Vienna University of Economics and Business
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Cognitive Diagram Understanding and Task Performance in Systems Analysis and Design
Get PDFModels play an important role in Systems Analysis and Design (SAD). A diagrammatic model is defined as a mapping from a domain to a visual representation in such a way that relevant information is preserved to meet a specific goal. So far, cognitive research on diagram criteria in relation to task performance has been fragmented. The aim of this paper is to (1) consolidate research on the cognitive processing steps involved during understanding and task performance with diagrams, (2) consolidate corresponding criteria for such diagrams to best support cognitive processing and (3) demonstrate the support effective diagrams provide for performing SAD tasks. Addressing the first aim, we develop a theoretical cognitive framework of task performance with diagrams called CogniDia. It integrates different cognitive theories from research on diagrams in software engineering and information systems. Regarding the second aim, we review the literature to organize criteria for effective cognitive processing of diagrams. We identify research gaps on verbal and task processing. Regarding the third aim, we use the theoretical cognitive framework to investigate how diagrams support the SAD process effectively
Markov-Modulated Affine Processes: Theory and Applications
No full textThe present thesis deals with Markov-modulated affine processes, a class of continuous time Markov processes that are created from affine processes by allowing some of their
coefficients to be a function of an exogenous Markov process. Affine processes have been formally studied and characterized by D. Duffie, D. Filipovic, and W. Schachermayer. This class of processes has proven to be an essential tool in modelling financial data as it is capable of capturing many stylized facts, but is at the same time remarkably tractable. However, for many specific applications in mathematical finance adding Markov-modulation to the drift, volatility or jump component of affine processes has facilitated the modelling of certain empirically observed phenomena that cannot be replicated by the standard affine model class.
The first part of this thesis is devoted to the study of theoretical aspects of Markov-modulated affine processes. We formally introduce this class of processes and prove its
existence via a martingale problem approach. We show that the formula for the characteristic function of the marginals of Markov-modulated affine processes has a computationally
convenient functional form. This in turn preserves much of the tractability of standard affine processes and allows for efficient calibration to data. Our setup is a substantial generalization of earlier work: First, we consider the case where the generator of the exogenous process is an unbounded operator (as is the case for diffusions or jump processes with infinite activity). Second, we allow for discontinuities in those coefficients of the modulated process that are controlled by the exogenous Markov process.
In the second part of this thesis we shift our focus away from the mathematical properties of Markov-modulated affine processes towards their applications in finance and economics. In the first application, we investigate European Safe Bonds (ESBies), a recently proposed class of synthetic securities that are supposed to improve the functioning of the European monetary union. In its core, ESBies form the senior tranche of a CDO backed by a diversified portfolio of sovereign bonds from all members of the euro area. The potential benefits of ESBies and other bond-backed securities hinge on the assertion that these products are really safe. We provide a comprehensive quantitative study of the risks associated with ESBies and related products, using an affine credit risk model with regime switching as vehicle for our analysis. We discuss a recent proposal of Standard and Poor’s for the rating of ESBies, we analyse the impact of model parameters and attachment points on the size and the volatility of the credit spread of ESBies and we consider several approaches to assess the market risk of ESBies. Moreover, we compare ESBies to synthetic securities created by pooling the senior tranche of national bonds. We conclude our analysis with a brief discussion of possible policy implications from our results.
The second application deals with financial bubbles. In particular, we aim to obtain an understanding of the microstructural mechanisms of stock price processes that lead to the formation of a bubble in the long run. We build a microscopic model that captures the most relevant stylized facts of tick-by-tick data and then study an appropriate scaling limit to infer which market conditions enable bubble formation in the long run. Our main findings are that liquidity asymmetry is a decisive factor in the formation of bubbles, that high market activity favors the development of a bubble, and that bubbles can even form in markets that
prevent statistical arbitrage opportunities.Security: staffonl
Reputational Risk and Corporate Tax Planning
Get PDFCorporate tax behavior has recently received considerable public interest, and anecdotal evidence suggests that firms are increasingly concerned about the reputational risk of tax planning. Using RepRisk data to capture firms’ reputational risk due to public scrutiny, this study examines the relationship between reputational risk and corporate tax planning. If managers anticipate higher costs of tax planning in response to higher reputational risk, firms might adjust their tax behavior. My results suggest that firms initially react to more public scrutiny and report higher GAAP effective tax rates. However, this association reverses once public scrutiny decays, suggesting that firms make rather superficial changes of their tax behavior in response to public pressure.Series: WU International Taxation Research Paper Serie
Optimal carbon pricing in general equilibrium: Temperature caps and stranded assets in an extended annual DSGE model
Get PDFThe general equilibrium model developed by Golosov et al. (2014), GHKT for short, is modified to allow for additional negative impacts of global warming on utility and productivity growth, mean reversion in the ratio of climate damages to production, labour-augmenting technical progress, and population growth. We also replace the GHKT assumption of full depreciation of capital each decade by annual logarithmic depreciation. Furthermore, we allow the government to use a lower discount rate than the private sector. We derive a tractable rule for the optimal carbon price for each of these extensions. We then simplify the GHKT model by making temperature a linear function of cumulative emissions and making the proportion of output lost due to global warming a linear function of temperature. Finally, we consider how the rule for the optimal carbon price must be modified to allow for a temperature cap, and what this implies for stranded oil and gas reserves. We illustrate our analytical results with a range of optimal policy simulations
Spatial spillover effects from agriculture drive deforestation in Mato Grosso, Brazil
Get PDFDeforestation of the Amazon rainforest is a threat to global climate, biodiversity, and many other
ecosystem services. In order to address this threat, an understanding of the drivers of deforestation
processes is required. Spillover effects and factors that differ across locations and over time play
important roles in these processes. They are largely disregarded in applied research and thus in the
design of evidence-based policies. In this study, we model connectivity between regions and consider
heterogeneous effects to gain more accurate quantitative insights into the inherent complexity
of deforestation. We investigate the impacts of agriculture in Mato Grosso, Brazil, for the period
2006–2017 considering spatial spillovers and varying impacts over time and space. Spillovers
between municipalities that emanate from croplands in the Amazon appear as the major driver of
deforestation, with no direct effects from agriculture in recent years. This suggests a moderate success
of the Soy Moratorium and Cattle Agreements, but highlights their inability to address indirect effects.
We find that the neglect of the spatial dimension and the assumption of homogeneous impacts lead
to distorted inference. Researchers need to be aware of the complex and dynamic processes behind
deforestation, in order to facilitate effective policy design
Identifying Challenges and Improvement Approaches for More Efficient Procurement Coordination in Relief Supply Chains
Get PDFCoordinating humanitarian organizations in the procurement of urgently needed relief items is complex and characterized by decentralization and isolated decision-making. The decentralized coordination of associated tasks often results in the duplication of efforts and redundant/incorrect relief items supplies into single disaster regions, having negative impacts on the most vulnerable ones. This paper devotes attention to the challenges that exist in the coordination of procurement activities in relief supply chains and asks for improvement approaches to facilitate more efficient demand satisfaction in disaster situations. Therefore, the authors apply multiple case study research including expert interviews with procurement agents and heads of logistics from international non-governmental organizations (NGOs), humanitarian start-ups and military logistics centers. Results indicate that a lack of incentives to cooperate, poor communication, unclear division of competences and noncompliance to standards and regulations constitute substantial challenges in procurement coordination. Moreover, expert interview results show that social media integration, procurement flexibility, cluster and collaborative coordination have potential to support improving the coordination of NGOs’ procurement activities. By presenting several theoretical propositions, this paper complements already existing literature and provides a reference point for future research. Practitioners can benefit from findings as they are provided with a guide that allows redesigning certain processes in procurement coordination
Environmental Portfolios - Evidence from screening and passive portfolio management
Get PDFEnvironmental portfolios via screening or optimization with respect to ecological criteria are not clear-cut concepts. Often, they urge investors to reduce the asset universe, which is accompanied by diversification losses. In this article, we show that a simple passive asset selection strategy based on environmental criteria allows ecological investors to adjust their portfolios without compromising or even reducing risk-adjusted financial performance. In detail, we show that screening does not lead to a significant financial performance reduction. Moreover, we propose an asset selection based on an environmental criteria that improves the portfolios’ financial performance, and further improves its potential positive environmental impact. Our results suggest that a combination of a screening and an environmental-scoring-based asset allocation seems to be a viable option for environmentally responsible investors leveraging the advantages of both strategies. Furthermore, we construct a risk factor CMP (clean minus polluting) and document a significant factor loading when added to the Fama–French five-factor model, suggesting the existence of a risk premium based on a firm’s environmental performance
Using Tomcat (a Java Web Server) to Create and Run Web Server Programs Written in ooRexx
Get PDFJava based web servers have been playing an important role in businesses for decades. Using "Java server pages (JSP)" with the "ScriptTagLibs" library allows programmers to use scripting languages to create text in JSPs rather than Java. This presentation introduces the basic concepts, supplies setup-information and a test JSP that should jump start Rexx and ooRexx programmers to create their own web servers with the logic written in ooRexx
Evolution of deterrence with costly reputation information
Get PDFDeterrence, a defender’s avoidance of a challenger’s attack based on the threat of retaliation, is a basic ingredient of social cooperation in several animal species and is ubiquitous in human societies. Deterrence theory has recognized that deterrence can only be based on credible threats, but retaliating being costly for the defender rules this out in one-shot interactions. If interactions
are repeated and observable, reputation building has been suggested as a way to sustain credibility and enable the evolution of deterrence. But this explanation ignores both the source and the costs of obtaining information on reputation. Even for small information costs successful deterrence is never evolutionarily stable. Here we use game-theoretic modelling and agent-based simulations to resolve this puzzle and to clarify under which conditions deterrence can nevertheless evolve and when it is bound to fail. Paradoxically, rich information on defenders’ past actions leads to a breakdown of deterrence, while with only minimal information deterrence can be highly successful. We argue that reputation-based deterrence sheds light on phenomena such as costly punishment and fairness, and might serve as a possible explanation for the evolution of informal property rights.Series: Department of Economics Working Paper Serie
Spatial variation in populist right voting in Austria, 2013–2017
Get PDFThe recent wave of populism sweeping Europe and the Americas generated considerable interest among political scientists, economists, sociologists and to some extent, geographers. The vast majority of these studies focuses on individual voter decisions or national comparisons over time but neglects the within-country spatial variation of the populist vote. This paper addresses this shortcoming and applies spatial econometric techniques to explore possible explanations for spatial variation in the increase of the populist right vote between the 2013 and 2017 national elections in Austria for 2118 municipalities. Spatial variation in voting shares can result from (1) compositional effects, regional differences in the composition of voters with different characteristics, (2) broad spatial, historically evolved institutional differences, such as membership to one of the nine states, (3) unequal integration of different types of regions into the global economy, such as peripheral regions, central urban regions, old industrial regions or tourist areas, (4) spatial vote spillovers due to localized social networks, and (5) unobserved spatial processes. We find that the populist right vote gains in Austrian municipalities are affected by all processes, but that the type of regions becomes insignificant once we correct for unobservable spatial structures in the regression framework. The increase in the share of foreigners, the share of foreigners, income and inequality levels, educational differences, selected state membership, as well as spatial spillovers of populist right voting are all important to explain spatial variation in the rise of the populist right vote