How (not) to operationalize
subnational political opportunity structures: a critique of Kestilä and
Söderlund’s study of regional elections.
Kai Arzheimer (Essex) and Elisabeth
Carter (Keele)
Abstract
Based on an aggregate analysis of the French regional elections of 2004, Kestilä and Söderlund (2007) examine the impact of subnational political opportunity structures on the success of the radical right and argue that such an approach can control for a wider range of factors and provide more reliable results than cross-national analyses. We dispute this claim on theoretical, conceptual and methodological grounds and demonstrate that their empirical findings are spurious.
Introduction
Analysing the
influence that features of the national political context exert on the vote for
Western Europe’s ‘extreme’ or ‘radical’ right[1] parties is now a minor industry (see for example Arzheimer & Carter
2006; Golder 2003; Jackman & Volpert 1996; Knigge 1998; Lubbers et al.
2002; Swank & Betz 2003), but in a recent contribution to this journal,
Kestilä and Söderlund (2007) argue that research should give more consideration
to what they call ‘subnational political opportunity structures’. According [k1]to Kestilä and Söderlund, focusing on the subnational context within one
country mitigates against three problems that trouble the existing contextual
analyses: i) at the subnational level, the number of contexts is large in
comparison to the number of relevant variables; ii) unique features of the pa
rty system are obviously held constant; and iii) the heterogeneity of
the radical right party family need not be of concern (2007: 774-775). [k2]
This theoretical claim is backed up by an ecological analysis of the
French regional elections of 2004. In a straightforward linear regression at
the level of the département, Kestilä and Söderlund relate the electoral
support for the Front National (henceforth FN) in the first round of those
elections, as well as an index of the FN’s electoral success (that assesses the
FN’s success in relation to the leading contender), to five aggregate
variables: turnout in the first round of the 2004 election, the logged district
magnitude in the previous regional elections of 1998, the effective number of
party lists (Laakso-Taagepera index) in 1998, the share of immigrants born
outside the European Union in 1999, and the unemployment rate in 1999. They
find that turnout and district magnitude have significant negative effects on
the FN’s electoral support,[2] whereas the effects of the number of party lists and unemployment are
positive and significant. Most interestingly, the effect of immigration is not
significantly different from zero in Kestilä and Söderlund’s model of FN
aggregate support. From these results, Kestilä and Söderlund conclude that the
radical right benefits from low turnout levels, and that greater
proportionality of the electoral system does not increase support for the
radical right but is actually related to substantially lower levels of
support. They also conclude that the FN benefited when the effective number of
party lists in 1998 was high, and when unemployment levels were high. By
contrast, the share of immigrants present in each département did not affect
the FN’s electoral score.
It should be
noted that, while the results that relate to the district magnitude are in line
with the findings of some other studies (e.g. Arzheimer & Carter 2006),
those that pertain to unemployment and immigration are not: in country-level
analyses the effect of unemployment is subject to on-going discussion, and the
effect of immigration has been consistently found to be strong and positive.
From their
results, and the findings of other studies notwithstanding, Kestilä and
Söderlund argue that the ‘subnational political opportunity structure has been
of great importance for the FN’ and more generally, that the subnational
approach ‘is able to control a wider range of factors pertaining to the
political system and tends to provide more reliable results’ (2007: 790).
Kestilä and
Söderlund have invited other scholars working in the field to engage in a
discussion of their unexpected findings. We have taken up this invitation
because, while we concur that features of the subnational context are
potentially relevant for the radical right vote and should be incorporated into
more comprehensive accounts of support for these parties, we are not convinced
by Kestilä and Söderlund’s conceptualization of what constitutes a subnational
political opportunity structure, and nor are we persuaded by the empirical
evidence they present.
We begin this
article by highlighting some of the theoretical, conceptual and methodological
problems present in Kestilä and Söderlund’s study. Then, since Kestilä and
Söderlund were extremely forthcoming in providing us with their data, we engage
in some re-analysis. In doing this we discuss the difficulties of estimating
and interpreting the coefficients in Kestilä and Söderlund’s model and, using
an indicator for the FN’s regional entrenchment that is independent of district
magnitude and of the effective number of party lists, we demonstrate that
features of the subnational political opportunity structure included in Kestilä
and Söderlund’s model are essentially spurious. We close by offering an
alternative operationalization of one of the key variables contained in Kestilä
and Söderlund’s model.
Subnational Political
Opportunity Structures: Conceptual Difficulties and Operationalization
The concept of
political opportunity structures is notoriously vague, but at its core is the
idea that certain variables can capture the degree of ‘openness or
accessibility of a political system for would-be political entrepreneurs’
(Arzheimer & Carter 2006: 422). If one accepts this as a working definition,
it follows that subnational political opportunity structures refer to a
set of regional or local conditions that would either facilitate or hamper the
attempts of the radical right to mobilize voters. Precisely because the concept
of political opportunity structures is so vague, identifying these conditions
and operationalizing these variables is a tricky task, and unfortunately, there
are problems with the way in which Kestilä and Söderlund have gone about this
in their study.
Our first
misgiving concerns the inclusion of (regional) party system fragmentation in
Kestilä and Söderlund’s model, operationalized by the variable ‘effective
number of party lists’. As Kestilä and Söderlund suggest, the level of party
system fragmentation might indeed be important to small or new parties either
because a high level of fragmentation at the previous election might indicate
that the system is open and therefore more favourable to such parties or,
conversely, because a high level of fragmentation might indicate that a wide
variety of alternatives already exists, rendering it difficult for a small or
new party to make a breakthrough (2007: 784).
However, using
this variable in relation to the FN is problematic because, as Kestilä and
Söderlund themselves point out, the FN is neither small nor new: it is a well
established political competitor that has acquired the status of third
political force in many parts of France (2007: 775). Therefore, given that it
is not knocking on the door of the French party system but is already clearly
inside it, the issue for the FN is not how accessible the party system is
(which is what party system fragmentation measures), but is how much political
space the party has or, put differently, how much competition it faces at the
right end of the political spectrum. In short, we would argue that party system
fragmentation is not an appropriate variable with which to measure party
competition in this instance and that a much more relevant variable would be
one that taps the ideological space available to the FN (see below).
Kestilä and
Söderlund do briefly discuss the ideological aspect of party competition when
they note that cross-national studies that have analysed the impact of
political opportunity structures have had to operationalize and measure
ideological convergence or divergence and issue adoption. However, although
they recognize ‘that the local party organisations may have an agenda somewhat
deviant from the national one’ (2007: 783), they do not include the ideological
dimension of party competition in their model on the basis that a subnational
analysis such as theirs benefits from being able to ‘hold the ideological
differences constant in each subunit due to the national character of the
campaign in the elections of 2004’ (2007: 775).
Now, it might
indeed be the case that the campaign for the regional elections of 2004 took on
a national character, but that does not mean that the contest was ideologically
similar in all départements. A quick glance at the first round of the 2004
regional election results reveals that in some regions competition on the right
of the political spectrum was played out simply between the FN and one
mainstream right party list (for example in Picardie). Elsewhere, however,
there was more than one mainstream right party list and/or more than one list
from the radical right. In Aquitaine, for instance, there were two mainstream
right party lists, while in the Rhône-Alpes region not only was there an FN
list, but there was also another ‘extreme right’ list. Similar patterns can be
found with respect to the 1998 regional elections – the results of which
Kestilä and Söderlund use to calculate their ‘effective number of party lists’.
The
ideological nature of party competition has therefore varied by region and
voters have been faced with a different choice of party lists according to
where they live. This is likely to be important in an explanation of the FN’s
success as the party may well be hindered by the presence of multiple
mainstream right lists, and may also experience lower vote shares in
départements where an alternative radical right list exists. By only including
the party system fragmentation variable in their model, Kestilä and Söderlund
fail to account for these trends.
Including the
effective number of parties or party lists in analyses of the radical right
party vote is also problematic for methodological reasons. This is because the
vote share of the very party whose electoral success is being explained (in
this case the FN) is included in the calculation of the effective number of
parties: (1 / S pi2) for N parties, where p is the vote share of party i). This
means that the two variables cannot possibly be independent of each other, and
that, given the construction of the index, there must be a non-linear
relationship between them, the exact shape of which depends on both the number
and relative strength of other parties.
The
co-variance of these two variables is most easily illustrated by simulation. To
do this, we selected the results from four random départements in the 1998
regional elections (since départements were treated as districts in 1998) and
let the FN’s vote share vary around its empirical value while holding the
relative support within the mainstream right bloc and the absolute
support for all other party lists constant.[3] Figure 1 illustrates the results of this simulation and clearly shows
that, at least in these four départements, a change in the fortunes of the FN
within the département would ceteris paribus have a strong, positive and almost
linear impact on the effective number of parties.[4]
[Figure 1 about here]
By including
the effective number of party lists in 1998 in their model, Kestilä and
Söderlund therefore effectively regress the FN’s success in 2004 on a variable
that already encompasses previous levels of support for the party. This is
problematic for theoretical reasons, and our simulation shows that it also has
very real implications in terms of interpreting the effect of this variable.
Turning to
district magnitude, we take no issue with Kestilä and Söderlund’s decision to
include this variable in their model. For theoretical reasons it makes sense to
do so: it will be harder for the FN – a medium-sized party – to win votes in
districts with a small magnitude than it will be for it to be successful in
districts with a greater magnitude. Moreover, this effect will be exacerbated
if the number of potential voters is small to begin with and if the party
decides to invest fewer resources in districts with a small magnitude than it
does in those with a larger magnitude.
What we are
unhappy with, however, is the way in which this variable has been
operationalized in Kestilä and Söderlund’s study. They regress the FN’s vote in
each département in 2004 on the (logged) district magnitude in the 1998
regional election, and we would argue this is troublesome for two reasons.
Firstly, the
inclusion of the (logged) district magnitude ignores the effect of legal
thresholds which can and do override the effects of district magnitude. In the
case of the electoral system of 1998, the five per cent legal threshold in
place at the département level effectively cancelled out the effects of
district magnitude in départements with a magnitude of 14 or more. Given that
the district magnitude was 14 or more in 50 of the 94 départements, this has
large implications for the model, and, as such, it would have made greater
sense to include the effective magnitude or the effective threshold rather than
simply the (logged) district magnitude.[5]
The second
reservation we have about Kestilä and Söderlund’s operationalization of
district magnitude concerns their decision to use the (logged) district
magnitude in the 1998 regional
election – i.e. in the previous
regional election. Kestilä and Söderlund do this because they maintain that
‘changes in electoral laws may not necessarily have an immediate effect’ and
that the psychological effect of an electoral system may take a while to
manifest itself. They also note that ‘the district magnitude of 1998 and seats
allocated to departments in 2004 have a very strong correlation’ (2007: 792,
note 7).
We certainly
do not dispute the fact that psychological effects of electoral systems may
take a while to register with voters, and as such, other than keeping an eye on
our comments above about legal thresholds, we would have no criticisms of the
use of this variable had the electoral system of 1998 been identical to that
used in 2004. The problem, however, is that it was not: the electoral system
used in 1998 was fundamentally different to that used in 2004.
The system
used in the 1998 regional elections (in use since the first regional elections
of 1986) was a one-round proportional electoral system. Between 3 and 72 seats
were distributed at the level of the département and, as mentioned above, there
was a five per cent legal threshold in place. In 2004 a new two-round electoral
system came into operation, however. Under this system, even though seats were
eventually divided up between departmental sections, it was at the level of the
region that lists were presented, votes were aggregated and seats were
distributed. The district magnitude of the regions ranged from 43 in the
Limousin and Franche-Comté regions to 209 in the Ile-de-France region but the
existence of legal thresholds meant that the effect of district magnitude was
effectively cancelled everywhere.[6]
Given that the
electoral system changed so fundamentally between 1998 and 2004, we believe
that it is unrealistic to argue that the 1998 system still exerted a
psychological effect on voters and political elites in 2004. If voters are
well-informed and rational enough to react to the mediating effects of
electoral systems in the first place, then they are hardly likely, on the one
hand, to take the effects of the 1998 electoral system into account, and yet,
on the other, to fail to notice that the system has been changed thoroughly in
the interim. And as concerns political elites, the effects of the 1998 system
will not have entered into their calculations in 2004. Rather they will have
taken the new electoral system into account when they decided on their
campaigning strategies and on the resources they would invest in each district
for the 2004 contest.
For these two
reasons, therefore, we would argue that it does not make sense to use the
(logged) district magnitude in the 1998 regional election as an indicator of
the openness or accessibility of the political system in 2004. And the fact
that the district magnitude of 1998 correlates very strongly with the seats
allocated to départements in 2004 does not allay our fears because this
correlation does not take account of the effects of legal thresholds and
because the number of seats distributed to départements in 2004 is irrelevant since
the allocation of seats took place at the level of the region, not at that of
the département.
We are also
uneasy about the inclusion of turnout in Kestilä and Söderlund’s model. The
issue here is not how this variable has been operationalized, but rather why it
is included in the model at all.
Of course,
turnout is commonly included in national and comparative election studies, and
a number of these works have observed a negative correlation between turnout
and support for parties that are not fully integrated into the party system
(Reif et al. 1997; van der Eijk et al. 1996), including the FN, whose vote
share has been found to be highly correlated with turnout in both presidential
and legislative elections (Auberger 2008). It makes good sense to include
turnout in studies of this kind since they are in the business of explaining
patterns in individual voter behaviour. In this instance, they are able account
for the negative correlation they find by arguing that, while politically
dissatisfied supporters of the established parties may refrain from voting
altogether, politically dissatisfied supporters of non-established parties can
express their dissatisfaction with their vote.
The purpose of
an analysis that seeks to assess the impact of political opportunity structures
on political parties is altogether different, however. Here the aim is to
investigate the opportunities and incentives that a given (subnational) context
affords parties and politicians, and crucially, we would contend that turnout is
not part of that context. Since the (local) turnout is clearly not known to
anyone before the evening of the election day, we would argue it is neither
part of an opportunity structure nor a general contextual variable that could
somehow affect the probability of a radical right vote.
We certainly
recognize that the level of turnout might reflect the attitudinal atmosphere or
the intensity of political competition in a particular locality, and that this
in turn, may indeed be important in explaining the success of a political
party. However, we have concerns about using turnout as an (ex-post facto)
indicator of attitudinal atmosphere or political competition because turnout
will be affected by a whole host of other factors including the political
tradition of an area, the specific local issues, the personalities involved in
the campaign, and even the weather. As such, interpreting the cause of
differing levels of turnout is highly problematic.
With their
last two variables, Kestilä and Söderlund assess the effect of immigration and
unemployment on the FN vote. Their model includes the share of the population
of each départment that is made up of immigrants born outside of the EU-15 and
of unemployed people.[7]
This, however, is problematic because the coefficients for immigration and
unemployment pick up at least three different things: i) they may represent a
true contextual effect whereby immigration and unemployment provide the FN with
an incentive to mobilize voters and whereby voters who feel strongly about
these issues have an opportunity to vote for a party that campaigns on them;
ii) they pick up the effect of the composition of the départements; and iii)
they reflect cross-level interactions between features of the context and
features of individuals.[8]
This becomes
clear if we consider départements with a high share of immigrants. If we assume
that the presence of immigrants facilitates mobilization by the FN, then people
living in such départements should, ceteris paribus, have a higher propensity to
vote for the radical right. This contextual effect should therefore
result in a positive aggregate correlation that reflects a subnational
political opportunity structure.
However,
things are not that simple because we also need to bear in mind the composition
of départements and their immigrant population. In 1999 (the year of the census
on which Kestilä and Söderlund rely), there were 4.0 million people living in
France who had been born outside the EU-15.[9]
However, the majority of these immigrants (57 per cent) were French citizens
and, as such, had the right to vote. Presumably, they and any of their children
born in France, as well as children born in France to non-naturalized
immigrants, and many of these people’s friends will have a probability of
voting for the FN that is close to zero. Everything else being equal,
therefore, these individual effects will result in a substantial
negative aggregate correlation that counteracts the positive relationship
resulting from the contextual effect.
Given that in
roughly one third of all départements immigrants born outside of the EU make up
more than five per cent of the population, and that in some départements of the
Ile-de-France and the Provence-Alpes-Côte d’Azur regions they comprise up to 20
per cent of the population, the individual effect is not negligible, something
which is reflected in the bad model fit for the banlieues of Paris (see below).
Finally, such a scenario implies a cross-level interaction too, in that while
the FN will be able to mobilize more voters because of high number of
immigrants, it will only be able to do so among non-immigrants.
The same logic
applies to the effect of unemployment, too. Observed aggregate correlations
between unemployment and the FN vote are the result of a contextual effect
(voters respond to regional unemployment levels), a compositional/individual
effect (the unemployed are presumably more likely to vote for the FN), and
possibly also a cross-level interaction effect: after all, it seems reasonable
to assume that the strength of the individual effect of unemployment varies
with the prevalence of unemployment in one’s environment.
The aggregate
correlations Kestilä and Söderlund present therefore conflate three
conceptually different effects, the nature and size of which are impossible to
separate without micro-data.[10]
In addition, because these coefficients reflect the highly aggregated net
result of different processes, they hide any co-variation that is likely to
exist both between and among individual and contextual variables.[11]
For these reasons, the coefficients for unemployment and immigration in Kestilä
and Söderlund’s model do not provide reliable information on the role of
unemployment and immigration within a political opportunity structure.
Estimating and interpreting the coefficients of
Kestilä and Söderlund’s model
As the
discussion above has demonstrated, Kestilä and Söderlund’s model is problematic
because all of the independent variables included in it raise theoretical,
conceptual and/or methodological concerns. In addition to the problems that
beset individual variables, the number of cases in Kestilä and Söderlund’s
model is not very large (N=94) and the units (départements) vary enormously in
terms of their population. The standard deviation for this variable is .48
million people, and the distribution is substantially right-skewed. The number
of inhabitants for the ten smallest départements varies between 77,000 and
190,000, whereas each of the ten largest départements has a population of
between 1.3 and 2.6 million people. The implication is that a lot of
information on individual behaviour is lost, and that the behaviour of citizens
in large départements will, ceteris paribus, have a smaller impact on the
aggregate correlations.[12]
However, even
leaving aside these concerns, the effects of the different independent
variables are either difficult to interpret or trivial. As mentioned already,
the effects of immigration and unemployment cannot be unambiguously interpreted
because both variables aggregate the individual characteristics of the voters
of the 94 départements of mainland France and, in the process, conflate
contextual and individual effects and cross-level interactions. As for the
other variables contained in the model, even though they capture features of
the départements that exist independently of the individuals living in them, as
we will demonstrate, their political impact is small – a fact that is not
apparent in Kestilä and Söderlund’s reading of their findings. Moreover, as we
will also show, the estimates in Kestilä and Söderlund’s model are highly
sensitive to the selection of cases.
Kestilä and
Söderlund interpret their results mainly with reference to the relative size of
the t-values, and this is problematic for three reasons. Firstly, the jury is
still out on the question of whether it makes sense to calculate (classical)
standard errors for data that are a population rather than a sample (Berk &
Freedman 2003). Secondly, if significance tests are to be carried out, the
calculation of the standard errors should take into account the spatial
correlations that exist between départements. Ignoring these dependences
violates the standard assumption that disturbances are identical and
independently distributed. And thirdly, and most importantly, the size of a
t-value (i.e. statistical significance) is not a criterion for substantive
relevance, and so it assists little to an interpretation of the effects of the
variable.
For these
reasons, rather than focussing on the t-values, we would suggest that the
effects of the variables are best interpreted by examining the expected change
in the FN’s vote share for a given change of the independent variables. At the
same time as examining this, it is also important to consider the distribution
of the independent variables if we are going to be able to say anything about
political realities.
Kestilä and
Söderlund do show us what the expected change in the FN’s vote share is for
changes in the independent variables. Indeed, although they do not discuss
these expected changes in the text, in Table 3 of their article we can see that
a unit increase in the logged district magnitude would reduce support for the
FN by 3.45 percentage points, whereas a unit increase in the effective number of
parties would increase the FN’s share by 1.14 points. However, what these
results do not do is take into account the distribution of the district
magnitude and the effective number of party lists across départements and as
such, they tell us little about the true impact of these variables on
particular départements.
Let us first
consider the logged district magnitude in 1998 and its distribution across
départements. By identifying the second and the third quartile we can ascertain
that in half the départements the total number of seats to be filled was
between 10 and 22. And we can work out that by increasing the district
magnitude from 10 to 22 while holding all other independent variables constant
the expected support for the FN would be reduced by a mere 2.7 points.[13]
This suggests that the effect of the district magnitude is fairly small across
these départements. What is more, if we were to examine the middle 90 per cent
of the distribution instead, we would find that the expected difference between
the smallest district of eight seats and the biggest district of 31 seats would
be 4.7 points. This is still not very large, and here we are considering the
vast majority of cases. Thus, even though the effect of the logged district
magnitude is statistically significant, it seems that it is only really
relevant when we consider very small and very large départements.[14]
When we repeat
this exercise for the effective number of party lists, we see that increasing
the effective number of party lists from 2.6 (the second quartile) to 3.5 (the
third) would increase support for the FN by just one percentage point. And if
we consider the middle 90 per cent of the distribution, where the effective
number of party lists ranges from 2.2 to 4.2, we see that a change from 2.2 to
4.2 would give rise to a 2.3 percentage point increase in the FN’s vote share.
As well as
taking into account the distribution of the independent variables across
départements we also need to bear in mind that their effect can be conditional
on the levels of the other four independent variables in each département. This
is the case for district magnitude: the bivariate correlation between district
magnitude and FN support is essentially nil in Kestilä and Söderlund’s model,
and only becomes negative once both turnout and unemployment are included in
the model. Yet if we move away from the overall model and consider different
subgroups of départements, we see that the relationship is actually positive
for départements with below-average unemployment and turnout levels, whereas it
is negative if either turnout or unemployment or both are above average. This
rings alarm bells because there is no obvious theoretical reason for this
finding. As such, and particularly because the number of units is low, it
points to the possibility that the negative effect of district magnitude (as
well as the positive effect of the number of party lists) may be spurious and
driven by outlying and otherwise unusual observations.
To investigate
this suspicion further, we calculated a number of diagnostics (studentized
residuals, Cook’s distance, and leverage values) that can be used to identify
problems with the model fit. We found that one département – Seine-Saint-Denis,
which, with the neighbouring départements of the Hauts-de-Seine and the
Val-de-Marne, forms the infamous banlieues of Paris – clearly stood out.
Seine-Saint-Denis has the highest share of immigrants born outside the EU and
the second-largest population of that group in absolute terms, and yet levels
of FN support here are far below what Kestilä and Söderlund’s model predicts:
while they predicted that the FN would poll 25.5 per cent in this département,
the actual result in 2004 was 15.8 per cent. This just goes to show what
happens when the contextual and compositional effects of the immigration rate
are conflated. Furthermore, the impact of this département on the model is
large as it is an influential data point in terms of the independent variables
and is the largest negative outlier. If it is excluded from the estimation the
coefficient for the immigration variable almost doubles and becomes
statistically significant.
The largest
positive outlier, by contrast, is the Vaucluse in the Provence-Alpes-Côte
d’Azur region. This département had an average district magnitude in 1998 and
slightly above-average figures for all other independent variables. While
Kestilä and Söderlund’s model predicts a vote share of 18.7 per cent for the FN
in the Vaucluse, the actual result was a staggering 28.5 per cent. The high
support for the FN in this département reflects a political tradition that
dates back to the 1980s. In the legislative elections of 1986, Jacques Bompard,
a founding member of the FN, polled 18 per cent for the party in this
département – one of the best results for the party in that election. Bompard
(who left the party in 2005) was also instrumental in the FN’s successes at the
local and the regional level, and in 1995 he became mayor of Orange (a
historical town in the Vaucluse), being one of the first members of the FN to
hold such an office.[15]
Since the
Vaucluse does not have much leverage (as regards the independent variables, it
is pretty average in almost every way), excluding it from the estimation does
not greatly affect the coefficients. However, with just 94 départements, the joint
leverage of a small group of three or four cases can easily be a problem (Fox
1997: 281). Indeed, it is possible to manipulate the coefficients considerably
by excluding a tiny fraction of the départements. For instance, excluding not
only the Vaucluse but also Paris (i.e. département 75) and the Territoire de
Belfort in the Franche-Comté region reduces the absolute value of the
coefficient for the logged district magnitude from -3.4 to -2.8. By contrast,
excluding Seine-Saint-Denis and two rural départements with low unemployment
and immigration rates – the Cantal in the Auvergne and the Haute-Vienne in the
Limousin – increases the coefficient to -4.3. Similarly, excluding
Seine-Saint-Denis together with the Haut-Rhin in Alsace (a FN stronghold) and
the Lot-et-Garonne in Aquitaine halves the coefficient for the effective number
of party lists.
The most
striking effect is observed if we consider the share of immigrants born outside
the EU. This coefficient is rather small (.15) and statistically insignificant
in Kestilä and Söderlund’s model. Excluding the Vaucluse and two other
départements where the FN is very successful – the Ain in the Rhône-Alpes
region and the Alpes-Maritime in Provence-Alpes-Côte d’Azur – further reduces
the effect of immigration to .03. However, excluding Paris, Seine-Saint-Denis
and either of the other banlieues départements (Val-de-Marne or Hauts-de-Seine)
almost triples the coefficient and turns immigration in a powerful (and
statistically highly significant) predictor of FN success. Not only does this
illustrate just how sensitive the estimates in Kestilä and Söderlund’s model
are to the selection of cases, but it also highlights once again that the model
conflates contextual (i.e. opportunity structure) and compositional (i.e.
individual) effects.
Clearly, one
could question this practice of excluding individual départements for
diagnostic purposes given that Kestilä and Söderlund are examining the
population of French départements rather than a sample. That said, doing this
does enable us to assess just how accurate an instrument Kestilä and
Söderlund’s model is for examining the impact of subnational political
opportunity structures on the FN vote in the regional elections of 2004, and indeed
for making generalizations beyond this particular electoral contest.
To further
investigate our concerns about the spurious nature of the effects of the
variables included in Kestilä and Söderlund’s model, we introduced an
alternative predictor into their model: the vote won by Jean-Marie Le Pen in
each département in the first round of the 2002 presidential election. The
theoretical relevance of this variable in the context of the regional elections
of 2004 is clearly only modest. That is, while we do expect Le Pen’s 2002 vote
score to be a strong predictor of the FN’s vote in the 2004 regional elections
because this would demonstrate that FN support at the departmental level is
stable over time, the main purpose of introducing this additional variable into
the model is to observe what happens to the effects of the other independent
variables.
We chose this
particular variable because it allows us to control for the fact that, over
decades, the FN has been much more successful in some parts of France than in
others (Bréchon & Mitra 1992), something which is due to the stabilizing
effect of local party organizations (Lipset & Rokkan 1967: 53) and to the
compositional effects and structural factors that benefit the party.
Furthermore, the vote won by Le Pen in 2002 is an attractive measure of FN
entrenchment because it cannot possibly have been affected by the district
magnitude and the effective number of party lists in the regional elections in
1998 as the 2002 election was held under a completely different electoral
system. As such, including this new variable in the regression should yield
unbiased results for the relationship between FN support in 2004 and district
magnitude/party system fragmentation in 1998, net of any other (stable) factors
that are related to FN success at the departmental level.
[Table 1 about here]
Table 1
presents the coefficients of Kestilä and Söderlund’s original model as well as
those for the augmented model (column 2). As we expected, the vote for Le Pen
in the presidential election of 2002 turns out to be a strong predictor of FN
success in the regional elections of 2004: each percentage point increase in
support in 2002 translates into an increase of .98 percentage points in the
party’s vote in 2004.
More
important, however, is the fact that, once the lepeniste vote is controlled for, all other factors except
unemployment are of very minor importance, with estimates that are very close
to zero.[16]
The lack of relevance of the five original independent variables is confirmed
by a further model (column 3 of Table 1) in which all of the five original
predictors are dropped and which shows FN support in the 2004 regional
elections to be essentially identical to Le Pen’s vote in 2002 minus a constant
of 2.7 percentage points.[17]
The discussion
above suggests that, in the first instance, the lack of robustness of Kestilä
and Söderlund’s model means it is unable to provide a compact description of the FN’s success at
the departmental level in the 2004 regional elections. However, from both of
the alternative models presented in Table 1 we have to conclude that the
features of the subnational political opportunity structure included in Kestilä
and Söderlund’s original model were largely irrelevant in explaining the FN’s
vote in the 2004 regional elections anyway. As such, Kestilä and Söderlund’s
model does not enable reliable inferences to be made about the impact of
contextual factors on the radical right vote in Western Europe more generally,
let alone allow for inferences that are more reliable than those made in the
existing cross-national studies.
Towards an
alternative model of FN success in the 2004 regional elections?
While we have
demonstrated that Kestilä and Söderlund’s analysis suffers from a whole host of
conceptual and methodological problems, we are still convinced that subnational
political opportunity structures can, in principle, be very useful in
accounting for the electoral success of radical right parties (and indeed any
other type of party) provided this concept is operationalized in a more
stringent way.
Given the data
at hand, and especially given the lack of micro-level data on immigration and
unemployment, the most obvious way the model may be improved is by replacing
the ‘effective number of party lists’ variable with a variable that captures
the ideological nature of party competition in the regional elections of 2004.
As we argued earlier, the effective number of party lists reflects the
accessibility of the regional party system, which is rather irrelevant in the
case of the FN. Moreover, this variable has an element of tautology to it as it
is not independent of previous levels of support for of the party. We therefore
suggest replacing the effective number of party lists with two very simple variables:
i) the presence of a second ‘extreme right’ list presented by the Mouvement
National Républicain (MNR), and ii) the number of lists submitted by parties of
the moderate right. Information pertaining to the lists presented in each
region is readily available from the French government’s website (www.interieur.gouv.fr/).
We would
expect the presence of an MNR list to reduce support for the FN, albeit only
slightly. Given that the MNR broke away from the FN in January 1999 and is led
by Le Pen’s former deputy, Bruno Mégret, one would expect many voters to see
this party as a substitute for the FN.[18]
As such, the presence of an MNR list should, ceteris paribus, reduce support
for the FN because the political space available to the FN is more crowded.
That said, we anticipate that the effect will only be modest because the MNR’s
challenge to the FN effectively collapsed with the 2002 presidential election
(Kuhn 2005: 102), when Mégret picked up only 2.3 per cent of the vote in the
first round while Le Pen won 16.7 per cent and went on to contest the second
round against the incumbent president, Chirac.
The number of
mainstream competitors should also have a negative effect on the FN’s vote.
Since this effect will not necessarily be linear, we will distinguish between
three different scenarios: the presence of a single mainstream right list; the
presence of two such lists; and the presence of three or more.
[Table 2 about here]
As a point of
reference, column 1 of Table 2 shows the regression of the FN’s vote share in
2004 on the effective number of party lists in 1998 – i.e. the indicator
favoured by Kestilä and Söderlund. The effect of this variable is slightly
stronger in this bivariate model than it was in Kestilä and Söderlund’s
complete model, but the very low R2 shows that it explains only a
tiny fraction of the variation in the FN’s support. What is more, as is evident
in column 2, the effect of the effective number of party lists disappears
completely if we control for entrenched FN support by once again introducing
our alternative predictor (the vote won by Le Pen in the first round of the
presidential elections of 2002) into the model.
Column 3 of
Table 2 presents the results of a model based on our alternative
operationalization of party competition. It includes a dummy variable which
takes a value of 1 in each département where the MNR presented a list, and
dummy variables for the presence of two mainstream right lists, and three or
more mainstream right party lists. This alternative model clearly fits the data
much better than the effective number of party lists model. It explains a
larger share of the variance in the FN’s vote, and the lower Bayesian
Information Criterion (BIC) indicates that even though it includes more
independent variables (and hence loses two degrees of freedom), this
alternative model is preferable to the effective number of party lists one.
In this model
the coefficients for competition from the moderate right have a straightforward
interpretation and confirm our expectations: the FN’s vote in 2004 is reduced
in départements where there were multiple moderate right lists. Compared to
départements where the moderate right presented just one list, the FN vote is
substantially (by over 6 percentage points) reduced where the party faced two
mainstream right party lists. Where there were more than two mainstream right
lists, the FN’s vote is reduced by over 3 percentage points.
Contrary to
our initial expectation, however, we see that the presence of an MNR list in
the 2004 elections does not
reduce support for the FN. Rather, the presence of an MNR list has a
substantial positive effect on the
vote of the FN in 2004: after controlling for party competition from the
mainstream right, the FN is on average 3.2 percentage points stronger in
départements where the MNR fields candidates. We might explain this unexpected
positive effect by pointing to the strategic choices made by the MNR’s
leadership. While the FN presented candidates in all regions (and all
départements), the MNR, stretched for money and staff, focussed its efforts on
regions where the radical right had done well in the past – i.e. in areas where
it might expect to do well. It contested 11 of the 14 regions where then FN had
won above-average results in 1998 but chose to fight in only 2 of the 7 regions
where the FN’s performance was below its average in 1998 (Cramér’s V=.49). The
coefficient therefore picks up both the negative impact of competition from the
MNR as well as the positive effect of previous FN support.
Our tentative explanation is confirmed by the
findings in column 4 of Table 2: once we introduce the now familiar indicator
for entrenched FN support, the effect of a competing MNR list becomes negative,
as expected. Moreover, the effects of competition from the moderate right
remain negative, though they are substantially reduced. This latter finding
might again reflect strategic considerations of the FN's competitors. After
all, there are clear incentives for the moderate right to present a unified
list in FN strongholds, something which is evidenced by a substantial
correlation of r=0.42 between the FN support in the preceding regional election
and the presence of a single mainstream right list.
The most important point about the model presented
in column 4 of Table 2 is that the presence of an MNR list and the
fragmentation of the mainstream right continue to have a theoretically
meaningful effect even if previous FN support is controlled for. Moreover, the
BIC indicates that this is an improvement over both the model that combined
Kestilä and Söderlund’s effective number of party lists and the lepeniste vote (column 2) and the ‘pure’
model of entrenched FN support from Table 1. We take this as evidence that
local/regional ideological competition matters and that it should be included
in a subnational political opportunity structure model for radical right
parties. The same cannot be said for the effective number of party lists.
As regards the other variables in Kestilä and
Söderlund’s model, there is, unfortunately, no ‘easy fix’. We believe that some
of them – namely turnout and district magnitude in 1998 – should not be
included in the model at all because their conceptual status is dubious.
Replacing district magnitude in 1998 with district magnitude in 2004 is also
not an option because there is effectively no variation in this variable due to
the legal thresholds in operation. And as for immigration and unemployment,
although these are clearly part of the subnational political opportunity
structure, in the absence of micro-level data it is simply not possible to
investigate their impact and to untangle their contextual, compositional and
cross-level effects.
Given this situation it appears that a major data
collection effort is required if subnational political opportunity structures
are to be operationalized rigorously and analysed fully and we would argue that
such an endeavour should really go beyond merging survey data with subnational
immigration and unemployment figures because Lubbers and Scheepers (2002) have
already conducted an analysis of this kind for France. Rather, in an ideal
world, a prospective project should collect data on variables that capture the
theoretical concept of subnational political opportunity structures. This might
include a content analysis of the local and regional media so as to capture its
tenor (see Boomgaarden & Vliegenthart 2007 for a recent application to the
national media in the Netherlands), an assessment of the organizational
strength of local parties (see Pedahzur & Brichta 2002 on the
institutionalization of the FN), and in-depth interviews with local political
elites to probe their stances on radical right issues.
Conclusion
In their
article, Kestilä and Söderlund highlight an important point, which although
sometimes discussed in theoretical terms (e.g. Eatwell 2003), has largely been
overlooked in empirical studies of the success of the radical right in Western
Europe: local and regional contexts should not be ignored. Unfortunately,
however, the importance of this message is somewhat obscured by the actual
analysis that Kestilä and Söderlund carry out. For the reasons outlined above,
we believe that there are difficulties with both Kestilä and Söderlund’s
conceptualization of subnational political opportunity structures and their
empirical findings.
A large data
collection exercise focussing on factors that capture the concept of
subnational political opportunity structures could potentially resolve many of
the problems that Kestilä and Söderlund encountered in their study. Moreover,
if time and resources were invested in any such future project, it would be all
the more useful to analyse the relevant variables in a cross-national
perspective. After all, authors such as Lubbers and Scheepers (2001, 2002) and
Dülmer and Klein (2005) have already applied standard models of radical right
voting to subnational units in individual countries.
That said, we
fully concede that constructing cross-national models of radical right voting
that contain rich information on very small subnational units (smaller even
than French départements) would be a substantial accomplishment. Although
collecting suitable data on one country is possible – as the British Election
Study demonstrated more than ten years ago – gathering appropriate, comparable
data across many countries would be a formidable feat. What is more, a
cross-national study of subnational political opportunity structures would have
to grapple with difficulties that are inherent to comparative analyses of this
kind. That is, it would have to deal with the trade-off that exists between
being able to draw conclusions that may be generalized beyond the cases in
question and being able to gain an understanding of the intricacies of the
particular contexts being examined. Indeed, some of the difficulties that
Kestilä and Söderlund faced in their study reflect this very point: on the one
hand their model is very sensitive to the selection of cases and hence does not
allow for generalizable inferences to be made beyond the context of the 2004
French regional elections, but yet, on the other, it does contain rich
information on the characteristics of the French regions and départements. This
trade-off between generalizability and richness of data might raise questions
over the very utility of any cross-national study of subnational political
opportunity structures. Yet, if an appropriate balance can somehow be struck
between these two concerns, we might learn a great deal more about the impact
of local and regional contexts on the vote for radical right parties.
Notes