IDEAS home Printed from https://ideas.repec.org/p/edj/ceauch/294.html
   My bibliography  Save this paper

A Spatial Model of Voting with Endogenous Proposals: Theory and Evidence from Chilean Senate

Author

Listed:
  • Matteo Triossi
  • Patricio Valdivieso
  • Benjamín Villena-Roldán

Abstract

Proposers strategically formulate legislative bills before voting takes place. However, spatial voting models that estimate legislator’s ideological preferences do not explicitly consider this fact. In our model, proposers determine the ideology and valence of legislative bills to maximize their objective functions. Approaching to the median legislator ideology and increasing costly valence increases the passing probability, but usually decreases the proposer’s payoff. Using quantile utility proposer preferences, the model becomes tractable and estimable. In this way, we deal with the bill sample selection problem to estimate legislator’s preferences and also, the ideology of proposers, the proposed valence change, and the ideological stance of the statu quo in a common scale. Using Chilean Senate 2009 - 2011 roll call data, our results suggests that (1) political party affiliation significantly affects Senators’ ideology, (2) popular, young and male Senators are more extremist, and (3) proposers during Bachelet and Piñera’s terms have similar ideologies. Key words:

Suggested Citation

  • Matteo Triossi & Patricio Valdivieso & Benjamín Villena-Roldán, 2013. "A Spatial Model of Voting with Endogenous Proposals: Theory and Evidence from Chilean Senate," Documentos de Trabajo 294, Centro de Economía Aplicada, Universidad de Chile.
  • Handle: RePEc:edj:ceauch:294
    as

    Download full text from publisher

    File URL: http://www.cea-uchile.cl/wp-content/uploads/doctrab/ASOCFILE120130516085941.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Manski, Charles F., 1986. "Ordinal Utility Models Of Decision Making Under Uncertainty," SSRI Workshop Series 292682, University of Wisconsin-Madison, Social Systems Research Institute.
    2. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    3. Clinton, Joshua D. & Meirowitz, Adam, 2001. "Agenda Constrained Legislator Ideal Points and the Spatial Voting Model," Political Analysis, Cambridge University Press, vol. 9(3), pages 242-259, January.
    4. Peress, Michael, 2009. "Small Chamber Ideal Point Estimation," Political Analysis, Cambridge University Press, vol. 17(3), pages 276-290, July.
    5. Gilligan, Thomas W & Krehbiel, Keith, 1987. "Collective Decisionmaking and Standing Committees: An Informational Rationale for Restrictive Amendment Procedures," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 3(2), pages 287-335, Fall.
    6. Marzena Rostek, 2010. "Quantile Maximization in Decision Theory ," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(1), pages 339-371.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Castro, Luciano de & Galvao, Antonio F. & Kim, Jeong Yeol & Montes-Rojas, Gabriel & Olmo, Jose, 2022. "Experiments on portfolio selection: A comparison between quantile preferences and expected utility decision models," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    2. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    3. de Castro, Luciano I. & Galvao, Antonio F. & Nunes, Daniel da Siva, 0. "Dynamic economics with quantile preferences," Theoretical Economics, Econometric Society.
    4. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2022. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 672-686.
    5. Charles F. Manski & Aleksey Tetenov, 2014. "The Quantile Performance of Statistical Treatment Rules Using Hypothesis Tests to Allocate a Population to Two Treatments," CeMMAP working papers CWP44/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
    7. Jarrod Burgh & Emerson Melo, 2024. "Censored Beliefs and Wishful Thinking," Papers 2402.01892, arXiv.org.
    8. de Castro, Luciano & Galvao, Antonio F. & Noussair, Charles N. & Qiao, Liang, 2022. "Do people maximize quantiles?," Games and Economic Behavior, Elsevier, vol. 132(C), pages 22-40.
    9. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.
    10. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    11. Luciano Castro & Antonio F. Galvao, 2022. "Static and dynamic quantile preferences," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(2), pages 747-779, April.
    12. Bruno C. Giovannetti, 2013. "Asset pricing under quantile utility maximization," Review of Financial Economics, John Wiley & Sons, vol. 22(4), pages 169-179, November.
    13. Chen, Si & Schildberg-Hörisch, Hannah, 2018. "Looking at the bright side: The motivation value of overconfidence," DICE Discussion Papers 291, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    14. Jozef Baruník & Matěj Nevrla, 2023. "Quantile Spectral Beta: A Tale of Tail Risks, Investment Horizons, and Asset Prices," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1590-1646.
    15. Xue Dong He & Zhaoli Jiang & Steven Kou, 2020. "Portfolio Selection under Median and Quantile Maximization," Papers 2008.10257, arXiv.org, revised Mar 2021.
    16. Christopher P. Chambers & Alan D. Miller, 2023. "Multiple Adjusted Quantiles," Papers 2305.06354, arXiv.org.
    17. Balter, Anne G. & Chau, Ki Wai & Schweizer, Nikolaus, 2024. "Comparative risk aversion vs. threshold choice in the Omega ratio," Omega, Elsevier, vol. 123(C).
    18. Salvatore Corrente & Salvatore Greco & Benedetto Matarazzo & Roman Słowiński, 2016. "Robust ordinal regression for decision under risk and uncertainty," Journal of Business Economics, Springer, vol. 86(1), pages 55-83, January.
    19. Luciano de Castro & Antonio F. Galvao & Gabriel Montes-Rojas & Jose Olmo, 2022. "Portfolio selection in quantile decision models," Annals of Finance, Springer, vol. 18(2), pages 133-181, June.
    20. Mikhail Sokolov, 2011. "Interval scalability of rank-dependent utility," Theory and Decision, Springer, vol. 70(3), pages 255-282, March.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:edj:ceauch:294. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/ceuclcl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.