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Marie Rekkas

Personal Details

First Name:Marie
Middle Name:
Last Name:Rekkas
Suffix:
RePEc Short-ID:pre255
[This author has chosen not to make the email address public]
http://www.sfu.ca/~mrekkas

Affiliation

Department of Economics
Simon Fraser University

Burnaby, Canada
https://www.sfu.ca/economics/
RePEc:edi:desfuca (more details at EDIRC)

Research output

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Jump to: Articles

Articles

  1. Rekkas, M., 2009. "Approximate inference for the multinomial logit model," Statistics & Probability Letters, Elsevier, vol. 79(2), pages 237-242, January.
  2. Rekkas, M. & Wong, A., 2008. "Implementing likelihood-based inference for fat-tailed distributions," Finance Research Letters, Elsevier, vol. 5(1), pages 32-46, March.
  3. M. Rekkas & Y. Sun & A. Wong, 2008. "Improved inference for first‐order autocorrelation using likelihood analysis," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(3), pages 513-532, May.
  4. Kevin Milligan & Marie Rekkas, 2008. "Campaign spending limits, incumbent spending, and election outcomes," Canadian Journal of Economics, Canadian Economics Association, vol. 41(4), pages 1351-1374, November.
  5. Marie Rekkas, 2007. "The Impact of Campaign Spending on Votes in Multiparty Elections," The Review of Economics and Statistics, MIT Press, vol. 89(3), pages 573-585, August.
  6. Fraser, D.A.S. & Rekkas, M. & Wong, A., 2005. "Highly accurate likelihood analysis for the seemingly unrelated regression problem," Journal of Econometrics, Elsevier, vol. 127(1), pages 17-33, July.
  7. Rekkas, M. & Wong, A., 2005. "Third-order inference for the Weibull distribution," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 499-525, April.

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.

Articles

  1. Rekkas, M. & Wong, A., 2008. "Implementing likelihood-based inference for fat-tailed distributions," Finance Research Letters, Elsevier, vol. 5(1), pages 32-46, March.

    Cited by:

    1. PREMINGER Arie & STORTI Giuseppe, 2017. "Least squares estimation for GARCH (1,1) model with heavy tailed errors," LIDAM Discussion Papers CORE 2017015, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  2. Kevin Milligan & Marie Rekkas, 2008. "Campaign spending limits, incumbent spending, and election outcomes," Canadian Journal of Economics, Canadian Economics Association, vol. 41(4), pages 1351-1374, November.

    Cited by:

    1. Abel François & Michael Visser & Lionel Wilner, 2022. "The petit effect of campaign spending on votes: using political financing reforms to measure spending impacts in multiparty elections," Post-Print hal-03701530, HAL.
    2. Eric Avis & Claudio Ferraz & Frederico Finan & Carlos Varjão, "undated". "Money and Politics: The Effects of Campaign Spending Limits on Political Competition and Incumbency Advantage," Textos para discussão 656, Department of Economics PUC-Rio (Brazil).
    3. Bombardini, Matilde & Trebbi, Francesco, 2011. "Votes or money? Theory and evidence from the US Congress," Journal of Public Economics, Elsevier, vol. 95(7), pages 587-611.
    4. William Pyle & Laura Solanko, 2013. "The composition and interests of Russia’s business lobbies: testing Olson’s hypothesis of the “encompassing organization”," Public Choice, Springer, vol. 155(1), pages 19-41, April.
    5. Pastine, Ivan & Pastine, Tuvana, 2012. "Incumbency advantage and political campaign spending limits," Journal of Public Economics, Elsevier, vol. 96(1), pages 20-32.
    6. Jan Brueckner & Kangoh Lee, 2015. "Negative campaigning in a probabilistic voting model," Public Choice, Springer, vol. 164(3), pages 379-399, September.
    7. Ivan Pastine & Tuvana Pastine, 2010. "Political Campaign Spending Limits," Economics Department Working Paper Series n213-10.pdf, Department of Economics, National University of Ireland - Maynooth.
    8. Abel François & Michael Visser & Lionel WILNER, 2016. "Campaign spending and legislative election outcomes: Exploiting the French political financing reforms of the mid-1990s," Working Papers 2016-28, Center for Research in Economics and Statistics.
    9. Martin Grossmann & Helmut Dietl, 2012. "Asymmetric contests with liquidity constraints," Public Choice, Springer, vol. 150(3), pages 691-713, March.
    10. Brandon Schaufele, 2013. "Dissent in Parliament as Reputation Building," Working Papers 1301E, University of Ottawa, Department of Economics.
    11. Tuvana Pastine & Ivan Pastine & Matthew T. Cole, 2013. "Incumbency Advantage in an Electoral Contest," Economics Department Working Paper Series n242-13.pdf, Department of Economics, National University of Ireland - Maynooth.
    12. Perez-Vincent, Santiago M., 2023. "A few signatures matter: Barriers to entry in Italian local politics," European Journal of Political Economy, Elsevier, vol. 78(C).
    13. Wang, Ao, 2021. "A BLP Demand Model of Product-Level Market Shares with Complementarity," The Warwick Economics Research Paper Series (TWERPS) 1351, University of Warwick, Department of Economics.
    14. Chad Kendall & Marie Rekkas, 2012. "Incumbency advantages in the Canadian Parliament," Canadian Journal of Economics, Canadian Economics Association, vol. 45(4), pages 1560-1585, November.

  3. Marie Rekkas, 2007. "The Impact of Campaign Spending on Votes in Multiparty Elections," The Review of Economics and Statistics, MIT Press, vol. 89(3), pages 573-585, August.

    Cited by:

    1. Nathan Canen & Kristopher Ramsay, 2023. "Quantifying Theory in Politics: Identification, Interpretation and the Role of Structural Methods," Papers 2302.01897, arXiv.org.
    2. Abel François & Michael Visser & Lionel Wilner, 2022. "The petit effect of campaign spending on votes: using political financing reforms to measure spending impacts in multiparty elections," Post-Print hal-03701530, HAL.
    3. Gordon, Brett R. & Hartmann, Wesley R., 2011. "Advertising Effects in Presidential Elections," Research Papers 2080, Stanford University, Graduate School of Business.
    4. Matias Iaryczower & Andrea Mattozzi, 2012. "The pro-competitive effect of campaign limits in non-majoritarian elections," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 49(3), pages 591-619, April.
    5. Bernardo S. Da Silveira & João M. P. De Mello, 2011. "Campaign Advertising and Election Outcomes: Quasi-natural Experiment Evidence from Gubernatorial Elections in Brazil," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(2), pages 590-612.
    6. Yasmine Bekkouche & Julia Cage & Edgard Dewitte, 2022. "The Heterogeneous Price of a Vote: Evidence from Multiparty Systems, 1993-2017," PSE-Ecole d'économie de Paris (Postprint) hal-03389172, HAL.
    7. Bruno Carvalho, 2021. "Campaign Spending in Local Elections: the Effects of Public Funding," Working Papers ECARES 2021-30, ULB -- Universite Libre de Bruxelles.
    8. Kevin Milligan & Marie Rekkas, 2008. "Campaign spending limits, incumbent spending, and election outcomes," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(4), pages 1351-1374, November.
    9. Arianna Degan, 2013. "Civic duty and political advertising," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(2), pages 531-564, March.
    10. Abel François & Michael Visser & Lionel WILNER, 2016. "Campaign spending and legislative election outcomes: Exploiting the French political financing reforms of the mid-1990s," Working Papers 2016-28, Center for Research in Economics and Statistics.
    11. I Gede Sthitaprajna Virananda & Teguh Dartanto & Bintang Dara Wijaya, 2021. "Does Money Matter for Electability? Lesson Learned From the 2014 Legislative Election in Indonesia," SAGE Open, , vol. 11(4), pages 21582440211, October.
    12. Kräkel, Matthias & Nieken, Petra & Przemeck, Judith, 2008. "Risk Taking in Winner-Take-All Competition," Bonn Econ Discussion Papers 7/2008, University of Bonn, Bonn Graduate School of Economics (BGSE).
    13. Yasmine Bekkouche & Julia Cage, 2019. "The Heterogeneous Price of a Vote: Evidence from France, 1993-2014," SciencePo Working papers Main hal-03393084, HAL.
    14. John Maloney & Andrew Pickering, 2013. "Political Competition, Political Donations, Economic Policy and Growth," Discussion Papers 13/21, Department of Economics, University of York.
    15. Cagé, Julia & Bekkouche, Yasmine, 2018. "The Heterogeneous Price of a Vote: Evidence from France, 1993-2014," CEPR Discussion Papers 12614, C.E.P.R. Discussion Papers.
    16. Wang, Ao, 2021. "A BLP Demand Model of Product-Level Market Shares with Complementarity," The Warwick Economics Research Paper Series (TWERPS) 1351, University of Warwick, Department of Economics.
    17. Tang, Meng-Chi & Huang, Ya-Wei, 2022. "The effect of endogenous campaign spending and voter heterogeneity on candidates' vote share: Empirical evidence from Taiwanese local elections," Economic Modelling, Elsevier, vol. 114(C).
    18. John Maloney & Andrew Pickering, 2018. "The Economic Consequences of Political Donation Limits," Economica, London School of Economics and Political Science, vol. 85(339), pages 479-517, July.
    19. Yasmine Bekkouche & Julia Cage & Edgard Dewitte, 2022. "The Heterogeneous Price of a Vote: Evidence from Multiparty Systems, 1993-2017," SciencePo Working papers Main hal-03389172, HAL.

  4. Fraser, D.A.S. & Rekkas, M. & Wong, A., 2005. "Highly accurate likelihood analysis for the seemingly unrelated regression problem," Journal of Econometrics, Elsevier, vol. 127(1), pages 17-33, July.

    Cited by:

    1. Wang, Min & Sun, Xiaoqian, 2012. "Bayesian inference for the correlation coefficient in two seemingly unrelated regressions," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2442-2453.
    2. Laurent GOMEZ, 2024. "La mobilité quotidienne des immigrés en France," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 59, pages 79-107.
    3. Zellner, Arnold & Ando, Tomohiro, 2010. "A direct Monte Carlo approach for Bayesian analysis of the seemingly unrelated regression model," Journal of Econometrics, Elsevier, vol. 159(1), pages 33-45, November.
    4. Tiong, Kah Yong & Ma, Zhenliang & Palmqvist, Carl-William, 2023. "Analyzing factors contributing to real-time train arrival delays using seemingly unrelated regression models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    5. Chwu-Shiun Tarng, 2014. "Third-order likelihood-based inference for the log-normal regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(9), pages 1976-1988, September.
    6. Meuer, Johannes & Rupietta, Christian & Backes-Gellner, Uschi, 2015. "Layers of co-existing innovation systems," Research Policy, Elsevier, vol. 44(4), pages 888-910.
    7. Zellner, Arnold & Ando, Tomohiro, 2010. "Bayesian and non-Bayesian analysis of the seemingly unrelated regression model with Student-t errors, and its application for forecasting," International Journal of Forecasting, Elsevier, vol. 26(2), pages 413-434, April.
    8. Zhao, Li & Xu, Xingzhong, 2017. "Generalized canonical correlation variables improved estimation in high dimensional seemingly unrelated regression models," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 119-126.

  5. Rekkas, M. & Wong, A., 2005. "Third-order inference for the Weibull distribution," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 499-525, April.

    Cited by:

    1. Chwu-Shiun Tarng, 2014. "Third-order likelihood-based inference for the log-normal regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(9), pages 1976-1988, September.

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