Andreas Graefe

Personal Details

First Name:	Andreas
Middle Name:
Last Name:	Graefe
Suffix:
RePEc Short-ID:	pgr243
	http://www.andreas-graefe.org

Affiliation

Institut für Kommunikationswissenschaft und Medienforschung, LMU München (Department of Communication Science and Media Research, LMU Munich)

http://www.en.ifkw.uni-muenchen.de/index.html
Munich, Germany

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:

1. Armstrong, J. Scott & Graefe, Andreas, 2009. "Predicting Elections from Biographical Information about Candidates," MPRA Paper 16461, University Library of Munich, Germany.

   Mentioned in:

   1. How to select presidential candidates based on their biography
      by Economic Logician in Economic Logic on 2009-09-14 19:58:00

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)

1. Kesten Green & J. Scott Armstrong & Andreas Graefe, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 17-20, Fall.
   • Green, Kesten C. & Armstrong, J. Scott & Graefe, Andreas, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," MPRA Paper 4663, University Library of Munich, Germany.

   Mentioned in:

   1. Delphi method in Wikipedia (English)
   2. デルファイ法 in Wikipedia (Japanese)
   3. Metoda Delphi in Wikipedia (Romanian)

Working papers

1. Armstrong, J. Scott & Graefe, Andreas, 2009. "Predicting Elections from Biographical Information about Candidates," MPRA Paper 16461, University Library of Munich, Germany.

   Cited by:

   1. Cote, Joseph A., 2011. "Predicting elections from biographical information about candidates: A commentary essay," Journal of Business Research, Elsevier, vol. 64(7), pages 696-698, July.
   2. Voss, Kevin E., 2011. "Voss wins the Presidency! A commentary essay on "Predicting elections from biographical information about candidates: A test of the index method"," Journal of Business Research, Elsevier, vol. 64(4), pages 345-347, April.
   3. Graefe, Andreas & Armstrong, J. Scott, 2011. "Conditions under which index models are useful: Reply to bio-index commentaries," Journal of Business Research, Elsevier, vol. 64(7), pages 693-695, July.

2. Graefe, Andreas & Armstrong, J. Scott, 2008. "Forecasting Elections from Voters’ Perceptions of Candidates’ Positions on Issues and Policies," MPRA Paper 9829, University Library of Munich, Germany.

   Cited by:

   1. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
      • Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
   2. Graefe, Andreas, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.
   3. Armstrong, J. Scott & Graefe, Andreas, 2009. "Predicting Elections from Biographical Information about Candidates," MPRA Paper 16461, University Library of Munich, Germany.
   4. Graefe, Andreas & Armstrong, J. Scott, 2011. "Conditions under which index models are useful: Reply to bio-index commentaries," Journal of Business Research, Elsevier, vol. 64(7), pages 693-695, July.
   5. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.

3. Green, Kesten C. & Armstrong, J. Scott & Graefe, Andreas, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," MPRA Paper 4663, University Library of Munich, Germany.
   • Kesten Green & J. Scott Armstrong & Andreas Graefe, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 17-20, Fall.

   Cited by:

   1. Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195.
      • Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195, January.
   2. Kerr, Norbert L. & Tindale, R. Scott, 2011. "Group-based forecasting?: A social psychological analysis," International Journal of Forecasting, Elsevier, vol. 27(1), pages 14-40, January.
   3. Maria Jose Marques & Gudrun Schwilch & Nina Lauterburg & Stephen Crittenden & Mehreteab Tesfai & Jannes Stolte & Pandi Zdruli & Claudio Zucca & Thorunn Petursdottir & Niki Evelpidou & Anna Karkani & Y, 2016. "Multifaceted Impacts of Sustainable Land Management in Drylands: A Review," Sustainability, MDPI, vol. 8(2), pages 1-34, February.
   4. Kerr, Norbert L. & Tindale, R. Scott, 2011. "Group-based forecasting?: A social psychological analysis," International Journal of Forecasting, Elsevier, vol. 27(1), pages 14-40.
   5. Keyvanfar, Ali & Shafaghat, Arezou & Abd Majid, Muhd Zaimi & Bin Lamit, Hasanuddin & Warid Hussin, Mohd & Binti Ali, Kherun Nita & Dhafer Saad, Alshahri, 2014. "User satisfaction adaptive behaviors for assessing energy efficient building indoor cooling and lighting environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 277-295.
   6. Samir Mili & Maria Bouhaddane, 2021. "Forecasting Global Developments and Challenges in Olive Oil Supply and Demand: A Delphi Survey from Spain," Agriculture, MDPI, vol. 11(3), pages 1-25, February.
   7. Bloem da Silveira Junior, Luiz A. & Vasconcellos, Eduardo & Vasconcellos Guedes, Liliana & Guedes, Luis Fernando A. & Costa, Renato Machado, 2018. "Technology roadmapping: A methodological proposition to refine Delphi results," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 194-206.
   8. Vicente Coll-Serrano & Salvador Carrasco-Arroyo & Olga Blasco-Blasco & Luis Vila-Lladosa, 2012. "Design of a Basic System of Indicators for Monitoring and Evaluating Spanish Cooperation’s Culture and Development Strategy," Evaluation Review, , vol. 36(4), pages 272-302, August.
   9. Robert Reig & Ramona Schoder, 2010. "Forecasting Accuracy: Comparing Prediction Markets And Surveys – An Experimental Study," Journal of Prediction Markets, University of Buckingham Press, vol. 4(3), pages 1-19.
   10. Soyeon Caren Han & Yulu Liang & Hyunsuk Chung & Hyejin Kim & Byeong Ho Kang, 2016. "Chinese trending search terms popularity rank prediction," Information Technology and Management, Springer, vol. 17(2), pages 133-139, June.
   11. Robert J. MacCoun, 2010. "Comment on "Rethinking America's Illegal Drug Policy"," NBER Chapters, in: Controlling Crime: Strategies and Tradeoffs, pages 281-289, National Bureau of Economic Research, Inc.
   12. Milan Daus & Katharina Koberger & Kaan Koca & Felix Beckers & Jorge Encinas Fernández & Barbara Weisbrod & Daniel Dietrich & Sabine Ulrike Gerbersdorf & Rüdiger Glaser & Stefan Haun & Hilmar Hofmann &, 2021. "Interdisciplinary Reservoir Management—A Tool for Sustainable Water Resources Management," Sustainability, MDPI, vol. 13(8), pages 1-21, April.
   13. Angela Dalton & Alan Brothers & Stephen Walsh & Paul Whitney, 2010. "Expert Elicitation Method Selection Process and Method Comparison," Labsi Experimental Economics Laboratory University of Siena 030, University of Siena.
   14. Liu, Yaqin & Zhao, Guohao & Zhao, Yushan, 2016. "An analysis of Chinese provincial carbon dioxide emission efficiencies based on energy consumption structure," Energy Policy, Elsevier, vol. 96(C), pages 524-533.
   15. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
   16. Joshua Becker & Abdullah Almaatouq & EmH{o}ke-'Agnes Horv'at, 2020. "Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion," Papers 2009.07202, arXiv.org, revised Mar 2021.
   17. Geoff Woolcott & Dan Chamberlain & Zachary Hawes & Michelle Drefs & Catherine D. Bruce & Brent Davis & Krista Francis & David Hallowell & Lynn McGarvey & Joan Moss & Joanne Mulligan & Yukari Okamoto &, 2020. "The central position of education in knowledge mobilization: insights from network analyses of spatial reasoning research across disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2323-2347, December.
   18. Ricardo Gomes & Alfeu Marques & Joaquim Sousa, 2013. "District Metered Areas Design Under Different Decision Makers’ Options: Cost Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4527-4543, October.
   19. Palma, David & Dios Ortuzar, Juan de & Casaubon, Gerard & Rizzi, Luis I. & Agosin, Eduardo, 2013. "Measuring consumer preferences using hybrid discrete choice models," Working Papers 164855, American Association of Wine Economists.
   20. Shin, Dong-Hee, 2015. "Effect of the customer experience on satisfaction with smartphones: Assessing smart satisfaction index with partial least squares," Telecommunications Policy, Elsevier, vol. 39(8), pages 627-641.
   21. Lang, Mark & Bharadwaj, Neeraj & Di Benedetto, C. Anthony, 2016. "How crowdsourcing improves prediction of market-oriented outcomes," Journal of Business Research, Elsevier, vol. 69(10), pages 4168-4176.
   22. Sungchul Kim & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Novel Forecasting Methodology for Sustainable Management of Defense Technology," Sustainability, MDPI, vol. 7(12), pages 1-17, December.

Articles

1. Andreas Graefe & J. Scott Armstrong, & Randall J. Jones & Alfred G. Cuz‡n, 2013. "Combined Forecasts of the 2012 Election: The PollyVote," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 28, pages 50-51, Winter.

   Cited by:

   1. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.

2. Graefe, Andreas & Armstrong, J. Scott, 2011. "Conditions under which index models are useful: Reply to bio-index commentaries," Journal of Business Research, Elsevier, vol. 64(7), pages 693-695, July.

   Cited by:

   1. Graefe, Andreas, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.
   2. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
   3. Loock, Moritz & Hinnen, Gieri, 2015. "Heuristics in organizations: A review and a research agenda," Journal of Business Research, Elsevier, vol. 68(9), pages 2027-2036.

3. Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195.
   • Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195, January.

   Cited by:

   1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
   2. Prommer, Lisa & Tiberius, Victor & Kraus, Sascha, 2020. "Exploring the future of startup leadership development," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
   3. Pennings, Clint L.P. & van Dalen, Jan & Rook, Laurens, 2019. "Coordinating judgmental forecasting: Coping with intentional biases," Omega, Elsevier, vol. 87(C), pages 46-56.
   4. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
      • Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
   5. Katherine A Smith & Segolame Setlhare & Allan DeCaen & Aaron Donoghue & Janell L Mensinger & Bingqing Zhang & Brennan Snow & Dikai Zambo & Kagiso Ndlovu & Ryan Littman-Quinn & Farhan Bhanji & Peter A , 2019. "Feasibility and preliminary validity evidence for remote video-based assessment of clinicians in a global health setting," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-13, August.
   6. Jaemyung Ahn & Olivier L. de Weck & Martin Steele, 2014. "Credibility Assessment of Models and Simulations Based on NASA’s Models and Simulation Standard Using the Delphi Method," Systems Engineering, John Wiley & Sons, vol. 17(2), pages 237-248, June.
   7. Jukrin Moon & Dongoo Lee & Taesik Lee & Jaemyung Ahn & Jindong Shin & Kyungho Yoon & Dongsik Choi, 2015. "Group Decision Procedure to Model the Dependency Structure of Complex Systems: Framework and Case Study for Critical Infrastructures," Systems Engineering, John Wiley & Sons, vol. 18(4), pages 323-338, July.
   8. Merfeld, Katrin & Wilhelms, Mark-Philipp & Henkel, Sven & Kreutzer, Karin, 2019. "Carsharing with shared autonomous vehicles: Uncovering drivers, barriers and future developments – A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 66-81.
   9. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
   10. Litsiou, Konstantia & Polychronakis, Yiannis & Karami, Azhdar & Nikolopoulos, Konstantinos, 2022. "Relative performance of judgmental methods for forecasting the success of megaprojects," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1185-1196.
   11. Nikolopoulos, Konstantinos & Litsa, Akrivi & Petropoulos, Fotios & Bougioukos, Vasileios & Khammash, Marwan, 2015. "Relative performance of methods for forecasting special events," Journal of Business Research, Elsevier, vol. 68(8), pages 1785-1791.
   12. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
   13. Christoph Diermann & Arnd Huchzermeier, 2017. "Case Article—Canyon Bicycles: Judgmental Demand Forecasting in Direct Sales," INFORMS Transactions on Education, INFORMS, vol. 17(2), pages 58-62, January.
   14. Bo Cowgill & Eric Zitzewitz, 2015. "Corporate Prediction Markets: Evidence from Google, Ford, and Firm X," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1309-1341.
   15. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael, 2014. "Collaborative forecasting in the food supply chain: A conceptual framework," International Journal of Production Economics, Elsevier, vol. 158(C), pages 120-135.
   16. Lian Jian & Rahul Sami, 2012. "Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution," Management Science, INFORMS, vol. 58(1), pages 123-140, January.
   17. Tommaso Ciarli & Alex Coad & Ismael Rafols, 2015. "Quantitative Analysis of Technology Futures: A review of Techniques, Uses and Characteristics," SPRU Working Paper Series 2015-23, SPRU - Science Policy Research Unit, University of Sussex Business School.
   18. Kopyto, Matthias & Lechler, Sabrina & von der Gracht, Heiko A. & Hartmann, Evi, 2020. "Potentials of blockchain technology in supply chain management: Long-term judgments of an international expert panel," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
   19. Muhammad Ridhuan Tony Lim Abdullah & Saedah Siraj & Zulkipli Ghazali, 2021. "An ISM Approach for Managing Critical Stakeholder Issues Regarding Carbon Capture and Storage (CCS) Deployment in Developing Asian Countries," Sustainability, MDPI, vol. 13(12), pages 1-23, June.
   20. Tiberius, Victor & Gojowy, Robin & Dabić, Marina, 2022. "Forecasting the future of robo advisory: A three-stage Delphi study on economic, technological, and societal implications," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
   21. Rengarajan, Srinath & Moser, Roger & Narayanamurthy, Gopalakrishnan, 2021. "Strategy tools in dynamic environments – An expert-panel study," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
   22. Bolger, Fergus & Rowe, Gene & Belton, Ian & Crawford, Megan M & Hamlin, Iain & Sissons, Aileen & Taylor Browne Lūka, Courtney & Vasilichi, Alexandrina & Wright, George, 2020. "The Simulated Group Response Paradigm: A new approach to the study of opinion change in Delphi and other structured-group techniques," OSF Preprints 4ufzg, Center for Open Science.
   23. Keller, Jonas & von der Gracht, Heiko A., 2014. "The influence of information and communication technology (ICT) on future foresight processes — Results from a Delphi survey," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 81-92.
   24. Spickermann, Alexander & Zimmermann, Martin & von der Gracht, Heiko A., 2014. "Surface- and deep-level diversity in panel selection — Exploring diversity effects on response behaviour in foresight," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 105-120.
   25. Laura Studen & Victor Tiberius, 2020. "Social Media, Quo Vadis? Prospective Development and Implications," Future Internet, MDPI, vol. 12(9), pages 1-22, August.
   26. Wright, George & Rowe, Gene, 2011. "Group-based judgmental forecasting: An integration of extant knowledge and the development of priorities for a new research agenda," International Journal of Forecasting, Elsevier, vol. 27(1), pages 1-13, January.
   27. Kauko, Karlo & Palmroos, Peter, 2014. "The Delphi method in forecasting financial markets— An experimental study," International Journal of Forecasting, Elsevier, vol. 30(2), pages 313-327.
   28. Christoph Markmann & Alexander Spickermann & Heiko A. von der Gracht & Alexander Brem, 2021. "Improving the question formulation in Delphi‐like surveys: Analysis of the effects of abstract language and amount of information on response behavior," Futures & Foresight Science, John Wiley & Sons, vol. 3(1), March.
   29. Cary Deck & David Porter, 2013. "Prediction Markets in the Laboratory," Working Papers 13-05, Chapman University, Economic Science Institute.
       • Cary Deck & David Porter, 2013. "Prediction Markets In The Laboratory," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 589-603, July.
   30. Marcin Kozak & Olesia Iefremova, 2014. "Implementation Of The Delphi Technique In Finance," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 10(4), pages 36-45, May.
   31. Winkler, Jens & Kuklinski, Christian Paul Jian-Wei & Moser, Roger, 2015. "Decision making in emerging markets: The Delphi approach's contribution to coping with uncertainty and equivocality," Journal of Business Research, Elsevier, vol. 68(5), pages 1118-1126.
   32. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
   33. Hanea, A.M. & McBride, M.F. & Burgman, M.A. & Wintle, B.C. & Fidler, F. & Flander, L. & Twardy, C.R. & Manning, B. & Mascaro, S., 2017. "I nvestigate D iscuss E stimate A ggregate for structured expert judgement," International Journal of Forecasting, Elsevier, vol. 33(1), pages 267-279.
   34. Julia A. Minson & Jennifer S. Mueller & Richard P. Larrick, 2018. "The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments," Management Science, INFORMS, vol. 64(9), pages 4177-4192, September.
   35. Apreda, Riccardo & Bonaccorsi, Andrea & dell'Orletta, Felice & Fantoni, Gualtiero, 2019. "Expert forecast and realized outcomes in technology foresight," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 277-288.
   36. Griffiths, Frances & Cave, Jonathan & Boardman, Felicity & Ren, Justin & Pawlikowska, Teresa & Ball, Robin & Clarke, Aileen & Cohen, Alan, 2012. "Social networks – The future for health care delivery," Social Science & Medicine, Elsevier, vol. 75(12), pages 2233-2241.
   37. Zeng, Michael A. & Koller, Hans & Jahn, Reimo, 2019. "Open radar groups: The integration of online communities into open foresight processes," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 204-217.
   38. Sung, Ming-Chien & McDonald, David C.J. & Johnson, Johnnie E.V. & Tai, Chung-Ching & Cheah, Eng-Tuck, 2019. "Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements," European Journal of Operational Research, Elsevier, vol. 272(1), pages 389-405.
   39. Steffen Keck & Wenjie Tang, 2021. "Elaborating or Aggregating? The Joint Effects of Group Decision-Making Structure and Systematic Errors on the Value of Group Interactions," Management Science, INFORMS, vol. 67(7), pages 4287-4309, July.
   40. Winkler, Jens & Moser, Roger, 2016. "Biases in future-oriented Delphi studies: A cognitive perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 63-76.

4. Armstrong, J. Scott & Graefe, Andreas, 2011. "Predicting elections from biographical information about candidates: A test of the index method," Journal of Business Research, Elsevier, vol. 64(7), pages 699-706, July.

   Cited by:

   1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
   2. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
      • Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
   3. Cote, Joseph A., 2011. "Predicting elections from biographical information about candidates: A commentary essay," Journal of Business Research, Elsevier, vol. 64(7), pages 696-698, July.
   4. Graefe, Andreas, 2023. "Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)," International Journal of Forecasting, Elsevier, vol. 39(1), pages 170-177.
   5. Graefe, Andreas, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.
   6. Philippe Jacquart & J. Scott Armstrong, 2013. "The Ombudsman: Are Top Executives Paid Enough? An Evidence-Based Review," Interfaces, INFORMS, vol. 43(6), pages 580-589, December.
   7. Woike, Jan K. & Hoffrage, Ulrich & Petty, Jeffrey S., 2015. "Picking profitable investments: The success of equal weighting in simulated venture capitalist decision making," Journal of Business Research, Elsevier, vol. 68(8), pages 1705-1716.
   8. David Stadelmann & Marco Portmann & Reiner Eichenberger, 2018. "Military Service of Politicians, Public Policy, and Parliamentary Decisions," CESifo Economic Studies, CESifo Group, vol. 64(4), pages 639-666.
   9. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017. "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper 83282, University Library of Munich, Germany.
   10. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
   11. Andreas Graefe & Kesten C Green & J Scott Armstrong, 2019. "Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-14, January.
   12. Marco Portmann & David Stadelmann, 2013. "Testing the Median Voter Model and Moving Beyond its Limits: Do Characteristics of Politicians Matter?," CREMA Working Paper Series 2013-05, Center for Research in Economics, Management and the Arts (CREMA).
   13. Armstrong, J. Scott, 2011. "Illusions in Regression Analysis," MPRA Paper 81663, University Library of Munich, Germany.

5. Andreas Graefe & J. Scott Armstrong & Alfred G. Cuzán & Randall J. Jones, Jr., 2009. "Combined Forecasts of the 2008 Election: The Pollyvote," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 12, pages 41-42, Winter.

   Cited by:

   1. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017. "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper 83282, University Library of Munich, Germany.
   2. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
   3. Graefe, Andreas, 2019. "Accuracy of German federal election forecasts, 2013 & 2017," International Journal of Forecasting, Elsevier, vol. 35(3), pages 868-877.

6. Andreas Graefe, 2008. "Prediction Markets – Defining Events and Motivating Participation," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 9, pages 30-32, Spring.

   Cited by:

   1. Andreas Heusler & Dominik Molitor & Martin Spann, 2019. "How Knowledge Stock Exchanges can increase student success in Massive Open Online Courses," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-17, September.

7. Andreas Graefe & Christof Weinhardt, 2008. "Long-Term Forecasting with Prediction Markets - A Field Experiment on Applicability and Expert Confidence," Journal of Prediction Markets, University of Buckingham Press, vol. 2(2), pages 71-91, September.

   Cited by:

   1. Patrick Buckley & Fergal O’Brien, 0. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-13.
   2. Buckley, Patrick, 2016. "Harnessing the wisdom of crowds: Decision spaces for prediction markets," Business Horizons, Elsevier, vol. 59(1), pages 85-94.
   3. Patrick Buckley & Fergal O’Brien, 2017. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 19(3), pages 611-623, June.

8. Kesten Green & J. Scott Armstrong & Andreas Graefe, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 17-20, Fall.
   • Green, Kesten C. & Armstrong, J. Scott & Graefe, Andreas, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," MPRA Paper 4663, University Library of Munich, Germany.
   See citations under working paper version above.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-FOR: Forecasting (3) 2007-09-09 2008-08-14 2009-08-02
2. NEP-CBE: Cognitive and Behavioural Economics (2) 2007-09-09 2008-08-14
3. NEP-CDM: Collective Decision-Making (2) 2008-08-14 2009-08-02
4. NEP-POL: Positive Political Economics (2) 2008-08-14 2009-08-02
5. NEP-ECM: Econometrics (1) 2009-08-02

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