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Luck of the Draw? Private Members’ Bills and the Electoral Connection*

Published online by Cambridge University Press:  09 May 2017

Brian D. Williams  and
Indridi H. Indridason Open the ORCID record for Indridi H. Indridason [Opens in a new window]
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Abstract

The legislative agenda in most parliamentary systems is controlled tightly by the government and bills offered by individual members of parliament have low rates of success. Yet, members of parliament (MPs) do seek to present (private) members’ bills even where the rate of adoption is very low. We argue that members’ bills serve as an electoral connection but also as an opportunity for MPs to signal competence to their co-partisans. To demonstrate the presence of an electoral connection we take advantage of the random selection of private members’ bills in the New Zealand House of Representatives and show that survey respondents approve more of electorate MPs whose bills were drawn on the ballot. In addition, we show that MPs respond to the incentives created by the voters and parties’ willingness to reward legislative effort and, consequently, that electorally vulnerable legislators are more likely to place members’ bills on the ballot.

Type
Original Articles
Information
Political Science Research and Methods , Volume 6 , Issue 2 , April 2018 , pp. 211 - 227
Copyright
© The European Political Science Association 2017 

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Footnotes

*

Brian D. Williams, Postdoctoral Research Associate, Department of Government, University of West Florida, 11000 University Parkway, Pensacola, FL 32514 (bwilliams1@uwf.edu). Indridi H. Indridason, Associate Professor, Department of Political Science, University of California, Riverside, 900 University Avenue, Riverside, CA 92521 (indridi.indridason@ucr.edu). The authors would like to thank Hannah Blumhardt for capable research assistance and Shaun Bowler, Jack Vowles, and the anonymous referees for useful comments and suggestions. To view supplementary material for this article, please visit https://doi.org/ 10.1017/psrm.2017.13

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Williams and Indridason Dataset

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http://dx.doi.org/10.7910/DVN/EYVIDZ
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