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Measuring the Median: The Risks of Inferring Beliefs from Votes

Published online by Cambridge University Press:  18 July 2012

Abstract

A large number of studies of ideological congruence, and of the effect of public opinion on policy outcomes more generally, have relied on the Kim-Fording (KF) measure of median voter opinion. This measure has the great virtue of being readily calculable – no direct measurement of voter opinion is required – but it rests on assumptions concerning party locations and voter behaviour that are unquestionably incorrect, at least some of the time. This article explores the sensitivity of the KF measure to violations of its core assumptions through simulation experiments. It then uses public opinion data to assess the degree to which consequential levels of violation occur in actual democratic systems. The article concludes with a discussion of what the KF median really measures and where it can – and cannot – be safely used.

Type
Articles
Copyright
Copyright © Cambridge University Press 2012

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Footnotes

*

Department of Political Science, Simon Fraser University (email: [email protected]). An online appendix is available at http://dx.doi.org/10.1017/S0007123412000269.

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21 The sole limitation imposed on party positions is that they cannot all be located on one side of the median voter's position.

22 Some of the interactions used in our analyses are dominated by one of their components, which undermines the interaction's capacity to play its intended role and creates excessive collinearity in the models. To deal with this problem, we standardized each variable before forming products.

23 Interestingly, even at very high levels of dimensional correlation (r is never exactly 1 in these simulations but becomes very close), the lines never converge.

24 The exception is Chile 2005, where 62 per cent of respondents placed themselves, improbably, at ‘1’ on the scale.

25 Warwick, Paul V., ‘Bilateralism or the Median Mandate? An Examination of Rival Perspectives on Democratic Governance’, European Journal of Political Research, 49 (2010), 124 Google Scholar

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27 If voters collectively misperceive party locations and act accordingly, the inaccuracy in the KF measure will tend to resemble that produced by random error. If positions derived from other sources are used, which do not agree with the voters’ collective estimates, an additional source of possible inaccuracy is introduced.

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30 The simulated data bear this out. In the data set in which vote choice is determined solely by left-right proximity, allocating each voter to the nearest 0.1 on the 0-1 scale (which is roughly equivalent) and applying this method produces an absolute mean error of 0.0008 (SD = 0.0006) across 10,000 simulated elections. This is one-third less than the KF error (mean = 0.0012, SD = 0.0018). Both levels of error are, of course, very small. The difference is that the KF median will become more deviant as valence and other facfactors come to play a role, whereas this median will not.

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32 For example, Pontusson and David Rueda, ‘The Politics of Inequality’; Adams and Somer-Topcu, ‘Moderate Now, Win Votes Later’ and Adams and Somer-Topcu, ‘Policy Adjustment by Parties in Response to Rival Parties?’.

33 Following standard practice, the government positions are estimated from the seat-weighted mean positions of their member parties.

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37 Kang and Powell, ‘Representation and Policy Responsiveness’, p. 1016Google Scholar

38 Kang and Powell, ‘Representation and Policy Responsiveness’, p. 1016Google Scholar

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