Dissertations / Theses on the topic 'Uncertainty'
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ONGARO, MALVINA. "Uncertainty for uncertain decision makers." Doctoral thesis, Università degli studi di Genova, 2022. https://hdl.handle.net/11567/1100017.
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First Chapter - While mainstream decision theory only allows for variations
in the severity of uncertainty, the plurality of labels with which uncertainty has been referred to in the literature and the variety of doubts that decision makers can have seem to suggest that there are different types of uncertainty. Given the importance that uncertainty has in almost any decision, understanding this plurality can be helpful to decide effectively. I propose an account of uncertainty as based on a disagreement between reasons supporting alternative mental attitudes. Under this account, dealing with uncertainty means dealing with disagreement; however, this disagreement can be radical, i.e. persistent under ideal cognitive and epistemic conditions. When this is the case, the disagreement and therefore the uncertainty cannot be resolved with an increase in evidence. I draw a typology of uncertainty reflecting the conditions that must obtain for the possibility of radical disagreement, and I trace the role that each of the types identified plays in decision making.Second Chapter - Decision theories have largely ignored the step of decision making in which the agent models the situation. Given that a decision can be represented with different models, and that these can lead to different recommendations, then without a principled way to assess them the agent’s choice is under-determined. As models require the agent to select the aspects that matter to the decision, an account of rational decision modelling must include a notion of relevance. I propose that the most rational model is the one taking into account all and only the considerations relevant for the decision. I define relevance for a decision as a matter of providing reasons for some option, and I identify four functional types of reasons leading to four corresponding types of relevance. I focus on what I call “constitutive relevance”, which provides the content of the decision model, and propose a formal definition of this concept.
Third Chapter - The increasing success of the evidence-based policy movement is raising the demand for empirically informed decision making. As arguably any policy decision happens under conditions of uncertainty, following our best available evidence to reduce the uncertainty seems a requirement of good decision making. However, not all the uncertainty faced by decision makers can be resolved by evidence. In this paper, we build on a philosophical analysis of uncertainty to identify the boundaries of scientific advice in policy decision making. We argue that the authority of scientific advisors is limited to cognitive uncertainty and cannot extend beyond it. While the appeal of evidence-based policy rests on a view of scientific advice as limited to cognitive uncertainty, in practice there is a risk of over-reliance on experts beyond the legitimate scope of their authority. We conclude by applying our framework to a real-world case of evidence based policy, where experts have overstepped their boundaries by ignoring non-cognitive types of uncertainty.
Fourth Chapter - The COVID-19 pandemic has presented the world with a series of new challenges, but the policy response may be difficult due to the severe uncertainty of our circumstances. While pressure to take timely action may push towards less inclusive decision procedures, in this paper I argue that precisely this uncertainty provides both democratic and epistemic reasons to include stakeholders in our collective decision making.
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Abdullah, Johari. "Uncertainty and uncertainty tolerance in service provisioning." Thesis, University of Newcastle upon Tyne, 2014. http://hdl.handle.net/10443/2467.
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Service, in general term is a type of economic activity where the consumers utilize labour and/or expertise of others to perform a specific task. The birth and continued growth of the Internet provide a new medium for services to be delivered, and enable services to become widely and readily available. In recent years, the Internet has become an important platform to provide services to the end users. Service provisioning, In the context of computing, is the process of providing users with access to data and technology resources. In a perfect operating environment, the entities involved can expect the system will perform as intended or up to an accepted level of quality. Unfortunately, disruptions or failures can occur which can affect the operation of the service. Thus, the entities involved, in particular the service requester faces a situation whereby the service requester’s belief towards certain process in the service provisioning life cycle is affected, i.e. deviates from the actual truth. This situation whereby the service requester’s belief is affected is referred as an uncertainty. in this thesis, we discuss and explore the issue of uncertainty throughout the service provisioning life cycle and provide a measure to tolerate uncertainty in service provisioning offer through the application of subjective probability framework. This thesis provides several key contributions to address the uncertainty issues in service provision- Ing system in particular, for a service requester to overcome the negative consequence of uncertainty. The key contributions are: (1) introduction to the issue of uncertainty in service provisioning system, (2) a new classification scheme for uncertainties in service provisioning system, (3) a unified view of uncertainty in service provisioning system based on temporal classification, which is linked to service requester’s view, (4) a concept of uncertainty tolerance for service provisioning, (5) an approach and framework for automated uncertainty tolerance in service provisioning offer. The approach and framework for uncertainty tolerance in service provisioning offer presented in this thesis is evaluated through an empirical study. The result from the study shows the viability of the approach and framework of the uncertainty tolerance Mechanism through the application of subjective probability theory. The result also shows the positive outcome of the mechanism in term of higher cumulative utility, and better acceptance rate for the service requester.
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Willquist, André. "Uncertainty Discretization for Motion Planning Under Uncertainty." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-170496.
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In this thesis, the problem of motion planning under uncertainty is explored. Motion planning under uncertainty is important since even with noise during the execution of the plan, it is desirable to keep the collision risk low. However, for the motion planning to be useful it needs to be possible to perform it in a reasonable time. The introduction of state uncertainty leads to a substantial increase in search time due to the additional dimensions it adds to the search space. In order to alleviate this problem, different approaches to pruning of the search space are explored. The initial approach is to prune states based on having strictly worse uncertainty and path cost than other found states. Having performed this initial pruning, an alternate approach to comparing uncertainties is examined in order to explore if it is possible to achieve a lower search time. The approach taken in order to lower the search time further is to discretize the covariance of a state by using a number of buckets. However, this discretization results in giving up the completeness and optimality of the algorithm. Having implemented these different ways of pruning, their performance is tested on a number of different scenarios. This is done by evaluating the planner using the pruning in several different scenarios including uncertainty and one without uncertainty. It is found that all of the pruning approaches reduce the overall search time compared to when no additional pruning based on the uncertainty is done. Additionally, it is indicated that the bucket-based approach reduce the search time to a greater extent than the strict pruning approach. Furthermore, the extensions made results in no increase in cost or a very small increase in cost for the explored scenarios. Based on these results, it is likely that the bucket pruning approach has some potential. However more studies, particularly with additional scenarios, needs to be made before any definitive conclusions can be made.
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Woolley, Richard. "Living uncertain lives : a study in the sociology of uncertainty /." View thesis, 2002. http://library.uws.edu.au/adt-NUWS/public/adt-NUWS20030721.144500/index.html.
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Thesis (Ph.D.) -- University of Western Sydney, 2002."Dissertation submitted in fulfillment of the requirements for the award of the degree of Doctor of Philosophy, September 2002." Bibliography: p. 445 - 466.
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Vergaray, Alfonso Ruben. "Rethinking Uncertainty: Spinoza and Hume on Shaping Uncertain Secular Futures." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/70844.
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This dissertation extends contemporary views about uncertainty. It does so through a reading of the role of uncertainty in the political thought of two modern philosophers, Baruch Spinoza and David Hume. Despite uncertainty's notable and multi-disciplinary appeal in the academic literature, the frame in which most scholars think about social and political uncertainty is one-sided. On the whole, contemporary scholars consider uncertainty as a problem in need of a remedy. In the social sciences uncertainty is transformed into risk in order to empirically calculate risk probabilities. The hope is that risks (uncertainties) can be controlled, reduced, and in all, mitigated. In this dissertation, I argue for a conceptual rethinking of uncertainty that expands its scope and reach to include a socially and politically beneficent understanding, a constructive form of uncertainty. In particular, I explore the ways social groups experience conditions of uncertainty in different contexts through an examination of what I term future-oriented and epistemic uncertainty in Hume and Spinoza's political thought. Spinoza's arguments for liberal democracy, and Hume's arguments favoring commercial society, are highlighted as instances of constructive uncertainty. The dissertation concludes by applying a general understanding of constructive uncertainty to the ideology of the American Dream in order to illustrate suggestively how a constructive conception of uncertainty might prove useful when critically engaging contemporary matters.Ph. D.
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MacAskill, William. "Normative uncertainty." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:8a8b60af-47cd-4abc-9d29-400136c89c0f.
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Very often, we are unsure about what we ought to do. Under what conditions should we help to improve the lives of distant strangers rather than those of our family members? At what point does an embryo or foetus become a person, with all the rights that that entails? Is it ever permissible to raise and kill non-human animals in order to use their meat for food? Sometimes, this uncertainty arises out of empirical uncertainty: we might not know to what extent non-human animals feel pain, or how much we are really able to improve the lives of distant strangers compared to our family members. But this uncertainty can also arise out of fundamental normative uncertainty: out of not knowing, for example, what moral weight the wellbeing of distant strangers has compared to the wellbeing of our family; or whether non-human animals are worthy of moral concern even given knowledge of all the facts about their biology and psychology. In fact, for even moderately reflective agents, decision-making under normative uncertainty is ubiquitous. Given this, one might have expected philosophers to have devoted considerable research time to the question of how one ought to take one’s normative uncertainty into account in one’s decisions. But the issue has been largely neglected. This thesis attempts to begin to fill this gap. It addresses the question: what ought one to do when one is uncertain about what one ought to do? It develops a view that I call metanormativism: the view that there are second-order norms that govern action that are relative to a decision-maker’s uncertainty about first-order normative claims. In consists of two distinct parts. The first part (Chapters 1-4) develops a general metanormative theory. I argue in favour of the view that decision-makers should maximise expected choice-worthiness, treating normative uncertainty analogously with how they treat empirical uncertainty. I defend this view at length in response to two key problems, which I call the problems of merely ordinal theories and the problem of intertheoretic comparisons. The second part (Chapters 5-7) explores the implications of metanormativism for other philosophical issues. I suggest that it has important implications for the theory of rational action in the face of incomparable values, for the causal/evidential debate in decision-theory, and for the value we should ascribe to research into moral philosophy.
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Boopathy, Komahan. "Uncertainty Quantification and Optimization Under Uncertainty Using Surrogate Models." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1398302731.
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Fiorito, Luca. "Nuclear data uncertainty propagation and uncertainty quantification in nuclear codes." Doctoral thesis, Universite Libre de Bruxelles, 2016. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/238375.
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Uncertainties in nuclear model responses must be quantified to define safety limits, minimize costs and define operational conditions in design. Response uncertainties can also be used to provide a feedback on the quality and reliability of parameter evaluations, such as nuclear data. The uncertainties of the predictive model responses sprout from several sources, e.g. nuclear data, model approximations, numerical solvers, influence of random variables. It was proved that the largest quantifiable sources of uncertainty in nuclear models, such as neutronics and burnup calculations, are the nuclear data, which are provided as evaluated best estimates and uncertainties/covariances in data libraries. Nuclear data uncertainties and/or covariances must be propagated to the model responses with dedicated uncertainty propagation tools. However, most of the nuclear codes for neutronics and burnup models do not have these capabilities and produce best-estimate results without uncertainties. In this work, the nuclear data uncertainty propagation was concentrated on the SCK•CEN code burnup ALEPH-2 and the Monte Carlo N-Particle code MCNP.Two sensitivity analysis procedures, i.e. FSAP and ASAP, based on linear perturbation theory were implemented in ALEPH-2. These routines can propagate nuclear data uncertainties in pure decay models. ASAP and ALEPH-2 were tested and validated against the decay heat and uncertainty quantification for several fission pulses and for the MYRRHA subcritical system. The decay uncertainty is necessary to define the reliability of the decay heat removal systems and prevent overheating and mechanical failure of the reactor components. It was proved that the propagation of independent fission yield and decay data uncertainties can be carried out with ASAP also in neutron irradiation models. Because of the ASAP limitations, the Monte Carlo sampling solver NUDUNA was used to propagate cross section covariances. The applicability constraints of ASAP drove our studies towards the development of a tool that could propagate the uncertainty of any nuclear datum. In addition, the uncertainty propagation tool was supposed to operate with multiple nuclear codes and systems, including non-linear models. The Monte Carlo sampling code SANDY was developed. SANDY is independent of the predictive model, as it only interacts with the nuclear data in input. Nuclear data are sampled from multivariate probability density functions and propagated through the model according to the Monte Carlo sampling theory. Not only can SANDY propagate nuclear data uncertainties and covariances to the model responses, but it is also able to identify the impact of each uncertainty contributor by decomposing the response variance. SANDY was extensively tested against integral parameters and was used to quantify the neutron multiplication factor uncertainty of the VENUS-F reactor.Further uncertainty propagation studies were carried out for the burnup models of light water reactor benchmarks. Our studies identified fission yields as the largest source of uncertainty for the nuclide density evolution curves of several fission products. However, the current data libraries provide evaluated fission yields and uncertainties devoid of covariance matrices. The lack of fission yield covariance information does not comply with the conservation equations that apply to a fission model, and generates inconsistency in the nuclear data. In this work, we generated fission yield covariance matrices using a generalised least-square method and a set of physical constraints. The fission yield covariance matrices solve the inconsistency in the nuclear data libraries and reduce the role of the fission yields in the uncertainty quantification of burnup models responses.Doctorat en Sciences de l'ingénieur et technologie
info:eu-repo/semantics/nonPublished
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Simangunsong, Eliot Sation. "Supply chain uncertainty : linking sources of uncertainty and management practices." Thesis, Lancaster University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556682.
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Supply chain uncertainty is a key issue that affects firm competitiveness (1993; Yang et al., 2004); and, therefore, identifying the major sources of uncertainty within supply chains and developing strategies to manage them is an important challenge (Sabri & Beamon, 2000). There is an emerging literature on supply chain uncertainty but additional empirical research is required to further develop understanding of this phenomenon. This leads to an important research question to explore what sources of uncertainty can be identified in practice, what are the dimensions of these sources, and how can they be managed. To address this research question, this thesis has developed a theoretical model of supply chain uncertainty. Using this theoretical model to structure the investigation, an empirical study has been conducted in the food industry in Indonesia with twelve inter-related companies (4 suppliers, 4 iv manufacturers, and 4 retailers). Twenty three semi-structured interviews with thirty two senior representatives from the twelve companies have been conducted; interviews were audio and video recorded, and analysed using Atlas.ti. A comprehensive approach, which goes beyond previous studies, has been undertaken. Fourteen sources of uncertainty, including those internal to the firm (e.g., manufacturing process), internal to the supply chain (e.g., supplier) and external (e.g., environment) have been explored and twenty two management strategies for reducing or coping with the relevant dimensions have been identified Other research contributions are also identified such as the dynamic and multi dimensional process of managing sources of uncertainty. The findings of the thesis have implications for managers. For example, reducing uncertainty strategies such as collaboration are generally preferred over coping with uncertainty strategies but are difficult to implement when sources of uncertainty span beyond the boundaries of the firm. Future research should explore issues emerging from this study, such as ethical issues affecting supply chain uncertainty. Keywords: Supply chain uncertainty; uncertainty management; case study research.
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Cheng, Haiyan. "Uncertainty Quantification and Uncertainty Reduction Techniques for Large-scale Simulations." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/28444.
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Modeling and simulations of large-scale systems are used extensively to not only better understand a natural phenomenon, but also to predict future events. Accurate model results are critical for design optimization and policy making. They can be used effectively to reduce the impact of a natural disaster or even prevent it from happening. In reality, model predictions are often affected by uncertainties in input data and model parameters, and by incomplete knowledge of the underlying physics. A deterministic simulation assumes one set of input conditions, and generates one result without considering uncertainties. It is of great interest to include uncertainty information in the simulation. By ``Uncertainty Quantification,'' we denote the ensemble of techniques used to model probabilistically the uncertainty in model inputs, to propagate it through the system, and to represent the resulting uncertainty in the model result. This added information provides a confidence level about the model forecast. For example, in environmental modeling, the model forecast, together with the quantified uncertainty information, can assist the policy makers in interpreting the simulation results and in making decisions accordingly. Another important goal in modeling and simulation is to improve the model accuracy and to increase the model prediction power. By merging real observation data into the dynamic system through the data assimilation (DA) technique, the overall uncertainty in the model is reduced. With the expansion of human knowledge and the development of modeling tools, simulation size and complexity are growing rapidly. This poses great challenges to uncertainty analysis techniques. Many conventional uncertainty quantification algorithms, such as the straightforward Monte Carlo method, become impractical for large-scale simulations. New algorithms need to be developed in order to quantify and reduce uncertainties in large-scale simulations.
This research explores novel uncertainty quantification and reduction techniques that are suitable for large-scale simulations. In the uncertainty quantification part, the non-sampling polynomial chaos (PC) method is investigated. An efficient implementation is proposed to reduce the high computational cost for the linear algebra involved in the PC Galerkin approach applied to stiff systems. A collocation least-squares method is proposed to compute the PC coefficients more efficiently. A novel uncertainty apportionment strategy is proposed to attribute the uncertainty in model results to different uncertainty sources. The apportionment results provide guidance for uncertainty reduction efforts. The uncertainty quantification and source apportionment techniques are implemented in the 3-D Sulfur Transport Eulerian Model (STEM-III) predicting pollute concentrations in the northeast region of the United States. Numerical results confirm the efficacy of the proposed techniques for large-scale systems and the potential impact for environmental protection policy making.
``Uncertainty Reduction'' describes the range of systematic techniques used to fuse information from multiple sources in order to increase the confidence one has in model results. Two DA techniques are widely used in current practice: the ensemble Kalman filter (EnKF) and the four-dimensional variational (4D-Var) approach. Each method has its advantages and disadvantages. By exploring the error reduction directions generated in the 4D-Var optimization process, we propose a hybrid approach to construct the error covariance matrix and to improve the static background error covariance matrix used in current 4D-Var practice. The updated covariance matrix between assimilation windows effectively reduces the root mean square error (RMSE) in the solution. The success of the hybrid covariance updates motivates the hybridization of EnKF and 4D-Var to further reduce uncertainties in the simulation results. Numerical tests show that the hybrid method improves the model accuracy and increases the model prediction quality.Ph. D.
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Clausen, Mork Jonas. "Dealing with uncertainty." Doctoral thesis, KTH, Filosofi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-72680.
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Uncertainty is, it seems, more or less constantly present in our lives. Even so, grasping the concept philosophically is far from trivial. In this doctoral thesis, uncertainty and its conceptual companion information are studied. Axiomatic analyses are provided and numerical measures suggested. In addition to these basic conceptual analyses, the widespread practice of so-called safety factor use in societal regulation is analyzed along with the interplay between science and policy in European regulation of chemicals and construction.QC 20120202
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Smith, James M. M. Arch Massachusetts Institute of Technology. "Architecture of uncertainty." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/34429.
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Thesis (M. Arch.)--Massachusetts Institute of Technology, Dept. of Architecture, 2006.Includes bibliographical references (p. [118]-[121]).
Machines have been used throughout history as an extension of the human body; a prosthetic device that can provide the opportunity to redefine the spatial experience of a given time and place. In this investigation the Pinhole camera was used as a device for capturing photographic images of an urban place. The images produced by the pinhole cameras are representations of the existing place and its experience. The representation of a place generated by the device mediates the relationship between the body and the landscape. This thesis explores the production of architectural form with respect to the uncertainties of our built environment, strategies of representation, and the construction of urban devices that re-define the spatial experience.
by James M. Smith.
M.Arch.
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West, Mark Carleton University Dissertation Architecture. "Architecture doubt uncertainty." Ottawa, 1996.
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Akten, Burcu Elif. "Generalized uncertainty relations /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.
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SANTAGIUSTINA, CARLO ROMANO, Massimo Warglien, and Michele Bernasconi. "Talking About Uncertainty." Doctoral thesis, Università Ca' Foscari di Venezia, 2018. http://hdl.handle.net/10278/3709814.
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In the first article we review existing theories of uncertainty. We devote particular attention to the relation between metacognition, uncertainty and probabilistic expectations. We also analyse the role of natural language and communication for the emergence and resolution of states of uncertainty. We hypothesize that agents feel uncertainty in relation to their levels of expected surprise, which depends on probabilistic expectations-gaps elicited during communication processes. Under this framework above tolerance levels of expected surprise can be considered informative signals. These signals can be used to coordinate, at the group and social level, processes of revision of probabilistic expectations. When above tolerance levels of uncertainty are explicated by agents through natural language, in communication networks and public information arenas, uncertainty acquires a systemic role of coordinating device for the revision of probabilistic expectations. The second article of this research seeks to empirically demonstrate that we can crowd source and aggregate decentralized signals of uncertainty, i.e. expected surprise, coming from market agents and civil society by using the web and more specifically Twitter as an information source that contains the wisdom of the crowds concerning the degree of uncertainty of targeted communities/groups of agents at a given moment in time. We extract and aggregate these signals to construct a set of civil society uncertainty proxies by country. We model the dependence among our civil society uncertainty indexes and existing policy and market uncertainty proxies, highlighting contagion channels and differences in their reactiveness to real-world events that occurred in the year 2016, like the EU-referendum vote and the US presidential elections. In the third article, we propose a new instrument, called Worldwide Uncertainty Network, to analyse the uncertainty contagion dynamics across time and areas of the world. Such an instrument can be used to identify the systemic importance of countries in terms of their civil society uncertainty social percolation role. Our results show that civil society uncertainty signals coming from the web may be fruitfully used to improve our understanding of uncertainty contagion and amplification mechanisms among countries and between markets, civil society and political systems.
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Santagiustina, Carlo Romano Marcello Alessandro <1988>. "Talking about uncertainty." Doctoral thesis, Università Ca' Foscari Venezia, 2018. http://hdl.handle.net/10579/13445.
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This empirical research seeks to demonstrate that we can decentralize, crowd source and aggregate signals of uncertainty coming from market agents and organizations, by using the Internet -and more specifically Twitter- as an information archive from which we extract the wisdom of the crowds concerning the state of uncertainty of a specific target system, like a country or a particular uncertainty source, in a given moment in time. We extract and aggregate these signals, constructing a set of specialized uncertainty indexes, by topic and/or by geographic-area. We model the dependence among these uncertainty indexes and other pre-existing uncertainty proxies and highlight differences in their reactiveness to real-world events that occurred in the year 2016, like the EU-referendum vote and the US presidential elections. Finally, we analyze and model the dynamics across time and space of uncertainty signals by geographic-area, to discriminate between, area specific feedback mechanisms, contagion among geographic-areas and international (multi-area) uncertainty shocks. Our results show that crowd-sourced uncertainty signals coming from Twitter may be fruitfully used to improve our understanding of uncertainty contagion and amplification mechanisms across geographic-areas and among market and non-market systems;
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Urganci, Ilksen. "Positional Uncertainty Analysis Using Data Uncertainy Engine A Case Study On Agricultural Land Parcels." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611409/index.pdf.
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Most of spatial data extraction and updating procedures require digitization of geographical entities from satellite imagery. During digitization, errors are introduced by factors like instrument deficiencies or user errors. In this study positional uncertainty of geographical objects, digitized from high resolution Quickbird satellite imagery, is assessed using Data Uncertainty Engine (DUE). It is a software tool for assessing uncertainties in environmental dataand generating realisations of uncertain data for use in uncertainty propagation analyses. A case study area in Kocaeli, Turkey that mostly includes agricultural land parcels is selected in order to evaluate positional uncertainty and obtain uncertainty boundaries for manually digitized fields. Geostatistical evaluation of discrepancy between reference data and digitized polygons are undertaken to analyse auto and cross correlation structures of errors. This process is utilized in order to estimate error model parameters which are employed in defining an uncertainty model within DUE. Error model parameters obtained from training data, are used to generate simulations for test data. Realisations of data derived via Monte Carlo Simulation using DUE, are evaluated to generate uncertainty boundaries for each object guiding user for further analyses with pre-defined information related to the accuracy of spatial entities. It is also aimed to assess area uncertainties affected by the position of spatial entities. For all different correlation structures and object models, weighted average positional error for this study is between 2.66 to 2.91 meters. At the end of uncertainty analysis, deformable object model produced the smallest uncertainty bandwidth by modelling cross correlation.
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Duan, Kaifeng. "Uncertainty Principle : a study of the uncertain relationship between people and object." Thesis, Konstfack, Industridesign, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-3791.
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When we observe or use something, its property seems to change because of the way we establish relationships with it. Inspired by the Uncertainty Principle – a physical theory published by Heisenberg in the year of 1927 – I take both people and objects as something always in an uncertain status. We cannot fully define objects, but only try to understand and live with it in a complex and constantly changing context.Three pieces of furniture are created to visualize the idea about how the relationships between people and objects could be from this viewpoint, exploring how far away people could accept the imperfect but surprising experience of the world.
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Schenk, Todd Edward William. "Institutionalizing uncertainty : exploring how infrastructure stakeholders can prepare for uncertain climate futures." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101372.
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Thesis: Ph. D. in Public Policy and Planning, Massachusetts Institute of Technology, Department of Urban Studies and Planning, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 355-384).
Climate change poses a range of threats to our infrastructure systems. Efforts to respond are complicated by the uncertainty and complexity involved. The uncertainties are pervasive, going beyond scientific and technical issues to include significant governance challenges. This dissertation examines how stakeholders are likely to make project-level decisions in practice, and how we can support better processes. It considers the implications of using multiple scenarios as a way to frame uncertainty, and of bringing multiple stakeholders together for decision-making. It is also concerned with the differences across governance regimes, focusing on Boston, Singapore and Rotterdam. The research process featured a role-play simulation (RPS) exercise run with participants as a way to introduce issues and facilitate experimentation. Participants overwhelmingly favored flexible approaches as a way to proceed despite uncertainties, making the best possible decisions today while leaving options open as conditions change and learning occurs. Unfortunately, this research suggests that there are substantial barriers to institutionalizing flexibility. Participants were also extremely positive on the use of scenarios as a way to frame uncertainty. However, the exercise runs underscored the challenges associated with their use; scenarios encourage users to consider the implications of an uncertain future, but can concurrently deny them the single standards they are familiar with using. Another key finding is that adaptation planning efforts are deliberative processes in which facilitation, the behavior of participants, and process design matter; the choices participants made had significant implications on exercise outcomes. Finally, participants behaved differently across the three cities, underscoring the importance of wider governance norms. This dissertation concludes with three recommendations: First, the development of boundary organizations that can foster the dynamic institutions necessary to advance flexible adaptation. Second, given the importance of salient, credible and legitimate scientific and technical information, I recommend the use of joint fact finding (JFF) techniques. Because of the dynamic nature of climate adaptation, I suggest that JFF be explicitly iterative in nature. Scenarios can help JFF groups to consider the uncertainties involved. Third, I recommend that researchers consider using exercises as tools for action research, particularly when considering nascent and complex issues like climate adaptation.
by Todd Edward William Schenk.
Ph. D. in Public Policy and Planning
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Lee, S. "Three essays on uncertainty : real and financial effects of uncertainty shocks." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/1570354/.
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The thesis consists of three essays on real and financial effects of uncertainty shocks. The first chapter investigates two different news-based uncertainty indices, Economic Policy Uncertainty Index (EPU) and Relative Sentiment Shift Index (RSS). I employ reduced form VAR and local projections (Jordá, 2005) to explore the differences in wait-and-see effect of uncertainty on the real economy. Surprises in either index lead to significant declines in production and employment and the effect is larger and persistent in the case of RSS shocks than EPU. In the second chapter, the probabilistic approach is applied to uncover the dependence structure in inflation uncertainty for the countries bordering a major currency area, the UK and the euro area. Inflation uncer¬tainty is measured by the conditional volatility removing entire forecastable variations by bivariate VAR GARCH model and joint distribution of uncertainties of two regions is estimated by using copula to account for non-linear association. The results show that the left tail events of inflation are positively correlated between the two regions. This implies that the appropriate monetary policy can be drawn if policymakers con¬sider the interconnectedness of the deflationary pressures. Finally, the third chapter examines the long run relationship between gross capital flow and its determinants, focusing on the impact of uncertainty as global and contagion factors. I apply bounds testing approach by Pesaran, Shin, and Smith (2001) allowing for the underlying re¬gressors being either I(0), I(1) or mutually cointegrated. Both gross capital inflows and outflows exhibit significant level relationship with global, contagion and domestic factors and uncertainty spillovers through financial linkages between the UK and the euro area play crucial role in predicting capital flows of the UK.
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Zimmermann, Jörg [Verfasser]. "Algebraic Uncertainty Theory : A Unifying Perspective on Reasoning under Uncertainty / Jörg Zimmermann." Bonn : Universitäts- und Landesbibliothek Bonn, 2013. http://d-nb.info/1044970340/34.
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Budzinski, Maik. "The differentiation between variability uncertainty and knowledge uncertainty in life cycle assessment." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-135913.
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The following thesis deals with methods to increase the reliability of the results in life cycle assessment. The paper is divided into two parts. The first part points out the typologies and sources of uncertainty in LCA and summarises the existing methods dealing with it. The methods are critically discussed and pros and cons are contrasted. Within the second part a case study is carried out. This study calculates the carbon footprint of a cosmetic product of Li-iL GmbH. Thereby the whole life cycle of the powder bath Blaue Traube is analysed. To increase the reliability of the result a procedure, derived from the first part, is applied. Recommendations to enhance the product´s sustainability are then given to the decision-makers of the company. Finally the applied procedure for dealing with uncertainty in LCAs is evaluated.
The aims of the thesis are to make a contribution to the understanding of uncertainty in life cycle assessment and to deal with it in a more consistent manner. As well, the carbon footprint of the powder bath shall be based on appropriate assumptions and shall consider occurring uncertainties.
Basing on discussed problems, a method is introduced to avoid the problematic merging of variability uncertainty and data uncertainty to generate probability distributions. The introduced uncertainty importance analysis allows a consistent differentiation of these types of uncertainty. Furthermore an assessment of the used data of LCA studies is possible.
The method is applied at a PCF study of the bath powder Blaue Traube of Li-iL GmbH. Thereby the analysis is carried out over the whole life cycle (cradle-to-grave) as well as cradle-to-gate. The study gives a practical example to the company determining the carbon footprint of products. In addition, it meets the requirements of ISO guidelines of publishing the study and comparing it with other products.
Within the PCF study the introduced method allows a differentiation of variability uncertainty and knowledge uncertainty. The included uncertainty importance analysis supports the assessment of each aggregated unit process within the analysed product system. Finally this analysis can provide a basis to collect additional, more reliable or uncertain data for critical processes.
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Chellaboina, Vijaya-Sekhar. "Robust stability and performance for linear and nonlinear uncertain systems with structured uncertainty." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/12903.
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Ferenc, Veszteg Róbert. "Auctions, Mechanisms and Uncertainty." Doctoral thesis, Universitat Autònoma de Barcelona, 2004. http://hdl.handle.net/10803/4057.
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Los mecanismos que permiten la interacción de los individuos tienen un gran impacto sobre los resultados de esta interacción. La teoría económica de diseño de mecanismos estudia el diseño de procedimientos de decisión social en situaciones en la cuales los agentes económicos guardan información privada y se comportan, la utilizan, de forma estratégica.Como ejemplo, considérese el caso en el cual la autoridad central de un país está considerando la posibilidad de declarar como "reserva nacional" una determinada área geográfica. Para poder tomar la decisión óptima, por ejemplo la que maximiza el bienestar social, ésta se tiene que basar en la información individual de las ciudades, estados, o agentes, cuya opinión sobre el problema que se considera se puede preguntar directamente, pero la verdad no se expresará sin los incentivos adecuados. Estos pueden aparecen como transferencias monetarias u otros instrumentos controlados por la autoridad. Con otras palabras, la teoría de diseño de mecanismos estudia la harmonización de los incentivos que se tienen que aplicar cuando un conjunto de agentes interactúa para que estos muestren un comportamiento deseado, es decir para que el resultado sea el intencionado.
La primera formalización de este problema se encuentra en el trabajo de Hurwitz (1972). No obstante, una de las primeras aplicaciones que se puede considerar como parte de la literatura de diseño de mecanismos lleva el nombre de Hayek, quien empezó a estudiar las limitaciones, en cuanto a la cantidad de información, de los planificadores centrales en los años 20. Él consideró un problema de gran escala al centrar su atención en el mecanismo del mercado libre. Se opuso firmemente al sistema socialista y describió su fallo principal como un problema de información.
Una aplicación similar es el diseño de una constitución que determina las acciones que los agentes pueden realizar (espacio de estrategias) y las reglas de votación que transforman votos en decisiones (funciones de pago). Al lado de la literatura sobre cómo reducir los fallos del mercado, sobre impuestos óptimos y teoría de bienes públicos, el diseño de subastas también aparece entre los sujetos del diseño de mecanismos.
Esta tesis está dividida en tres capítulos que presentan estudios completos y separados de situaciones económicas en las cuales la información, la incertidumbre, juega un papel importante. Los resultados se han obtenido con la ayuda de la teoría de juegos y el enfoque estándar de la literatura del diseño de mecanismos. El primer capítulo propone el uso del mecanismo "multipujas" ("multibidding game"; veáse Pérez-Castrillo y Wettstein (2002)) en situaciones con información imperfecta y desarrolla sus propiedades teóricas. El segundo capítulo es un trabajo empírico, utiliza datos experimentales y contrasta las predicciones teóricas del primero. La tesis se finaliza con el estudio de los conceptos de justicia en un marco donde los agentes toman sus decisiones bajo incertidumbre.
Mechanisms through which individuals interact may have important impact on the outcomes of this interaction. The economic theory of mechanism design is concerned with the design of social decision procedures for situations in which economic agents own relevant private information and behave, i.e. use it, strategically.
As an example, consider the case in which the central authority of a country is studying the possibility of declaring national reserve a given geographic area. In order to come up with the optimal decision, that for instance maximizes social welfare, it should be conditioned on the related information owned by cities, states, or individuals. They might be asked directly for their opinion on the underlying problem, but will not report their information truthfully unless proper incentives are given to them through monetary transfers or some other instruments controlled by the authority. In other words, mechanism design theory is concerned with the harmonization of incentives that must be applied to a set of agents that interact in order to get those agents to exhibit some desired behavior, i.e. in order the schemes to work as intended. The central authority, or social planner, of this example who acts on behalf of the whole society can also be replaced by an imaginary social goal or by a principal who is pursuing his own interest.
The formalization of this problem can be find in the seminal work by Hurwicz (1972). Nevertheless, one of the first applications that can be considered as from the theory of mechanism design is due to Hayek who started to study the limitations on the amount of information that central planners can acquire in the early 1920s. He considered a large scale problem focusing his attention on the free market mechanism. He fiercely opposed to the socialist system from every angle and described the main problem as a problem of information.
A similar application is the design of a constitution that determines the actions that agents may take (strategy space) and the electoral rules that transform votes into decisions (outcome function). Along with the literature on the ways of reducing market failures, on optimal taxation and public good theory, the design of auctions is also subject of the field of mechanism design.
This thesis dissertation is divided into three chapters that present self-contained studies of economic situations in which private information, i.e. uncertainty, plays an important role. In deriving the results game theoretic tools and the approach taken by the mechanism design literature are used. The first chapter proposes the use of the multibidding mechanism (check Pérez-Castrillo y Wettstein (2002)) in situations with imperfect information and explores its theoretical properties. The second chapter is an empirical work, it uses experimental data and tests the theoretical predictions of the first. The thesis ends with the study of fairness concepts in an environment in which agents take their decisions under uncertainty.
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Soupre, Matthieu. "Essays on economic uncertainty." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664416.
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These essays propose different measures of economic uncertainty and evaluate its impact at the microeconomic and macroeconomic level. The first essay in Chapter 2 proposes a measure of macroeconomic uncertainty that allows to distinguish its vari-ous components. Metrics of Knightian uncertainty and risk are proposed, and their respective impact on a number of economic aggregates is evaluated. Chapter 3 extends the classical approach to measuring uncertainty – a mean squared error-based quantity –to entropy methods in econometrics. Several information-theoretic measures of uncertainty are motivated, derived, and estimated on two data sets: the Survey of Professional Forecasters used in Chapter 2, to show that the conclusions hold with this different approach; and the Survey of Economic Expectations, to show how information theoretic measures of uncertainty can help study different situations not afforded by the mean-squared error approach. Chapter 4 studies uncertainty from the point of view of forecasting and propose a measure of forecasting uncertainty to study how business cycles can affect this particular dimension of Knightian uncertainty. Chapter 5 considers the question of the efficacy of fiscal policy in periods of uncertainty, and does so in a way that accounts for the comovements of economic uncertainty with recessions through an conditional adjustment to the classical smooth-transition state dependent models. Chapter 6 concludes.Aquesta tesi proposa diferents mesures d’incertesa econòmica i avalua el seu impacte a nivell microeconòmic i macroeconòmic. El primer assaig, al Capítol 2, proposa una mesura de la incertesa macroeconòmica que permet distingir entre les seves múltiples components. Es proposen mètriques d’incertesa i risc de Knight, i se n’avaluen els seus respectius impactes sobre diverses magnituds econòmiques. En el Capítol 3 s’amplia l’enfocament clàssic per la mesura de la incertesa – l’error quadràtic mig – als mètodes d’entropia en econometria. Les diverses mesures d’incertesa que fan servir la teoría la informació estan motivades, derivades i estimades en dos conjunts de dades: el Survey of Professional Forecasters, que s’utilitza al Capítol 2 per demostrar que les conclusions es mantenen amb aquest nou enfocament; i el Survey of Economic Expectations, que es fa servir per mostrar com aquestes mesures d’informació poden ajudar a estudiar situacions diferents que els mètodes classics amb error quadràtic mig. El Capítol 4 estudia la incertesa des del punt de vista de la predicció i proposa una mesura d’incertesa de previsió per estudiar com els cicles econòmics poden afectar aquesta dimensió particular de la incertesa knightiana. El Capítol 5 examina la qüestió de l’eficàcia de la política fiscal en períodes d’incertesa, i ho fa de manera que ajusta per als moviments de la incertesa econòmica amb les recessions. També es proposa una nova classe de models depenents de l’estat que inclou condicionalitat. El Capítol 6 conté les conclusions.
Esta tesis propone diferentes medidas de incertidumbre económica y evalúa su impacto a nivel microeconómico y macroeconómico. El primer ensayo en el Capítulo 2 propone una medida de la incertidumbre macroeconómica que permite distinguir entre sus diversos componentes. Se proponen métricas de incertidumbre y riesgo de Knight, y se evalúan sus respectivos impactos sobre diversas cantidades económicas. El Capítulo 3 amplía el enfoque clásico para medir la incertidumbre - del error cuadrático medio -, a los métodos de entropía en econometría. Varias medidas de incertidumbre que utilizan la teoría de la información están motivadas, derivadas y estimadas en dos conjuntos de datos: el Survey of Professional Forecasters que se utiliza en el Capítulo 2 para demostrar que las conclusiones se mantienen con este nuevo enfoque y el Survey of Economic Expectations, para mostrar cómo estas medidas de información pueden ayudar a estudiar situaciones diferentes de las que los métodos clásicos con error cuadrático medio permiten. El Capítulo 4 estudia la incertidumbre desde el punto de vista de la predicción y propone una medida de incertidumbre de previsión para estudiar cómo los ciclos económicos pueden afectar a esta dimensión particular de la incertidumbre knightiana. El Capítulo 5 examina la cuestión de la eficacia de la política fiscal en períodos de incertidumbre, y lo hace de una manera que tiene en cuenta los movimientos de la incertidumbre económica con las recesiones. Además, se propone una nueva clase de modelos dependientes del estado que incluye condicionalidad. El Capítulo 6 concluye la tesis.
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Zhu, Yuntao. "Semidefinite programming under uncertainty." Online access for everyone, 2006. http://www.dissertations.wsu.edu/Dissertations/summer2006/y%5Fzhu%5F073106.pdf.
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Nartey, Mohammed Donkor, and Anyinka Nkongtenden Ndobegang. "SUPPLIER SELECTION UNDER UNCERTAINTY." Thesis, Jönköping University, Jönköping International Business School, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-1189.
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The role of purchasing in supply chain management has received and continues to receive increasing attention as the years go by. Purchasing enhances efficiency and competitiveness among other benefits but to realize these benefits it is imperative to select and maintain competent suppliers. However, many factors affect a firm’s ability to choose the right supplier. Uncertainty is an issue that has received great attention. It affects all functions of a company consequently affecting purchasing and supplier selection. This thesis seeks to provide an understanding of the supplier selection process and criteria under circumstances of uncertainty in the case where the potential supplier under evaluation is a newly created company. The authors try to find out if uncertainty varies with firm’s age and tested the suitability of existing criteria on the selection of newly created firms. They also sought ways by which uncertainty can be reduced.One of the realisations of this thesis is that there is a relationship between the characteristics or problems faced by new firms and uncertainty. Uncertainties created by new firms include lack of trust and commitment, inadequate finance, poor quality, unreliable delivery times, inadequate logistic technological capabilities. No new types or sources of uncertainty were discovered however, it was found that uncertainty was certainly higher when working with new firms. The criteria delivery, quality, cost/price, financial position and communication and technology were recognized as the commonly used criteria a fact confirmed from empirical results as well as in previous literature. However other criteria such as ISO certification, reliability, credibility, good references and product development were also identified. These criteria had existed before but did not receive the same attention in previous studies. This show that focus is shifting from solely relying on quantitative factors to include qualitative criteria. The study identified that some methods of minimising uncertainty could include detailed financial analyses, site visit, intensive verification, close relationships, ISO certification, good references and recommendations. It is worth noting that uncertainty cannot be entirely eliminated in all situations
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Dreborg, Karl Henrik. "Scenarios and structural uncertainty." Doctoral thesis, KTH, Infrastructure, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3697.
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Söderström, Ulf. "Monetary policy under uncertainty." Doctoral thesis, Handelshögskolan i Stockholm, Samhällsekonomi (S), 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-646.
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This thesis contains four chapters, each of which examines different aspects of the uncertainty facing monetary policymakers.''Monetary policy and market interest rates'' investigates how interest rates set on financial markets respond to policy actions taken by the monetary authorities. The reaction of market rates is shown to depend crucially on market participants' interpretation of the factors underlying the policy move. These theoretical predictions find support in an empirical analysis of the U.S. financial markets.''Predicting monetary policy using federal funds futures prices'' examines how prices of federal funds futures contracts can be used to predict policy moves by the Federal Reserve. Although the futures prices exhibit systematic variation across trading days and calendar months, they are shown to be fairly successful in predicting the federal funds rate target that will prevailafter the next meeting of the Federal Open Market Committee from 1994 to 1998.''Monetary policy with uncertain parameters'' examines the effects of parameter uncertainty on the optimal monetary policy strategy. Under certain parameter configurations, increasing uncertainty is shown to lead to more aggressive policy, in contrast to the accepted wisdom.''Should central banks be more aggressive?'' examines why a certain class of monetary policy models leads to more aggressive policy prescriptions than what is observed in reality. These counterfactual results are shown to be due to model restrictions rather than central banks being too cautious in their policy behavior. An unrestricted model, taking the dynamics of the economy and multiplicative parameter uncertainty into account, leads to optimal policy prescriptions which are very close to observed Federal Reserve behavior.Diss. Stockholm : Handelshögskolan, 1999
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Frost, Robert E. III. "Uncertainty and Information Processing." TopSCHOLAR®, 2011. http://digitalcommons.wku.edu/theses/1120.
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The purpose of these two studies was to examine two factors that may influence the effects of uncertainty on information processing. The first factor is the positioning of uncertainty relative to a target of judgment, and how this affects people’s judgment processing. The second factor had to do with the degree to which uncertainty signals active goal conflict or not. In the first study, 145 participants with a mean age of 19.51 were induced with uncertainty either before or after information about the target accused of illegal behavior. The results demonstrated that uncertainty before information produced higher guilt judgments of the target and uncertainty after information produced lower guilt judgments towards the target, but only in a subset of conditions. The second study, with 121 participants and a mean age was 19.58, primed participants with one of two different goals. It then induced uncertainty threat which either was or was not relevant to the primed goal, and asked participants to make judgments based on information given about the target as in Study 1. The results revealed that for women, but not for men, uncertainty threat produced stronger guilt judgments when the uncertainty was relevant to the primed goal. Together, these results indicate that both the positioning and goal relevance of uncertainty may impact its effect on information processing.
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Mathieu, Michael. "Unsupervised Learning under Uncertainty." Thesis, New York University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10261120.
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Deep learning, in particular neural networks, achieved remarkable success in the recent years. However, most of it is based on supervised learning, and relies on ever larger datasets, and immense computing power. One step towards general artificial intelligence is to build a model of the world, with enough knowledge to acquire a kind of ``common sense''. Representations learned by such a model could be reused in a number of other tasks. It would reduce the requirement for labelled samples and possibly acquire a deeper understanding of the problem. The vast quantities of knowledge required to build common sense precludes the use of supervised learning, and suggests to rely on unsupervised learning instead.
The concept of uncertainty is central to unsupervised learning. The task is usually to learn a complex, multimodal distribution. Density estimation and generative models aim at representing the whole distribution of the data, while predictive learning consists of predicting the state of the world given the context and, more often than not, the prediction is not unique. That may be because the model lacks the capacity or the computing power to make a certain prediction, or because the future depends on parameters that are not part of the observation. Finally, the world can be chaotic of truly stochastic. Representing complex, multimodal continuous distributions with deep neural networks is still an open problem.
In this thesis, we first assess the difficulties of representing probabilities in high dimensional spaces, and review the related work in this domain. We then introduce two methods to address the problem of video prediction, first using a novel form of linearizing auto-encoders and latent variables, and secondly using Generative Adversarial Networks (GANs). We show how GANs can be seen as trainable loss functions to represent uncertainty, then how they can be used to disentangle factors of variation. Finally, we explore a new non-probabilistic framework for GANs.
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Söderström, Ulf. "Monetary policy under uncertainty /." Stockholm : Economic Research Institute, Stockholm School of Economics (Ekonomiska forskningsinstitutet vid Handelshögsk.) (EFI), 1999. http://www.hhs.se/efi/summary/506.htm.
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Hudson, David. "Inflation, uncertainty and investment /." Title page, contents and introduction only, 1993. http://web4.library.adelaide.edu.au/theses/09EC/09ech885.pdf.
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Runde, Jochen. "Essays on Keynesian uncertainty." Thesis, University of Cambridge, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239619.
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McCormick, Gregory. "Pump scheduling under uncertainty." Thesis, Brunel University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268976.
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White, Lucy. "Strategic behaviour under uncertainty." Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322808.
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Yavuz, Devrim. "Uncertainty and financial fragility." Thesis, University of Exeter, 2010. http://hdl.handle.net/10036/3036.
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My thesis analyzes various types of uncertainties and their effects on financial fragility in the context of information asymmetries and bank-run models. When various generations of currency crisis are considered, it is observed that the financial system and fragilities associated with it plays a critical role in more recent crisis episodes. Therefore, focusing on the financial system can possibly lead to a better understanding of how and why these crises took place. The analysis presented here aims to provide some new insights about this topic. In the first chapter I tried to analyze how public borrowing can affect financial fragility when how a private bank finances its lending to the government is private information. I built a simple theoretical model where the government basically borrows from a commercial bank. The objective of the government is to realize borrowing at the lowest possible cost but at the same time it cares about the financial stability. The risk averse commercial bank, on the other hand, maximizes utility by allocating the financing of its lending among a safe and a risky loan where the amount it uses from the safe source considered to be a measure of financial stability. Moral hazard arises as the amount of safe loan used is not observable to the government. Under the assumption that the risk premium is decreasing in income, I show, when the government is not able push the rate down below a certain level, it can trade a rise in borrowing costs with some financial stability. In other words, although pushing the rate down is good both for borrowing costs and financial stability, under asymmetric information, it may be optimal to design a contract with a reward scheme and accept a higher cost for borrowing for a relatively more reliable financial system. This chapter contributes to the literature by identifying a potential moral hazard problem in the process of public borrowing and displays how it can lead to a higher than optimal level of financial fragility when the economic policy gets obsessed with lowering the borrowing costs. The analysis provided is also interesting as it displays an unusual case where the borrower rather than the lender faces issues resulting from asymmetric information. In the second chapter, a bank-run model used to analyze effects of uncertainty on financial fragility in terms of maturity mismatch. I use an extended version of the well-known Diamond & Dybvig model by introducing short term borrowing where the future cost of borrowing is unknown. This creates an additional source of maturity mismatch and the demand deposit contracts are now vulnerable to both depositor and lender panics. The key is when the borrowing and investment decisions are made the total cost of borrowing is unknown but the deposit contract can be written contingent on this cost. This creates different consumption paths for patient and impatient agents and they bear different degrees of interest rate risk. The characterization of the contract shows interest risk is mainly borne by early consumers particularly for higher roll over costs. In times of crisis the most liquid funds are the ones that are used first and hence consumers who need urgent liquidity suffers most. The main contribution of this part is that, it combines a bank run model with aggregate uncertainty with short-term borrowing. It also sheds some light on the dynamics of financial problems in developing countries. The last chapter analyzes risk sharing under private banking. Once again a version of Diamond & Dybvig framework is used. Instead of assuming a banking structure where consumers form a union to achieve optimal risk sharing, I consider a private bank that maximizes profits. I analyze the deposit contract under different assumptions about how the bank and the depositors consider the probability of a bank run. The original Diamond & Dybvig model, implicitly assumes the probability of a bank-run is sufficiently small to ensure participation. With a private bank, I allow partial participation and optimizing depositors automatically establish individual rationality. This leads to a supply of deposits (or demand for risk sharing function) which varies along with the payments offered in the contract. Therefore, the bank faces a trade-off between the rates it offer and the amount of deposits it can attract. This basically leads a new set of equilibrium contracts to come out which are not possible under standard risk sharing. Depending on the risk averseness of the consumers these alternative contracts produce different levels of financial fragility. This last chapter contributes to the literature by considering the possible risk sharing contracts under a profit maximizing monopolistic commercial bank. It also briefly discusses how this may effect financial fragility.
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Philpott, Mark Stuart. "Convoy routing under uncertainty." Thesis, University of East Anglia, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.405399.
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Jaaskela, Jarkko Petteri. "Monetary policy under uncertainty." Thesis, Birkbeck (University of London), 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.401857.
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Brus, T. "Multimodality, uncertainty and aggregation." Thesis, University of Warwick, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.372199.
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Greco, Veronica. "Uncertainty, stress, and health." Thesis, University of York, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341481.
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Dixon, Elsbeth Clare. "Representing uncertainty in models." Thesis, University of Cambridge, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.279578.
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Darnell, Catherine Arianne. "Children's understanding of uncertainty." Thesis, University of Birmingham, 2016. http://etheses.bham.ac.uk//id/eprint/6562/.
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In seven experiments this thesis explored the processing responsible for children’s understanding of uncertainty. Through distinguishing between types of evidence and types of uncertainty a new framework was created in which to investigate the relationships between children’s varying metacognitive abilities. Experiments 1 to 3 focussed on 5-to-7-year-olds’ behavioural awareness of uncertainty, exploring the basis of children’s confidence judgements and their influence on strategic behaviour. Children demonstrated a dissociation between these two behaviours suggesting younger children’s metacognitive abilities are based on a two-system process. Experiments 4 to 6 investigated children’s behavioural sensitivity to uncertainty, exploring the relationship between children’s ease of imagining and their decision making. An interesting difference in response latencies was demonstrated across types of uncertainty, suggesting children’s strategic behaviours are based on the ease with which an answer comes to mind. In Experiment 7, 4-to-8-year-olds’ alternative sensitivity was explored, examining children’s appreciation of possibilities through a novel eye-tracking paradigm. Children demonstrated an acknowledgment of the multiple possibilities associated with partial ignorance suggesting a possible meta-representational basis to children’s metacognitive abilities. Taken together these findings offer new insights into the development of children’s metacognition and the processing systems behind their uncertainty understanding.
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Yang, Juan. "Education choices under uncertainty." Thesis, University of York, 2007. http://etheses.whiterose.ac.uk/11014/.
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Cubukgil, Evren. "Uncertainty and firm investment." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:c3fb67f9-adf2-41ac-98b9-cb2878e2b2d6.
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This thesis explores effects of uncertainty on firm investment that are described in estimates of firm level investment specifications which include proxies for uncertainty over expected future firm profitability. A panel data set of UK firms covering the period 1987-2000 is used to estimate firm level investment specifications. Within year volatility in stock returns - a common proxy for firm specific uncertainty in previous literature - is compared with covariance measures between stock returns and market returns representing un-diversifiable risk from the CAPM; and with alternative uncertainty proxies based on volatility in I/B/E/S securities analysts' forecasts of earnings per share. Within estimates of firm level investment specifications, the thesis investigates the sensitivity of coefficients on uncertainty terms to the choice of underlying investment specification: error correction model between the natural logarithms of capital and sales; or the Hayashi (1982) Q model of investment. Coefficients on stock return volatility measures of uncertainty terms are found to vary significantly between estimates of error correction and average q specifications. Differences between coefficients estimated on uncertainty terms across estimates of these two investment specifications are supported with simulated data. Uncertainty measures based on volatility in I/B/E/S securities analysts' forecasts of earnings per share are found to be much more informative of investment behaviour than within year stock return volatility in estimates of both error correction and average q specifications. Coefficients on I/B/E/S uncertainty proxies imply more consistent investment-uncertainty relationships across estimates of error correction and average q specifications for the UK panel data set.
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Smietanka, Pawel. "Essays on macroeconomic uncertainty." Thesis, University of Nottingham, 2016. http://eprints.nottingham.ac.uk/34989/.
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Recent data shows that more than £440 billion in cash has been piling up in the accounts of UK companies. At the same time, the investment outlays and corporate payouts have reached a 60-year low. What makes firms hold such enormous cash stocks instead of spending them on investment or returning them to shareholders? To what extent has the rising degree of uncertainty about macroeconomic conditions affected companies’ decisions? In this thesis we try to address these questions and, controlling for cyclical changes and financial factors, quantify the extent to which macroeconomic uncertainty has affected investments, cash holdings and equity payouts of UK companies. In the first substantive chapter we describe how information about macroeconomic uncertainty can be obtained from surveys of professional forecasters by applying a method initially proposed by Lucas (1972). We construct a theoretical model in which professional forecasters combine predictions based on public information with private beliefs which are defined as predictions based solely on private information sets. In the model, the combination of predictions produced on the basis of public and private information sets leads to a combined forecast which is reported by forecasters in their regular statements. We extract private beliefs from reported forecasts and then use them to construct our measure of macroeconomic uncertainty. The use of predictions based on private knowledge instead of reported forecasts makes our measure of macroeconomic uncertainty distinct from other uncertainty proxies and highlights the important role of beliefs as the driving force of uncertainty. Based on the measure constructed here we conclude that macroeconomic uncertainty increases either when the overall volatility of the underlying economic processes increases or when economic conditions are perceived as more changeable. We then take the model to the data using outcomes of surveys of economic forecasters and compute a measure of macroeconomic uncertainty for the UK and the US. The results point to an interesting phenomenon. In both countries the most variation in macroeconomic uncertainty comes from changes in the perceived volatility, and not from changes in the volatility of underlying economic processes. Moreover, a comparison of our measure of macroeconomic uncertainty with other uncertainty proxies reveals that in the US our uncertainty measure is most similar to an uncertainty proxy based on disagreement among forecasters, while in the UK it is most similar to an uncertainty proxy based on average variance reported by professional forecasters. Furthermore, it appears that the period of elevated uncertainty in the UK was more prolonged than it has been believed so far. In the second substantive chapter we examine the effects of uncertainty on corporate investments of a large panel of UK companies between 1998–2012 using the measure described earlier. Our regression equation is based on an extended version of a Tobin’s Q model and is estimated by the system GMM estimator. Apart from including the value of Tobin’s Q, which captures the ratio of the market value of capital to its book value, we also control for cash flow ratios, sales dynamic, individual uncertainty, business cycle and macroeconomic uncertainty. Our hypothesis is that macroeconomic uncertainty, defined as the expected volatility of the purely unforecastable component of the GDP growth rate conditional on information available at time t, negatively affects corporate investment ratios. We find indeed that a surge in macroeconomic uncertainty measured in this way is linked to a significant fall in investment ratios even after controlling for cyclical changes and a range of other factors. We also show that the effect of macroeconomic uncertainty on corporate investment is mainly driven by companies that are averagely financially constrained. These results are consistent with theories suggesting that the asymmetry of information is an important channel in the investment-uncertainty relationship and validate our measure of uncertainty. In the third substantive chapter we analyse the effects of changes in the degree of macroeconomic uncertainty on corporate cash management practices. Our analysis indicates that an increase in the degree of uncertainty about macroeconomic conditions leads to an increase in corporate cash holdings even after controlling for a range of factors. We also find that the effects of macroeconomic uncertainty are particularly strong among the most financially constrained companies. Such companies increase cash holdings significantly more than the less financially constrained companies. To complete the analysis of cash management practices we show that in uncertain times firms pay out lower dividends and reduce share buybacks. These results suggest that when uncertainty is rising firms adjust payout policy to obtain additional cash which they use to hedge unpredictable future cash flows. Our empirical results are consistent with the theoretical findings made by Almeida et al. (2004) and Han and Qiu (2007). Two important policy implications can be drawn from these results. First, if policy makers want to encourage companies to reduce their excessive cash holdings, which are sometimes referred to as “dead money”, they need to address sources of uncertainty which induces companies to accumulate cash in order to hedge unpredictable future cash flows. Second, smaller, less mature companies tend to be particularly affected by uncertain economic conditions. Well-designed policy needs to be developed that would address the problem of credit tightness and asymmetry of information between lenders and borrowers which may lead to suboptimal level of investment and excessive cash stocks in years when macroeconomic uncertainty is particularly high.
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Горобченко, Денис Володимирович, Денис Владимирович Горобченко, and Denys Volodymyrovych Horobchenko. "Climate change uncertainty debates." Thesis, Видавництво СумДУ, 2007. http://essuir.sumdu.edu.ua/handle/123456789/12811.
Full textAbstract:
Anyone familiar with the climate change debate is familiar with the ―scientific uncertainty‖ argument, which usually goes something like this:
The response to climate change must be based on sound science, not on speculation or theory. There is too much uncertainty and too much that we do not know about climate change. It would be irresponsible to undertake measures to reduce emissions, which could carry high economic costs, until we know that these are warranted.
When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/12811
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Shaer, Nicole. "The paradox of uncertainty." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/28321.
Full textAbstract:
This work represents my engagement with uncertainty, as I have defined and contained it. As an artist, my research strategy has been to work with uncertainty in a felt sense, using my hands as a way to access a different sort of thinking. To this end, I have allowed, created, sustained and magnified the presence of uncertainty in my studio, as a focused, experiential study within the practice of making art. Uncertainty might be understood in many ways, so I will begin with the common definition as that which is ‘not able to be relied on; not known or definite’ (OED, 2016). Psychology professor Michael Smithson characterises the Western perception of uncertainty as a predominantly negative anticipation of what cannot be known (Bammer and Smithson, 2008: 18).Such a perception of uncertainty as a threat, may encourage the use of control as a means to contain the unknown. Smithson’s description reflects the prevailing attitude of my upbringing and this project represents the exploration of a different paradigm. The Paradox of Uncertainty alludes to the coexistence of two apparently opposing views of uncertainty, which I have sought to integrate through my art practice. My interest in uncertainty originates in years of effort to overcome anxiety, which I understand as the physiological manifestation of a fearful relationship with uncertainty that results in a habitual psychological struggle to out-plan the future. In contrast with the prevailing medical conception of anxiety as a form of mentalillness, philosopher Martin Heidegger considers anxiety to be an ‘irreducible, existential state of being[...] aris[ing] from the self-reflexive awareness of our own“potentiality-for-being”’ (Gordon, 2013: 106). The existential psychologist, Rollo May (1977: 38) offers a functional link between uncertainty and anxiety, noting that ‘whenever possibility is visualised by an individual, anxiety is potentially present in the same experience.’ Developing May’s concept of anxiety as a normal part of lived experience, psychologist Kerry Gordon (2013: 107) expands on the relationship between anxiety and creativity, saying:
Creativity, authenticity, uncertainty, anxiety—these cannot be separated. To live a creative existence means to live with uncertainty. To live an authentic existence means to live with anxiety.
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Du, Preez Johan. "Price formation under uncertainty." Master's thesis, University of Cape Town, 2003. http://hdl.handle.net/11427/14975.
Full textAbstract:
Bibliography: leaves 170-173.The analysis presented in this thesis is aimed at better understanding the role of expectations to the price formation process. Since general competitive analysis lacks a coherent explanation of how expectations are formulated it is difficult to promote theories that assume agents have no structural knowledge in favour of theories that assume agents have significant structural knowledge, e.g. rational expectations hypothesis versus the theory of rational beliefs. Accordingly, empirical evidence is presented to support analyses of models in which agents are not assumed to have structural knowledge. Simple general equilibrium models are used to illustrate that modelling risk requires a thorough analysis of investor expectations embedded in asset prices to better understand the information conveyed by observed risk premia. Analysis of the role of diverse expectations in competitive equilibria shows that a prerequisite for the existence of a short-run Walrasian monetary equilibrium is the existence of at least one agent whose expectations are insensitive to current prices. Ergodic theory shows that any stable dynamical system generates a stationary probability measure based on its underlying generating probability that is unrelated to the data generated by the dynamical system. This result is used to show that the conditions under which diverse beliefs arise are sufficiently general to warrant the study of the impact of diverse expectations on the price formation process. Enthusiasm for models that allow diverse beliefs is however tempered by a review of Sunspot theory that show that it is not necessary to abandon the rational expectations hypothesis in order for competitive markets to be subject to speculative fluctuations that are driven by expectations. This analysis is reinforced by a known example that shows that adaptive learning rules can lead rational agents to believe in nonstationary, indeterminate equilibria that are locally stable, such as Sunspot Equilibria. This leads to an important conclusion; diverse beliefs are not temporary phenomena since disequilibrium-learning analysis cannot be relied on to teach investors the economy's equilibrium map.
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Jerow, Samuel B. "Fiscal Policy and Uncertainty." Miami University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=miami1533112993662019.
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