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Parliamentary Questions and the Probability of Reelection in the UK House of Commons

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  • Tucker, Luc

Abstract

Members of worldwide parliaments partake in debates, where they have the opportunity to hold governments to account by asking pre-submitted questions. The UK House of Commons uses a ballot system to determine which members are selected to ask a question from those who expressed an interest in doing so. This paper is the first in the literature to exploit this randomization to show that the asking of such questions increases a member’s chances of being reelected by their constituents. It is shown that while the ordering of parliamentary questions is determined at random, the practicalities of conducting debates introduce a potentially endogenous element to the determination of which questions receive oral answers (particularly the speed at which questions are answered). This paper uses a matched sampling approach to cope with such non-random cases, but also includes alternative results, to show that the findings are not reliant on the use of this technique.

Suggested Citation

  • Tucker, Luc, 2013. "Parliamentary Questions and the Probability of Reelection in the UK House of Commons," Economic Research Papers 270436, University of Warwick - Department of Economics.
    • Handle: RePEc:ags:uwarer:270436
    DOI: 10.22004/ag.econ.270436
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    References listed on IDEAS

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    1. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    2. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    3. Angrist, Joshua D & Lavy, Victor, 2001. "Does Teacher Training Affect Pupil Learning? Evidence from Matched Comparisons in Jerusalem Public Schools," Journal of Labor Economics, University of Chicago Press, vol. 19(2), pages 343-369, April.
    4. Shane Martin, 2011. "Using Parliamentary Questions to Measure Constituency Focus: An Application to the Irish Case," Political Studies, Political Studies Association, vol. 59(2), pages 472-488, June.
    5. Sanders, David & Clarke, Harold D. & Stewart, Marianne C. & Whiteley, Paul, 2007. "Does Mode Matter For Modeling Political Choice? Evidence From the 2005 British Election Study," Political Analysis, Cambridge University Press, vol. 15(3), pages 257-285, July.
    6. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    7. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(3), pages 199-236, July.
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