The Meaningful Votes: Voting on Brexit in the British House of Commons

Abstract

Why do politicians rebel and vote against the party line when high stakes bills come to the floor of the legislature? To address that question, we leverage the three so-called Meaningful Votes that took place in the British House of Commons between January and March 2019 on the Withdrawal Agreement that the Conservative government had reached with the European Union. The bill was defeated decisively three times following a major revolt amongst Conservative backbench Members of Parliament (MPs). We find that three factors influenced their rebellion calculus: the MP’s own ideological views, constituency preferences and career concerns. Somewhat paradoxically, the rebellion within the Conservative Party came from MPs who had supported Leave in the 2016 Brexit referendum and from MPs elected in Leave-leaning constituencies.

Full text

Vol.:(0123456789)
Public Choice (2021) 186:587–617
https://doi.org/10.1007/s11127-019-00762-9
1 3
The Meaningful Votes: Voting onBrexit intheBritish House
ofCommons
TokeAidt1,2,5 · FelixGrey1,3· AlexandruSavu1,4
Received: 19 August 2019 / Accepted: 3 December 2019 / Published online: 14 December 2019
© The Author(s) 2019
Abstract
Why do politicians rebel and vote against the party line when high stakes bills come to the
floor of the legislature? To address that question, we leverage the three so-called Meaning-
ful Votes that took place in the British House of Commons between January and March
2019 on the Withdrawal Agreement that the Conservative government had reached with
the European Union. The bill was defeated decisively three times following a major revolt
amongst Conservative backbench Members of Parliament (MPs). We find that three factors
influenced their rebellion calculus: the MP’s own ideological views, constituency prefer-
ences and career concerns. Somewhat paradoxically, the rebellion within the Conservative
Party came from MPs who had supported Leave in the 2016 Brexit referendum and from
MPs elected in Leave-leaning constituencies.
Keywords Brexit· Roll call votes· Rebels· Party discipline· Party coherence· House of
Commons
JEL Classification D72
1 Introduction
In January 2019 the United Kingdom’s Conservative government led by Prime Minister
Theresa May suffered the worst defeat ever recorded in the history of the House of Com-
mons. Its flagship policy, leaving the European Union (EU) in a way that compromised
between the polarized “Hard Brexit” and “Remain” factions in Parliament, was defeated by
432 to 202 votes, a majority of 230. The principal reason for the defeat was a huge rebel-
lion by 118 Conservative Members of Parliament (MPs). In March the government held
* Toke Aidt
tsa23@econ.cam.ac.uk
1 Faculty ofEconomics, University ofCambridge, Cambridge, UK
2 Jesus College, University ofCambridge, Cambridge, UK
3 Corpus Christi College, University ofCambridge, Cambridge, UK
4 Fitzwilliam College, University ofCambridge, Cambridge, UK
5 CESifo, Munich, Germany
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two further votes, on the same policy, and again lost by large margins: 149 and 58. Two
months later the Prime Minister announced her resignation.
Those three so-called Meaningful Votes on May’s Withdrawal Agreement rank among
the great votes of British parliamentary history. They echo the vote on the repeal of the
Corn Laws, which put an end to trade protection of agricultural products and split the Tory
party in 1846 (Schonhardt-Bailey 2006), and also the Great Reform Act, which altered the
system of parliamentary representation in 1832, with Tory MPs who broke the party line
playing a pivotal role (Aidt and Franck 2013, 2019). It is historically very rare for a UK
government to lose with more than 100 votes on a key piece of legislations. The last time
was in 1924, when the minority Labour government of Ramsay MacDonald was defeated
by margins of 166, 161 and 140.
In this paper, we seek to explain why Conservative MPs rebelled and understand what
drove their individual decisions not to toe the party line. We argue that the three Mean-
ingful Votes potentially can provide valuable general insights into why MPs rebel against
their leaders and why the organizational structures and mechanisms that normally ensure
party discipline and unity occasionally break down, resulting in the government being
“rolled” and losing important votes. The sequence of Meaningful Votes has at least four
appealing features that allow us to do just that. First, as already noted, it is rare that a high
stakes government bill is defeated so decisively. Second, it was not a so-called free vote on
which the party leaders allow their co-partisan MPs to vote as they like. On the contrary,
both the Conservative Party and the Labour Party “whipped”, demanding that MPs toe the
respective party lines. It thus was not costless for MPs to rebel. Third, as a consequence of
the 2016 Brexit referendum, we, uniquely, observe revealed preferences on the question
of leaving the EU for each MP (we know how they voted and campaigned) and for their
voters in each of Britain’s 650 parliamentary constituencies (we know the shares voting
Leave and Remain). Fourth, the MPs effectively voted on the same bill three times, which
also is highly unusual. That information enables us to develop an innovative test of career
concerns.
The purpose of the paper is, therefore, two-fold. First, we want to document the corre-
lates underlying the mass rebellion against the Withdrawal Agreement (May’s deal) inside
the Conservative Party. Second, we want to leverage the unique features of the sequence of
Meaningful Votes to test the “tripartite model” of party rebellion (Muller and Strom 1999).
The model, which we outline in Sect.4, postulates that an MP’s voting decision is a func-
tion of three potentially conflicting factors: the MP’s own preferences (his or her ideology),
political career concerns, and the preferences of their constituents. The fact that we observe
plausible proxies for the revealed preference of the MPs and their constituents enables us
to contribute to the extensive literature on party discipline and rebellion (see Kam 2014;
Kirkland and Slapin 2018).
Our inquiry into the rebellion amongst Conservative backbench MPs yields the follow-
ing insights. First, we find evidence that MPs were influenced by their own preferences,
career concerns and constituency preferences, but that their own preferences were almost
twice as important as the other two factors. Specifically, MPs who had voted and cam-
paigned against leaving the EU in the referendum (Remain MPs) were almost 40 percent-
age points more likely to support May’s deal than other (Leave) MPs, while MPs represent-
ing constituencies with (one standard deviation) more Leave voters were 17 percentage
points less likely to support the deal. MPs mindful of their career prospects under a May
government were about 20 percentage points more likely to support May’s deal. We also
present (suggestive) evidence that the prospect of promotion to posts in a future govern-
ment motivated the MPs. Somewhat paradoxically, the rebellion within the Conservative
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Party that defeated May’s deal in the House of Commons three times in a row originated
from MPs who had supported Leave in the referendum and from MPs elected in Leave
leaning constituencies. Second, we find that the effects are heterogeneous across differ-
ent sub-samples of MPs in theoretically interesting ways. MPs elected to safe seats placed
more weight on career concerns than MPs elected in marginal seats who placed more
weight on constituency preferences in their rebellion calculus. Leave MPs but not Remain
MPs were motivated by constituency preferences. That conclusion consistent with two
types of grandstanding: Leave MPs could signal “ideological purity” to their Leave voters
by opposing May’s deal; Remain MPs could pander to their Leave voters by “converting”
and voting for May’s deal. MPs with a history of rebellion did not weight career concerns
differently from party loyalists in their voting calculus.
The rest of the paper is organized as follows. Section2 offers a short literature review
that places our study in context. Section3 sets out the background to the three Meaningful
Votes. Section4 presents the “tripartite” model of partisan rebellion. Section5 presents the
data. Section6 explains our estimation strategy. Section7 presents the results. Section8
concludes.
2 Literature review
Our analysis of the sequence of Meaningful Votes contributes to two main strands of lit-
erature. First, we contribute to the literature on party discipline and roll call rebels (for
overviews, see Kirkland and Slapin 2018 or Kam 2014). The central question in that lit-
erature is why individual politicians decide to defy the political party to which they belong
and vote against the party’s agreed policy in roll call votes or parliamentary divisions (as
they are known in the UK). Krehbiel (1993) views rebellions as a competition between
politicians’ ideological preferences, their concern about re-election, and their loyalty
to their party. Loyalty may, in turn, be induced by political career concerns (Muller and
Strom 1999) or through a process of political socialization (Crowe 1986). We build on that
theoretical framework. Empirical work has focused on the United States where roll call
rebellion is widespread and it is common for moderate legislators to “cross the aisle” (e.g.,
Kirkland and Slapin 2018). However, in spite of greater party discipline in many parlia-
mentarian systems, it is not uncommon for individual “backbench” politicians (i.e., those
with no positions in government) to revolt against their party in many other countries too
(e.g., Kam 2009; Morgenstern 2003; Carey 2008; Hix etal. 2007; Kauder et al. 2017).
Unlike in US politics, however, in the United Kingdom and elsewhere discipline-break-
ers tend to be politicians with ideologically extreme views (Kam 2009), and they belong
mainly to the governing party (Kirkland and Slapin 2018). The available evidence sug-
gests that voters pay some attention to how their representatives vote, at least when the
issue is controversial, and that they reward them for rebelling (e.g., Longley 1998; Johnston
etal. 2002; Pattie etal. 1994; Bertelli and Dolan 2009; Vivyan and Wagner 2012; Camp-
bell etal. 2019). The evidence also shows that career concerns play a role (e.g., Benedetto
and Hix 2007; Eggers and Spirling 2018) although the evidence on whether parties actu-
ally punish individual politicians for voting against the party line is mixed (Eggers and
Spirling 2016; Kauder et al. 2017). We contribute to that empirical literature by studying
how ideology, career concerns and voter preferences shaped the pattern of rebellion within
the Conservative Party in the British House of Commons on an especially high stakes bill.
In particular, we are able to leverage the fact that we have plausible measures of both MP
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and voter preferences on the issue to evaluate the relative importance of the three forces
that generally influence a politician’s decision to rebel.
Second, our analysis contributes to the fast emerging literature on the causes of the
Brexit referendum result itself.1 Becker etal. (2017), Arnorsson and Zoega (2018), Zhang
(2018) and Fidrmuc et al. (2019) use aggregate vote share results at the local authority,
constituency or ward level to study the socio-economic correlates of the Leave vote share.
Four groups of correlates were important. The first group includes indicators of socio-eco-
nomic deprivation. The Leave vote share was high in areas with low levels of education,
low incomes, historical reliance on manufacturing employment, and high unemployment
rates (Becker etal. 2017). The second group includes demographic factors. Areas with
large proportions of British male adults and with high proportions of elderly voters pre-
dominately voted Leave (Zhang 2018). The third group of correlates relates to immigra-
tion, which played an important role for the rhetoric of the referendum campaign. Areas
with high net immigration were more likely to vote Leave (Arnorsson and Zoega 2018).
The final group of correlates relates to the direct benefits an area has received over the
years from the EU’s Cohesion Fund.2 Areas that received more money from the Cohesion
Fund were moderately more supportive of Remain, but this effect is dwarfed by the fact
that those areas had low turnouts in the referendum (Fidrmuc etal. 2019).
It is, of course, always a danger trying to infer individual vote intentions from aggregate
vote share data (the ecological fallacy), so the correlations should be interpreted with cau-
tion. A better approach is to examine individual-level survey data and a number of studies
have done so previously. They largely confirm what the correlations reported above sug-
gest. Alabrese etal. (2019), for example, find that voting Leave is associated with older
age, white ethnicity, low educational attainment, infrequent use of smartphones and the
internet, receiving public benefits, adverse health, and low life satisfaction. Others have
found that negative attitudes towards immigration increase the probability that an individ-
ual voted Leave (Arnorsson and Zoega 2018) and that the generational divide—younger
individuals are less Eurosceptical than older ones—reflects a combination of individuals’
experience of the EU during their formative years and differences in access to education
for different generations (Fox and Pearce 2018). Another approach to understanding why
many voters supported Leave in the referendum is to study support for the United Kingdom
Independence Party (UKIP)—a single-issue party that since the 1990s has campaigned for
the United Kingdom to leave the European Union. Using within individual variation in
exposure to welfare cuts, Fetzer (2019) shows that individuals were more likely to “feel
close” to UKIP after they were affected personally by the government’s austerity program.
Insofar as UKIP support is a good proxy for how an individual voted in the 2016 referen-
dum, the results suggest that austerity played a major role in bringing about the referendum
result. In conclusion, the evidence, both from the analysis of aggregate vote share data
and from the analysis of individual vote choices, suggest that socio-economic deprivation,
austerity, demographics, and attitudes to immigration contributed to the referendum result
favoring Leave. We add to that literature by studying another aspect of the Brexit process—
the sequence of Meaningful Votes. This provides new insights into the link between the
1 See Clarke etal. (2017) for a comprehensive analysis of the Brexit referendum and its background.
2 The Cohesion Fund redistribute funds from the EU budget to Member States whose Gross National
Income (GNI) per inhabitant is less than 90% of the EU average. It aims at reducing economic and social
disparities.
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referendum result in particular constituencies and the ways in which the MPs elected in
those constituencies behaved in Parliament.
3 The narrative: What actually happened?
The relationship with Europe has been a major issue for the UK’s center-right Conservative
Party for the past 50 years. The UK joined the EU in 1973 under a Conservative govern-
ment, but with a broad base of political support: in a 1975 referendum on EU membership
67% of voters and all major political parties supported joining.3 However, over the next
40 years, the EU moved from being primarily a trading bloc, to a much closer economic
and political union. That process was bitterly, but unsuccessfully, opposed by a minority
of Conservative Party MPs, especially in the early 1990s when the Maastricht Treaty (an
expansion of EU powers with a corresponding loss of UK sovereignty) came into force
(Sowemimo 1996). In parallel to those events, a minority of generally right-leaning vot-
ers favoured leaving the EU. Support for that position grew in response to migration from
Eastern European countries that joined the EU from 2004 onwards. The United Kingdom
Independence Party (UKIP), a single issue party advocating the UK’s departure from the
EU, began to gain significant support, principally at the expense of the Conservative Party:
in EU Parliamentary elections, UKIP came third in 2004, second in 2009 and first in 2014
(e.g., Clarke etal. 2016).
In an attempt to both neutralize growing voter support for UKIP and deal with internal
divisions in the Conservative Party, Conservative Prime Minister David Cameron offered
a referendum on EU membership as part of his re-election campaign in 2015, alongside
an attempt to renegotiate the UK’s relationship with the EU.4 In the short run, the policy
was a successful: somewhat against expectations the Conservatives won the 2015 election
and UKIP support collapsed. In order to achieve Cameron’s second aim of mending divi-
sions within the Conservative Party, he allowed his MPs to campaign for either side in
the 2016 referendum, rather than requiring them to toe the party line and support con-
tinued membership in the EU (“Remain”). A significant minority of both backbench and
frontbench, i.e., those serving in the government, Conservatives campaigned subsequently
for exiting the EU (“Leave”). The referendum was held on 23 June 2016, and resulted in
an unexpected victory for Leave, with 52% of the vote (and considerable geographic and
demographic heterogeneity; see Becker et al. 2017). Cameron resigned immediately, and
was replaced as Prime Minister by Conservative MP Theresa May, who began the process
of withdrawing from the EU. Under EU law, a member state can leave the union by trigger-
ing Article 50 of the Lisbon Treaty. That provision gives that member state up to two years
to negotiate a Withdrawal Agreement with the EU, which sets out the terms under which it
leaves (covering everything from future customs arrangements to past pension liabilities).
If no agreement is in place at the two-year deadline, the member state can leave without an
3 At the time the bloc was called the EEC (European Economic Community), becoming the EU in 1993.
For simplicity this article uses EU throughout.
4 Bernholz et al. (2004) propose a reform of EU institutions that would protect the subsidiarity principle
and create effective checks and balances by breaking the Commission’s agenda monopoly. If that proposal
had been adopted in the mid-2000s, the critique levied against the EU by many British euro-sceptics regard-
ing the risk of an EU super state and democratic deficits would have been answered.
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agreement, or can ask for an extension of the negotiating period, during which the country
remains part of the EU.
Over the course of the two-year UK-EU negotiation of the Withdrawal Agreement, divi-
sions within the Conservative Party deepened. On one side, many Leavers became “Hard
Brexiteers”, such as senior government minister Boris Johnson and members of the Euro-
pean Research Group (ERG), who increasingly favoured a policy of little or no future coop-
eration with the EU (“no deal”). On the other side, a smaller group of former Remainers
favored a “Soft Brexit”, a close future relationship with the EU resembling full member-
ship. In November 2018, the final Withdrawal Agreement was struck between May and the
EU. Although that did not specify all aspects of the future UK-EU relationship, generally
speaking it was a compromise somewhere between Hard and Soft Brexit. Over the course
of the negotiations, Johnson and several other high profile Hard Brexiteer government min-
isters resigned in protest at compromises made by May.
The final step was for Parliament to pass the Withdrawal Agreement. That requirement
itself was the result of an earlier parliamentary setback for May, when MPs succeeded—
against the wishes the government—in securing a “Meaningful Vote” on whatever terms
the UK eventually left the EU on. Five full days of parliamentary debate were set aside,
with the vote to be held on 11 December 2018. The Whips, MPs whose jobs it is to ensure
internal party discipline, worked hard to persuade potential rebels to back the government.
The main tool at their disposal is the prospect of future promotion in government. Over
the course of the debate, it became clear that May was not going to win the vote, so she
Table 1 Breakdown ofthe Meaningful Votes by Party and Govt. Positions
Frontbench MPs hold government posts; backbench MPs do not. SNP is the Scottish National Party; DUP
is the Democratic Unionist Party; LD is the Liberal Democrats. The four Conservative MPs who abstained
were the two Whips, the Deputy Speaker and, in the second vote, MP Douglas Ross (who ended up voting
with the government in the third vote); the Whips served as Tellers and, as such, they are not counted in
the totals of those voting for or against a motion and we include them amongst those who abstained; the
Speaker and the Deputy Speaker traditionally abstain on all votes. We record the MPs as belonging to the
party that they belonged to in January 2019 (before the first Meaningful Vote), but note that ten MPs (three
Conservative MPs and seven Labour MPs) resigned from their respective parties between the first and the
second Meaningful Vote. For the purpose of the statistical analysis, it does not make any difference if we
eliminate the three Conservative MPs who resigned from the sample for the second and third vote
First vote Second vote Third vote
For Against Abstain For Against Abstain For Against Abstain
Panel A—Vote by Party
Conservative 196 118 3 235 78 4 277 37 3
Labour 3 248 5 4 247 5 6 243 7
LD 0 11 0 0 11 0 0 11 0
SNP 0 35 0 0 35 0 0 34 1
DUP 0 10 0 0 10 0 0 10 0
Other 3 10 8 3 10 8 3 9 9
Total 202 432 16 242 391 17 286 344 20
Panel B—Conservatives by Govt. Position
Frontbench 93 0 2 93 0 2 93 0 2
Backbench 103 118 1 142 78 2 184 37 1
Total 196 118 3 235 78 4 277 37 3
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delayed it to 15 January 2019, in an attempt to buy more time in which to persuade poten-
tial rebels. That strategy was not successful: the first Meaningful Vote was lost by the gov-
ernment by 432 to 202 votes, a majority of 230, representing the most serious defeat of a
UK government in the history of Parliament.
Table1 shows the breakdown of MPs’ votes on the three Meaningful Votes by party
(panel A) and for the Conservative Party between front- and backbenchers (panel B). From
these data, we see that a number of factors contributed to May’s defeat. The Democratic
Unionist Party (DUP)—a socially conservative, pro-Brexit, Northern Irish party—which
had agreed to support the Conservative government (having lost its majority in the 2017
general election), but rebelled because in their view the Withdrawal Agreement treated
Northern Ireland differently to the rest of the UK (related to the so-called Irish backstop
problem). Very few pro-Brexit MPs from the center-Left opposition Labour Party ended up
supporting the government.5 The centrist Liberal Democrats (LD) and center-left Scottish
National Party (SNP) opposed the government unanimously, but that opposition had been
anticipated. By far the main factor behind May’s defeat was the huge scale of the rebellion
by her own backbench MPs. The frontbenchers with government posts, on the other hand,
toed the line and none of them rebelled (Table1, panel B).
After the vote, the EU refused to renegotiate the Withdrawal Agreement; under Article
50, time was running out before the UK would either have to ask for an extension (politi-
cally very costly for the Conservatives) or leave without a deal (economically very costly
for the country). May, therefore, held a Second Meaningful Vote on 12 March 2019, essen-
tially a repeat vote on the policy that had been rejected two months before (some minor
changes in interpretation of certain aspects of it were introduced). May and her Whips
worked hard to persuade rebel Conservative MPs, but again unsuccessfully: the govern-
ment lost by 391 to 242 votes, a majority of 149. Following that defeat, she asked the EU
for an extension, rather than leaving with no deal at end of March.
On the day the UK originally was supposed to leave the EU, May held a Third Meaning-
ful Vote, again on essentially the same Withdrawal Agreement. She and her Whips made
a final push to persuade rebels, increasingly with the threat to Hard Brexiteers that Brexit
may not happen at all if the Withdrawal Agreement was not passed. Again, the government
lost, although it cut its margin of defeat, from 344 to 286 votes, a majority of 58. Boris
Johnson was the most prominent rebel to change his mind, and vote with the government
for the first time on that final vote.
Immediately after losing the third vote, May had to ask the EU for another extension of
Article 50, a further major political humiliation. In local and EU elections in May 2019,
the Conservatives did exceptionally badly. With the central policy of the government in
disarray and her party falling apart, the Prime Minister announced her resignation on 24
May 2019.6
5 Some predictions at the time of the first vote had up to 30 Labour MPs intending to vote with the govern-
ment. More generally, Brexit has produced serious internal divisions in the Labour Party, although they did
not have a major impact on the Meaningful Votes. Hence, this article focuses on the Conservative Party.
6 Three major aspects of the breakdown the Conservative party’s unity were the following. May suffered a
large number of resignations of both junior and senior ministers: from 11 June 2017 onwards, 33 ministers
resigned over Brexit. Four Conservative MPs also defected from the party over Brexit, either to new par-
ties or to sit as independents. On 11 December 2018, the day the first Meaningful Vote originally was to
be held, Theresa May faced an internal Conservative Party vote of No Confidence, brought by Hard Brexit
ERG (European Research Group) members, which she defeated.
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Johnson, the frontrunner to replace May among Conservative Party members (who
select the party leader), won the ensuing leadership contest and became Prime Minister
in July 2019. A proponent of Hard Brexit, he replaced much of May’s relatively balanced
government with a group of Hard Brexiteers in all of the most senior government posts.
Johnson negotiated some changes to the Withdrawal Agreement concerning the Irish back-
stop, and on 22 October 2019 MPs passed a second reading of the resulting bill by a major-
ity of 30. However, they also voted down Johnson’s attempt to rush through the legislation
in time for him not to have to extend the UK’s membership of the EU past 31 October
(politically costly for Johnson after his ‘do or die’ commitment to leaving before that date).
Hence, Johnson pushed for and eventually obtained a general election on 12 December
2019. The parliament that rejected May’s deal three times, therefore, never got a chance to
have a final say on Johnson’s deal: passing a second reading does not indicate that the bill
necessarily would have become law. Many MPs who voted for it at the second reading, for
example, were said to be planning amendments radically to soften the deal in ways Johnson
had categorically ruled out.
4 Theoretical framework
In this section, we develop a theoretical framework that explains why politicians (hence-
forth MPs) may decide to vote against their own party’s policy, and which we use to struc-
ture our empirical investigation of the Meaningful Votes. For that reason, we formulate the
framework with reference to the Westminster system. This system is characterized by a
high level of party unity in general, a clear government-opposition divide, agenda control
monopolized by the Cabinet within the governing party, and MPs elected in single-member
districts with local party organizations having significant input into who is selected to rep-
resent the constituency (e.g., Baughman 2004).7
MPs are members of political parties and are elected under those party labels and on
the party manifesto. The members share policy preferences and have common goals, but
only up to a point. Within a party, in general, substantial preference heterogeneity on par-
ticular issues exists, with extreme and moderate MPs both belonging to the same party.
Such heterogeneity creates a fundamental tension for party members between supporting
the party’s policy (selected by the party leadership), which will appeal to some but not to
all, and pursuing their own preferred policy. Party leaders are, of course, well aware of that
tension and will seek to devise incentives and rules to enforce party discipline, create party
coherence and avoid mass rebellion on critical bills (Kam 2014). Party leaders can, in prin-
ciple, pursue that goal by controlling the selection of candidates to be fielded (select only
candidates who will toe the party line), by controlling the policy agenda (make sure that
7 Broader legislative institutions and party structures help shape the costs and benefits for politicians to
deviate from the party line, along with the constraints that party leaders face in creating party coherence
(Krehbiel 1993). The differences, for example, between a Westminster-type system and a US-type system
often are emphasised (Gaines and Garrett 1993). Stratmann (2006) leverages the mixed plurality and pro-
portional election system in Germany to show that federal politicians who are elected under plurality rule
from single member districts are more likely than those elected on a party list under proportional repre-
sentation to vote against party lines in roll call votes. For a comparative study of the UK and the US, see
Kirkland and Slapin (2018) and for a study of the European Parliament see Benedetto and Hix (2007). For a
study of the consequences of government ideology, see Aidt etal. (2018).
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proposals are agreeable to most party members), by fostering socialization (Crowe 1986),
and by sharing and withholding the perks of public office strategically.
Building on Muller and Strom (1999)’s tripartite model, we make a distinction between
three factors that affect an MP’s decision to rebel against his or her party. The first consid-
eration is ideology: MPs care about policy and their position on a particular issue often
deviates from the party’s official stance. That gap may motivate an MP to rebel. The second
consideration is career concerns: MPs usually want a legislative career. In the Westmin-
ster system, where agenda control is monopolized by the Cabinet, political promotion is
about government posts for members of the governing party and about posts in the shadow
cabinet for opposition MPs. Such allocation procedures make rebellion costly for back-
benchers as well as for frontbenchers (those with government or shadow government posts)
because party leaders can withhold promotion for rebellious backbenchers and demote
frontbenchers who do not toe the line.8 The third consideration is constituency preferences
and re-election. In the Westminster system, MPs are elected to represent the voters in their
constituency. As argued by, for example, Gaines and Garrett (1993), Kirkland and Slapin
(2018), Kam (2009) and many others, MPs in that system have an incentive, albeit not nec-
essarily as strong an incentive as US legislators, to develop a persona independent of their
party that connects them with their constituents and their local party organization. They
can do so publicly by deviating from their party’s policy on issues that their voters and
selectors in the local party organization care particularly about in parliamentary divisions.
Such grandstanding signals their ideological purity, integrity or trustworthiness, gets them
media exposure and can potentially insulate them from the electoral unpopularity (in their
constituency) of the party’s policy.9
Within the public choice tradition, MPs are viewed as rational decision makers who
need to navigate the foregoing three considerations when they decide if they should rebel
on a particular issue. More often than not, the forces pull in different directions and MPs
find themselves in the cross fire at the center of a triangle with their voters, their ideologi-
cal conviction, and their party (Hix etal. 2007; Morgenstern 2003; Saiegh 2011). Figure1
illustrates this tripartite model of roll call voting.
The costs and benefits of rebellion differ systematically between the governing and
opposition parties on the one hand, and within the governing party (or coalition) between
the frontbenchers with government posts and backbenchers without on the other. First,
with regard to the government-opposition split, Kirkland and Slapin (2018) argue that it is
MPs with extreme preferences (far from the center) within the governing party that stand
to benefit the most from rebellion. That is because they can signal to their constituents that
they are “ideologically pure” by voting against the party line and expect to be rewarded
8 Bertelli and Dolan (2009) present evidence from intervention in House of Commons’s debates related to
health care that is consistent with political careerism. The evidence on whether party leaders in actual fact
punish rebels by denying them promotion is mixed. Eggers and Spirling (2016) study over 20,000 parlia-
mentary divisions that took place between 1836 and 1910 in the British House of Commons and show that
more loyal MPs were more likely to obtain ministerial posts. In contrast, Kauder etal. (2017) study 218 roll
call votes in the German federal parliament (Bundestag) and ask if rebels are punished by party leaders by
being allocated a less attractive position on the party list in the next election. They find that parties do not
punish politicians who have voted against the party line in that way.
9 Campbell et al. (2019) and Vivyan and Wagner (2012) present evidence from the UK that deviating
from the party line can help MPs seeking re-election. Pattie etal. (1994) show that rebellion on high pro-
file issues, such as capital punishment or the poll tax, had affected the re-election prospects of the rebels,
but otherwise they find no discernible consequences. Ragusa (2016) shows that US legislators take more
extreme positions if they won election to the Senate after representing a highly partisan state.
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electorally for it. For opposition MPs, the incentive to break the party line to signal “ideo-
logical purity” is weaker. Assuming that the opposition party will vote against the govern-
ment’s policy, neither extreme nor moderate (who are relatively close to the center) oppo-
sition MPs are likely to gain electorally by breaking the party line because most of their
voters would, in fact, prefer the opposition party’s official policy stance to that of the gov-
ernment. All rebels, of course, face the cost of the disciplinary actions taken by their party
leaders in response, but the benefit of rebellion between the party of government and the
opposition clearly is asymmetric. That logic is consistent with the fact that it is MPs with
extreme views that tend to rebel in the House of Commons and that MPs from the govern-
ing party are more likely to rebel than MPs from the opposition (e.g., Benedetto and Hix
2007; Kirkland and Slapin 2018).
Second, the within-party difference between front- and backbenchers is important and
arises from the fact that frontbenchers have much more to lose from rebelling (their perks
and posts, the ability to formulate policy and so on). Backbenchers also have to mind their
political careers, but those who have been “passed over” for political promotion or those
who have been demoted from the frontbench previously have less to lose (Kam 2009). That
logic suggests that it is amongst “old” backbenchers that most rebels can be found. The
cause of a backbench revolt by that group of MPs may not just be that they are unhappy
with the party’s policy, but also may be because they hope to destabilize the leader under
whom their political careers have stalled. Such considerations give rise to two distinct
career motives. On the one hand, MPs can promote their careers by pleasing the current
leadership of their party if the leadership is sufficiently stable to justify the expectation of
future rewards for good behaviour. On the other hand, MPs can promote their careers by
destabilising the current leader of their party and encouraging a leadership challenge. If
successful, the revolting MPs reasonably may expect to be rewarded by the new leader.
5 The data andoperationalization
Our objective is to study how MPs resolved the tension among their personal ideological
views, career concerns and constituency preferences in the context of the three Meaning-
ful Votes on May’s deal. The raw numbers (reported in Table1) clearly show that party
cohesion was strong among all opposition parties. All but six opposition MPs in the first
Fig. 1 The MPs in crossfire: the
tripartite model.
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Meaningful Vote and nine in the third toed their respective party lines.10 An implication,
then, is that the rebellion that defeated May’s deal three times in a row took place within
the governing Conservative Party.11 Our focus is, therefore, on the 317 Conservative MPs.
We have recorded how each of them voted in the three Meaningful Votes and coded the
indicator variable VOTE as one if the (Conservative) MP supported the Withdrawal Agree-
ment, voting with the government, and zero if the MP rebelled by voting against.
While, theoretically, the three factors of the tripartite model—ideology, career con-
cerns and constituency preferences—are distinct, in practice they often overlap and it is a
challenge to measure them independently. With that caveat in mind, we now explain how
we operationalize and measure those factors. First, we operationalize the MPs’ ideologi-
cal positions on the Brexit question by how they voted and campaigned in the 2016 refer-
endum on leaving the European Union. For Conservative MPs, the referendum, arguably,
was a “free vote” on which the MPs could vote and campaign as they liked. The official
policy of the Cameron government that had called the referendum was to vote Remain, but
many leading Tory MPs—most notably Boris Johnson and Michael Gove—campaigned to
leave. We code the dummy variable REMAIN MP as one if the MP voted and campaigned
for remain in the referendum and zero otherwise. We argue that such an expressed prefer-
ence is a good measure of each MP’s personal judgment of the merits of leaving the EU.12
However, we acknowledge that how the MPs voted in the referendum can, in principle,
also reflect career concerns and constituency preferences. In our judgment, it is unlikely
that many Conservative MPs viewed their position on the referendum question as a career
move. It was widely expected that the Remain side would win and the Cameron govern-
ment was unlikely to reward or punish MPs for the stance they took, as Cameron had called
the referendum, at least partly, to settle the “Europe question” within the Conservative
Party once and for all. It is harder to dismiss the possibility that a significant number of
MPs (who did not have strong views on the issue of Europe) chose their positions to match
the (perceived) preferences of their constituents. If that were the case, we would expect to
find a strong correlation between an MP’s position and that of his or her constituents. In
fact, the correlation between the leave stance of the MPs and the Leave vote share of their
constituents is just 0.129. That correlation does, of course, not rule out that the dummy
variable REMAIN MP captures a mixture of personal and constituency preferences. To bol-
ster our interpretation of the variable, we exploit in a robustness check that Theresa May
called a general election in 2017 and that we can make a distinction between (current) MPs
who were elected before (in 2015) and after (in 2017) the referendum. It is reasonable to
expect that constituency preferences played little role in the stances taken by the “MPs”
who did not get elected until after the referendum; for them, the expressed preference in
the referendum is a reflection of their personal views. We also stress that we condition on a
12 Moreover, it is plausible to argue that most of them were voting socio-tropically, i.e., were thinking
about what, in their view, was best for the country, rather than ego-tropically, i.e., were thinking about the
private benefit that they would derive from the result. See Nannestad and Paldam (1994) and Lewis-Beck
and Stegmaier (2013) for a discussion of the distinction between ego- and socio-tropic voting.
10 Dewan and Spirling (2011) develop a game theoretical argument for why opposition parties are able
to act coherently in spite of the temptation of some of their MPs to support the government’s policy. The
source of such strategic opposition is that if the opposition as a block vote against the government (and no
opposition MP deviates from that), it can force the government to propose a more moderate policy than oth-
erwise and that outcome is in the interest of all opposition MPs.
11 The “rebellion” by the 10 MPs from the Democratic Unionist Party (DUP) which May’s government
relied on for a parliamentary majority also was important but not pivotal.
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host of constituency characteristics and on the share of leave voters in the estimations. That
strategy helps isolate the variation in REMAIN MP that represents the MPs’ personal pref-
erences from the variation that may relate to constituency preferences.
Second, to operationalize career concerns, we make a distinction between “junior”
and “senior” backbenchers, on the one hand, and between backbenchers and members of
the government (frontbenchers) on the other. As discussed above, the group of “senior”
backbenchers, i.e., those with long parliamentary tenures, consists of two sub-groups: one
group has been “passed over” for government jobs previously and have little prospect of
ever getting one under the current Prime Minister; the other consists of MPs who previ-
ously have served in government but have resigned or been dismissed. Either group has
little to lose from rebellion because what the government and its Whips can do to sanction
them for such behavior is limited since they have little chance of promotion under the cur-
rent leadership. They are, therefore, ceteris paribus more likely to rebel than “junior” MPs
who are newly elected to their seats and who are particularly concerned with their political
career prospects under the current leadership. On top of that, if the power base of the cur-
rent leadership inside the party is fragile, then MPs may anticipate that if they rebel, the
current leadership eventually will fall and a new Prime Minster will be appointed. Likely,
the new leader will replace many of the old frontbenchers and promote MPs from the back-
bench. Consequently, MPs who think they have a fair chance of being part of a new gov-
ernment have an extra incentive to rebel. However, that strategy, arguably, is more appeal-
ing to “senior” than to ‘junior” backbenchers who hope to get back into government. So,
“junior” MPs have two reasons to toe the party line: they fear sanctions from the current
government and they do not anticipate rewards from a new government should the current
government fall because of rebellion. We code two variables to capture those calculations.
The first, FRONTBENCH, is a dummy variable coded one if the MP holds a position in
government and zero otherwise. The second, JUNIOR MP, is a dummy variable coded one
if the MP was first elected in either in 2015 or 2017, and zero otherwise.13 The fact that we
observe the same MPs voting on the same policy three times and we observe a change in
Prime Minister (from Theresa May to Boris Johnson) open a window of opportunity for a
more refined test of career concerns related to destabilizing the current leader. We return to
that issue in Sect.7.2.
Third, the Brexit situation provides a unique opportunity for measuring the constituency
preferences since we know, in the aggregate, how voters in each constituency voted in the
2016 referendum.14 We code the variable LEAVE VOTE SHARE as the fraction of voters in
each constituency who voted Leave in the referendum.
We also have collected information on many other MP and constituency specific charac-
teristics. The constituency specific control variables include population size, the unemploy-
ment rate, the share of foreign-born residents, the share of residents with higher education,
the age structure of the constituency, and share of public employment, all measured at the
parliamentary constituency level. The MP specific control variables include the MP’s age,
gender and win margin in the 2017 election. We also enter a rebellion index that proxies for
13 The most recent previous election was in 2010, so by the time of the Meaningful Votes in 2019 an MP
with JUNIOR MP=0 had served as an MP for at least eight years, long enough to be considered for a gov-
ernment position.
14 Given that actual numbers often are not reported at the parliamentary constituency level, we follow the
political science literature (see e.g. Heath and Goodwin 2017) and use estimates constructed by Hanretty
(2017).
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the MP’s tendency to rebel against his or her own party in the past. We have standardized
these data so that all non-binary variables have a standard deviation of one. Appendix A
lists and defines all of the variables we use in the statistical analysis and provides details on
their sources. Table2 reports summary statistics. The data and the Stata code to replicate
the results are deposited along with the paper.
6 Estimation strategy
We want to estimate the following statistical model:
where i is the index for a Conservative MP (and for his or her constituency since all constit-
uencies are single seat), v is the index for the three Meaningful Votes with
v∈{
1, 2, 3
}
and
Xi
is a vector of control variables. We want to understand how the three forces—ideology,
career concerns and constituency preferences—influence the decision to rebel by voting
(1)
VOTE i,v=F[𝛼v+𝛽1IDEOLOGYi+𝛽2CAREERi+𝛽3CONSTITUENCYi+𝛽4Xi]
Table 2 Summary statistics for sample of Conservative backbench MPs
Appendix A lists the definitions of the variables and provides details regarding the sources. Appendix
Table10 provides summary statistics for the sample of all Conservative MPs. * These variables are coded
for the sub-sample of Conservative backbench MPs who voted against the Withdrawal Agreement in the
first Meaningful Vote. See Sect.7.2 for more details
Variable (1) (2) (3) (4) (5)
N Mean SD Min. Max.
VOTE (Binary) 662 0.648 0.478 0 1
VOTE CHANGE 1-2* (Binary) 118 0.331 0.472 0 1
VOTE CHANGE 2-3* (Binary) 118 0.356 0.481 0 1
Main determinants
REMAIN MP (Binary) 222 0.464 0.500 0 1
JUNIOR MP (Binary) 222 0.365 0.482 0 1
LEAVE VOTE SHARE (%) 222 55.1 8.79 25.7 75.0
JOHNSON GOVERNMENT SENIOR* (Binary) 118 0.068 0.252 0 1
JOHNSON GOVERNMENT JUNIOR* (Binary) 118 0.076 0.267 0 1
Constituency controls
FOREIGN (%) 222 8.56 6.51 2.40 46.9
POPULATION (No.) 222 99,558 11,238 58,873 140,264
UNEMPLOYED (%) 222 1.59 0.795 0.503 4.81
PUBLIC (%) 222 18.1 6.75 5.60 47.1
EDUCATED (%) 222 27.2 6.94 12.3 55.2
WORKING AGE (%) 222 60.7 2.86 51.4 70.3
MP controls
AGE (years) 222 52.3 10.8 27.0 78.0
FEMALE (Binary) 222 0.176 0.381 0 1
REBELLION (Index) 222 0.723 1.87 0 21.8
WIN MARGIN (pp) 222 22.6 12.8 0.066 49.7
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against May’s deal. We use REMAIN MP to proxy for ideology, LEAVE VOTE SHARE
to proxy for constituency preferences and JUNIOR MP and FRONTBENCH to proxy for
career concerns in the main specifications, but consider a number of refinements aimed at
validating those three proxies. We estimate Eq. (1) with a probit estimator and, in speci-
fications when we pool the three votes, we cluster the standard errors at the constituency
level to account for the fact that we study a sequence of votes.
We know from Table 1 that all Conservative frontbench MPs supported the govern-
ment’s Withdrawal Agreement in the three Meaningful Votes. This implies that we cannot
include FRONTBENCH in the probit specification (the variable predicts the outcome per-
fectly and is dropped). For that reason, the main analysis is restricted to the sample of Con-
servative backbenchers where we observe variation in VOTE. To compare the effect of the
FRONTBENCH variable to the others, we estimate a linear probability model on the sam-
ple of all Conservative MPs. We also know from Table1 that 81 Conservative (backbench)
MPs changed their votes from opposition to support in the sequence of votes. To study why
they did so, we estimate a version of Eq. (1) where we replace VOTE with either VOTE
CHANGE 1-2 or VOTE CHANGE 2-3. Those variables record whether the MPs changed
their votes in the second or third Meaningful Vote relative to the position they took in the
previous vote, respectively.
7 Results
We present the results in three subsections. In Sect.7.1, we discuss the main results and
a validation test of the proxy for the MPs’ personal preferences. In Sect.7.2, we test for
career concerns related to promotion to government posts in a future administration. In
Sect. 7.3, we investigate heterogeneity in the effects across three dimensions related to
electoral competition, history of rebellion, and the MP’s personal preferences.
7.1 Main results
Table3 reports the main results. Column (1) shows a parsimonious specification without
any control variables other than the dummy variables for the three Meaningful Votes, col-
umn (2) adds the constituency specific control variables, and column (3) adds MP-specific
control variables. We report marginal effects evaluated at the means of the variables. In
column (4), we report the results from a linear probability model estimated with Ordinary
Least Squares (OLS) wherein we can include all Conservative MPs, including those serv-
ing on the frontbench in the sample.
Looking across Table3, we observe that the four variables capturing personal pref-
erences (REMAIN MP), career concerns (JUNIOR MP and FRONTBENCH), and con-
stituency preferences (LEAVE VOTE SHARE) are all strongly correlated with MP sup-
port for May’s deal. The effects are stable across specifications as we add the control
variables, except for LEAVE VOTE SHARE which is very imprecisely estimated in the
parsimonious specification in column (1). That is, perhaps, not so surprising because
the constituency specific controls include many of the variables—such as the unem-
ployment rate and the share of highly educated residents in the constituency—which
we know are correlated with the share of Leave voters (see, e.g., Becker etal. 2017).
Specifically, we find that REMAIN MP and the two career concerns variables JUNIOR
MP and FRONTBENCH are positively correlated with the probability of voting for
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May’s deal and that LEAVE VOTE SHARE is negatively correlated. That is, MPs who
had voted and campaigned against leaving the EU in the referendum were almost 40
percentage points more likely to support May’s deal than other MPs, while MPs repre-
senting constituencies with (one standard deviation) more Leave voters were 15 percent-
age points less likely to support the deal. Junior MPs mindful of their career prospects
under a May government were about 22 percentage points more likely to support her
deal and so were frontbench MPs serving in the government [column (4)]. Relatively
speaking, ideology (as captured by the MP’s revealed preference for membership of the
EU) appears to be about twice as important a factor as career concerns and constitu-
ency preferences. In sum, we conclude that the rebellion did not come from MPs with
strong career concerns. That result is in line with previous findings in the literature on
roll call rebels (see, e.g., Benedetto and Hix 2007). Rather, and somewhat paradoxically,
Table 3 The probability of voting for the Withdrawal Agreement in the three Meaningful Votes combined
Columns (1)–(3) report Probit estimates (marginal effects evaluated at the mean of the explanatory vari-
ables) for the sample of Conservative backbenchers and column (4) reports OLS estimates for the sample
of all Conservative MPs. The dependent variable (VOTE) is a binary variable equal to one whenever an MP
voted in support of the Withdrawal Agreement and zero when the MP rebelled by voting against. REMAIN
MP is a binary variable equal to one if the MP voted for remaining within the EU in the 2016 referendum;
JUNIOR MP is a binary variable equal to one if the MP was elected to the House of Commons either in
2015 or 2017; LEAVE VOTE SHARE is the standardized share of voters who voted Leave in the referendum
in 2016 in each constituency; and FRONTBENCH is a binary variable equal to one if the MP holds a posi-
tion in government. All specifications include vote dummies. Constituency controls include population size,
the unemployment rate, the share of constituents working in the public sector, the share of constituents with
a higher education degree, and the share of constituents who are of working age. MP controls include gen-
der, age, an index of the MP’s history of rebellion, and the MP’s win margin in the last election. Standard
errors (in round brackets) are clustered at the constituency level; p-values are given in [square brackets];
∗p
<
0.10
,
∗∗p
<
0.05
,
∗∗∗p
<
0.01
Outcome: VOTE Backbencher sample Full sample
(1) (2) (3) (4)
Probit Probit Probit OLS
FRONTBENCH – – – 0.329***
(0.035)
[0.000]
REMAIN MP 0.379*** 0.369*** 0.393*** 0.264***
(0.048) (0.049) (0.048) (0.034)
[0.000] [0.000] [0.000] [0.000]
JUNIOR MP 0.179*** 0.145** 0.223*** 0.146***
(0.053) (0.058) (0.069) (0.047)
[0.001] [0.012] [0.001] [0.002]
LEAVE VOTE SHARE −0.002 −0.156** −0.151** −0.069*
(0.029) (0.066) (0.073) (0.036)
[0.949] [0.017] [0.038] [0.063]
Vote dummies Ye s Yes Ye s Yes
Const. controls No Yes Ye s Yes
MP controls No No Yes Ye s
N 662 662 662 941
(Pseudo-)R2 0.22 0.25 0.27 0.33
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rebellion came from MPs who had supported Leave in the referendum and from MPs
elected in Leave leaning constituencies.
Table4 reports the results (corresponding to the specification with the full set of control
variables in Table3, column (3) for each of the three Meaningful Votes separately. That
evidence is important to consider because a significant shift in the scale of the rebellion
materialized from 118 Conservative MPs, dropping in the first Meaningful Vote down to
37 in the third. The results are qualitatively similar across the three votes: the marginal
effects have the same signs and are, with one exception, statistically significant. Impor-
tantly, the tests for whether the marginal effects are the same in the first and third vote
reported in column (4), however, show the quantitative importances of ideology and career
concerns, but not constituency preferences, weakened over time, in line with the fact that
more and more backbenchers rallied behind May’s deal as time went on.15 To illustrate,
Table 4 The probability of voting for the Withdrawal Agreement in each of the three Meaningful Votes
separately
The table reports Probit estimates (marginal effects evaluated at the mean of the explanatory variables) for
the sample of Conservative backbenchers separately for the three Meaningful Votes. The dependent vari-
able (VOTE) is a binary variable equal to one whenever an MP voted in support of the Withdrawal Agree-
ment and zero if the MP rebelled by voting against. REMAIN MP is a binary variable equal to one if the MP
voted for remaining within the EU in the 2016 referendum; JUNIOR MP is a binary variable equal to one
if the MP was elected to the House of Commons either in 2015 or 2017; and LEAVE VOTE SHARE is the
standardized share of voters who voted Leave in the referendum in 2016 in each constituency. All specifi-
cations include vote dummies. Constituency controls include population size, the unemployment rate, the
share of constituents working in the public sector, the share of constituents with a higher education degree,
and the share of constituents who are of working age. MP controls include gender, age, an index of the
MP’s history of rebellion, and the MP’s win margin in the last election. The p-value reported in column (4)
is associated with the one-sided null hypothesis that the marginal effect of the respective row variable is
numerically smaller in the third vote [column (3)] than in the first vote [column (1)]. Robust standard errors
(in round brackets); p-values are given in [square brackets];
∗p
<
0.10
,
∗∗ p
<
0.05
,
∗∗∗ p
<
0.01
Outcome: VOTE (1) (2) (3) (4)
1st Vote 2nd Vote 3rd Vote Diff. p-value
REMAIN MP 0.556*** 0.399*** 0.158*** 0.000
(0.061) (0.059) (0.044)
[0.000] [0.000] [0.000]
JUNIOR MP 0.327*** 0.209** 0.112** 0.031
(0.103) (0.087) (0.051)
[0.002] [0.016] [0.027]
LEAVE VOTE SHARE −0.150 −0.165* −0.120** 0.414
(0.121) (0.088) (0.061)
[0.217] [0.061] [0.048]
Controls Yes Ye s Yes –
N 221 220 221 –
Pseudo-R20.31 0.22 0.17 –
15 It is not straight-forward to compare coefficients in a non-linear model. We follow Mood (2010) and
use a one-sided z-test to calculate, for each variable, if one marginal effect (rather than the raw probit
coefficients) is large (smaller) than the other. We use the same procedure in the heterogeneity analysis in
Sect.7.3.
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relative to the first Meaningful Vote, wherein the MPs who had voted Remain in 2016
were 56 percentage points more likely to support May’s deal, the marginal effect dropped
down to 16 percentage points by the time of the third Meaningful Vote. We also note that
the fraction of the variance explained by the three factors (as measured by the Pseudo-
R2
)
drops from 31 to 17%.
As discussed above, we cannot fully rule out that the estimated marginal effect of
REMAIN MP, which records the stance of each MP in the 2016 referendum, captures
constituency as well as the MP’s personal preferences. The fact that we condition on the
LEAVE VOTE SHARE and, thus, estimate the effect of REMAIN MP holding the prefer-
ences of the voters in each constituency for leaving the European Union constant militates
against that interpretation. Yet, it is important to consider the issue further.
The MPs who voted on the Withdrawal Agreement in the three Meaningful Votes can
be divided between those who also were part of the 2015 Parliament and, therefore, were
serving as representatives at the time of the referendum, and those who were not members
of the past legislative (i.e., those entering the House of Commons in 2017). If the MPs’
stances in the referendum were selected strategically to match constituency preferences, we
conjecture that the incentive to do so would be much stronger for those who already were
MPs at the time of the referendum. After all the MPs elected in 2017 did not know in 2016
that they would be running in a general election shortly after the referendum vote and, thus,
their incentive to match their stances with those of future voters arguable is much weaker.
For them, it stands to reason that the referendum vote does reflect their personal preference.
Given that consideration, we can isolate the effect of the MPs’ personal preferences by
restricting the sample to the Conservative backbench MPs who did not serve in parliament
at the time of the 2016 referendum and test if those who voted Remain are more likely
than those who did not to vote for the Withdrawal Agreement. Table5 reports three speci-
fications with different sets of control variables similar to Table3. We see that REMAIN
Table 5 The probability of voting
for the Withdrawal Agreement
for the Conservative backbench
MPs not serving in 2016
The table reports Probit estimates (marginal effects evaluated at the
mean of the explanatory variables) for the sample of Conservative
backbenchers who did not serve as representatives at the time of the
2016 EU Membership Referendum. Due to limited variation, the vari-
able JUNIOR MP is omitted. The other variables are as in the speci-
fications reported in Table3, columns (1) to (3). Standard errors (in
round brackets) are clustered at the constituency level; p-values are
given in [square brackets];
∗p
<
0.10
,
∗∗p
<
0.05
,
∗∗∗p
<
0.01
Outcome: VOTE (1) (2) (3)
Probit Probit Probit
REMAIN MP 0.295*** 0.286*** 0.295***
(0.103) (0.093) (0.105)
[0.004] [0.002] [0.005]
LEAVE VOTE SHARE −0.066* −0.148** −0.084
(0.037) (0.065) (0.082)
[0.076] [0.023] [0.303]
Vote dummies Ye s Yes Yes
Const. controls No Yes Ye s
MP controls No No Yes
N 104 104 104
Pseudo-R20.27 0.33 0.38
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MP is statistically significant in all specifications, and that the marginal effect is about 30
percentage points compared to 40 percentage points in the full sample (see Table3). The
result bolsters our interpretation of REMAIN MP as a plausible proxy for the MPs’ per-
sonal preferences.
7.2 Career concerns andleader replacement
So far we have assumed that the MPs’ career concerns are shaped by the ability of the
current party leadership to reward loyalty and punish rebellion. However, the prospect of
a career under a new party leader also can be a strong motivator for rebelling against the
current leadership, particularly so if its position is perceived to be weak and rebellion is a
means to weaken it further. In the context of the three Meaningful Votes, it is clear that the
position of the May government was fragile. This, combined with the fact that she eventu-
ally was replaced by Boris Johnson as Prime Minster, opens up a unique opportunity to test
if the backbenchers’ vote choices in the Meaningful Votes were influenced by the prospect
of a promotion under a future Johnson-led government. To do that, we note two points.
Firstly, since Theresa May had “survived” an internal vote of no confidence before the first
meaningful vote, it is reasonable to assume that expectations of a change in leadership were
lower at the time of the first vote than at the time of the last. This motivates investigating
why some Conservative backbenchers changed their positions on the Withdrawal Agree-
ment between the first, second and third votes. Secondly, Johnson widely was tipped as the
most likely candidate to replace May if her administration were to fall. He announced just
before the third Meaningful Vote that he would support it after having voted against in the
previous votes.16 We can use Johnson’s PM expectations to test if those MPs who (ex post)
got promoted by his new administration were “loyal” to him and also switched their votes
when he did. If so, such vote switching would be consistent with the prospect of promotion
under a future government being a motivator.
To implement that test, we code the two variables JOHNSON GOVERNMENT SEN-
IOR and JOHNSON GOVERNMENT JUNIOR which are set equal to one if an MP got a
senior (Cabinet) or a junior (non-cabinet) post, respectively, in the Johnson administration.
We, then, test whether those variables can predict if the 118 Conservative backbench MPs
who voted against the Withdrawal Agreement in the first Meaningful Vote changed the way
they voted in subsequent votes. Table6 reports the results. In column (1), the dependent
variable (VOTE CHANGE 1-2) is a dummy equal to one for MPs who voted against in the
first Meaningful Vote and for in the second (zero otherwise). In column (2), the dependent
variable (VOTE CHANGE 2-3) is a dummy equal to one for MPs who voted against in the
second Meaningful Vote and for in the third (zero otherwise). While our results should
be interpreted cautiously because of the small sample size,17 we see that the MPs who
were appointed to senior positions in the Johnson administration were 36 percentage points
less likely to change their votes between the first and the second vote, but 36 percentage
points more likely to switch between the second and the third vote. Those appointed junior
16 Since the DUP was sure to vote against for a third time, it would have required a major rebellion in the
Labour Party to create a majority for the Withdrawal Agreement, even if most of the rebels on the Con-
servative backbench switched their votes. So, Johnson’s change of mind never was likely to make a material
difference in the outcome of the vote.
17 Only about 7% of the backbenchers who voted initially against the Withdrawal Agreement are now part
of the Johnson Cabinet.
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Public Choice (2021) 186:587–617
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positions were not more likely to change their vote than other MPs. That finding is consist-
ent with a “follow Johnson effect” whereby the rebels who anticipated (correctly) that they
might get senior posts in a Johnson administration changed their votes when Johnson did.
Although other explanations for that pattern are possible, it suggests that career concerns
related to rewards by a future leader were salient.
Table 6 Voting with Johnson: the probability that the 118 Conservative backbench MPs who voted against
the Withdrawal Agreement in the first Meaningful vote subsequently switched their vote
The sample is restricted to Conservative backbencher MPs who voted against the Withdrawal Agreement in
the first Meaningful Vote. In column (1), the dependent variable (VOTE CHANGE 1-2) is a dummy equal
to one for MPs who voted against in the first Meaningful Vote and for in the second (zero otherwise). In
column (2), the dependent variable (VOTE CHANGE 2-3) is a dummy equal to one for MPs who voted
against in the second Meaningful Vote and for in the third (zero otherwise). The dummy variable JOHN-
SON GOVERNMENT SENIOR is equal to one if the MP was appointed to a senior (Cabinet) position in
the Johnson administration (zero otherwise). The dummy variable JOHNSON GOVERNMENT JUNIOR is
equal to one if the MP was appointed to a junior (non-cabinet) governmental position in the Johnson admin-
istration (zero otherwise). The model is a linear probability model estimated with Ordinary Least Squares
(OLS). The probit estimates are similar. However, because no MP who got a senior position in the Johnson
administration started supporting Theresa May’s deal in the 2nd vote, we cannot estimate the specifica-
tion in column (1) with that estimator. REMAIN MP is a binary variable equal to one if the MP voted for
remaining within the EU in the 2016 referendum; JUNIOR MP is a binary variable equal to one if the MP
was elected to the House of Commons either in 2015 or 2017; LEAVE VOTE SHARE is the standardized
share of voters who voted Leave in the referendum in 2016 in each constituency. Constituency controls
include population size, the unemployment rate, the share of constituents working in the public sector, the
share of constituents with a higher education degree, and the share of constituents who are of working age.
MP controls include gender, age, an index of the MP’s history of rebellion, and the MP’s win margin in the
last election. Robust standard errors are reported in (round brackets); p values are given in [square brack-
ets];
∗p
<
0.10
,
∗∗p
<
0.05
,
∗∗∗p
<
0.01
Outcome: VOTE CHANGE (1) (2)
Switch in 2nd vote Switch in 3rd vote
JOHNSON GOVERNMENT SENIOR −0.363*** 0.362**
(0.105) (0.161)
[0.001] [0.027]
JOHNSON GOVERNMENT JUNIOR 0.113 0.070
(0.188) (0.187)
[0.550] [0.712]
REMAIN MP 0.092 −0.028
(0.111) (0.108)
[0.407] [0.799]
JUNIOR MP −0.098 0.110
(0.153) (0.150)
[0.523] [0.463]
LEAVE VOTE SHARE −0.010 −0.141
(0.136) (0.130)
[0.944] [0.283]
Const. controls Ye s Yes
MP controls Yes Ye s
N 118 118
R2
0.17 0.15
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7.3 Heterogeneity
We explore three dimensions of heterogeneity in the main results: constituency competi-
tiveness, history of rebellion, and the MP’s personal preferences.18
7.3.1 Constituency competitiveness
The relative importance of ideology, career concerns and constituency preferences in an
MP’s rebellion calculus is likely to be influenced by the competitiveness the MP’s seat.
An MP elected to a safe seat by a large majority is likely to put more weight on career
concerns and ideology than on constituency preferences than an MP elected to a marginal
seat. To investigate that hypothesis, we split the sample of Conservative backbench MPs
into sub-samples defined by their win margins in the 2017 general election and re-estimate
Eq. (1) on these sub-samples. We define a seat as marginal if it is in the bottom 25% of the
distribution with win margins below 11 percentage points and safe if it is in the top 50% of
the distribution with a win margin above 23 percentage points.
Table 7 reports the results. Column (1) repeats the baseline model estimated on the
entire sample of backbench Conservative MPs. In columns (2) and (3), we report the results
for safe and marginal seats separately. We observe a remarkable difference in the relative
importance of career concerns and constituency preferences between MPs elected in safe
versus marginal seats. Specifically, the effect of career concerns is significantly weaker in
marginal constituencies, while the influence of constituency preferences is significantly
stronger. The results align with previous findings by Baughman (2004), who associates the
greater attention paid to constituency preferences by MPs under electoral threat by pander-
ing to local party officials whose support is essential for future electoral success. Likewise,
Kauder and Potrafke (2019) show that conservative politicians elected in safe rather than
in contested districts were less likely to support same-sex marriage in a roll call vote in the
national German parliament (Bundestag).
While those results should not necessarily be interpreted causally because win margins
may be correlated with unobserved mediating factors, we do believe that they bring cred-
ibility to our main findings. If the main results from Table3 were wholly spurious, we
would have no reason to expect the particular pattern we observe when the sample is split
between safe and marginal seats. Hence, while making a causal claim is not possible with
the data at hand, the results in Table7 are in line with what we would expect theoretically,
which is reassuring.
7.3.2 History ofrebellion
While many MPs are loyal, some MPs are serial rebels and have long histories of
voting against their parties. Famous examples include the now leader of the Labour
Party Jeremy Corbyn and the shadow Chancellor John McDonnell and, amongst the
Conservatives, the MP Philip Hollobone. We conjecture that an MP with a history of
rebellion would respond differently to, in particular, career concerns than an MP who
18 Methodologically, we study heterogeneity by splitting the sample along the relevant dimension and then
test if the marginal effects of the core variables are different in the two sub-samples. An alternative is to
introduce interaction terms. However, since we are interested in heterogeneity across many variables, that
approach, despite the efficiency gain associated with a larger sample, is inferior for our purposes.
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Public Choice (2021) 186:587–617
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always has been loyal. An MP who has rebelled at least once may, from a career point
of view, perceive another rebellious vote differently from an MP who has been loyal in
the past.
Based on the the “rebellion history index” constructed by the website The Public
Whip from divisions in the House of Commons over the period from June 2017 to
November 2018 (i.e., before the first Meaningful Vote), we have divided the sample
of Conservative backbench MPs into two groups: those who never rebelled in the past
and for whom a vote against the Withdrawal Agreement would be their first rebellious
vote (first-time rebels) and those who rebelled at least once prior to the first Meaning-
ful Vote (serial rebels). We re-estimate Eq. (1) on the two sub-samples. Table8 reports
the results. From columns (2) and (3), we observe that based on a comparison of the
marginal effects (28 versus 19 percentage points), career concerns do appear to matter
more for first-time than for serial rebels, but the difference is not statistically signifi-
cant. An MP’s history of rebellion, thus, did not make much of a difference for how
they voted on Brexit.
Table 7 The probability of voting for the Withdrawal Agreement in safe versus marginal seats
The table reports Probit estimates (marginal effects evaluated at the mean of the explanatory variables)
for the sample of Conservative backbenchers and for the three votes combined. Column (1) replicates the
full baseline results from Table3. Columns (2) and (3) estimate the model separately for safe (top 50% of
the win margin distribution) and marginal (bottom 25% of the distribution) seats. The dependent variable
(VOTE) is a binary variable equal to one whenever an MP voted in support of the Withdrawal Agreement
and zero if the MP rebelled by voting against. REMAIN MP is a binary variable equal to one if the MP
voted for remaining within the EU in the 2016 referendum; JUNIOR MP is a binary variable equal to one
if the MP was elected to the House of Commons either in 2015 or 2017; and LEAVE VOTE SHARE is the
standardized share of voters who voted Leave in the referendum in 2016 in each constituency. All specifi-
cations include vote dummies. Constituency controls include population size, the unemployment rate, the
share of constituents working in the public sector, the share of constituents with a higher education degree,
and the share of constituents who are of working age. MP controls include gender, age, an index of the
MP’s history of rebellion, and the MP’s win margin in the last election. The p-value reported in column (4)
is associated with the one-sided null hypothesis that the marginal effect of the respective row variable is
larger (smaller) in one sub-sample than in the other. Standard errors (in round brackets) are clustered at the
constituency level; p values are given in [square brackets];
∗p
<
0.10
,
∗∗p
<
0.05
,
∗∗∗p
<
0.01
Outcome: VOTE (1) (2) (3) (4)
Baseline Safe Marginal Diff. p-value
REMAIN MP 0.393*** 0.493*** 0.431*** 0.278
(0.048) (0.076) (0.085)
[0.000] [0.000] [0.000]
JUNIOR MP 0.223*** 0.271*** -0.048 0.034
(0.069) (0.105) (0.139)
[0.001] [0.010] [0.730]
LEAVE VOTE SHARE −0.151** −0.055 −0.314*** 0.076
(0.073) (0.154) (0.095)
[0.038] [0.722] [0.001]
Vote dummies Yes Yes Ye s –
Controls Yes Yes Ye s –
N 662 330 164 –
Pseudo-R20.27 0.30 0.46 –
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Public Choice (2021) 186:587–617
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7.3.3 The MPs’ personal Brexit preference
We already have established that conservative backbench MPs who supported Remain in
the 2016 referendum were more likely to support May’s deal in the three Meaningful Votes
than Leave MPs. We split the sample into Leave and Remain MP sub-samples in order
to investigate if the two groups of MPs reacted differently to career concerns and to con-
stituency preferences. Table9 reports the results. We observe that Remain MPs reacted to
career concerns and not to constituency preferences, while for Leave MPs, career concerns
appear to play no role, but they were more likely to vote against the deal if elected in con-
stituencies with large fractions of Leave voters. However, despite the fact that the mar-
ginal effect on JUNIOR MP is insignificant for Leave MPs and significant for Remain MPs,
the difference between the two marginal effects is not statistically significant. For LEAVE
VOTE SHARE the difference is significant. One interpretation of that evidence is that Leave
MPs, many of whom belong to the European Research Group (ERG) led by Jacob Rees-
Mogg, signalled “ideological purity” to the Leave voters and local party officials in their
Table 8 The probability of voting for the Withdrawal Agreement, breakdown by history of past rebellion
The table reports Probit estimates (marginal effects evaluated at the mean of the explanatory variables) for
the sample of Conservative backbenchers and the three Meaningful Votes combined. Column (1) replicates
the full baseline results from Table3, excluding the rebellion index control. Column (2) restricts the sample
to MPs who had not rebelled prior to November 2017 (first-time rebels); column (3) restricts the sample
to MPs who had rebelled at least once before (serial rebels). The dependent variable (VOTE) is a binary
variable equal to one whenever an MP voted in support of the Withdrawal Agreement and zero if the MP
rebelled by voting against. REMAIN MP is a binary variable equal to one if the MP voted for remaining
within the EU in the 2016 referendum; JUNIOR MP is a binary variable equal to one if the MP was elected
to the House of Commons either in 2015 or 2017; and LEAVE VOTE SHARE is the standardized share of
voters who voted Leave in the referendum in 2016 in each constituency. All specifications include vote
dummies. Constituency controls include population size, the unemployment rate, the share of constituents
working in the public sector, the share of constituents with a higher education degree, and the share of
constituents who are of working age. MP controls include gender, age, and the MP’s win margin in the last
election. The p-value reported in column (4) is associated with the one-sided null hypothesis that the mar-
ginal effect of the respective row variable is larger (smaller) in one sub-sample than in the other. Standard
errors (in round brackets) are clustered at the constituency level; p values are given in [square brackets];
∗p
<
0.10
,
∗∗p
<
0.05
,
∗∗∗p
<
0.01
Outcome: VOTE (1) (2) (3) (4)
Baseline First-time rebels Serial rebels Diff. p-value
REMAIN MP 0.371*** 0.397*** 0.399*** 0.491
(0.049) (0.064) (0.074)
[0.000] [0.000] [0.000]
JUNIOR MP 0.227*** 0.280*** 0.189** 0.257
(0.068) (0.101) (0.096)
[0.001] [0.006] [0.048]
LEAVE VOTE SHARE −0.154** −0.115 −0.197* 0.298
(0.072) (0.116) (0.101)
[0.034] [0.321] [0.052]
Vote dummies Yes Ye s Yes –
Controls Yes Ye s Yes –
N 662 306 356 –
Pseudo-R20.26 0.32 0.26 –
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constituencies by voting against May’s deal which they considered to be too “soft” (involv-
ing a risk of locking the UK into a customs union through the so-called Irish backstop).
Remain MPs with political careers to look after, on the other hand, could signal purity to
their Leave voters and local party officials by “converting” (accepting the result of the ref-
erendum) and supporting May’s attempt to get a deal through.
7.4 Johnson’s October 2019 Brexit deal
As discussed in Sect.3, Prime Minister Johnson put a new Brexit deal before Parliament
which passed its second reading on 22 October 2019 with a majority of 30. It got no fur-
ther because a general election was called. As explained, passing a second reading is not
equivalent to passing one of the Meaningful Votes considered above, but some interesting
patterns nevertheless should be noted. The 30 MP majority was achieved largely thanks to
24 Labour MPs defying their party and either voting for Johnson’s deal (19) or abstaining
(5). By comparing descriptive statistics, these rebel Labour MPs appear to be guided by
motivations similar to those of the Conservative rebels analyzed above. Rebel Labour MPs
had substantially higher constituency Leave vote shares than loyal Labour MPs (62.2% vs.
50.1%), they were less likely to have campaigned for Remain (87.5% vs. 98.2%), and less
Table 9 The probability of voting for the Withdrawal Agreement for remain and leave MPs
The table reports Probit estimates (marginal effects evaluated at the mean of the explanatory variables)
for the sample of Conservative backbenchers for the three Meaningful Votes combined. Column (1) rep-
licates the baseline result from Table3, excluding REMAIN MP. Column (2) restricts the sample to MPs
who voted Leave in the 2016 referendum (Leave MPs). Column (3) restricts the sample to MPs who voted
Remain in the referendum (Remain MPs). The dependent variable (VOTE) is a binary variable equal to one
whenever an MP voted in support of the Withdrawal Agreement and zero if the MP rebelled. REMAIN MP
is a binary variable equal to one if the MP voted for remaining within the EU in the 2016 referendum; JUN-
IOR MP is a binary variable equal to one if the MP was elected to the House of Commons either in 2015 or
2017; and LEAVE VOTE SHARE is the standardized share of voters who voted Leave in the referendum in
2016 in each constituency. All specifications include vote dummies. Constituency controls include popula-
tion size, the unemployment rate, the share of constituents working in the public sector, the share of con-
stituents with a higher education degree, and the share of constituents who are of working age. MP controls
include gender, age, an index of the MP’s history of rebellion, and the MP’s win margin in the last election.
The p-value reported in column (4) is associated with the one-sided null hypothesis that the marginal effect
of the respective row variable is larger (smaller) in one sub-sample than in the other. Standard errors (in
round brackets) are clustered at the constituency level; p-values are given in [square brackets];
∗p
<
0.10
,
∗∗p
<
0.05
,
∗∗∗p
<
0.01
Outcome: VOTE (1) (2) (3) (4)
Baseline Leave MPs Remain MPs Diff. p-value
JUNIOR MP 0.211*** 0.135 0.231*** 0.233
(0.069) (0.118) (0.060)
[0.002] [0.254] [0.000]
LEAVE VOTE SHARE −0.155** −0.253** 0.008 0.013
(0.069) (0.100) (0.061)
[0.026] [0.011] [0.893]
Vote dummies Yes Ye s Ye s –
Controls Yes Ye s Ye s –
N 662 354 308 –
Pseudo-R20.15 0.21 0.27 –
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likely to be junior (33.3% vs. 42.4%). Hence, we see patterns of rebellion by Labour MPs
consistent with our findings for Conservative MPs.
8 Conclusions
We study the three Meaningful Votes that took place in the British House of Common
between January and March 2019 in which the Conservative government’s Withdrawal
Agreement with the European Union was defeated decisively. Instrumental for that result
was a major revolt on the Conservative backbench. We argue that this high-stakes situation
can provide insights into why politicians revolt against their own parties more generally.
We find evidence that personal preferences (ideology), constituency preferences and career
concerns mattered. We also find (suggestive) evidence that the rebellion on the Conserva-
tive backbench was, in part, motivated by the prospect of bringing the May government
down. An interesting question for future research is to study the electoral consequences of
the rebellion for individual MPs. That is, do voters reward or punish them for the ways they
voted on the highly contentious Brexit issue? A related question that also deserves atten-
tion is how the Conservative Party internally rewards or punishes rebellious MPs, i.e., how
will the rebellion affect their long-term career prospects?
Acknowledgements We would like to thank Niklas Potrafke, Colin Jennings, Thomas Stratmann, Pierre-
Guillaume Méon and the participants in the 2019 Silvaplana workshop in political economy for constructive
comments. We are also grateful for the helpful advice from the reviewers and the editor.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Com-
mons licence, and indicate if changes were made. The images or other third party material in this article
are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly
from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.
Appendix A: denitions andsources
This Appendix lists and defines the variables we use in the statistical analysis and gives the
sources.
• VOTE is a dummy variable coded one if an MP voted for the government’s deal and
zero if they voted against; coded separately for each of the three votes. This coding
takes into account that the Tellers, the Speaker and the deputy Speaker do not cast a
vote. Note: Data retrieved April 2019. Source: House of Commo ns Votes
• VOTE CHANGE 1-2 (VOTE CHANGE 2-3) is a dummy equal to one for MPs who
voted against in the first (second) Meaningful Vote and for in the second (third) (zero
otherwise). Note: Data retrieved April 2019. Source: House of Commo ns Votes
• REMAIN MP is a dummy variable coded one if the MP voted and campaigned to
remain in the referendum and zero otherwise. Note: Data retrieved November 2018.
Source: SkyNe ws Analy sis
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Public Choice (2021) 186:587–617
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• FRONTBENCH is a dummy variable coded one if the MP holds a governmental posi-
tion and zero otherwise. Note: Data retrieved November 2018. Source: House of
Commo ns Libra ry
• JUNIOR MP is a dummy variable coded one if the MP first entered Parliament either in
2015 or 2017 and zero otherwise. Note: Data retrieved November 2018. Source: House
of Commo ns Libra ry
• LEAVE VOTE SHARE records the (estimated) share of the electorate in each constitu-
ency who voted to leave the EU in the 2016 referendum. Note: Data retrieved Novem-
ber 2018. Source: Hanre tty, 2017
• FOREIGN records the share of people residing within a constituency that have not
been born within the UK. Data for March 2015. Note: Data retrieved November 2018.
Source: Offic e for Natio nal Stati stics
• PUBLIC records the share of people residing within a constituency employed in the
public sector. Data for March 2015. Note: Data retrieved November 2018. Source: Offic
e for Natio nal Stati stics
• EDUCATED records the March share of people residing within a constituency that
have a degree of higher education. Data for March 2015. Note: Data retrieved Novem-
ber 2018. Source: Offic e for Natio nal Stati stics
• POPULATION records the number of people residing within a constituency. Data for
June 2016. Note: Data retrieved November 2018. Source: House of Commo ns Libra ry
Local Data
• WORKING AGE records the share of people residing within a constituency that are
between 16 and 64 years old. Data for June 2016. Note: Data retrieved November 2018.
Source: House of Commo ns Libra ry Local Data
• UNEMPLOYED records the unemployment rate within a constituency. Data for June
2016. Note: Data retrieved November 2018. Source: House of Commo ns Libra ry Local
Data
• AGE records the representative’s age in years. Note: Data retrieved November 2018.
Source: House of Commo ns Libra ry
• FEMALE is a dummy variable coded one if the MP is female. Note: Data retrieved
November 2018. Source: House of Commo ns Libra ry
• REBELLION is an index variable which proxies for the number of times a repre-
sentative has voted against the majority vote of the representative’s party. Note: Data
retrieved November 2018. Source: The Publi c Whip
• WIN MARGIN records, for each constituency, the difference between the vote share of
the winning candidate and the vote share of the runner up. Note: Data retrieved Novem-
ber 2018. Source: House of Commo ns Libra ry
• JOHNSON GOVERNMENT SENIOR is equal to one if the MP was appointed to a
senior (Cabinet) position in the Johnson administration (zero otherwise). Note: Data
retrieved July 31 2019. Source: BBC News
• JOHNSON GOVERNMENT JUNIOR is equal to one if the MP was appointed to a jun-
ior (non-cabinet) governmental position in the Johnson administration (zero otherwise).
Note: Data retrieved July 31 2019. Source: BBC News
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Appendix B: additional data andestimation results
See Tables10, 11, 12, 13 and 14.
Table 10 Summary statistics for sample of all Conservative MPs
Appendix A lists definitions of the variables and provides details regarding the sources. The sample is used
to estimate the specification in Table3, column (4)
Variable (1) (2) (3) (4) (5)
N Mean SD Min. Max.
VOTE (Binary) 941 0.752 0.432 0 1
Main determinants
FRONTBENCH (Binary) 317 0.300 0.459 0 1
REMAIN MP (Binary) 317 0.546 0.499 0 1
JUNIOR MP (Binary) 317 0.300 0.459 0 1
LEAVE VOTE SHARE (%) 317 55.0 8.77 25.7 75.0
Constituency controls
FOREIGN (%) 317 8.86 6.94 2.30 52.0
POPULATION (No.) 317 100,324 11,371 58,873 140,264
UNEMPLOYED (%) 317 1.53 0.770 0.393 4.81
PUBLIC (%) 317 17.8 6.56 5.60 47.1
EDUCATED (%) 317 27.6 7.14 12.3 55.2
WORKING AGE (%) 317 60.8 2.79 51.4 73.6
MP controls
AGE (years) 317 51.6 9.85 27.0 78.0
FEMALE (Binary) 317 0.211 0.409 0 1
REBELLION (Index) 317 0.636 1.59 0 21.8
WIN MARGIN (pp) 317 23.2 13.1 0.066 49.7
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Table 11 The probability of voting for the Withdrawal Agreement in the three Meaningful Votes combined,
Linear Probability Model
The table reports the results from a linear probability model estimated with Ordinary Least Squares (OLS)
on the sample of all Conservative MPs (panel A) and for the sample of backbench MPs (panel B). The
dependent variable (VOTE) is a binary variable equal to one whenever an MP voted in support of the With-
drawal Agreement and zero when the MP rebelled by voting against. REMAIN MP is a binary variable
equal to one if the MP voted for remaining within the EU in the 2016 referendum; JUNIOR MP is a binary
variable equal to one if the MP was elected to the House of Commons either in 2015 or 2017; LEAVE
VOTE SHARE is the standardized share of voters who voted Leave in the referendum in 2016 in each con-
stituency; and FRONTBENCH is a binary variable equal to one if the MP holds a position in government.
All specifications include vote dummies. Constituency controls include population size, the unemployment
rate, the share of constituents working in the public sector, the share of constituents with a higher education
degree, and the share of constituents who are of working age. MP controls include gender, age, an index of
the MP’s history of rebellion, and the MP’s win margin in the last election. Standard errors (in round brack-
ets) are clustered at the constituency level; p values are given in [square brackets];
∗p
<
0.10
,
∗∗p
<
0.05
,
∗∗∗p
<
0.01
A. All Conservatives B. Conservative Backbenchers
FRONTBENCH 0.305*** 0.311*** 0.329*** – – –
(0.031) (0.031) (0.035)
[0.000] [0.000] [0.000]
REMAIN MP 0.264*** 0.256*** 0.264*** 0.346*** 0.329*** 0.341***
(0.036) (0.035) (0.034) (0.045) (0.046) (0.044)
[0.000] [0.000] [0.000] [0.000] [0.000] [0.000]
JUNIOR MP 0.122*** 0.099** 0.146*** 0.143*** 0.115** 0.174***
(0.038) (0.039) (0.047) (0.045) (0.049) (0.062)
[0.001] [0.011] [0.002] [0.002] [0.019] [0.006]
LEAVE VOTE SHARE 0.0001 −0.081** −0.069* −0.005 −0.102** −0.085*
(0.016) (0.034) (0.037) (0.023) (0.045) (0.048)
[0.993] [0.018] [0.063] [0.842] [0.023] [0.078]
Vote dummies Yes Yes Ye s Yes Ye s Ye s
Const. controls No Ye s Ye s No Yes Ye s
MP controls No No Yes No No Ye s
N 941 941 941 662 662 662
R2
0.30 0.32 0.33 0.26 0.28 0.30
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Public Choice (2021) 186:587–617
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Table 12 The probability of voting for the Withdrawal Agreement in the three Meaningful Votes combined
(Probit coefficients)
Columns (1)–(3) report Probit estimates (rather than marginal effects) for the sample of Conservative back-
benchers and column (4) reports OLS estimates for the sample of all Conservative MPs. The dependent var-
iable (VOTE) is a binary variable equal to one whenever an MP voted in support of the Withdrawal Agree-
ment and zero when the MP rebelled by voting against. REMAIN MP is a binary variable equal to one if the
MP voted for remaining within the EU in the 2016 referendum; JUNIOR MP is a binary variable equal to
one if the MP was elected to the House of Commons either in 2015 or 2017; LEAVE VOTE SHARE is the
standardized share of voters who voted Leave in the referendum in 2016 in each constituency; and FRONT-
BENCH is a binary variable equal to one if the MP holds a position in government. All specifications
include vote dummies. Constituency controls include population size, the unemployment rate, the share of
constituents working in the public sector, the share of constituents with a higher education degree, and the
share of constituents who are of working age. MP controls include gender, age, an index of the MP’s history
of rebellion, and the MP’s win margin in the last election. Standard errors (in round brackets) are clustered
at the constituency level; p values are given in [square brackets];
∗p
<
0.10
,
∗∗p
<
0.05
,
∗∗∗p
<
0.01
Outcome: VOTE Backbencher sample Full sample
(1) (2) (3) (4)
Probit Probit Probit OLS
FRONTBENCH – – – 0.329***
(0.035)
[0.000]
REMAIN MP 1.14*** 1.12*** 1.22*** 0.264***
(0.170) (0.174) (0.170) (0.034)
[0.000] [0.000] [0.000] [0.000]
JUNIOR MP 0.533*** 0.433** 0.695*** 0.146***
(0.165) (0.181) (0.231) (0.047)
[0.001] [0.017] [0.003] [0.002]
LEAVE VOTE SHARE −0.005 −0.447** −0.439** −0.069*
(0.083) (0.0187) (0.212) (0.037)
[0.949] [0.017] [0.038] [0.035]
Vote dummies Ye s Yes Ye s Yes
Const. controls No Yes Ye s Yes
MP controls No No Yes Ye s
N 662 662 662 941
(Pseudo-)R2 0.22 0.25 0.27 0.33
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Public Choice (2021) 186:587–617
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Table 13 Breakdown of Meaningful Votes by Party and Government Positions (Alternative Affiliation Defi-
nition)
This table shows the distribution of votes across the three Meaningful Votes taking into account that three
Conservative MPs and seven Labour MPs resigned and became independent between the first and the sec-
ond Meaningful Vote
First vote Second vote Third vote
For Against Abstain For Against Abstain For Against Abstain
Panel A—Vote by Party
Conservative 196 118 3 235 75 4 277 34 3
Labour 3 248 5 3 238 5 5 234 7
LD 0 11 0 0 11 0 0 11 0
SNP 0 35 0 0 35 0 0 34 1
DUP 0 10 0 0 10 0 0 10 0
Other 3 10 8 4 22 8 4 21 9
Total 202 432 16 242 391 17 286 344 20
Panel B—Conservatives by Govt. Position
Frontbench 93 0 2 93 0 2 93 0 2
Backbench 103 118 1 142 75 2 184 34 1
Total 196 118 3 235 75 4 277 34 3
Table 14 The probability of voting for the Withdrawal Agreement in the three Meaningful Votess sepa-
rately (alternative affiliation definition)
Columns (1) to (3) report the results corresponding to Table4 on a sample that including only MPs that
were officially part of the Conservative party at the time of each vote. This, therefore, takes into account
that three Conservative MPs resigned between the first and the second Meaningful Vote (see Table13). We
observe that this makes almost no difference to the results, except in the second Meaningful Vote where
LEAVE VOTE SHARE is imprecisely estimated with a p-value of 12%. Column (4) reports the results for
the combined sample (but in the second and third Meaningful Vote without the three MPs who resigned),
corresponding to Table3, column (3). We see that the results are very similar; * p < 0.10 , ** p < 0.05 ,
*** p < 0.01
Outcome: VOTE (1) (2) (3) (4) (5)
1st Vote 2nd Vote 3rd Vote Pooled Diff. p-value
REMAIN MP 0.556*** 0.411*** 0.164*** 0.404*** 0.000
(0.061) (0.058) (0.043) (0.047)
[0.000] [0.000] [0.000] [0.000]
JUNIOR MP 0.327*** 0.211** 0.104** 0.223*** 0.026
(0.103) (0.085) (0.049) (0.068)
[0.002] [0.013] [0.031] [0.001]
LEAVE VOTE SHARE −0.150 −0.152* −0.106* −0.144** 0.371
(0.121) (0.086) (0.057) (0.071)
[0.217] [0.077] [0.066] [0.044]
Vote dummies No No No Yes –
Controls Yes Ye s Yes Ye s –
N 221 217 218 656 –
Pseudo-R2 0.31 0.24 0.17 0.29 –
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