Information Flow Between Prediction Markets, Polls and Media: Evidence from the 2008 Presidential Primaries
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- 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.
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- Jacobsen, Ben & Potters, Jan & Schram, Arthur & van Winden, Frans & Wit, Jorgen, 2000.
"(In)accuracy of a European political stock market: The influence of common value structures,"
European Economic Review, Elsevier, vol. 44(2), pages 205-230, February.
- Potters, J.J.M. & Jacobsen, B. & Schram, A. & van Winden, F.A.A.M. & Wit, J., 2000. "(In)accuracy of a European political stockmarket : The influence of common value structures," Other publications TiSEM 871eef99-1e85-4985-9e94-e, Tilburg University, School of Economics and Management.
- Steger, Wayne P., 2008. "Forecasting the presidential primary vote: Viability, ideology and momentum," International Journal of Forecasting, Elsevier, vol. 24(2), pages 193-208.
- Berg, Joyce & Forsythe, Robert & Nelson, Forrest & Rietz, Thomas, 2008. "Results from a Dozen Years of Election Futures Markets Research," Handbook of Experimental Economics Results, in: Charles R. Plott & Vernon L. Smith (ed.), Handbook of Experimental Economics Results, edition 1, volume 1, chapter 80, pages 742-751, Elsevier.
- Andrew Leigh & Justin Wolfers, 2006.
"Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets,"
The Economic Record, The Economic Society of Australia, vol. 82(258), pages 325-340, September.
- Andrew Leigh & Justin Wolfers, 2005. "Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets," CEPR Discussion Papers 502, Centre for Economic Policy Research, Research School of Economics, Australian National University.
- Andrew Leigh & Justin Wolfers, 2006. "Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets," NBER Working Papers 12053, National Bureau of Economic Research, Inc.
- Wolfers, Justin & ,, 2006. "Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets," CEPR Discussion Papers 5555, C.E.P.R. Discussion Papers.
- Leigh, Andrew & Wolfers, Justin, 2006. "Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets," IZA Discussion Papers 1972, Institute of Labor Economics (IZA).
- Jonathan B. Hill, 2007.
"Efficient tests of long-run causation in trivariate VAR processes with a rolling window study of the money-income relationship,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 747-765.
- Jonathan B. Hill, 2004. "Efficient Tests of Long-Run Causation in Trivariate VAR Processes with a Rolling Window Study of the Money-Income Relationship," Macroeconomics 0407013, University Library of Munich, Germany, revised 15 Feb 2006.
- 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.
- Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
- Kou, S. G. & Sobel, Michael E., 2004. "Forecasting the Vote: A Theoretical Comparison of Election Markets and Public Opinion Polls," Political Analysis, Cambridge University Press, vol. 12(3), pages 277-295, July.
- Jean-Marie Dufour & Eric Renault, 1998.
"Short Run and Long Run Causality in Time Series: Theory,"
Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
- Dufour, J.M. & Renault, E., 1995. "Short-Run and Long-Rub Causality in Time Series: Theory," Cahiers de recherche 9538, Universite de Montreal, Departement de sciences economiques.
- Dufour, J.M. & Renault, E., 1995. "Short-Run and Long-Rub Causality in Time Series: Theory," Cahiers de recherche 9538, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Christian Franz Horn & Bjoern Sven Ivens & Michael Ohneberg & Alexander Brem, 2014. "Ideas Markets: Prediction Markets – A literature review 2014," Journal of Prediction Markets, University of Buckingham Press, vol. 8(2), pages 89-126.
- Justin Wolfers & Eric Zitzewitz, 2004.
"Prediction Markets,"
Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
- Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," NBER Working Papers 10504, National Bureau of Economic Research, Inc.
- Wolfers, Justin & Zitzewitz, Eric, 2004. "Prediction Markets," Research Papers 1854, Stanford University, Graduate School of Business.
- Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Discussion Papers 03-025, Stanford Institute for Economic Policy Research.
- Murr, Andreas E., 2015. "The wisdom of crowds: Applying Condorcet’s jury theorem to forecasting US presidential elections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 916-929.
- Taamouti, Abderrahim & Bouezmarni, Taoufik & El Ghouch, Anouar, 2014.
"Nonparametric estimation and inference for conditional density based Granger causality measures,"
Journal of Econometrics, Elsevier, vol. 180(2), pages 251-264.
- Taamouti, Abderrahim & Bouezmarni, Taoufik & El Ghouch, Anouar, 2014. "Nonparametric estimation and inference for conditional density based Granger causality measures," LIDAM Reprints ISBA 2014025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Gelman, Andrew & King, Gary, 1993. "Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable?," British Journal of Political Science, Cambridge University Press, vol. 23(4), pages 409-451, October.
- Lewis-Beck, Michael S. & Tien, Charles, 1999. "Voters as forecasters: a micromodel of election prediction," International Journal of Forecasting, Elsevier, vol. 15(2), pages 175-184, April.
- Rothschild, David, 2015. "Combining forecasts for elections: Accurate, relevant, and timely," International Journal of Forecasting, Elsevier, vol. 31(3), pages 952-964.
- Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
- Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
- Geweke, John & Meese, Richard & Dent, Warren, 1983. "Comparing alternative tests of causality in temporal systems : Analytic results and experimental evidence," Journal of Econometrics, Elsevier, vol. 21(2), pages 161-194, February.
- Joyce E. Berg & Thomas A. Rietz, 2003. "Prediction Markets as Decision Support Systems," Information Systems Frontiers, Springer, vol. 5(1), pages 79-93, January.
- 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.
- Georgios Tziralis & Ilias Tatsiopoulos, 2007. "Prediction Markets: An Extended Literature Review," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 75-91, February.
- Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
- Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
- Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
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