Predicting general election outcomes: campaigns and changing voter knowledge at the 2017 general election in England
Author
Abstract
Suggested Citation
DOI: 10.1007/s11135-018-0819-1
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- Leiter, Debra & Murr, Andreas & Rascón Ramírez, Ericka & Stegmaier, Mary, 2018. "Social networks and citizen election forecasting: The more friends the better," International Journal of Forecasting, Elsevier, vol. 34(2), pages 235-248.
- Stiers, Dieter & Dassonneville, Ruth, 2018. "Affect versus cognition: Wishful thinking on election day," International Journal of Forecasting, Elsevier, vol. 34(2), pages 199-215.
- Matthew Blackwell & James Honaker & Gary King, 2017.
"A Unified Approach to Measurement Error and Missing Data: Overview and Applications,"
Sociological Methods & Research, , vol. 46(3), pages 303-341, August.
- Matthew Blackwell & James Honaker & Gary King, "undated". "A Unified Approach to Measurement Error and Missing Data: Overview and Applications," Working Paper 6388, Harvard University OpenScholar.
- Lewis-Beck, Michael S. & Skalaban, Andrew, 1989. "Citizen Forecasting: Can Voters See into the Future?," British Journal of Political Science, Cambridge University Press, vol. 19(1), pages 146-153, January.
- Pattie, C. J. & Johnston, R. J., 2003. "Hanging on the Telephone? Doorstep and Telephone Canvassing at the British General Election of 1997," British Journal of Political Science, Cambridge University Press, vol. 33(2), pages 303-322, April.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Anurag Barthwal & Mamta Bhatt & Shwetank Avikal & Chandra Prakash, 2025. "Machine learning-based prediction models for electoral outcomes in India: a comparative analysis of exit polls from 2014–2021," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(1), pages 313-338, February.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Temporão, Mickael & Dufresne, Yannick & Savoie, Justin & Linden, Clifton van der, 2019. "Crowdsourcing the vote: New horizons in citizen forecasting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 1-10.
- Matthew Blackwell & James Honaker & Gary King, 2017.
"A Unified Approach to Measurement Error and Missing Data: Overview and Applications,"
Sociological Methods & Research, , vol. 46(3), pages 303-341, August.
- Matthew Blackwell & James Honaker & Gary King, "undated". "A Unified Approach to Measurement Error and Missing Data: Overview and Applications," Working Paper 6388, Harvard University OpenScholar.
- Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2017.
"Generalized partially linear regression with misclassified data and an application to labour market transitions,"
Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 145-159.
- Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2015. "Generalised partially linear regression with misclassied data and an application to labour market transitions," FDZ-Methodenreport 201510 (en), Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
- Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2015. "Generalised partially linear regression with misclassified data and an application to labour market transitions," ZEW Discussion Papers 15-043, ZEW - Leibniz Centre for European Economic Research.
- Meyer, Bruce D. & Mittag, Nikolas, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," IZA Discussion Papers 12266, Institute of Labor Economics (IZA).
- Sebastian Barfort & Nikolaj Harmon & Frederik Hjorth & Asmus Leth Olsen, 2015. "Dishonesty and Selection into Public Service in Denmark: Who Runs the World’s Least Corrupt Public Sector?," Discussion Papers 15-12, University of Copenhagen. Department of Economics.
- Khan, Urmee & Lieli, Robert P., 2018.
"Information flow between prediction markets, polls and media: Evidence from the 2008 presidential primaries,"
International Journal of Forecasting, Elsevier, vol. 34(4), pages 696-710.
- Urmee Khan & Robert Lieli, 2016. "Information Flow Between Prediction Markets, Polls and Media: Evidence from the 2008 Presidential Primaries," Working Papers 201610, University of California at Riverside, Department of Economics.
- Urmee Khan & Robert Lieli, 2017. "Information Flow Between Prediction Markets, Polls and Media: Evidence from the 2008 Presidential Primaries," Working Papers 201711, University of California at Riverside, Department of Economics.
- repec:osf:osfxxx:2m9fy_v1 is not listed on IDEAS
- Stiers, Dieter & Dassonneville, Ruth, 2018. "Affect versus cognition: Wishful thinking on election day," International Journal of Forecasting, Elsevier, vol. 34(2), pages 199-215.
- Meffert, Michael F. & Gschwend, Thomas, 2007.
"Voting for coalitions? : The role of coalition preferences and expectations in voting behavior,"
Papers
07-64, Sonderforschungsbreich 504.
- Meffert, Michael F. & Gschwend, Thomas, 2007. "Voting for Coalitions? The Role of Coalition Preferences and Expectations in Voting Behavior," Sonderforschungsbereich 504 Publications 07-64, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
- Jonathan B Slapin, 2014. "Measurement, model testing, and legislative influence in the European Union," European Union Politics, , vol. 15(1), pages 24-42, March.
- Hager, Anselm & Hensel, Lukas & Hermle, Johannes & Roth, Christopher, 2020.
"Does Party Competition Affect Political Activism?,"
CAGE Online Working Paper Series
488, Competitive Advantage in the Global Economy (CAGE).
- Anselm Hager & Johannes Hermle & Lukas Hensel & Christopher Roth, 2020. "Does Party Competition Affect Political Activism?," CESifo Working Paper Series 8431, CESifo.
- Hager, Anselm & Hensel, Lukas & Hermle, Johannes & Roth, Christopher, 2020. "Does Party Competition Affect Political Activism?," The Warwick Economics Research Paper Series (TWERPS) 1278, University of Warwick, Department of Economics.
- Rodolphe Desbordes & Gary Koop, 2014.
"The Known Unknowns of Governance,"
Working Paper series
38_14, Rimini Centre for Economic Analysis.
- Rodolphe Desbordes & Gary Koop, 2014. "The known unknowns of governance," Working Papers 1407, University of Strathclyde Business School, Department of Economics.
- Ton de Waal & Arnout van Delden & Sander Scholtus, 2020. "Multi‐source Statistics: Basic Situations and Methods," International Statistical Review, International Statistical Institute, vol. 88(1), pages 203-228, April.
- Joscha Legewie, 2018. "Living on the Edge: Neighborhood Boundaries and the Spatial Dynamics of Violent Crime," Demography, Springer;Population Association of America (PAA), vol. 55(5), pages 1957-1977, October.
- Kuwayama, Yusuke & Olmstead, Sheila & Zheng, Jiameng, 2022. "A more comprehensive estimate of the value of water quality," Journal of Public Economics, Elsevier, vol. 207(C).
- Johannes Bettin & Meike Wollni, 2020. "Environmental Concern and Urbanization in India: Towards Psychological Complexity," Sustainability, MDPI, vol. 12(24), pages 1-25, December.
- Folgert Karsdorp & Lauren Fonteyn, 2019. "Cultural entrenchment of folktales is encoded in language," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-12, December.
- Leiter, Debra & Murr, Andreas & Rascón Ramírez, Ericka & Stegmaier, Mary, 2018. "Social networks and citizen election forecasting: The more friends the better," International Journal of Forecasting, Elsevier, vol. 34(2), pages 235-248.
- Lennart Sjöberg, 2009. "Are all crowds equally wise? a comparison of political election forecasts by experts and the public," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 1-18.
- Franch, Fabio, 2021. "Political preferences nowcasting with factor analysis and internet data: The 2012 and 2016 US presidential elections," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
- Raghul Gandhi Venkatesan & Bagavandas Mappillairaju, 2024. "Early student dropout detection in Indian secondary education with special reference to selected districts in Tamil Nadu: a machine learning-based survival analysis approach," Journal of Computational Social Science, Springer, vol. 7(3), pages 2309-2331, December.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:53:y:2019:i:3:d:10.1007_s11135-018-0819-1. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.