiting public investment
(2004)
The consumption equivalence method is the theoretical basis of public cost-benefit analysis. Consumption equivalence public capital prices are explicitly introduces in order to sufficiently care for the opportunity cost of public expenditure. This can solve the dispute about the social rate of discount within public cost-benefit analysis witch was generated on a criterion looking similar to the capital value formula, known as Lind’s approach. The social rate of discount is liberated from opportunity costs considerations and the discounting away of the effects for future welfare vanishes. The corresponding question whether one should accept a positive value of the pure rate of social time preference is an old issue. Its current state between the prescriptive and descriptive view can also be interpreted as a consequence of the oversimplification of standard cost– benefit analysis. But apart from an economic self-process the pure rate of social time preference is also defined as a business-as-usual value of social distance discounting. Hence, a political choice has to be made about this rate which is free in principal.
An exhaustive and disjoint decomposition of social choice situations is derived in a general set theoretical framework using the new tools of the Lifted Pareto relation on the power set of social states representing a pre-choice comparison of choice option sets. The main result is the classification of social choice situations which include three types of social choice problems. First, we usually observe the common incompleteness of the Pareto relation. Second, a kind of non-compactness problem of a choice set of social states can be generated. Finally, both can be combined. The first problem root can be regarded as natural everyday dilemma of social choice theory whereas the second may probably be much more due to modeling technique implications. The distinction is enabled at a very general set theoretical level. Hence, the derived classification of social choice situations is applicable on almost every relevant economic model.
Many European countries have experienced a significant increase of unemployment in recent years. This paper reviews several theoretical models that try to explain this phenomenon. Predominantly, these models claim a link between the poor performance of European labor markets and the high level of market regulation. Commonly referred to as the Eurosclerosis debate, prominent approaches consider insider-outsider relationships, search-models, and the influence of hiring and firing costs on equilibrium employment. The paper presents empirical evidence of each model and studies the relevance of the identified rigidities as a determinant of high unemployment in Europe. Furthermore, a case study analyzes the unemployment problem in Germany and critically discusses new reform efforts. In particular this section analyzes whether the recently enacted Hartz reforms can induce higher employment.
Public pensions in the U.S.
(2005)
Contents: The Public Old Age Insurance of the U.S. -Historical overview -Technical details -Individual equity and social adequacy The Economic Problem of Old Age -Risks and economic security -Old age, retirement, and idividual precaution -Insurance markets, market failures, and social insurance -Options for public pension systems The Problems of Social Security -The financial balance of OASDI -Causes of the long-run problems -Rates of return -Conclusion - The case for Social Security reform Proposed Remedies -Full, partial, or no privatization? -The President's Commission to Strengthen Social Security -Kotlikoff's Personal Security System -The Diamond-Orszag Three-Part plan
The requirements of modern e-learning techniques change. Aspects such as community interaction, flexibility, pervasive learning and increasing mobility in communication habits become more important. To meet these challenges e-learning platforms must provide support on mobile learning. Most approaches try to adopt centralised and static e-learning mechanisms to mobile devices. However, often technically it is not possible for all kinds of devices to be connected to a central server. Therefore we introduce an application of a mobile e-learning network which operates totally decentralised with the help of an underlying ad hoc network architecture. Furthermore the concept of ad hoc messaging network (AMNET) is used as basis system architecture for our approach to implement a platform for pervasive mobile e-learning.
The present thesis introduces an iterative expert-based Bayesian approach for assessing greenhouse gas (GHG) emissions from the 2030 German new vehicle fleet and quantifying the impacts of their main drivers. A first set of expert interviews has been carried out in order to identify technologies which may help to lower car GHG emissions and to quantify their emission reduction potentials. Moreover, experts were asked for their probability assessments that the different technologies will be widely adopted, as well as for important prerequisites that could foster or hamper their adoption. Drawing on the results of these expert interviews, a Bayesian Belief Network has been built which explicitly models three vehicle types: Internal Combustion Engine Vehicles (which include mild and full Hybrid Electric Vehicles), Plug-In Hybrid Electric Vehicles, and Battery Electric Vehicles. The conditional dependencies of twelve central variables within the BBN - battery energy, fuel and electricity consumption, relative costs, and sales shares of the vehicle types - have been quantified by experts from German car manufacturers in a second series of interviews. For each of the seven second-round interviews, an expert's individually specified BBN results. The BBN have been run for different hypothetical 2030 scenarios which differ, e.g., in regard to battery development, regulation, and fuel and electricity GHG intensities. The present thesis delivers results both in regard to the subject of the investigation and in regard to its method. On the subject level, it has been found that the different experts expect 2030 German new car fleet emission to be at 50 to 65% of 2008 new fleet emissions under the baseline scenario. They can be further reduced to 40 to 50% of the emissions of the 2008 fleet though a combination of a higher share of renewables in the electricity mix, a larger share of biofuels in the fuel mix, and a stricter regulation of car CO$_2$ emissions in the European Union. Technically, 2030 German new car fleet GHG emissions can be reduced to a minimum of 18 to 44% of 2008 emissions, a development which can not be triggered by any combination of measures modeled in the BBN alone but needs further commitment. Out of a wealth of existing BBN, few have been specified by individual experts through elicitation, and to my knowledge, none of them has been employed for analyzing perspectives for the future. On the level of methods, this work shows that expert-based BBN are a valuable tool for making experts' expectations for the future explicit and amenable to the analysis of different hypothetical scenarios. BBN can also be employed for quantifying the impacts of main drivers. They have been demonstrated to be a valuable tool for iterative stakeholder-based science approaches.
Background:
Research into the application of virtual reality technology in the health care sector has rapidly increased, resulting in a large body of research that is difficult to keep up with.
Objective:
We will provide an overview of the annual publication numbers in this field and the most productive and influential countries, journals, and authors, as well as the most used, most co-occurring, and most recent keywords.
Methods:
Based on a data set of 356 publications and 20,363 citations derived from Web of Science, we conducted a bibliometric analysis using BibExcel, HistCite, and VOSviewer.
Results:
The strongest growth in publications occurred in 2020, accounting for 29.49% of all publications so far. The most productive countries are the United States, the United Kingdom, and Spain; the most influential countries are the United States, Canada, and the United Kingdom. The most productive journals are the Journal of Medical Internet Research (JMIR), JMIR Serious Games, and the Games for Health Journal; the most influential journals are Patient Education and Counselling, Medical Education, and Quality of Life Research. The most productive authors are Riva, del Piccolo, and Schwebel; the most influential authors are Finset, del Piccolo, and Eide. The most frequently occurring keywords other than “virtual” and “reality” are “training,” “trial,” and “patients.” The most relevant research themes are communication, education, and novel treatments; the most recent research trends are fitness and exergames.
Conclusions:
The analysis shows that the field has left its infant state and its specialization is advancing, with a clear focus on patient usability.
We collect a network dataset of tenured economics faculty in Austria, Germany and Switzerland. We rank the 100 institutions included with a minimum violation ranking. This ranking is positively and significantly correlated with the Times Higher Education ranking of economics institutions. According to the network ranking, individuals on average go down about 23 ranks from their doctoral institution to their employing institution. While the share of females in our dataset is only 15%, we do not observe a significant gender hiring gap (a difference in rank changes between male and female faculty). We conduct a robustness check with the Handelsblatt and the Times Higher Education ranking. According to these rankings, individuals on average go down only about two ranks. We do not observe a significant gender hiring gap using these two rankings (although the dataset underlying this analysis is small and these estimates are likely to be noisy). Finally, we discuss the limitations of the network ranking in our context.
Creative thinking is an indispensable cognitive skill that is becoming increasingly important. In the present research, we tested the impact of games on creativity and emotions in a between-subject online experiment with four conditions (N = 658). (1) participants played a simple puzzle game that allowed many solutions (priming divergent thinking); (2) participants played a short game that required one fitting solution (priming convergent thinking); (3) participants performed mental arithmetic; (4) passive control condition. Results show that divergent and convergent creativity were higher after playing games and lower after mental arithmetic. Positive emotions did not function as a mediator, even though they were also heightened after playing the games and lower after mental arithmetic. However, contrary to previous research, we found no direct effect of emotions, creative self-efficacy, and growth- vs. fixed on creative performance. We discuss practical implications for digital learning and application settings.