Search results for 'Forecasting' (try it on Scholar)

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  1. Lauren N. Harkrider, Alexandra E. MacDougall, Zhanna Bagdasarov, James F. Johnson, Michael D. Mumford, Shane Connelly & Lynn D. Devenport (2014). Retracted Article: Improving Case-Based Ethics Training: How Modeling Behaviors and Forecasting Influence Effectiveness. Science and Engineering Ethics 20 (1):299-299.score: 21.0
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  2. Augusto Forti (ed.) (1984). Scientific Forecasting and Human Needs: Trends, Methods, and Message: Proceedings of a Symposium Held in Tbilisi, Ussr, 6-11 December 1981. [REVIEW] Pergamon.score: 21.0
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  3. Ota Sulc (1977). Methodology of Forecasting Complex Development Processes of the Scientific and Technological Revolution. Centre for the Study of Science, Technology, and Develop[Ment], Council of Scientific and Industrial Research.score: 21.0
     
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  4. Nigel Harvey (2007). Use of Heuristics: Insights From Forecasting Research. Thinking and Reasoning 13 (1):5 – 24.score: 18.0
    Tversky and Kahneman (1974) originally discussed three main heuristics: availability, representativeness, and anchoring-and-adjustment. Research on judgemental forecasting suggests that the type of information on which forecasts are based is the primary factor determining the type of heuristic that people use to make their predictions. Specifically, availability is used when forecasts are based on information held in memory; representativeness is important when the value of one variable is forecast from explicit information about the value of another variable; and anchoring-and-adjustment is (...)
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  5. Cheryl K. Stenmark, Alison L. Antes, Xiaoqian Wang, Jared J. Caughron, Chase E. Thiel & Michael D. Mumford (2010). Strategies in Forecasting Outcomes in Ethical Decision-Making: Identifying and Analyzing the Causes of the Problem. Ethics and Behavior 20 (2):110 – 127.score: 18.0
    This study examined the role of key causal analysis strategies in forecasting and ethical decision-making. Undergraduate participants took on the role of the key actor in several ethical problems and were asked to identify and analyze the causes, forecast potential outcomes, and make a decision about each problem. Time pressure and analytic mindset were manipulated while participants worked through these problems. The results indicated that forecast quality was associated with decision ethicality, and the identification of the critical causes of (...)
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  6. Michael D. Mumford, Chase E. Thiel, Jared J. Caughron, Xiaoqian Wang, Alison L. Antes & Cheryl K. Stenmark (2010). Strategies in Forecasting Outcomes in Ethical Decision-Making: Identifying and Analyzing the Causes of the Problem. Ethics and Behavior 20 (2):110-127.score: 18.0
    This study examined the role of key causal analysis strategies in forecasting and ethical decision-making. Undergraduate participants took on the role of the key actor in several ethical problems and were asked to identify and analyze the causes, forecast potential outcomes, and make a decision about each problem. Time pressure and analytic mindset were manipulated while participants worked through these problems. The results indicated that forecast quality was associated with decision ethicality, and the identification of the critical causes of (...)
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  7. David A. Bessler & Zijun Wang (2012). D-Separation, Forecasting, and Economic Science: A Conjecture. [REVIEW] Theory and Decision 73 (2):295-314.score: 18.0
    The paper considers the conjecture that forecasts from preferred economic models or theories d-separate forecasts from less preferred models or theories from the Actual realization of the variable for which a scientific explanation is sought. D-separation provides a succinct notion to represent forecast dominance of one set of forecasts over another; it provides, as well, a criterion for model preference as a fundamental device for progress in economic science. We demonstrate these ideas with examples from three areas of economic modeling.
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  8. Robert S. Goldfarb, H. O. Stekler & Joel David (2005). Methodological Issues in Forecasting: Insights From the Egregious Business Forecast Errors of Late 1930. Journal of Economic Methodology 12 (4):517-542.score: 18.0
    This paper examines some economic forecasts made in late 1930 that were intended to predict economic activity in the United States in order to shed light on several methodological issues. We document that these forecasts were extremely optimistic, predicting that the recession in the US would soon end, and that 1931 would show a recovery. These forecasts displayed egregious errors, because 1931 witnessed the largest negative growth rate for the US economy in any year in the twentieth century. A specific (...)
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  9. Lauren N. Harkrider, Chase E. Thiel, Zhanna Bagdasarov, Michael D. Mumford, James F. Johnson, Shane Connelly & Lynn D. Devenport (2012). Improving Case-Based Ethics Training with Codes of Conduct and Forecasting Content. Ethics and Behavior 22 (4):258 - 280.score: 18.0
    Although case-based training is popular for ethics education, little is known about how specific case content influences training effectiveness. Therefore, the effects of (a) codes of ethical conduct and (b) forecasting content were investigated. Results revealed richer cases, including both codes and forecasting content, led to increased knowledge acquisition, greater sensemaking strategy use, and better decision ethicality. With richer cases, a specific pattern emerged. Specifically, content describing codes alone was more effective when combined with short-term forecasts, whereas content (...)
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  10. Cheryl Stenmark (2013). Forecasting and Ethical Decision Making: What Matters? Ethics and Behavior 23 (6):445-462.score: 18.0
    This study examined how the number and types of consequences considered are related to forecasting and ethical decision making. Undergraduate participants took on the role of the key actor in several ethical problems and were asked to forecast potential outcomes and make a decision about each problem. Performance pressure was manipulated by ostensibly making rewards contingent on good problem-solving performance. The results indicated that forecast quality was associated with decision ethicality, and the identification of the critical consequences of the (...)
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  11. Peter Ayton, Alice Pott & Najat Elwakili (2007). Affective Forecasting: Why Can't People Predict Their Emotions? Thinking and Reasoning 13 (1):62 – 80.score: 16.0
    Two studies explore the frequently reported finding that affective forecasts are too extreme. In the first study, driving test candidates forecast the emotional consequences of failing. Test failers overestimated the duration of their disappointment. Greater previous experience of this emotional event did not lead to any greater accuracy of the forecasts, suggesting that learning about one's own emotions is difficult. Failers' self-assessed chances of passing were lower a week after the test than immediately prior to the test; this difference correlated (...)
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  12. Teddy Seidenfeld, Mark Schervish & Jay Kadane, Forecasting with Imprecise/Indeterminate Probabilities [IP] – Some Preliminary Findings.score: 16.0
    Part 1 Background on de Finetti’s twin criteria of coherence: Coherence1: 2-sided previsions free from dominance through a Book. Coherence2: Forecasts free from dominance under Brier (squared error) score. Part 2 IP theory based on a scoring rule.
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  13. David Nerini, Jean Pierre Durbec, Claude Mante, Fabrice Garcia & Badih Ghattas (2000). Forecasting Physicochemical Variables by a Classification Tree Method. Application to the Berre Lagoon (South France). Acta Biotheoretica 48 (3-4).score: 16.0
    The dynamics of the "Etang de Berre", a brackish lagoon situated close to the French Mediterranean sea coast, is strongly disturbed by freshwater inputs coming from an hydroelectric power station. The system dynamics has been described as a sequence of daily typical states from a set of physicochemical variables such as temperature, salinity and dissolved oxygen rates collected over three years by an automatic sampling station. Each daily pattern summarizes the evolution, hour by hour of the physicochemical variables. This article (...)
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  14. Philip E. Tetlock, Michael C. Horowitz & Richard Herrmann (2012). Should “Systems Thinkers” Accept the Limits on Political Forecasting or Push the Limits? Critical Review 24 (3):375-391.score: 16.0
    Historical analysis and policy making often require counterfactual thought experiments that isolate hypothesized causes from a vast array of historical possibilities. However, a core precept of Jervis's ?systems thinking? is that causes are so interconnected that the historian can only with great difficulty imagine causation by subtracting all variables but one. Prediction, according to Jervis, is even more problematic: The more sensitive an event is to initial conditions (e.g., butterfly effects), the harder it is to derive accurate forecasts. Nevertheless, if (...)
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  15. Roman Frigg, Seamus Bradley, Reason L. Machete & Leonard A. Smith, Probabilistic Forecasting: Why Model Imperfection is a Poison Pill.score: 15.0
    This volume is a serious attempt to open up the subject of European philosophy of science to real thought, and provide the structural basis for the interdisciplinary development of its specialist fields, but also to provoke reflection on the idea of ‘European philosophy of science’. This efforts should foster a contemporaneous reflection on what might be meant by philosophy of science in Europe and European philosophy of science, and how in fact awareness of it could assist philosophers interpret and motivate (...)
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  16. Martin Wachs (1990). Ethics and Advocacy in Forecasting for Public Policy. Business and Professional Ethics Journal 9 (1/2):141-157.score: 15.0
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  17. Robert Evans (2007). Social Networks and Private Spaces in Economic Forecasting. Studies in History and Philosophy of Science Part A 38 (4):686-697.score: 15.0
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  18. Monique Mh Pollmann & Catrin Finkenauer (2009). Empathic Forecasting: How Do We Predict Other People's Feelings? Cognition and Emotion 23 (5):978-1001.score: 15.0
  19. Rosamond Rhodes & James J. Strain (2007). Affective Forecasting and Its Implications for Medical Ethics. Cambridge Quarterly of Healthcare Ethics 17 (01):54-65.score: 15.0
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  20. Friedel Weinert (1999). Predicting the Future: An Introduction to the Theory of Forecasting by Nicholas Rescher. State University of New York Press, Albany, 1998, Pp. XI + 232. Philosophy 74 (1):122-139.score: 15.0
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  21. Francis X. Diebold & Glenn D. Rudebusch (2013). Yield Curve Modeling and Forecasting: The Dynamic Nelson-Siegel Approach. Princeton University Press.score: 15.0
    In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful.
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  22. Vladimir Faifr, Fedor Gal, Martin Potucek & Milos Zeman (1984). Forecasting Modelling by Means of the KPM Method. World Futures 20 (1):105-133.score: 15.0
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  23. F. Mobio (2000). Stock-Market Forecasting as Cosmography. Diogenes 48 (190):43-57.score: 15.0
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  24. Peter Gärdenfors (1982). Dynamic Models as Tools for Forecasting and Planning: A Presentation and Some Methodological Aspects. Theory and Decision 14 (3):237-273.score: 15.0
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  25. Nada Gligorov (2009). Reconsidering the Impact of Affective Forecasting. Cambridge Quarterly of Healthcare Ethics 18 (02):166-.score: 15.0
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  26. Rosamond Rhodes & James J. Strain (2009). Further Thoughts About Affective Forecasting Biases in Medicine: A Response to Nada Gligorov. Cambridge Quarterly of Healthcare Ethics 18 (02):174-.score: 15.0
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  27. Seweryn Żurawicki (1975). Seweryn Żurawicki, Problemy Prognozowania Ekonomicznego (Problems of Economic Forecasting). Dialectics and Humanism 2 (4):173-175.score: 15.0
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  28. Shyi-Ming Chen (2002). Forecasting Enrollments Based on High-Order Fuzzy Time Series. In Robert Trappl (ed.), Cybernetics and Systems. Austrian Society for Cybernetics Studies. 33--1.score: 15.0
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  29. Hugh Duncan Grant (1937). Long-Range Weather Forecasting. Thought 12 (2):265-282.score: 15.0
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  30. Clive Wj Granger (2012). The Philosophy of Economic Forecasting. In Uskali Mäki, Dov M. Gabbay, Paul Thagard & John Woods (eds.), Philosophy of Economics. North Holland.score: 15.0
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  31. Sine N. Just, Nico Mouton & Jonas Gabrielsen (2013). Looking Forward: On the Uses of Forecasting in Market Formation. International Journal of Management Concepts and Philosophy 7 (3/4):224.score: 15.0
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  32. Alexandra E. MacDougall, Lauren N. Harkrider, Zhanna Bagdasarov, James F. Johnson, Chase E. Thiel, Juandre Peacock, Michael D. Mumford, Lynn D. Devenport & Shane Connelly (2014). Examining the Effects of Incremental Case Presentation and Forecasting Outcomes on Case-Based Ethics Instruction. Ethics and Behavior 24 (2):126-150.score: 15.0
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  33. Nicholas Rescher (1997). Predicting the Future: An Introduction to the Theory of Forecasting. State University of New York Press.score: 15.0
    Develops a general theory of prediction that encompasses its fundamental principles, methodology, and practice and gives an overview of its promises and problems.
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  34. Susanne Scheibe, Rui Mata & Laura L. Carstensen (2011). Age Differences in Affective Forecasting and Experienced Emotion Surrounding the 2008 US Presidential Election. Cognition and Emotion 25 (6):1029-1044.score: 15.0
  35. Devon Stillwell (2013). Genetic Counseling in Historical Perspective: Understanding Our Hereditary Past and Forecasting Our Genomic Future. Studies in History and Philosophy of Science Part A 44 (4):618-622.score: 15.0
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  36. Lambert Williams & William Thomas (2009). The Epistemologies of Non-Forecasting Simulations, Part II: Climate, Chaos, Computing Style, and the Contextual Plasticity of Error. Science in Context 22 (2):271.score: 15.0
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  37. Stanley R. Barrett (1999). Forecasting Theory: Problems and Exemplars in the Twenty-First Century. In E. L. Cerroni-Long (ed.), Anthropological Theory in North America. Bergin & Garvey. 255.score: 15.0
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  38. Daniel B. Botkin, Henrik Saxe, Miguel B. Araujo, Richard Betts, Richard Hw Bradshaw, Tomas Cedhagen, Peter Chesson, Terry P. Dawson, Julie R. Etterson & Daniel P. Faith (2007). Forecasting the Effects of Global Warming on Biodiversity. BioScience 57 (3):227-236.score: 15.0
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  39. Newton C. A. da Costa & FranciscoAntonio Doria (1994). Gödel Incompleteness in Analysis, with an Application to the Forecasting Problem in the Social Sciences. Philosophia Naturalis 31 (1):1-24.score: 15.0
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  40. J. Barnard Gilmore (1991). On Forecasting Validity and Finessing Reliability. Behavioral and Brain Sciences 14 (1):148-149.score: 15.0
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  41. N. Harvey & P. Ayton (1990). Actor-Observer Differences in Judgmental Probability Forecasting of Control Response Efficacy. Bulletin of the Psychonomic Society 28 (6):523-523.score: 15.0
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  42. Michael Hoerger, Stuart W. Quirk, Benjamin P. Chapman & Paul R. Duberstein (2012). Affective Forecasting and Self-Rated Symptoms of Depression, Anxiety, and Hypomania: Evidence for a Dysphoric Forecasting Bias. Cognition and Emotion 26 (6):1098-1106.score: 15.0
  43. Wei Huang, Lean Yu, Shouyang Wang, Yukun Bao & Lin Wang (2006). Computational Finance and Business Intelligence-Comparisons of the Different Frequencies of Input Data for Neural Networks in Foreign Exchange Rates Forecasting. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 517-524.score: 15.0
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  44. M. R. Hyman (1988). The Timeliness Problem in the Application of Bass-Type New Product-Growth Models to Durable Sales Forecasting. Journal of Business Research 16 (1):31--47.score: 15.0
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  45. Alfred Kähler (forthcoming). Forecasting the Business Cycle. Social Research.score: 15.0
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  46. Robert Kubey (2000). TV and the Internet: Pitfalls in Forecasting the Future. Knowledge, Technology and Policy 13 (2):63-85.score: 15.0
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  47. F. Kutta, A. Hodek, J. Dvorak, V. Rab, Z. Drab, L. Machon, J. Jirasek & M. Nebesky (1978). Ideological Discussion on Topic Planning-and-Forecasting-Social-Processes. Filosoficky Casopis 26 (2):329-347.score: 15.0
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  48. George Loewenstein (2007). Affect Regulation and Affective Forecasting. In James J. Gross (ed.), Handbook of Emotion Regulation. Guilford Press. 180--203.score: 15.0
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  49. Franco Modigliani (forthcoming). Fluctuations in the Saving Ratio: A Problem in Economic Forecasting. Social Research.score: 15.0
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  50. Alexander Mourelatos (2005). The Ancients''Meteorology': Forecasting and Cosmic Natural History. Rhizai. A Journal for Ancient Philosophy and Science 2:279-291.score: 15.0
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