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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

Research output

as
Jump to: Working papers Articles

Working papers

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

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.
  2. Andreas Graefe & Randy Jones & Scott Armstrong & Alfred Cuzán, 2012. "The PollyVote’s Year-Ahead Forecast of the 2012 U.S. Presidential Election," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 24, pages 13-14, Winter.
  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.
  4. 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.
  5. Andreas Graefe, 2011. "Prediction Markets and the “Trough of Disillusionment”," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 23, pages 43-46, Fall.
  6. 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.
  7. Andreas Graefe, 2010. "Prediction Markets for Forecasting Drug Development," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 17, pages 8-12, Spring.
  8. Andreas Graefe, 2010. "Are Prediction Markets More Accurate than Simple Surveys?," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 19, pages 39-43, Fall.
  9. 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.
  10. 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.
  11. 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.
  12. 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.

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 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.

    Mentioned in:

    1. Metoda Delphi in Wikipedia (Romanian)
    2. Delphi method in Wikipedia (English)

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.

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

  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.

    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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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, Open Access Journal, vol. 8(2), pages 1-34, February.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Sungchul Kim & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Novel Forecasting Methodology for Sustainable Management of Defense Technology," Sustainability, MDPI, Open Access Journal, 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 & 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. 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, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.

  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.

    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. 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.
    3. 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.
    4. Cary Deck & David Porter, 2013. "Prediction Markets in the Laboratory," Working Papers 13-05, Chapman University, Economic Science Institute.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Bo Cowgill & Eric Zitzewitz, 2015. "Corporate Prediction Markets: Evidence from Google, Ford, and Firm X," Review of Economic Studies, Oxford University Press, vol. 82(4), pages 1309-1341.
    13. 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.
    14. 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.
    15. 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.
    16. 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 and Technology Policy Research, University of Sussex.
    17. 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.
    18. 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.

  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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. Armstrong, J. Scott, 2011. "Illusions in Regression Analysis," MPRA Paper 81663, University Library of Munich, Germany.
    9. Graefe, Andreas, 2015. "Improving forecasts using equally weighted predictors," Journal of Business Research, Elsevier, vol. 68(8), pages 1792-1799.

  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.

  6. 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.

  7. 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.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

Featured entries

This author is featured on the following reading lists, publication compilations or Wikipedia entries:
  1. Technology Assessment

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 & 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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