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Seniority-Based Nominations and Political Careers

Published online by Cambridge University Press:  14 September 2020

ALEXANDRA CIRONE*
Affiliation:
Cornell University
GARY W. COX*
Affiliation:
Stanford University
JON H. FIVA*
Affiliation:
BI Norwegian Business School
*
Alexandra Cirone, Assistant Professor, Department of Government, Cornell University, aec287@cornell.edu.
Gary W. Cox, William Bennett Munro Professor of Political Science, Department of Political Science, Stanford University, gwcox@stanford.edu.
Jon H. Fiva, Professor of Economics, Department of Economics, BI Norwegian Business School, jon.h.fiva@bi.no.
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Abstract

This paper investigates party use of seniority systems to allocate nominations for elected and appointed offices. Such systems, which can regulate party members’ access to offices at multiple levels of their careers, are defined by two main rules or norms: an incumbent re-nomination norm and a seniority progression norm. Using comprehensive electoral and candidate data from Norwegian local and national elections from 1945 to 2019, we find systematic patterns consistent with these two norms. Our work illuminates an institutional aspect of candidate selection that the current literature has ignored while noting some of the important consequences of seniority-based nominations for party cohesion and stability.

Information

Type
Research Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the American Political Science Association
Figure 0

Figure 1. Fraction of Candidates with Political Experience from Local and Regional Office before Entering Parliament for the First Time

Note: Sample is restricted to candidates winning a seat in parliament for the first time during the 1945–2009 period (N = 1,077). Appendix Table A.1 gives the number of observations by election year. Direct elections for the regional office are first held in 1975.
Figure 1

Figure 2. Kernel Density Plots Describing Cabinet Member’s Political Career

Note: Sample is restricted to candidates being promoted to the cabinet for the first time during the 1980–2009 period (N = 136). We base the kernel density plots on individuals that, respectively, are ever elected to a feeder office (N = 104), are ever running for national office (N = 120), and are ever winning a seat in parliament (N = 101).
Figure 2

Figure 3. Illustration of the Norwegian Nomination Hierarchy

Note: The figure illustrates the Norwegian nomination hierarchy, emphasizing steps relevant to our empirical application. Numbers in parentheses reflect the number of candidates/seats/positions/spots available in the 2015 local government election or 2017 national election. The number of cabinet positions varies within each administration; to be consistent with our sample, here we use the size of the cabinet for 2015.
Figure 3

Figure 4. Candidate Background (Top-Panel) and Local Election Outcomes (Bottom Panel)

Note: The sample is limited to candidates in the top ten positions for the main party lists running during the 2007–2011 period. We exclude candidates running for lists that fail to win any seat in the current election (N = 40,549). We exclude the 2003 election, due to missing information about candidate background characteristics. Candidates’ background characteristics are measured in the election year. Candidates with more than upper secondary education are classified as highly educated. Income is measured in constant (2015) NOK 1,000 in the election year and is truncated at NOK 5,000,000.
Figure 4

Figure 5. Analysis of RQ1: Seniority Progression at the Local Level

Note: The top panels display standard RD plots using a bandwidth of 10 percentage points. Separate linear lines are estimated below and above the discontinuity using the underlying data, not the binned scatter points. The solid vertical line represents a zero win margin, indicating the transition from barely missing out on a seat to barely winning. Each dot represents a binned average for 1 percentage point intervals. The baseline sample consists of all candidates running for municipal office for the main parties during the 2003–2011 period (N = 160,546). We exclude candidates running for lists that do not win any seats (4,000 observations), candidates where we lack information about personal votes (11,000 observations), and cases with ties between two candidates (which are broken by the initial ranking on the list) (700 observations). The final sample is restricted to candidates that are next in line to win a seat or first in line to lose a seat, and the vote margin is less than 10 percentage points (N = 8,136). The bottom panels display the RD estimates and 95% confidence intervals as a function of the bandwidth chosen. The black triangles correspond to the point estimate from the optimal bandwidth chosen by the Calonico, Cattaneo, and Titiunik (2014) algorithm, as obtained by the rdrobust module in Stata.
Figure 5

Figure 6. Analysis of RQ2: Seniority Progression from Mayor to National Politics

Note: The top-row displays averages of Run, Win, and Days for lists with and without the mayor by list rank of the candidate. The second row provides estimates of λ1,…,λ10 based on Equation 4. The sample is restricted to candidates ranked in position 1 − 10 for one of the seven main parties during the 2003–2011 period (N = 61,689). We exclude candidates that previously ran for national office, municipalities with directly elected mayors, and lists where the elected mayor is not in the top-ranked position. Standard errors are clustered at the party-parliamentary district-year level (398 clusters).
Figure 6

Figure 7. Analysis of RQ3: Incumbent Re-Nomination and Re-Election

Note: The full sample covers national election candidates running for one of the seven main parties during the 1953–2013 period. We define a winnable spot as a position on the ballot that would secure a seat in parliament if the election outcome was as in the previous election. We limit the RD analysis to candidates that are less than 5 percentage points away from the seat threshold in the current election, that never previously won a seat in parliament or were close to doing so (i.e., within the five percentage window), and are without any experience from cabinet (N = 985). Separate linear regression lines are estimated to the left and right of the discontinuity using the underlying data, not the binned scatter points. The bottom panels show how the RD estimate varies as a function of the bandwidth chosen. The black triangles correspond to the point estimate from the optimal bandwidth chosen by the Calonico, Cattaneo, and Titiunik (2014) algorithm, as obtained by the rdrobust module in Stata.
Figure 7

Figure 8. Analysis of RQ4: Seats in Parliament and Higher Offices

Note: See Figure 7.
Figure 8

Table 1. Intra-Party Competition over Nomination

Figure 9

Figure 9. National-Level Re-Nomination, Overall and in Winnable Spots, by Four Categories

Note: This figure displays the fraction re-nominated (left-hand panel), the fraction re-nominated in a winnable spot (center panel), and the fraction elected (right-hand panel), with corresponding 95% confidence intervals, by four categories: deputies that did not replace an MP that died in office (N = 6,542), elected candidates (N = 933), deputies that replace MPs that die early in their election period (below the median; N = 16), and deputies that replace MPs that die late in their election period (above the median; N = 16). We exclude five deputies promoted less than six months before the next election because they are promoted after the lists for the next election must be ready. The sample is limited to candidates that never previously won a seat in parliament.
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