Готові списки джерел за темами / Uncertainty risk

Добірка наукової літератури з теми "Uncertainty risk"

Автор: Grafiati
Опубліковано: 11 березня 2023

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Статті в журналах з теми "Uncertainty risk"

1

Bélyácz, Iván, and Katalin Daubner. "Uncertainity of risk and increasing risk of uncertainty in business decisions." Economy & finance 8, no. 3 (2021): 264–312. http://dx.doi.org/10.33908/ef.2021.3.2.

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Our paper follows the development of theory regarding the position of risk and uncertainty in economics from the publication of works by Knight (1921) and Keynes (1921) until the recent past. The starting point is presented by the relevant remarks of the thinkers of classical economics. Next, we describe the turning point related to Knight and Keynes and reveal the theoretical roots of risk taking. In the core chapter of the paper the authors make an attempt to re-interpret “animal spirits” as the intention for risk taking. A separate chapter is devoted to the relationship of rational choice and risk, and another one about the canonisation of risk in economics. In further parts of the paper, we examine the intentions to relativize the difference between risk and uncertainty, the negligence of uncertainty in the neo-classical system, the attempts to merge risk and uncertainty and the disruption of the unity of risk taking and risk bearing. Finally, the authors come to the conclusion that Knight’s and Keynes’ doctrines of risk and uncertainty have stood the test of time.
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2

Griffin, R. L. "Uncertain about uncertainty in pest risk analysis." Acta Horticulturae, no. 1105 (December 2015): 315–20. http://dx.doi.org/10.17660/actahortic.2015.1105.45.

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3

A. Kuzmin, Evgeny. "Risk and uncertainty in concept of corporate lifecycle." Problems and Perspectives in Management 15, no. 1 (March 29, 2017): 107–14. http://dx.doi.org/10.21511/ppm.15(1).2017.11.

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Regularly changed destructive periods in organizational development mean that the lifecycle exists. A nature of its formation hides a number of important conceptual regularities. One aspect of these trends is relationship between distribution of uncertainty and risks in lifecycle models, underlying motives of their formation and determining participation in development of organizational immunity. A closer definition of these issues is an objective of this research. The paper reviews the history of the lifecycle concept, gives its analysis and possible applications in management studies. In the analytical review of literature, there is an attempt of theoretical systematization for some provisions from the concept on consistency and continuity of stages turnover, on conditions of their identification and a nonlinear path. For discussions of the scientific community, the author presents hypotheses of the available effect of compression (density) in development stages, as well as heterogenic risk concentration. There is an assumption that economic systems have different orders for both the general and short lifecycles. Based on generalized theoretical and methodological provisions of stages in the lifecycle phases, the author attempts to combine functional and evolutionary models. The author also details distinctive features in the process of control over uncertainty and risks in the sequence of development stages.
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4

Leicester, R. H. "Uncertainty and risk." Australian Journal of Structural Engineering 18, no. 1 (January 2, 2017): 1–2. http://dx.doi.org/10.1080/13287982.2017.1335963.

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5

May, Robert. "Risk and uncertainty." Nature 411, no. 6840 (June 2001): 891. http://dx.doi.org/10.1038/35082158.

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Carter, Tony. "Risk and Uncertainty." Journal of Hospital Marketing & Public Relations 20, no. 1 (January 12, 2010): 66–86. http://dx.doi.org/10.1080/15390940903451014.

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Toma, Simona-Valeria, Mioara Chiriţă, and Daniela Şarpe. "Risk and Uncertainty." Procedia Economics and Finance 3 (2012): 975–80. http://dx.doi.org/10.1016/s2212-5671(12)00260-2.

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Schendel, Dan. "Risk and uncertainty." Strategic Entrepreneurship Journal 1, no. 1-2 (2007): 53–55. http://dx.doi.org/10.1002/sej.17.

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9

Brzezicka, Justyna, and Radoslaw Wisniewski. "Identifying Selected Behavioral Determinants of Risk and Uncertainty on the Real Estate Market." Real Estate Management and Valuation 22, no. 2 (July 8, 2014): 30–40. http://dx.doi.org/10.2478/remav-2014-0015.

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Abstract Various market behaviors can be characterized as risky or uncertain, thus their observation is important to the real estate market system. The extensive use of behavioral factors facilitates their implementation and studies in relation to the real estate market system. The behavioral approach has established its own instrumentation which enables elements of risk and uncertainty to be quantified. The belief that behavioral determinants connected with risk and uncertainty occur in the real estate market system (REMS) is the research hypothesis of the present paper which aims to: 1) analyze risk and uncertainty in the REM system using the behavioral approach, 2) identify and systematize behavioral determinants of risk and uncertainly shaping the REM, 3) develop a methodology for measuring behavioral determinants of risk and uncertainty in the REM, 4) present the significance of behavioral determinants of risk and uncertainty on the example of the Olsztyn REM. The aims were realized by means of a laboratory experiment conducted on a representative sample, as well as through the statistical verification of the obtained results. The article builds on current knowledge regarding the mechanisms of how the REM operates by introducing new issues connected with the behavioral approach to the topic of risk and uncertainty.
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Zhai, Jia, Haitao Zheng, Manying Bai, and Yunyun Jiang. "An Uncertain Alternating Renewal Insurance Risk Model." Mathematical Problems in Engineering 2020 (July 6, 2020): 1–13. http://dx.doi.org/10.1155/2020/3856323.

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The claim process in an insurance risk model with uncertainty is traditionally described by an uncertain renewal reward process. However, the claim process actually includes two processes, which are called the report process and the payment process, respectively. An alternative way is to describe the claim process by an uncertain alternating renewal reward process. Therefore, this paper proposes an insurance risk model under uncertain measure in which the claim process is supposed to be an alternating renewal reward process and the premium process is regarded as a renewal reward process. Then, the paper also gives the inverse uncertainty distribution of the insurance risk process. The expression of ruin index and the uncertainty distribution of the ruin time are derived which both have explicit expressions based on given uncertainty distributions. Finally, several examples are provided to illustrate the modeling ideas.
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Дисертації з теми "Uncertainty risk"

1

Loukoianova, Elena. "Risk, uncertainty, and fiscal institutions." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616105.

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2

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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3

Krüger, Niclas. "Infrastructure investment planning under uncertainty /." Örebro : Örebro University, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-6618.

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Filipsson, Monika. "Uncertainty, variability and environmental risk analysis." Doctoral thesis, Linnéuniversitetet, Institutionen för naturvetenskap, NV, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-11193.

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The negative effects of hazardous substances and possible measures that can be taken are evaluated in the environmental risk analysis process, consisting of risk assessment, risk communication and risk management. Uncertainty due to lack of knowledge and natural variability are always present in this process. The aim of this thesis is to evaluate some tools as well as discuss the management of uncertainty and variability, as it is necessary to treat them both in a reliable and transparent way to gain regulatory acceptance in decision making. The catalytic effects of various metals on the formation of chlorinated aromatic compounds during the heating of fly ash were investigated (paper I). Copper showed a positive catalytic effect, while cobalt, chromium and vanadium showed a catalytic effect for degradation. Knowledge of the catalytic effects may facilitate the choice and design of combustion processes to decrease emissions, but it also provides valuable information to identify and characterize the hazard. Exposure factors of importance in risk assessment (physiological parameters, time use factors and food consumption) were collected and evaluated (paper II). Interindividual variability was characterized by mean, standard deviation, skewness, kurtosis and multiple percentiles, while uncertainty in these parameters was estimated with confidence intervals. How these statistical parameters can be applied was shown in two exposure assessments (papers III and IV). Probability bounds analysis was used as a probabilistic approach, which enables separate propagation of uncertainty and variability even in cases where the availability of data is limited. In paper III it was determined that the exposure cannot be expected to cause any negative health effects for recreational users of a public bathing place. Paper IV concluded that the uncertainty interval in the estimated exposure increased when accounting for possible changes in climate-sensitive model variables. Risk managers often need to rely on precaution and an increased uncertainty may therefore have implications for risk management decisions. Paper V focuses on risk management and a questionnaire was sent to employees at all Swedish County Administrative Boards working with contaminated land. It was concluded that the gender, age and work experience of the employees, as well as the funding source of the risk assessment, all have an impact on the reviewing of risk assessments. Gender was the most significant factor, and it also affected the perception of knowledge.
Negativa effekter orsakade av skadliga ämnen och möjliga åtgärder bedöms och utvärderas i en miljöriskanalys, som kan delas i riskbedömning, riskkommunikation och riskhantering. Osäkerhet som beror på kunskapsbrist samt naturlig variabilitet finns alltid närvarande i denna process. Syftet med avhandlingen är att utvärdera några tillvägagångssätt samt diskutera hur osäkerhet och variabilitet hanteras då det är nödvändigt att båda hanteras trovärdigt och transparent för att riskbedömningen ska vara användbar för beslutsfattande. Metallers katalytiska effekt på bildning av klorerade aromatiska ämnen under upphettning av flygaska undersöktes (artikel I). Koppar visade en positiv katalytisk effekt medan kobolt, krom och vanadin istället katalyserade nedbrytningen. Kunskap om katalytisk potential för bildning av skadliga ämnen är viktigt vid val och design av förbränningsprocesser för att minska utsläppen, men det är också ett exempel på hur en fara kan identifieras och karaktäriseras. Information om exponeringsfaktorer som är viktiga i riskbedömning (fysiologiska parametrar, tidsanvändning och livsmedelskonsumtion) samlades in och analyserades (artikel II). Interindividuell variabilitet karaktäriserades av medel, standardavvikelse, skevhet, kurtosis (toppighet) och multipla percentiler medan osäkerhet i dessa parametrar skattades med konfidensintervall. Hur dessa statistiska parametrar kan tillämpas i exponeringsbedömningar visas i artikel III och IV. Probability bounds analysis användes som probabilistisk metod, vilket gör det möjligt att separera osäkerhet och variabilitet i bedömningen även när tillgången på data är begränsad. Exponeringsbedömningen i artikel III visade att vid nu rådande föroreningshalter i sediment i en badsjö så medför inte bad någon hälsofara. I artikel IV visades att osäkerhetsintervallet i den skattade exponeringen ökar när hänsyn tas till förändringar i klimatkänsliga modellvariabler. Riskhanterare måste ta hänsyn till försiktighetsprincipen och en ökad osäkerhet kan därmed få konsekvenser för riskhanteringsbesluten. Artikel V fokuserar på riskhantering och en enkät skickades till alla anställda som arbetar med förorenad mark på länsstyrelserna i Sverige. Det konstaterades att anställdas kön, ålder och erfarenhet har en inverkan på granskningsprocessen av riskbedömningar. Kön var den mest signifikanta variabeln, vilken också påverkade perceptionen av kunskap. Skillnader i de anställdas svar kunde också ses beroende på om riskbedömningen finansierades av statliga bidrag eller av en ansvarig verksamhetsutövare.
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Johnson, David G. "Representations of uncertainty in risk analysis." Thesis, Loughborough University, 1998. https://dspace.lboro.ac.uk/2134/31941.

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Uncertainty in situations involving risk is frequently modelled by assuming a plausible form of probability distribution for the uncertain quantities involved, and estimating the relevant parameters of that distribution based on the knowledge and judgement of informed experts or decision makers. The distributions assumed are usually uni-modal (and often bell-shaped) around some most likely value, with the Normal, Beta, Gamma and Triangular distributions being popular choices.
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Gallagher, Raymond. "Uncertainty modelling in quantitative risk analysis." Thesis, University of Liverpool, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367676.

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Werner, Jana. "Risk and uncertainty in project management." Thesis, Heriot-Watt University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.525618.

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8

Hantzsche, Arno. "Fiscal uncertainty and sovereign credit risk." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/49976/.

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This doctoral thesis studies sovereign credit risk during periods of uncertainty about the state of a government's fiscal position. A new measure of fiscal uncertainty is introduced, based on the disagreement in official forecasts of the public budget deficit, and forecast revisions to approximate common uncertainty shocks. It is shown that in the aftermath of the global financial crisis, fiscal uncertainty increased substantially in advanced economies. The effects of fiscal uncertainty are largely unknown, in particular in the context of sovereign credit risk. To estimate the response of sovereign credit ratings to fiscal uncertainty, a new empirical framework is developed for the analysis of rating determinants. Rating transition is modelled as the joint outcome of two processes, which determine the frequency of rating changes, and their direction. This thesis finds that fiscal uncertainty is perceived a credit risk by rating agencies and increases the probability of a rating downgrade. Fiscal uncertainty also affects the attention paid to sovereign ratings. An event study analysis shows that the attention to rating announcements increases, the more noisy publicly available information about fiscal outcomes is.
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OH, Joonseok. "The macroeconomics of uncertainty." Doctoral thesis, European University Institute, 2019. http://hdl.handle.net/1814/64465.

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Defence date: 25 September 2019
Examining Board: Prof. Evi Pappa, Universidad Carlos III Madrid (Supervisor); Prof. Axelle Ferrière, Paris School of Economics; Prof. Guido Ascari, University of Oxford; Prof. Johannes Pfeifer, University of Cologne
This thesis comprises three essays that analyze how uncertainty affects the macroeconomy. Each essay investigates a particular feature of uncertainty propagation. The first essay studies the effects of uncertainty shocks on economic activity, focusing on inflation. I consider standard New Keynesian models with Rotemberg-type and Calvo-type price rigidities. Despite the belief that the two schemes are equivalent, I show that they generate different dynamics in response to uncertainty shocks. In the Rotemberg model, uncertainty shocks decrease output and inflation, in line with the empirical results. By contrast, in the Calvo model, uncertainty shocks decrease output but raise inflation because of firms’ precautionary pricing motive. The second essay, written with Dario Bonciani, shows that uncertainty shocks negatively affect economic activity not only in the short, but also in the long run. We build a New Keynesian model with endogenous growth and Epstein-Zin preferences. A decline in R&D by higher uncertainty determines a fall in productivity, which causes a long-term decrease in the macroeconomic aggregates. This long-term risk affects households’ consumption process, which exacerbates the overall negative effects of uncertainty shocks. The third essay, prepared with Anna Rogantini Picco, illustrates how economic agents’ heterogeneity is crucial for the propagation of uncertainty shocks. We build a heterogeneous agent New Keynesian model with search and matching frictions and Calvo pricing. Unemployment risk for imperfectly insured households amplifies their precautionary savings through increased uncertainty, thus further depressing consumption. Therefore, uncertainty shocks have considerably adverse effects and lead to a decrease in inflation.
-- 1 The Propagation of Uncertainty Shocks: Rotemberg vs. Calvo -- 2 The Long-Run Effects of Uncertainty Shocks -- 3 Macro Uncertainty and Unemployment Risk -- Bibliography -- Appendix A Appendix to Chapter 1 -- Appendix B Appendix to Chapter 2
Chapter 1 'The Propagation of Uncertainty Shocks: Rotemberg vs. Calvo' of the PhD thesis draws upon an earlier version published as EUI ECO WP 2019/01
Chapter 2 'The Long-Run Effects of Uncertainty Shocks' of the PhD thesis draws upon an earlier version published as Bank of England Staff WP 2019/802
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Samson, Sundeep. "Performance based decisions under uncertainty and risk." Connect to this title online, 2008. http://etd.lib.clemson.edu/documents/1219855032/.

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Книги з теми "Uncertainty risk"

1

Abdellaoui, Mohammed, R. Duncan Luce, Mark J. Machina, and Bertrand Munier, eds. Uncertainty and Risk. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-48935-1.

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Firoozye, Nick B., and Fauziah Ariff. Managing Uncertainty, Mitigating Risk. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/9781137334541.

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Watson, Sean, and Anthony Moran, eds. Trust, Risk and Uncertainty. London: Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230506039.

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Olofsson, Anna, and Jens O. Zinn, eds. Researching Risk and Uncertainty. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-95852-1.

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5

Aven, Terje, Piero Baraldi, Roger Flage, and Enrico Zio, eds. Uncertainty in Risk Assessment. Chichester, United Kingdom: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118763032.

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Hellström, Tomas, and Merle Jacob. Policy Uncertainty and Risk. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1559-3.

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Risk, uncertainty and profit. Mineola, NY: Dover Publications, 2006.

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8

Risk, uncertainty, and profit. Kissimmee, Fla: Signalman Publishing, 2009.

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9

Grundy, A. N. Uncertainty and risk management. Kingston upon Thames: Croner, 2003.

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10

1962-, Watson Sean, and Moran Anthony, eds. Trust, risk, and uncertainty. Basingstoke, Hampshire: Palgrave Macmillan, 2005.

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Частини книг з теми "Uncertainty risk"

1

Rescher, Nicholas. "Uncertainty." In Risk Theory, 31–36. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78502-4_6.

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Rescher, Nicholas. "Uncertainty." In Risk Theory, 31–36. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78502-4_6.

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3

Yoe, Charles. "Uncertainty." In Principles of Risk Analysis, 27–46. Second edition. | Boca Raton : Taylor and Francis, CRC Press, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429021121-2.

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Yoe, Charles. "Uncertainty." In Primer on Risk Analysis, 29–53. Second edition. | Boca Raton : Taylor & Francis, CRC Press, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429021145-2.

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Liu, Baoding. "Uncertain Risk Analysis." In Uncertainty Theory, 115–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13959-8_3.

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Liu, Baoding. "Uncertain Risk Analysis." In Uncertainty Theory, 137–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44354-5_6.

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van Asselt, Marjolein B. A. "Uncertainty." In Perspectives on Uncertainty and Risk, 75–146. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-017-2583-5_3.

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Tapiero, Charles S. "Uncertainty Economics." In Engineering Risk and Finance, 333–74. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-6234-7_10.

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Rose, Adam, Fynnwin Prager, Zhenhua Chen, Samrat Chatterjee, Dan Wei, Nathaniel Heatwole, and Eric Warren. "Uncertainty Analysis." In Integrated Disaster Risk Management, 87–97. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-2567-9_7.

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Jensen, Jesper Lyng, and Susanne Sublett. "Risk and Uncertainty." In Redefining Risk & Return, 19–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-41369-3_4.

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Тези доповідей конференцій з теми "Uncertainty risk"

1

Kulhawy, Fred H. "Foundation Engineering, Geotechnical Uncertainty, and Reliability-Based Design." In Geo-Risk 2017. Reston, VA: American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784480731.015.

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Negreiros, J., M. Painho, A. Cristina Costa, P. Cabral, and F. Aguilar. "The local confidence uncertainty plume of SAKWeb©." In RISK ANALYSIS 2008. Southampton, UK: WIT Press, 2008. http://dx.doi.org/10.2495/risk080091.

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Fabbri, A. G., and C. J. Chung. "On spatial uncertainty in hazard and risk assessment." In RISK ANALYSIS 2014. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/risk140011.

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Chen, Zekai, Nan He, and Chengbo Zhang. "Risk Management and Uncertainty." In 2022 2nd International Conference on Enterprise Management and Economic Development (ICEMED 2022). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/aebmr.k.220603.115.

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Angulo, Mauricio, and Wilson H. Tang. "Optimal Ground-Water Detection Monitoring System Design under Uncertainty." In Geo-Risk 2017. Reston, VA: American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784480731.026.

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Beck, Andre, Wellison Gomes, Rafael Lopez, and Leandro Miguel. "Robust, Risk and Robust Risk Optimization under Uncertainties." In 3rd International Symposium on Uncertainty Quantification and Stochastic Modeling. Rio de Janeiro, Brazil: ABCM Brazilian Society of Mechanical Sciences and Engineering, 2015. http://dx.doi.org/10.20906/cps/usm-2016-0038.

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Michaels, Paul. "Uncertainty in a Geophysical Survey for a Bridge Foundation Design." In Geo-Risk 2017. Reston, VA: American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784480724.060.

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8

Zhao, Tengyuan, and Yu Wang. "Effect of Model Uncertainty on Probabilistic Characterization of Soil Property." In Geo-Risk 2017. Reston, VA: American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784480724.044.

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9

Negreiros, J., M. Painho, M. Aguilar, and F. Aguilar. "Risk assessment: the global confidence uncertainty plume of SAKWeb©." In RISK ANALYSIS 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/risk100031.

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10

Wang, Xun, and Mary-Anne Williams. "Risk, Uncertainty and Possible Worlds." In 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust (PASSAT) / 2011 IEEE Third Int'l Conference on Social Computing (SocialCom). IEEE, 2011. http://dx.doi.org/10.1109/passat/socialcom.2011.130.

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Звіти організацій з теми "Uncertainty risk"

1

Hodrick, Robert. Risk, Uncertainty and Exchange Rates. Cambridge, MA: National Bureau of Economic Research, November 1987. http://dx.doi.org/10.3386/w2429.

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2

Bekaert, Geert, Marie Hoerova, and Marco Lo Duca. Risk, Uncertainty and Monetary Policy. Cambridge, MA: National Bureau of Economic Research, September 2010. http://dx.doi.org/10.3386/w16397.

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3

Pastor, Lubos, and Pietro Veronesi. Political Uncertainty and Risk Premia. Cambridge, MA: National Bureau of Economic Research, September 2011. http://dx.doi.org/10.3386/w17464.

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4

Bekaert, Geert, Eric Engstrom, and Yuhang Xing. Risk, Uncertainty and Asset Prices. Cambridge, MA: National Bureau of Economic Research, May 2006. http://dx.doi.org/10.3386/w12248.

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5

Rish, W. R. Approach to uncertainty in risk analysis. Office of Scientific and Technical Information (OSTI), August 1988. http://dx.doi.org/10.2172/7141098.

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6

Laughman, Robert L. Managing Uncertainty: Risk Management in Acquisition. Fort Belvoir, VA: Defense Technical Information Center, March 2010. http://dx.doi.org/10.21236/ada520010.

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7

Quah, John, Ludovic Renou, and Matthew Polisson. Revealed preferences over risk and uncertainty. Institute for Fiscal Studies, September 2015. http://dx.doi.org/10.1920/wp.ifs.2015.1525.

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8

Johri, Alok, Shahed Khan, and César Sosa-Padilla. Interest Rate Uncertainty and Sovereign Default Risk. Cambridge, MA: National Bureau of Economic Research, August 2020. http://dx.doi.org/10.3386/w27639.

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9

Broesius, Michael T. The spectre of uncertainty in communicating technological risk. Office of Scientific and Technical Information (OSTI), December 1993. http://dx.doi.org/10.2172/10143021.

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10

Bekaert, Geert, Eric Engstrom, and Nancy Xu. The Time Variation in Risk Appetite and Uncertainty. Cambridge, MA: National Bureau of Economic Research, March 2019. http://dx.doi.org/10.3386/w25673.

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