Arrested Development
How electoral systems have shaped the ability of rural interests to hold back
welfare expansion, 1871−2002
Magnus Rasmussen† and Carl Henrik Knutsen*
†
Department of Political Science, Aarhus University
* Department of Political Science, University of Oslo
Word count: 11 763 (incl. notes and references; excl. tables, figures and front-page)
Abstract
Although some scholars suggest that rural groups contribute to welfare state expansion, we
highlight their strong incentives to restrain it. Nonetheless, rural groups’ ability to achieve this
policy preference hinges on their power resources, but also the electoral system. In majoritarian
systems, agrarian groups can win majorities when electorally strong, or pressure candidates in
undecided districts, allowing them to veto welfare legislation. In proportional systems, this is less
feasible even for resource-rich rural groups; instead, agrarian groups sometimes “concede”
welfare legislation for other policy-concessions in post-electoral bargaining. We illustrate this
argument by drawing on experiences from Great Britain and Norway, and systematically test it
using data from 1871−2002 for 96 democracies. We find very robust evidence that agrarian
groups, when strong, effectively arrest welfare state development in majoritarian systems, but not
in proportional. As expected, the electoral system matters less for welfare state expansion when
agrarian groups are weak.
We would like to thank Bjørn Høyland, Henning Finseraas, Jon Fiva, Andreas Kotsadam, Jørgen Møller, Øyvind S.
Skorge and attendees at workshops at Aarhus University and at the Institute for Social Research (ISF), Oslo, for very
helpful comments and suggestions. Thanks also to Michael Miller for kindly sharing his data.
1. Introduction
We argue that rural interests hinder the enactment of welfare policy legislation or critically shape
the structure of such legislation when enacted, depending on the electoral system they operate
within.1 More specifically, we propose – and find strong evidence – that rural groups, mainly
representing agrarian interests, effectively “veto” welfare legislation under plurality or
majoritarian (henceforth “majoritarian”) systems, at least when they can draw on substantial
power resources.2 In majoritarian systems, agrarian groups, which often have strong interests in
slowing down welfare state expansion, can more easily win majorities when electorally strong, or
pressure candidates in undecided districts to work against welfare legislation. This is not so under
proportional representation (PR) electoral rules, where even powerful rural groups are unable to
arrest welfare state expansion. Under PR, rural groups often rather settle for post-electoral
bargaining and compromise with urban groups, entailing new welfare legislation.
Much work exists on the development and expansion of the welfare state, but the role of rural
interest groups in affecting this development remains a comparatively understudied subject.
Nonetheless, some studies have suggested – in contrast with our argument below – that rural
interests have helped bring about encompassing welfare states, often drawing on historical
developments in Scandinavian countries3. We provide an alternative interpretation of these
developments below. More generally, the major studies that do consider how agrarian interest
groups shape, or have historically shaped, welfare expansion mainly treat them as an indirect
force represented by rightist parties, focus more narrowly on the role of family farmers, or
There exists a well of specific electoral rules that further distinguish systems within the broad “majoritarian” versus
“proportional” categories (e.g., Cox 1997; Grofman and Lijphart 2003). However, for the purpose of our theoretical
argument, the broad categorization is sufficient for detailing the expected political dynamics. While we also test
models employing mixed and semi-PR systems as a separate category in our empirical analysis, most models are run,
and yield very clear results, even when employing the cruder dichotomization. We leave the potential importance of
more nuanced system characteristics for future research, but note that the more fine-grained our distinctions are, the
fewer the degrees of freedom in the analysis – the extreme being one “idiosyncratic” electoral system per regime.
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highlight their diminishing power with the advent of industrialization.4 Despite the latter
observation, agrarian groups remained sizeable long into the 20th century even in industrialized
OECD countries (and still remain sizeable in many other democracies today), and the literature
on interest group politics highlight the capacities of rural interests to organize and realize their
policy preferences even when moderately sized. 5
Thus, this paper bridges and contributes to two large literatures, on welfare state development
and on effects of electoral institutions, by placing the focus on the role of electoral system
features in affecting the strategies, and eventual success, of rural interests in restraining welfare
state expansion. The literature on the (political and policy) effects of electoral systems argues that
majoritarian systems reduce public spending and concentrate resources to local interest groups,
but has not elaborated on how such systems, more specifically, help rural interests hinder the
expansion of welfare policies. 6 We show how placing explicit attention on rural interest groups,
and how they operate under different electoral systems, contributes to explain variations in
welfare state expansion – both historically (mainly in developed democracies) and currently
(mainly in less developed democracies).
In the next section, we review relevant literature on electoral systems. Thereafter, we elaborate on
our theoretical argument, drawing on the historical experiences of Great Britain and Norway for
illustration. After that, we present our data material and discuss operationalizations and design.
Before the final concluding discussion, we present the large-n empirical analysis. We employ a
newly collected cross-section time series dataset on welfare state programs in six major policy
Given the strong correspondence between agrarian and rural interest groups in most countries, we use “rural” and
“agrarian” interchangeably below. Empirically, our main measure taps strength of agrarian groups, more specifically,
but results are similar in tests using a broader measure capturing rural groups, more generally.
3 Baldwin 1990; Esping-Andersen 1990; Esping-Andersen and Korpi 1986; Manow 2009
4 e.g. Flora and Heidenheimer 1981; Huber and Stephens 2001
5 see, e.g., Acemoglu 2001; De Gorter and Swinnen 2002
6 Iversen and Soskice 2006; Lijphart 2012; Persson and Tabellini 2004; Persson, Roland, and Tabellini 2007;
Rogowski 1987; Vernby 2007
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areas, including data from 96 democracies with time series from 1871−2002. We find very robust
support for the key hypothesis from our argument – the negative effect of having strong rural
interest groups on welfare state expansion is more substantial under majoritarian systems than
under PR – for instance when using our baseline negative binomial model specification, and even
when controlling for country- and time-fixed effects. The result is also robust to employing
different statistical techniques, different operationalizations of key variables, different controls,
and across relevant sub-samples. When rural interests are at least moderately strong, far fewer
major welfare state programs are introduced in majoritarian than in PR systems. As expected,
there is no robust evidence that majoritarian systems are less likely to adopt welfare programs
when rural interests are weak. Hence, the strength of rural interests transfers into greater policy
impact under majoritarian rules than under PR.
2. Electoral systems, political dynamics, and policy outcomes
Electoral systems matter for various outcomes, including which groups are represented in the
legislature7, and they also shape the incentives of the politicians that are ultimately elected8.
Without reviewing this literature in its entirety9, we note some findings of direct relevance to our
argument, focusing on distinctions between majoritarian and PR systems.
First, Duverger10 observed that majoritarian systems – due to “mechanical” and “psychological”
effects – tend to reduce the number of effective parties relative to PR. This strengthens
incentives for various groups, such as business or agricultural interests, to join together under
larger and more loosely knit parties. 11 Second, the lower number of effective legislative parties
(and the steep vote-seat share relationship discussed below) promote single-party majority
e.g., Lijphart 2012
e.g., Persson and Tabellini 2004
9 Consult, e.g., Rodden 2009
10 Duverger 1951; see also Cox 1997
11 Martin and Swank 2008
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governments in majoritarian systems, whereas coalition governments are more likely under PR12.
Third, with some caveats related to the geographical distribution of voters, a percentage point
change in vote share has larger ramifications for legislative seats in majoritarian systems than in
PR13. This increases the sensitivity of parties, and particularly of exposed candidates, to the
demands of their voters under majoritarian rules, inducing increased “accountability” and
“responsiveness”.14 Candidates and parties turn particularly responsive when voters are organized
around clearly formulated interests15, and when voters can credibly threaten electoral boycotts or
voting for alternative candidates or parties. Further, majoritarian elections often hinge on a
limited number of undecided districts16, allowing well-organized interests groups to target a few
(highly responsive) candidates for policy concessions.
In the next section, we detail how such differences in “political logics” make agrarian interests
better able to block enactment of comprehensive social policy programs under majoritarian
electoral systems than under PR. While this particular link has not been identified, extant studies
have documented that electoral systems have several other, related, policy consequences: Persson,
Tabellini, and Trebbi17 highlight how the accountability and responsiveness properties of
majoritarian systems allow voters to constrain corruption, while Rogowski and colleagues18
propose that higher accountability under majoritarian rules induces the adoption of policies
lowering price levels and inflation for consumers. This responsiveness aspect may arguably also
lead to “less beneficial” policy outcomes. Rogowski19 highlights how PR systems are more
conducive to free-trade policies and majoritarian systems to protectionism of targeted sectors,
e.g. Powell 2000
Persson, Roland, and Tabellini 2000; Powell 2000
14 Clark, Golder, and Golder 2012; Vernby 2007.
15 see, e.g., Rogowski 1987
16 Persson, Roland, and Tabellini 2000
17 Persson, Tabellini, and Trebbi 2003
18 e.g. Chang et al. 2010; Chang, Kayser, and Rogowski 2008; Rogowski 1987; Rogowski and Kayser 2002
19 Rogowski (1987)
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suggesting that geographically concentrated interest groups can more easily lobby or pressure
individual candidates in exposed (and small) districts under majoritarian rules.
The electoral system also matters for policies pertaining to public spending, with further
implications for, e.g., redistribution20 and economic growth21. Majoritarian rules alter the
composition of public spending so that spending is typically oriented less towards universal
programs and more towards targeted, narrow programs and projects22. PR systems also induce
higher overall levels of spending (and taxation). Persson, Roland, and Tabellini23 suggest that this
stems from PR inducing coalition government, where all partners push their pet policies, whereas
Iversen and Soskice24 highlight that PR facilitates center-left governing coalitions. Indeed, the
latter study provides evidence that PR thereby enhances redistribution. Insofar as democratic
welfare programs have progressive consequences, our argument below thus provides further
detail to the PR—redistribution link proposed by Iversen and Soskice.
3. The strategies and bargaining of rural interest group under different
electoral systems, and its consequences for welfare policies
After having reviewed the more general features of electoral systems, our argument specifies how
they expectedly manifest themselves in moderating the influence of strong rural interests on
welfare state expansion. We do so by separately treating the majoritarian, and then the PR
context. Before that, we elaborate on the second vital component of our argument, namely the
preferences and power resources of rural interest groups.
3.1 The preferences and power resources of rural interest groups
Iversen and Soskice 2006; Manow 2009
Knutsen 2011
22 Persson and Tabellini 2004
23 Persson, Roland, and Tabellini 2007
24 Iversen and Soskice 2006
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What policies would rural groups want to implement if they were allowed to pick freely? While
there is certainly heterogeneity of actors and preferences in such groups within (and between)
countries, preferences are widely assumed to be fairly congruent and clear in some policy areas. 25
These include food import tariffs and quotas, and agricultural subsidies. If our argument holds
more generally (i.e., also in other policy areas than welfare legislation), we should expect, for
example, agricultural import tariffs to be higher, under majoritarian systems, everything else
equal, at least when rural interest groups are fairly strong. As detailed below, resourceful rural
groups can more effectively veto policies threatening their preferences under majoritarian
systems than under PR, where they must often yield and try to bargain. If rural interests – even
with abundant power resources – accept losses in some areas, even if they sometimes maintain
their first preference in others, such groups will lose out more frequently in different policy areas
under PR.26
We highlight that rural actors often have strong incentives to work against the introduction of
major welfare state programs. This might, at first glance, seem to contrast with interpretations of
these groups’ policy preferences in some extant studies. Rural interests, and especially family
farmers, have been considered decisive in bringing about the encompassing welfare state, with
researchers pointing especially to Scandinavian countries. 27 Nuancing this view, we argue that the
major rural groups − including landlords, estate farmers, smallholders and even family farmers –
actually have had (and in many countries still have) strong incentives to restrain welfare state
See, e.g., Acemoglu and Robinson 2001
Indeed, when running simple tests on measures capturing tariffs and international trade, we find a resembling
interaction pattern to that documented below on welfare policies. Although this pattern is less robust than for
welfare policies, this further enhances the credibility of our argument (see Appendix A8). We would have wanted to
test similar models on more specific data on, for example, import tariffs on agricultural products than the more
aggregated index that we tested, but we were unfortunately unable to find such data with time series overlapping
those that we study in our core models (which end in 2002). We thus leave a more thorough investigation of the
theoretically interesting interaction between electoral systems and strength of rural interests on trade policies for
future research.
27 Baldwin 1990; Esping-Andersen 1990; Esping-Andersen and Korpi 1986; Manow 2009
25
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expansion.28 How does this square with the perceived role of farmers in some earlier studies? To
exemplify based on the history of one Scandinavian country, we detail how farmers in Norway
attempted to arrest welfare state development as best they could under majoritarian rules, but
only entered into comprehensive welfare policy bargaining (and then only for certain programs),
when their effective veto power was lost under PR.29 Farmers especially worked against the
introduction of unemployment benefits, fearing this would redistribute resources from rural to
urban areas. Farmers were thus not a voluntary “driving force” behind welfare state expansion.
To elaborate, rural groups have several reasons for resisting welfare benefits. First, the
employment risks associated with industrialization is higher in urban professions than rural,
meaning that rural tax-payers end up subsidizing programs they are unlikely to need30. Second,
social policies reduce costs of unemployment in urban professions, and are/were therefore also
assumed to increase urban migration. This, over time, reduces the labor supply for rural
employers, increasing wages and giving rural groups an especially strong reason to resist
unemployment benefits31. Landlords and estate farmers, but also family farmers, have often
advocated that issues of unemployment should be dealt with within the peasant economy itself,
with the landlord either finding new work or feeding the worker in low production periods. 32
Third, the distinction between employers and employee was, and still is, blurred in the rural
sector. Taking on the role of self-employed or employers interchangeably, even primarily (rural)
This proposition is, for example, in line with the historical fact that close to all early social policy programs was
very often restricted to urban workers (e.g., Flora and Heidenheimer 1981); indeed, this pro-urban bias probably
reinforced rural groups’ resistance to welfare expansion.
29 Indeed, accounts of Danish and Swedish welfare state expansion suggest that they follow many of the same
trajectories as we discuss for Norway. For example, rural interests within the liberal party in Denmark was not
necessarily against unemployment insurance, but this was after they had made sure that rural municipalities would
not end up subsidizing urban schemes – see Nørgaard 1997. In Sweden, rural interest were able to veto any
unemployment bill until they enacted a highly circumscribed relief-work system in 1918 - see Edling 2006.
30 Since life expectancy was higher in the country-side until modern times, rural groups would in some countries,
such as Denmark, champion old-age pensions as a way to “extract subsidies” to the country-side see Baldwin 1990
on this points. This incentive disappeared as life expectancy soon increased more rapidly in urban than rural areas.
31 Edling 2006
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wage-workers are unlikely to be beneficiaries of welfare legislation. Instead, they most likely end
up having to pay for its introduction, particularly since their main source of income, land, is easily
taxed.3334 Thus, there are numerous theoretical reasons to expect rural groups to work against
welfare state expansion.
However, having clear preferences alone is insufficient for obtaining one’s ideal policy; one also
needs the capacity to affect decision making. In other words, political actors require power
resources to realize their preferences. In a democratic setting, such resources critically include the
number of voters that can be mobilized. But, also economic resources count35, for instance
because they can be used for lobbying purposes. Further, individual actors with common goals
still need to solve critical collective action problems to work effectively in tandem, and welldeveloped (and well-funded) organizations are key in this regard36. This suggests that only when
rural interests are associated with sufficient resources – in the form of people (and, particularly,
voters), economic production and income, and strong organizations – can they realize their
interests, for instance in stopping the expansion of welfare programs preferred by various urban
actors37.
However, as the literature review indicated, electoral rules are also important for transforming
votes and resources into political clout, and ultimately policies. We thus highlight how the
electoral system affects the capacity of rural groups to realize their preferred policy outcome.
Mares 2003, 74,94–95. Also other factors probably contributed to the lack of support for nation-wide
unemployment programs in rural areas; for example, employment centers were usually restricted to urban areas,
forcing rural workers to travel just to register for benefits.
33 Alston and Ferrie 1985; Ansell and Samuels 2014, 38–39; Boix 2003; Mahoney 2003, 146; Mares 2004; Moore
2003; Stephens 1989; Ziblatt 2008
34 Alternatively, where such legislation cannot be stopped, rural groups have historically often preferred voluntary
social insurance, paid for directly by contributions of urban employers and workers - See Baldwin 1990 and Edling
2006.
35 Przeworski 2010; Rokkan 1966
36 e.g., Olson 1965; Olson 1982
37 Ansell and Samuels 2014; Ardanaz and Mares 2013
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More specifically, we expect otherwise resourceful rural interest groups to be far more capable of
arresting welfare state expansion under majoritarian electoral systems.
3.2 The lack of welfare policy expansion under majoritarian systems
We noted how politicians in majoritarian systems are particularly sensitive to organized interests
and voters in districts that are “undecided”, and they also prioritize “cheaper” districts with few
voters per delegate. After industrialization and urbanization from the mid-19th century onwards,
many majoritarian countries have had far more rural districts and candidates than their
corresponding populations would imply under proportionality Chen and Rodden 2013; Rodden
2010. This should make organized agricultural and other rural interests particularly effective
players. In other words, majoritarian systems have often been biased against urban interests, with
the presence of rotten boroughs and mandate distributions benefiting rural areas Chen and
Rodden 2013; Rodden 2010. Electoral success has therefore been more likely for rural interests in
majoritarian systems.
Second, even with the loss of electoral majority, rural interests groups should have strong
political, and thus policy, influence in majoritarian system. This follows from majoritarian
elections usually hinging on a set of undecided districts38, allowing well-organized interests groups
to target government candidates running there, for example by threatening to withdraw support
if the government goes through with their policy proposals. And, agricultural interests have,
historically, often had coherent, well-structured and effective organizations.39 The generally
steeper mapping from votes to legislature seats in majoritarian systems − with only modest losses
of votes often leading to large seat losses40 – means that politicians are more sensitive to the
preferences of clearly voiced interests. This is particularly so when these interests represent fairly
Persson, Roland, and Tabellini 2000
This same facet of majoritarian systems can, of course, under the right circumstances, be used by other interest
groups; also those that favor welfare state expansion, such as trade unions see ANONYMIZED REFERENCE
38
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broad groups of voters and can credibly be expected to organize, for instance, election boycotts.
Additionally, the size of the electoral district is typically much lower (most often 1 delegate per
district) in majoritarian systems; as Rogowski41 highlights, this further contributes to delegates
being closely linked to particular sectoral producer interests. Hence, delegates representing small
rural districts will likely be strong advocates of their constituents’ preferences. In PR systems
delegates will typically come from districts including both urban and rural areas and rather be
more responsive to the leadership of national-level parties (which are typically stronger under
PR42).
To illustrate, we discuss how the British majoritarian electoral system may contribute to explain
one interesting comparative puzzle in early welfare state development: Why was Great Britain,
during the late 19th and early 20th centuries, a laggard in enacting major welfare programs
compared to several continental European countries? Various factors often linked to welfare
state expansion (e.g., income, industrialization, urbanization and union organization) were more
weakly present in, for example, Austrian-Hungary, Italy, France, and Germany in 1900.43 The
absence of any major British welfare program except for an employer liability scheme for
industrial accidents, cobbled with the presence of structural factors that presumably facilitate
welfare development, require explanation.44 The traditional explanation has been the presence of
a strong liberal tradition.45 But, this runs counter to the fact that liberals introduced the first
e.g., Powell 2000
Rogowski 1987
42 Gerring and Thacker 2008
43 Great Britain was leading internationally in union density (13% vs 2% in Austrian-Hungary, 2% in Italy, 3% in
France, and 6% in Germany; data from ANONYMIZED REFERENCE) literacy (94% vs 72% in AustrianHungary, 54% in Italy, 82% in France, missing data for Germany; data from Banks 2013), and GDP per capita (5443
PPP-adjusted USD in 1990 prices vs 3760 USD in Austrian-Hungary, 1878 USD in Italy, 3265 USD in France, and
3948 USD in Germany; data from Maddison 2007).
44 Orloff and Skocpol 1984 claim that Great Britain was a pioneer in lunching the welfare state only makes sense in
the comparison with the United States, and does not take into account the structural factors that would predict major
expansion in Great Britain compared to other continental nations. In comparison, Austrian-Hungary, Italy and
France had enacted two major social policy programs (in the areas coded by our data), and Germany four.
45 Rimlinger 1971; Thane 1978; Thane 1984
40
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major social policy schemes and tried (unsuccessfully) to tax the rural elite.46 Hence, it was
perhaps not the absence of parties with an ideological position compatible with social regulation
and taxes that hindered British welfare development.
The British case makes sense, however, when considering how the electoral system – but
admittedly also other aspects of the political system, such as the House of Lords – allowed rural
elites to restrain tax growth and block welfare legislation. The infamous Rotten Boroughs
disappeared with the 1832 Reform Act, and later Reform Acts of 1867 and 1884, and the
Redistribution of Seats Act of 1885, expanded the franchise and evened out vote-seat share
discrepancies between different constituencies. Despite this, rural interests – and notably the
Gentry – were still prominent in parliament for decades. While only around 11% of British GDP
came from agriculture at the time, the 1885 election was the first where MPs related to commerce
and industry outnumbered those related to the landed aristocracy47. Prior to 1885, Wright notes
that “Calne (Wiltshire) had one seat for 5000 population48; Liverpool had one seat for 185,000. A
county division of Lancashire, industrial in character, had one seat for 150,000, whilst a rural
borough in the south-west had one seat for 12,000”. While boroughs with populations smaller
than 15 000 ceased to exist with the 1885 act, districts with 15 000 sent one MP to parliament,
just as those with 50 000; and, the larger urban areas only sent two. This helped ensure
overrepresentation of rural interests which, together with Conservative Party domination of the
House of Lords and government, allowed them to stave off welfare expansion for yet some years,
during which various programs were enacted in less industrialized countries. Britain kept its
limited welfare model, which aim was to only “aid the most impoverished”49, until the early 20th
Adelman 1995; Boix 2010; Packer 2001, 22:62–63
Searle 2005, 138
48 Wright 1970
49 Baldwin 1990: 100
46
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century.50 Thus, British agricultural interests remained effective in maneuvering the country’s
majoritarian electoral system (and two-chamber parliamentary system) to arrest welfare state
expansion.
In sum, rural interests have typically been overrepresented in majoritarian systems, and the
system also creates strong responsiveness links between politicians from these overrepresented
districts and organized rural interest groups. We propose that these factors work in tandem,
allowing rural interests (that control at least a modest amount of power resources) to restrict
welfare state expansion under majoritarian electoral rules.
3.3 Welfare policy expansion under PR systems
In PR systems, neither overrepresentation of rural interests nor the strong links of responsiveness
apply to the same extent51, thereby mitigating the veto power rural interests can employ to further
their ideal policies. Thus, rural interests groups will expectedly more often have to “accept” the
introduction of welfare legislation in democracies with PR systems. Importantly, PR systems
most often lack pivotal districts, and have a smaller rural bias in the distribution of votes to
mandates. It is difficult for any single group to obtain electoral majorities under PR, and coalition
governments or minority governments (seeking ad hoc support from different parliamentary
constellations) are far more common52. This is amplified by the “Duvergerian” mechanisms
inducing higher party system fragmentation under PR. Regarding rural interests, more specifically,
When the breakthrough finally took place it was only because the landed elite was “attacked on all fronts”. The
new liberal government of 1906, with its people budget, aimed to effectively redistribute power from landed elites to
urban and rural tenants’ government with a flurry of proposals from new tax rules, redistributive land-arrangements
and social policies. Landlords in the house of lords were effective in blocking property taxes targeted to rural elites,
and land-reforms designed to effectively shift power from the landlord and estate owners to smallholders was mostly
ineffectual (Packer 2001, 62–63), but had to concede on social policy. From 1906 to 1911, liberal governments with
the support of labor candidates enacted programs covering old-age, health and sickness unemployment.
51 Rodden 2010; Vernby 2007
52 Müller and Strøm 1999; Powell 2000
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rural organizations with anti-welfare aspirations are usually represented within larger parties
under majoritarian systems. In contrast, they often form their own party-organization under PR.53
Under majoritarian rules, the combination of a few pivotal districts with steeper vote mapping
increase incumbents’ sensitivity to pressure or intimidation. This allows agrarian interest groups
to influence policy through the mechanisms sketched above, even without organizing a separate
political party. In contrast, PR systems more likely yield unsuccessful outcomes from the
viewpoint of agrarian interests – such as the passing and implementation of welfare state
programs without their approval – simply due to the loss of de facto veto power under PR.
Inter-party bargaining may sometimes provide rural interests, often organized in a distinct,
moderately sized party, with partial success under PR. The political dynamics of PR systems could
induce rural groups and parties representing them to enter into negotiations with other groups
and parties, such as social democratic parties representing urban workers or liberals representing
urban middle classes. Since the outcome of an urban-urban coalition could lead to both welfare
state expansion and the absence of tariffs and agricultural subsidies (the “worst-case scenario”),
rural groups have strong incentives to enter such negotiations. Indeed, they might even be willing
to concede certain types of welfare expansions that are not too directly hostile to their interests –
while avoiding others such as dramatic expansion of unemployment benefits programs − and
bargain for compensatory payments for accepting such reforms (particularly given that the
alternative option often is the realization of their “worst-case scenario”). Even if we would expect
differences in the specific bargains struck between the rural interests and, for example, liberals
(maintaining export subsidies perhaps being a more likely compensation) or social democrats
The actions of the Norwegian agrarian organization (Norsk Landmandsforbund) are illustrative - see Rokkan 1987.
First established in 1896, the farmers were one of the strongest interest organizations in Norway. Under majoritarian
rules, the farmers focused their activity on influencing the two main parties at that time, the Conservative Pary
(Høyre) and (particularly) the Liberal Party (Venstre). This policy was abandoned in 1920, coinciding perfectly with
the introduction of a PR system in Norway, when the agrarians set up their own Farmer Party and won
representation in the following election.
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(maintaining agricultural tariffs perhaps being a more likely compensation), we expect one endresult to be a more frequent enactment of social policy programs. Note that enactment of social
policy programs is also a likely outcome of coalitions between urban middle classes and urban
workers. In sum, PR systems should more often observe welfare program expansions than
majoritarian systems (at least as long as the agricultural sector is fairly sizeable).
The Norwegian case in the decades prior to WWII illustrates how agrarian interests in
proportional systems must accept some degree of welfare expansion, but also how they sometimes
can make effective legislative bargains to maintain their favored policy in other areas. In the
European context, Norway was a late industrializer and a poor agrarian society in the early 20 th
century. Norway is particularly interesting since it changed from a majoritarian to a proportional
system in 1920. At the time, about 34% of GDP came from agriculture. The Liberal Party, with
strong ties to agricultural interests, had held the prime minister for most years since
independence from Sweden in 1905. Unsurprisingly, by 1920 rural, majoritarian Norway was the
only Scandinavian country without an implemented national old-age pension program.
The Liberal Party was severely weakened in 1920, when the agrarian interests broke out and
formed the Farmer Party with the introduction of PR. The breakthrough for old-age pensions
came only 3 years after. In 1923 a government led by the conservatives, with social democratic
support, pushed through Norway’s first old-age pension system. The reform was never
implemented, however, much because of the drastic economic crisis that shook Norway and the
rest of Europe from the late 1920s54.
The implementation of old-age pensions had to wait some years, when the rural interests were
displaced enough by the extended economic crisis of the 1930s to accept social policies in trade
54
Seip 1994
14
for other policies. This culminated in the 1935 Crisis Agreement (“Kriseforliket”); social
democrats provided their support for agricultural subsidies and tariffs in exchange for the
farmers’ support for a social democratic government and social policy measures55. With Farmer
Party backing, the social democratic government thus implemented the proposed 1924 old-age
pension program in 1936.
Unemployment insurance followed a different trajectory. Norway introduced a voluntary
insurance scheme in 1906, but this was only after the rural coalition blocked reform initiatives in
1902-1904, and severely circumscribed the program. Even if the Liberal Party supported the
initiative (the trade unions asked for subsidies in 1902, but the question was put forward to the
parliament by a liberal candidate), candidates representing farmer interests voted against their
own party recommendation. The ensuing system of 1906 was therefore to put the main cost of
the program on the municipalities, with extra transfers to rural and agrarian municipalities56. This
effectively shielded the rural interests from the costs of industrial worker joblessness, and worked
against urban migration. It also left the program highly inadequate to face large economic
downturns, as illustrated during the 1920s when several union-run insurance funds (“kasser”)
went bankrupt57. As expected, the Liberal Party was effectively split under the 1902-1904 debates
between representatives from urban and industrial areas, and those representing rural
constituencies.58 Then, in 1920, the switch to PR mitigated the veto-power of the agrarian
interests, and contributed to them entering into bargaining on expanding the Norwegian welfare
state. However, when compulsory unemployment insurance was put on the table, it proved too
big a pill to swallow for the Farmer Party. It voted against the proposed legislation in 1937, but
the social democrats succeeded in getting the reform through in any case with the support of
Rokkan 1987, 77
Edling 2006, 106
57 Rothstein 1992, 45
55
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(what was left of) the Liberal Party. Hence, the rural interests were unable to stop the compulsory
coverage unemployment program under PR.
The Norwegian case thus closely follows the trajectory predicted by our more general argument;
a switch to PR reduces the effective veto power of rural interests, and opens up for welfare state
expansion – sometimes despite direct opposition from rural interest groups, and sometimes with
the “support” of these groups, but then only in exchange for considerable policy concessions.
3.4 Specifying the empirical implications
While suggestive, the British and Norwegian cases do, of course, not provide confirmatory
evidence for our argument. For example, the differential positions taken by the rural elites in
these countries could also stem from differences in rural ownership structure59; in 1900 only 12
percent of holdings were “family farms” in Great Britain compared to 74 in Norway, implying a
more egalitarian rural sector in Norway (which may make welfare programs more easily
acceptable, see Baldwin 1990. Further, even if our illustrations are embedded in specific contexts,
the logic of our theoretical argument should be more broadly applicable, both in space and time.
As long as rural interests have incentives to block welfare state expansion, (at least many of) the
electoral system mechanisms highlighted should generate a similar pattern in, for instance, young
African or Asian democracies today.
We therefore turn to more systematic tests, using data from 96 countries with some time series
covering more than 130 years, in models controlling for various factors that may confound the
relationship of interest. While employing such an extensive sample may introduce concerns of
unit-heterogeneity (and we do also test geographically and historically more restricted samples), it
Sickness insurance observed a resembling trajectory to unemployment under majoritarian rules. When the issue of
compulsory sickness insurance was raised in 1897, representatives from the countryside were able to postpone the
enactment until 1909 and urban workers ended up bearing the brunt of the contributions Carroll 2005, 65–66.
59 see, e.g., Ansell and Samuels 2014
58
16
enables us to account for country- and time-fixed effects on welfare-state characteristics. This is
critical for mitigating bias that may, for instance, stem from PR systems being systematically
adopted in countries that are more prone to have expansive welfare states, or that agricultural
interest groups have been gradually weakened (relative to urban) in many countries over the last
two centuries. The country- and time-fixed effects are especially important since it is very hard to
identify strong and valid instruments, for instance, for electoral system (see our discussion of
instrument variable models below and Acemoglu60). To further mitigate such issues, we also, for
example, test models including the lagged dependent variable as a regressor.
The two first (naïve) hypotheses that we test are:
H1) PR systems increase the number of major welfare programs enacted relative to majoritarian
systems.
H2) A more sizeable (and thus more powerful; see discussions in Section 4) agricultural sector
reduces the number of major welfare programs enacted.
However, we remind that the above argument assumes that members of rural interest groups not
only have the ability to vote (meaning that our argument is restricted to fairly modern
democracies), but that these voters are numerous in relative terms. Further, it assumes that these
interests have their own organizations for coordinating actions against “pro-welfare interests”,
and their leverage is only sufficient when they remain a fairly important cornerstone of the
economy. Moreover, Acemoglu and Robinson61 detail how the viability of interest organizations
critically depends on having at least a modest number of members. All of these factors relate to
the relative economic importance of the agricultural sector. As the relative size of the agricultural
sector declines, so would their voting numbers and financial resources compared to other
60
61
Acemoglu 2005
Acemoglu and Robinson 2001
17
interests groups, such as urban workers and their parties (e.g., social democratic parties, urban
liberal parties) and interest organizations (e.g., trade unions). We therefore expect the difference
between majoritarian and PR systems, in terms of welfare state extension, to be clear and
substantial only when the agricultural sector is fairly sizeable, and that the difference should
disappear when the agricultural sector dwindles below a critical level where it can be considered
politically negligible (under any electoral system). This leads to our main hypothesis:
H3) The effect of a more sizeable agricultural sector on the number of major welfare programs
enacted is larger under majoritarian systems than under PR.
4. Data and empirical design
In order to test our hypotheses we first run a set of negative binominal models on welfare state
extension using data on the number of major welfare state transfer programs enacted. These
baseline models cover 96 democracies, with maximum time series from 1871−2002. In contrast
to previous investigations of electoral institutions and social policy, our sample contains 27
within-country changes in the electoral system (PR vs Majoritarian) measure. Hence, our
extensive sample allows us to (also) employ fixed effects models that exclude all cross-country
variation, thereby mitigating omitted variable bias. This is important, since it is otherwise difficult
to separate effects of the electoral system from those of other (fairly) country-fixed factors, such
as “national norms and values” affecting the preferences of the electorate and other political
actors on welfare state characteristics. We return to particular specifications below, but first
present our measures.
4.1 Data and operationalization of key variables
Data on the six major welfare state transfer programs − old-age pensions; unemployment benefits;
maternity benefits; family allowances; work injury benefits; sickness benefits − are drawn from the recently
18
constructed Social Policies Around the World (SPAW) dataset, which we describe in more detail
in ANONYMIZED REFERENCE. We refer to this paper and the codebook for specifics on
the sources and exact coding rules used. There, we also conduct closer discussions on the
reliability and validity of the data. But, in brief, validity is enhanced through careful crosschecking of several sources.62 The existence of a program is, for practical purposes and possibility
of cross-country comparisons, coded using de jure criteria. In order to distinguish major programs
from minor programs, we only count programs where at least one of the following larger socioeconomic groups is covered: industrial/production workers; small-firm workers; self-employed;
agricultural workers; students; employers; temporary/casual workers; family/domestic workers.
Further, we only code programs regulated trough national legislation. For this baseline measure,
we make no distinction between, for instance, voluntary or compulsory insurance programs, and
strictly means-tested programs based on any property criteria are not considered (programs that
means-test based on income are, however, included).
SPAW includes data for 223 countries, with maximum time series from 1790--2010. Numerous sources were
employed in the coding, including country-specific sources. However, the main sources are the ILO Legislative series
(1919-) and various US Labor Department SSPTW-reports (1937-). In addition to coding the existence of programs
in the various social policy areas, SPAW also contains numerous program-specific variables on eligibility (who can
partake in the program) and distributive potential (the program’s inherent capacity to allocate benefits to members).
62
19
Figure 1: The distribution according to number of enacted major social laws (old-age pensions;
unemployment benefits; maternity benefits; family allowances; work injury benefits; sickness
benefits) for all observations entering our baseline model (Model 5, Table 1).
To capture variations in the scope of the welfare state in our baseline models, we construct a
count variable capturing major welfare state programs in different policy areas (we also consider
models on whether at least one program was or was not introduced in a given year). Since we
have data on six major types of programs, this summary variable goes from 0–6, with the average
country-year observation in our sample having 4 programs and the standard deviation being 2.1.
Figure 1 provides a histogram with the distribution on this count variable for the about 3000
country-year observations entering our baseline Model 5 from Table 1 (for descriptive statistics
on all variables, see Appendix A1).
To measure the power resources of rural groups, we mainly use agricultural income as share of
GDP as our proxy, with data provided by Miller 2013. The mean score in our sample is 31%,
with a standard deviation of 22%, whereas the minimum and maximum scores are 0 and 93%,
20
respectively. Thus, we follow Dovring63 in that the strength of agricultural interests follows their
economic position. As agricultural share of GDP declines, we assume that the relative bargaining
power of these interest groups tends to decline. While this measure is not ideal (as it, for example,
does not capture the organizational characteristics pertaining to rural interest groups), it has the
clear advantage that data exists over the entire period of our inquiry.
To check the validity of this measure, in terms of capturing a broader concept of rural interest
group strength, we use what data is available on historical agricultural organization64, and coded
the number of organized workers in the agricultural sector for the years 1896 and 1925. The
correlation between this measure and agricultural income/GDP is decent (.54; 27 obs),
suggesting that the latter may tap also other aspects of rural interest group strength than just their
economic resources. Alternative measures, such as the number of people employed in agriculture,
are less appropriate, also for instance due to shorter time series, but we still note that the
correlation between our measure and the measure from Banks 2008 on the share employed in
agriculture is very high (.98). We also conduct robustness tests using data on urbanization, which
is the only other relevant measure we know of with extensive coverage, as an alternative proxy on
the strength of rural groups.
To measure electoral systems, we use the data collected by Schjølset (2008, pp. 135–142), and
which was used by Knutsen (2011) to estimate the effect of electoral systems on economic
growth. Schjølset’s data are unique in that they provide extensive time series going back to the
19th century, being the only available source allowing tests over the entire relevant time period.
Schjølset’s classification is tri-partite, distinguishing mixed/semi-PR systems from plurality and
majoritarian systems, and from “full” PR systems. As our theory only refers to the
PR−majoritarian distinction, we start out by creating a dummy variable coding PR systems as 1,
63
Dovring 1956
21
and majoritarian as well as mixed and semi-PR systems as 0. To ensure that this somewhat
arbitrary placement of the “hybrid category” does not drive results, we also test models
employing dummy variables for both semi-PR and PR systems, with majoritarian as the reference
category.
4.2 Choice of empirical model and control variables
Since our dependent variable is a count variable, a standard OLS model will be both biased and
inefficient. Count models are constructed to remedy this65. The simplest count model, the
Poisson model, requires that the conditional mean of the dependent variable is equal to the
conditional variance. This does not seem to hold in our sample, as it shows significant overdispersion. Therefore, we opt for a negative binominal model, which corrects for over-dispersion
and narrows the estimated confidence intervals compared to Poisson regression. Nevertheless,
our results are robust to employing Poisson and OLS models (see Appendix A2), as well as logit
models on the adoption of a new program.
We test models using various sets of controls. We start out with fairly sparse models, but also test
quite extensive (“extra” controls are discussed when introduced below). First, both the
enactments of social policy laws and shifts in electoral systems have tended to follow periodic
patterns66, and overall the late 19th and 20th history has seen a clear expansion of major welfare
programs globally. Our argument suggests that this, in part, stems from the relative decline of
agriculture over time, and controlling for temporal trends may thus attenuate our results (indeed,
results turn even stronger when omitting temporal controls). Nevertheless, there are too many
other potentially relevant factors correlated with time, such as ideological currents. Thus, our
Flores 1971
King 1988
66 Flora and Heidenheimer 1981; Lijphart 2012
64
65
22
baseline models include decade-fixed effects. The results are robust to using alternative
specifications such as a linear time trend or year dummies.67
Variation in enactment of electoral systems and social policy laws, and prevalence of agricultural
production, may also stem from differences between countries in fairly stable characteristics, such
as geographical location, soil and climatic characteristics, religious affiliation, or other slowchanging cultural differences. We include country dummies to control for such differences (but
also test models allowing cross-country variation). The inclusion of country- and time-fixed
effects implies that our baseline model is fairly conservative, and it is thus noteworthy that they
yield such clear results.
We always control for log GDP per capita68, for example because richer countries have more
resources available for running major welfare programs. We also control for trade openness
(imports+exports/GDP; data from Barbieri, Keshk, and Pollins69
to account for open
economies potentially being more conducive to extensive welfare states70. We increase the
number of controls in subsequent models to further guard against omitted variable bias, for
instance including a measure of family farm holdings to control for differences in agricultural
structure. The results are robust.
Finally, we test models on reduced samples, both spatially and historically, to obtain indications
of whether our argument applies only in certain countries and eras or more generally across time
and space.
However, we note that there were issues with calculating the variance-covariance matrix, and more specifically the
standard errors for the year dummies for some of the latter models.
68 Using data from Maddison 2007
69 Barbieri, Keshk, and Pollins 2008
70 See Cameron 1978 and Mares 2004
67
23
5. Results
Table 1 presents results from our baseline models and selected robustness tests; additional
robustness tests are reported in the Appendix. The two first models pertain to our “naïve”
Hypotheses 1 and 2 on the non-conditional relationships between electoral system and size of the
agricultural sector, on the one hand, and the scope of the welfare state on the other. These
negative binomial models include the PR dummy, agricultural income/GDP, log GDP per capita,
trade openness and decade dummies. Model 1 allows for cross-country comparisons by omitting
the country dummies, whereas Model 2 includes country dummies.
The results for PR are very similar when including and excluding the country-fixed effects; the
point estimate from Model 2, for instance, suggests that switching to a PR system – for a country
with mean scores on all other variables – increases the predicted number of major welfare laws
enacted by 1.1, with the 95% confidence interval extending from 0.9 to 1.4. The PR coefficients
are highly significant both in Model 1 and 2. Hence, these simplistic (in the sense that they
exclude the theoretically relevant interaction term) models yield clear support for Hypothesis 1.
Regarding Hypothesis 2, there is a negative and highly significant relationship between
agricultural share of GDP and welfare laws enacted. Hence, there is evidence corroborating the
expectation on how strong agricultural interests not only have the incentive, but also the political
power, to stall welfare state expansion.71 Regarding the control variables, Models 1 and 2 report
that rich countries systematically enact more laws, whereas more open economies, everything else
equal, are less likely to do so.
Nonetheless, our theoretical argument suggests that Model 1 and 2 in Table 1 are miss-specified.
More specifically, we expect that the effect of the electoral system on the scope of the welfare
state should be contingent on the clout of agricultural interests. Likewise, the effect of
24
agricultural interests’ resources on constraining the welfare state should be far weaker in PR
systems than majoritarian. To incorporate this and test Hypothesis 3, we add a multiplicative
interaction term (PR*Agricultural income/GDP).
The interaction models report clear support for Hypothesis 3; the estimated impact of PR on
enactment of major welfare laws increases systematically, and sharply, with the agricultural
sector’s size in the economy. In other words, the impact of plural-majoritarian systems in
restraining the welfare state is far stronger in contexts where agrarian interests have more
resources. The interaction term is always highly significant. For instance, t=5.4 in Model 3
including decade dummies but excluding country dummies, t=14.7 in Model 4 excluding decade
dummies but including country dummies, and t=9.3 in Model 5 including both decade- and
country dummies. The result is also retained when rather including year dummies or a time trend,
and when running Poisson or OLS (e.g., Model 6, Table 1) regressions instead of negative
binomial.
We probed alternative specifications also of the model without interaction term (e.g. year dummies/time trend,
adding controls, or employing alternative estimators), and both PR and agricultural share of GDP are robust.
71
25
Table 1: Electoral system, rural interests, and enactment of major welfare laws
Dep.var.:
Estimation:
PR
Agricult. inc./GDP
(1)
Nr. enacted
Neg Bin
(2)
Nr. enacted
Neg Bin
(3)
Nr. enacted
Neg Bin
(4)
Nr. enacted
Neg Bin
(5)
Nr. enacted
Neg Bin
(6)
Nr. enacted
OLS
(7)
Nr. enacted
Neg Bin
(8)
New enacted
Logit
(9)
Nr. enacted
Neg Bin
(10)
Nr. enacted
Neg Bin
(11)
Nr. enacted
Neg Bin
(12)
Nr. enacted
Neg.Bin.
(13)
Nr. enacted
Neg Bin
0.264***
(20.82)
-0.00504***
(-9.62)
0.287***
(8.02)
-0.00450***
(-8.23)
0.183***
(10.18)
-0.00678***
(-9.62)
0.00326***
(5.43)
0.281***
(4.82)
-0.0199***
(-14.86)
0.0180***
(14.66)
0.0349
(0.87)
-0.0106***
(-10.39)
0.00833***
(9.33)
0.426***
(3.83)
-0.0148***
(-7.14)
0.00716***
(3.31)
-0.0684*
(-2.36)
-0.00585***
(-8.13)
0.00611***
(9.58)
-0.507
(-0.35)
-0.156***
(-3.87)
0.0892**
(3.06)
0.0805
(1.86)
-0.0105***
(-10.42)
0.00760***
(8.45)
-0.0486***
(-5.65)
-0.00853***
(-8.50)
0.00683***
(8.35)
0.0197
(0.33)
-0.0123***
(-8.75)
0.00983***
(7.75)
-0.0398
(-0.65)
0.00395*
(2.57)
0.576***
(11.15)
-1.082***
(-6.54)
-0.0679***
(-13.58)
0.0449***
(10.02)
PR*Agric.inc./GDP
Semi-PR
Semi-PR*Ag.in./GDP
0.0112***
(11.41)
-0.00689***
(-9.53)
Urbanization
PR*Urbanization
Lagged dep. variable
GDP/capita (log)
Trade Openness
0.107***
(7.93)
-0.249***
(-8.03)
-0.0251
(-1.04)
-0.308***
(-15.04)
0.0941***
(6.86)
-0.191***
(-6.13)
Yes
Yes
Yes
Yes
2998
96
1871-2002
0.232
10250.5
2998
96
1871-2002
0.290
9660.3
2998
96
1871-2002
0.233
10241.0
0.269***
(18.75)
-0.0642***
(-3.85)
0.00713
(0.40)
-1.286***
(-5.22)
0.452
(0.53)
-11.99**
(-3.19)
0.364***
(15.17)
-0.411***
(-12.27)
-0.0420
(-1.78)
-0.220***
(-10.67)
1.377***
(23.33)
-0.496***
(-3.78)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
2998
96
1871-2002
0.232
10410.2
2998
96
1871-2002
0.292
9637.2
2998
96
1871-2002
2982
96
1871-2002
0.308
9381.4
2192
45
1900-2002
0.239
539.3
Family Farms
-0.0398
(-1.73)
-0.212***
(-10.43)
-0.221***
(-9.96)
-0.0243
(-1.09)
0.725***
(8.00)
-1.684
(-1.68)
Yes
Yes
-0.0472**
(-2.92)
0.0302**
(3.24)
0.000101
(0.35)
0.000515***
(3.52)
0.216**
(2.98)
0.146***
(4.75)
-0.00543**
(-3.07)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
2962
96
1871-2002
0.296
9499.9
1113
48
1951-2002
0.077
4059.4
2998
96
1871-2002
0.293
9639.6
3086
97
1871-2002
0.292
9914.5
1100
40
1871-1959
0.335
3297.3
-0.0254
(-0.99)
-0.198***
(-9.78)
-0.00486***
(-8.68)
Union Density
Democracy (BMR)
Population (log)
Gov.spending/GDP
Country dummies
Time period dummies
Observations
Countries
Max time series
Pseudo R2
AIC
Notes: * p < 0.05, ** p < 0.01, *** p < 0.001. Dependent variable is the number of major welfare programs enacted across the six major social policy areas, or a dummy capturing whether at least one program was
enacted that year. t-statistics are reported in parentheses. The negative binomial models are calculated with Huber sandwich standard errors, and the OLS model with panel-corrected standard errors and a common
Ar(1) error correction term.
26
Models accounting for both country- and time-fixed effects provide a strong test; they account,
e.g., for the possibility that our results are driven by particular countries being more likely to
adopt PR and promote welfare legislation for various other reasons. To further account for
potential endogeneity biases, particularly related to endogenous adoption of electoral systems72,
we also tested instrumental variable models. Finding instruments for electoral system that are
both strong and valid has proven hard. Still, we tried out various combinations of the suggested
instruments from Persson and Tabellini73, related for example to the last time point of
constitutional change (using global constitutional fashions as exogenous variation). We tested
different panel data 2SLS specifications, and they all replicate the highly significant interaction
term, as predicted by our argument and Hypothesis 3 – and, also the sign of the linear terms for
PR and agricultural income share correspond with those in our baseline Model 5 and are highly
significant. The instruments are often found to be strong. Nonetheless, the Sargan tests suggest
that the exclusion restriction may not hold in any of the models we tested, and this – together
with the previous criticisms of these instruments and that the point estimates are often
implausibly large – makes us not trust these specifications (which is why we do not report them).
In any case, the significant interaction term holds up also when adding a lagged dependent
variable as regressor (see Model 6, Table 1; Appendix A3), i.e. when controlling for the number
of programs in place in the prior year. Correspondingly, we also tested models (both OLS and
logit) on the adoption of (at least) one new program in a given year, and the interaction term
remains robust. As an illustration, Model 7, Table 1 reports that the interaction term is significant
at the 1% level in a logit model on adoption of a new program including country-fixed effects
and controlling for the number of programs already in place. Hence, Hypothesis 3 finds support
72
73
Cusack, Iversen, and Soskice 2010
Persson and Tabellini 2003
27
independent of whether we consider the number of programs in place or adopting new
programs.
In contrast to the “naïve” Hypothesis 1, postulating an unconditional effect of the electoral
system, our theoretical argument did not suggest that the PR—plural-majoritarian distinction
should matter much for welfare law enactment where agricultural interests are negligible
(although there might exist other arguments implying this). Then again, our interaction models
produce very mixed results for the linear PR term, which could be interpreted as estimating the
effect when there is no agricultural production. For example, Model 3 suggests a positive effect
of PR even when agricultural production is non-existent, whereas Model 5 does not suggest any
relationship.
Figure 2: Predicted number of major social laws (with 95% confidence intervals), by electoral
system, over agricultural income as share of GDP. The predictions are based on Model 5, Table
1, and all other variables in the model are set to their respective mean values.
28
To better illustrate the substantive nature of our findings, Figure 2 draws on the estimates of the
baseline Model 5 to plot the predicted number of major welfare laws for PR and pluralmajoritarian systems, respectively, with 95% confidence intervals around the point predictions.
The predictions are made for a hypothetical observation with mean values on all other variables.
As indicated above, there is no significant difference between PR and majoritarian systems when
agricultural income makes up a minuscule share of the economy. In this case, the 95%
confidence intervals overlap, and the hypothetical “average” observation is predicted to have just
below 5 major welfare laws. However, when the agricultural sector increases just slightly in size,
the difference between the electoral systems turns clear. Already when agricultural share of GDP
is around 10% (the share observed, e.g., in UK around 1900), PR systems are predicted to have
more than ½ additional law and the confidence intervals do not overlap. For agrarian societies
where agricultural income makes up 50% of GDP, majoritarian systems are predicted to have
almost 2 fewer such laws than PR systems. Further, Figure 2 shows that whereas the predicted
number of social laws in majoritarian systems responds strongly to the size of the agricultural
sector, PR systems are always predicted to have somewhere between 4 and 5 laws.
Another way to state the latter point is that the size of the agricultural sector, and the related
resources available for rural interests groups to draw from, has a clear negative impact on the
scope of the welfare state, but only in majoritarian systems. To further highlight this, Figure 3
presents the predicted effect of a 1 percentage point increase in agricultural income/GDP (same
model and assumptions as for Figure 2). Such an increase is predicted to systematically reduce the
number of social laws in both systems, but the predicted reduction is almost 4 times larger in
majoritarian systems.
29
Figure 3: Predicted change in number of major social laws (with 95% confidence intervals), by
electoral system, for 1 percentage point increase in agricultural income/GDP. The predictions are
based on Model 5, Table 1, and all other variables in the model are set to their respective mean
values.
The above-discussed results are not sensitive to the particular control variables entered into the
model. Although the inclusion of country- and year-fixed effects should strongly reduce the
possibility that our results are driven by omitted variable bias, our baseline model is otherwise
sparse. Model 8, Table 1 adds the perhaps most relevant additional control, related to agricultural
ownership structure. Discussing the cases of Britain and Norway, we noted that their differential
ownership structure could have led to differential positions to welfare expansion by agricultural
interests in these cases74. Further, ownership structure could be related to the support for
redistribution, more generally75, and agricultural ownership structure also correlates with electoral
systems (the presence of family farms is much higher in PR than in Majoritarian systems).
Therefore, we control for the share of family farms.76 However, the coefficient for agricultural
Ansell and Samuels 2014; Baldwin 1990; Boix 2003
Barth, Finseraas, and Moene 2014; Luebbert 1991
76 As Vanhanen 1977only reports data per decade, we follow Boix, Miller, and Rosato 2012 in linearly interpolating
missing data between reported observations.
74
75
30
income/GDP remains negative and significant, and the interaction with electoral system still
behaves as theoretically expected, with a t-value of 8.5. Interestingly, as we show in Appendix A4,
the interaction remains significant also when we investigate split samples according to the median
level of the family farms measure in 1871, for both samples. Hence, not only does controlling for
agricultural ownership structure leave our core result unchanged, but our theorized interaction
between the electoral system and strength of rural interests holds up both in societies with an
egalitarian land-ownership structure and in societies with an inegalitarian structure.
More generally, our results are very robust to including various potentially relevant confounders.
For instance, we noted that the British landed interests were able to use the House of Lords to
slow down welfare state expansion, suggesting that other constitutional arrangements (that
possibly co-vary with electoral systems) may drive our result. However, controlling for federalism
and form of government does not alter our core results, as shown in Appendix A6. We also
tested several additional models including other variables that may confound the relationship of
theoretical interest here, such as the organizational strength of the “pro-welfare coalitions”, as
proxied by union density (data from A 2015) and the dichotomous Boix, Miller and Rosato
(BMR) measure of democracy77. Regarding the latter, although our analysis pertains only to
democracies the results could still be affected by the inclusion of autocracies (which could, e.g.,
typically be more agrarian and enact fewer welfare laws), since Schjølset uses and inclusive
operationalization of democracies (Polity index ≥3). The results hold also when we restrict the
sample only to BMR democracies, or use a higher (≥6) Polity threshold for sample inclusion
(Appendix A5). Further, we test models including (log) population and public spending/GDP
(although this may induce post-treatment bias, we wanted to ensure that we are not simply
capturing a more general spending effect). Our core results are robust, even in models including
several additional controls at the same time (as exemplified by Model 10, Table 1).
31
In Model 11 we check whether our results are sensitive to the operationalization of electoral
system, and more specifically to combining semi-PR (as classified by Schjølset) with majoritarian
systems. Hence, this model includes two dummies, one for Semi-PR and one for full PR systems
(majoritarian is the reference category), and interact both with agricultural income/GDP. The
results are again consistent with our expectations; both interaction terms are significant (although
only at 5 percent for Semi-PR) with the expected sign, and increasing share of GDP originating
from agriculture is only negatively related with number of major welfare laws in majoritarian
systems (see Appendix A7).
We would have loved to test our hypotheses by using a measure that more fully captures the
power of rural interests, including also their organizational capacity and not only the economic
resources they can draw from. However, we have not found any such measure that is comparable
across countries and with decent time series coverage. Although we consider agricultural share of
GDP, for reasons outlined above, to be the best available proxy, Model 12 checks whether the
results are sensitive to using the only other proxy with extensive coverage that we know of,
urbanization. In one way urbanization is an even broader measure, since it covers the size of nonagricultural rural population groups. We expect rural interests to, ceteris paribus, be less prominent
political players in urbanized societies. Indeed, Model 12 yields the same clear interaction pattern
with electoral systems; the welfare-state enhancing effect of PR is less prominent in urbanized
societies than in rural.
Finally, we tested our models on particular subsets of the sample, and again the results of interest
turn out surprisingly stable. First, we employ the traditional sample of “old”, industrialized
OECD countries, in which most states developed fairly encompassing welfare states during the
20th century, and from which we drew both cases illustrating our argument (Great Britain and
77
Boix, Miller, and Rosato 2012
32
Norway).78 Only analyzing this arguably more homogeneous set of countries probably alleviates
potential issues with unit-heterogeneity affecting our inferences, but also addresses another
potential issue; the data quality may generally be higher for these countries. Also when restricting
our sample to these countries we find clear evidence of our hypothesized interaction pattern (see
Appendix A8). However the, experiences of the industrial countries are not alone driving the
results in our baseline models; the pattern is more general. Notably, the results are retained also
when re-running the regression only on countries that are not among the old, industrialized
countries (see Appendix A8 also for this result).
Since our argument pertains to the historical expansion of the welfare state, and at least some
countries had already developed very extensive such systems several decades ago, we tested our
models on shorter time series. These are – given the inclusion of country dummies and the
limited number of changes to the electoral systems in such shorter samples – demanding tests.
Model 13 reports our baseline run on time series extending from 1871−1959. Note that the
number of countries included also drops substantially (from 96 to 40), since many countries
entering the full sample were autocracies or colonies prior to 1960. Also when restricting our
attention to this time period, we clearly identify the expected interaction pattern (t=9.5 for the
interaction term). We experimented with an even more restricted sample, which is yet more
demanding estimation-wise, dropping all observations after 1945 to see whether our results hold
for the first period of welfare state expansion. Also here, the effect for agricultural income/GDP
is negative and clear in majoritarian systems, whereas it is actually estimated to be positive in PR
systems. Despite always being sizeable, the interaction effect is now only statistically significant at
conventional levels when omitting the country-dummies. However, this is not strange given that
The countries included are: Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan,
Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, and USA.
78
33
only 750 observations are included and there are very few within-country changes between PR
and majoritarian systems in this sub-sample.
Interestingly, re-estimating the same models on post-1945 data also yields clear evidence of the
hypothesized interaction pattern. While UK and Norway, for instance, experienced urbanization
and expanded welfare states prior to or right after 1945, numerous other countries observed
these processes far later (or have yet to observe them).
In sum, the split-sample tests suggest that our theorized mechanisms on how rural interests
groups are able to constrain welfare state expansion under majoritarian electoral systems, but not
under PR, can operate under quite different historical and geographic contexts.
6. Conclusion
We have argued that rural interest groups have clear incentives to slow down welfare state
expansion. In some contexts − for instance when they can draw on substantial economic
resources, command a large number of voters, and are well organized – rural groups could be
expected to have a fair shot at succeeding with this policy goal. However, we further argued that
such success is also highly dependent on the institutional framework in which these groups
operate, even when restricting our attention to democratic settings. More specifically, rural
interests are far more likely to be successful in transforming their power resources into
restraining the expansion of the welfare state under majoritarian electoral rules than under PR.
Overall, we find strong and (surprisingly) consistent evidence for our contention that rural
interests have a negative effect on welfare state expansion, but that this effect is strongly
moderated by the electoral system in place. This result is very robust, and holds for instance
when controlling for country- and time-fixed effects, income level, trade openness, the
agricultural ownership structure, and several other relevant factors. Further, the effect is
34
recovered in samples consisting only of industrialized, old OECD countries and in samples
including younger and less industrialized democracies. The hypothesized effect pattern also
manifests itself both when studying more recent decades and when restricting our attention to
developments taking place historically.
We drew on experiences from late-19th century UK and early-20th century Norway when outlining
our argument. These cases suggested that the following mechanisms may be important for
explaining the differential development of welfare states: In PR systems, agrarians had less sway
over government, having to resort to the second best option of bargaining with either liberals or
social democrats and accept the introduction of social policies in exchange for other policy
achievements. In majoritarian systems, political power was biased in favor of rural interests,
allowing veto power over welfare legislation. Only when the agrarian power base is broken by
large-scale industrialization and urbanization will a majoritarian system be likely to allow for the
establishment of an encompassing welfare state.
To further assess our theoretical argument, future research could provide deeper, process-tracing
case studies (and preferably also on different countries than Norway and the UK), examining the
relevance of the proposed mechanisms in more detail than our illustrative cases. Further, our
theoretical argument can easily be generalized to cover other policy goals of salience to rural
interest groups, such as tariffs or important quotas on food stuffs. Hence, future research could
also assess our argument with quantitative evidence on different policy issues than welfare state
expansion (given available data), by investigating how electoral system and the power resources
of such groups interact.
35
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Online Appendices for
“Arrested Development: How electoral systems have shaped the
ability of rural interests to hold back welfare expansion, 1871−2002”
In addition to descriptive statistics (provided in Appendix A1), the following online appendices
provide tables and figures displaying results from a number of robustness tests and extensions
mentioned in the paper.
The order of the Appendices is as follows: Appendix A1 provides descriptive statistics for the
variables entering our baseline model. A2 shows results from OLS models, whereas A3 shows
results from models including a lagged dependent variable. A4 displays results for sub-samples of
countries with relatively high and relatively low land inequality, as measured by Vanhanen’s family
farms measure. A5 presents models restricted to only democracies using the BMR measure of
democracy and models using a stricter threshold-criterion on the Polity index for being counted
as a democracy (and thus included). A6 displays models with controls for federalism and
parliamentarianism, but also including several additional controls. A7 plots the conditional
marginal effects of the electoral systems and the effect of agrarian interest conditional on
electoral system including also Semi-PR systems. In A8 we present the results from restricting
our models to OECD-countries and to non-OECD countries. Please note that the model using
only OECD-countries would not converge without a time-trend. At last, A8 presents a set of
ECM and Random effect models testing whether agrarian groups are more likely to receive tariffs
under majoritarian rules, as predicted by our theory.
40
Appendix A1: Descriptive statistics
Table A1. Descriptive statistics restricted to the 2998 observations
(Model 5, in Table 1).
Average
STD
Encompassing
4.1
2.0
Agriculture %
30.0
22
PR
.50
.50
GDP/capita (logged)
8.6
.90
Openness
.15
.19
41
entering our baseline model
MIN
0
0
0
5.8
.00
MAX
6
93
1
10.4
1.6
Appendix A2 Robustness tests: Re-doing negative binomial model in Table 1 using OLS
with panel corrected standard errors and AR(1) correction
Table A2. Rural interests, electoral systems and enactment of major welfare laws (dependent variable),
1871-2002, estimated with OLS and panel corrected standard errors with AR(1) correction
Agricultural/GDP
PR
PR*
Agricultural/GDP
Trade Openness
GDP (log)
(1)
-0.00694**
(2)
-0.0148***
(3)
-0.0148***
(-3.21)
0.249*
(2.51)
0.00318
(-7.14)
0.426***
(3.83)
0.00716***
(-7.14)
0.426***
(3.83)
0.00716***
(1.54)
0.196
(1.49)
0.759***
(12.36)
(3.31)
-0.496***
(-3.78)
1.377***
(23.33)
(3.31)
-0.496***
(-3.78)
1.377***
(23.33)
Union Density
(4)
0.0307***
(-6.45)
0.132
(0.98)
0.00891**
(5)
0.0144***
(-6.86)
0.465***
(4.18)
0.00665**
(6)
-0.00728***
(7)
-0.0136***
(-3.78)
0.434***
(4.17)
0.00285
(-6.57)
0.185
(1.69)
0.00885***
(2.67)
-0.485***
(-3.43)
0.789***
(7.87)
0.0116***
(6.79)
(3.04)
-0.537***
(-4.17)
1.366***
(23.51)
(1.43)
-0.280*
(-2.16)
0.922***
(13.79)
(4.15)
-0.491***
(-3.82)
0.987***
(14.14)
0.304***
Democracy
(BMR)
(5.01)
1.249***
(12.10)
Population (log)
No
Yes
Yes
Yes
Yes
Yes
0.0289***
(10.66)
Yes
2998
2998
2998
1564
2998
2998
2962
Family Farms
Country
Dummies
Observations
(8)
0.0206***
(-4.00)
0.000851
(0.01)
0.0108**
(3.24)
-0.288
(-1.90)
0.359**
(3.26)
0.0113***
(6.78)
0.189
(0.97)
0.654***
(3.69)
0.0224***
(7.72)
Yes
1545
t statistics in parentheses. Constant and country dummies excluded. Model 1-8 calculated with Panel-Corrected Standard Errors and a
Common Ar(1) error correction term. * p < 0.05, ** p < 0.01, *** p < 0.001
42
Appendix A3 Robustness tests: Re-doing main models from table 1 using a lagged
dependent variable
Table A3. Rural interests, electoral systems and enactment of major welfare laws (dependent
variable), 1871-2002. Including lagged dependent variable; selected baseline models
Neg. binomial
Neg. binomial
OLS PCSE
Dependent variablet-1
0.283***
0.371***
0.904***
(64.55)
(30.61)
(90.55)
Agricultural inc./GDP
-0.00240***
-0.00859***
-0.00345***
(-8.84)
(-9.74)
(-4.49)
PR
-0.0435***
-0.0867*
0.0971*
(-7.02)
(-2.27)
(2.28)
***
***
PR*Agricultural inc./GDP
0.00233
0.0102
0.00299***
(10.11)
(12.90)
(3.58)
Trade Openness
-0.00270
0.0141
-0.141**
(-0.27)
(0.69)
(-3.08)
***
***
GDP (log)
-0.0693
-0.0993
0.105***
(-11.16)
(-5.48)
(4.42)
Country Dummies
No
Yes
Yes
Period Dummies
Yes
No
No
Observations
2982
2982
2982
Pseudo R2
0.304
0.287
AIC
9252.6
9631.7
Constant, country, and period dummies excluded. Model 1-2 calculated with Huber sandwich standard errors,
model 3 with panel-corrected standard errors and a common Ar(1) error correction term. * p < 0.05, ** p < 0.01,
*** p < 0.001
43
Appendix A4 restricted sample to high or low farm inequality
Table A4. Rural interests, electoral systems, and enactment of major welfare laws (dependent
variable), 1871-2002, in High and Low Farm inequality settings using negative binomial
regression.
(1)
(2)
High Farm inequality
Low Farm inequality
Agricultural inc./GDP
-0.00368***
-0.0278***
(-4.99)
(-3.33)
PR
0.0375
-0.448
(1.09)
(-1.00)
PR*Agricultural inc./GDP
0.00363***
0.0216*
(4.86)
(2.54)
Trade Openness
-0.222***
0.192
(-12.41)
(1.67)
GDP/capita (logged)
0.114***
-0.393**
(5.24)
(-3.12)
Country Dummies
Yes
Yes
Period Dummies
Yes
Yes
Observations
2583
411
2
Pseudo R
0.247
0.475
AIC
8550.6
1023.7
t statistics in parentheses. Low (high) inequality is defined as below (above) the mean in share family farms in
1871 (19 %). Constant, country, and period dummies excluded. * p < 0.05, ** p < 0.01, *** p < 0.001
44
Appendix A5 restricted democracy selection criterion
Table A5. Rural interests, electoral systems, and enactment of major welfare laws (dependent
variable), 1871-2002, restricted to fully democratic countries sample using negative binomial
regression
(1)
(2)
BMR restricted sample
Polity 2 restricted sample
Agricult. inc./GDP
-0.00691***
-0.00698***
(-7.32)
(-6.12)
PR
0.0672
0.0763
(1.76)
(1.86)
***
PR*Agricult. inc./GDP
0.00566
0.00608***
(6.41)
(5.77)
***
Trade Openness
-0.233
-0.170***
(-12.41)
(-8.80)
GDP/capita (log)
0.00750
0.0192
(0.34)
(0.84)
Country Dummies
Yes
Yes
Period Dummies
Yes
Yes
Observations
2628
2373
Pseudo R2
0.231
0.259
AIC
8814.8
7852.0
t statistics in parentheses. BMR sample restricted to all observations scoring 1 (Democracy) in Boix et. al.
democracy measure. Polity 2 sample restricted to all observations scoring above 6 on the polity 2 index.
Constant, country, and period dummies excluded. Model 1-2 calculated with Huber sandwich standard errors. *
p < 0.05, ** p < 0.01, *** p < 0.001
45
Appendix A6 Robustness tests: controlling also for federalism and parliamentarianism
Table A6. Rural interests, electoral systems and enactment of major welfare laws (dependent
variable), 1871-2002, using negative binomial regression
Agricult. inc./GDP
PR
PR* Agricult. inc./GDP
Hybrid
Federal
Semi-Presidential
Parliamentary
GDP/capita (log)
Trade Openness
(1)
Nr. enacted programs
-0.02***
(-15.740)
0.3***
(4.196)
0.02***
(14.277)
0.2***
(4.444)
0.4***
(4.982)
0.2**
(3.187)
0.3***
(3.970)
0.4***
(15.709)
-0.5***
(-14.567)
(2)
Nr. enacted programs
-0.01***
(-11.736)
-0.04
(-0.979)
0.01***
(11.016)
0.02
(0.552)
0.05
(1.143)
0.2***
(5.929)
0.2***
(4.249)
-0.03
(-1.178)
-0.2***
(-9.826)
Yes
No
2987
0.236
10335.3
Yes
Yes
2987
0.294
9595.7
Union Density
Democracy (BMR)
Population (log)
Family Farms
Country Dummies
Period Dummies
Observations
Pseudo R2
AIC
(3)
Nr. enacted programs
-0.01***
(-8.622)
-0.2***
(-4.639)
0.009***
(8.533)
-0.03
(-1.479)
0.02
(0.928)
0.1***
(4.913)
0.1***
(3.574)
-0.01
(-0.460)
0.06**
(2.603)
0.0007*
(2.072)
0.02
(0.343)
0.4***
(7.833)
-0.004***
(-7.571)
Yes
Yes
1543
0.177
5401.9
t statistics in parentheses Constant, country, and period dummies excluded. Model 1-3 calculated with Huber
sandwich standard errors. Reference category is a presidential, unitary, majoritarian system. * p < 0.05, ** p <
0.01, *** p < 0.001
46
Appendix A7: Plotted conditional marginal effects with Semi-PR measure using model 12
from table 1.
Figure A1. The Conditional Marginal effect of agrarian share over electoral systems on the number of
predicted major welfare laws with 95% CI
47
Figure A2. The Conditional Marginal effect of Electoral systems over agrarian share of GDP on the
number of predicted major welfare laws with 95% CI
48
Appendix A8 Robustness tests: Testing for causal heterogeneity by splitting sample into
OECD vs non-OECD countries.
Table A7. Rural interests, electoral systems, and enactment of major welfare laws (dependent
variable), 1871-2002, restricted to current OECD countries (1-2) or non-OECD countries (3-4),
using Negative Binominal regression.
Agricultural/GDP
PR* Agricultural/GDP
Trade Openness
GDP (log)
PR* Agricultural/GDP
Time Trend
Country Dummies
Time Period Dummies
Observations
Pseudo R2
AIC
(1)
OECD sample
-0.04***
(-10.508)
-0.3**
(-2.957)
0.03***
(9.681)
-1.0***
(-14.675)
-0.7***
(-11.760)
Yes
Yes
No
1210
0.321
3960.0
(2)
OECD sample
-0.01**
(-2.987)
-0.09
(-1.098)
0.005*
(2.031)
0.07
(1.439)
-0.07
(-1.533)
No
Yes
Yes
1210
0.363
3740.4
(3)
Non-OECD Sample
-0.01***
(-9.116)
0.5***
(5.008)
0.010***
(7.285)
0.3***
(11.155)
-0.4***
(-5.885)
No
Yes
No
1788
0.202
6155.6
(4)
Non-OECD Sample
-0.004***
(-4.481)
0.05
(0.890)
0.003***
(3.975)
-0.02
(-0.672)
0.2***
(3.805)
No
Yes
Yes
1788
0.249
5836.9
t statistics in parentheses. Constant, time trend, country, and period dummies excluded. Model 1-4 calculated with Huber sandwich standard
errors. * p < 0.05, ** p < 0.01, *** p < 0.001
49
Appendix A9 Tariffs models
Table A8. Rural interests, electoral systems and restrictions, and economic globalization
(dependent variable) using the KOF-index (Tariffs and actual trade flows)
Lagged dep. var
Agricult.
inc./GDP
PR
PR*
Agricult.
inc./GDP
GDP/capita (log)
(1)
PCSE
-0.0160***
(-3.73)
(2)
ECM
-0.0523***
(-5.89)
(3)
ECM
-0.107***
(-9.92)
(4)
ECM
-0.152***
(-11.01)
(5)
RE
-0.153***
(-10.93)
(6)
RE
-0.0182***
(-4.50)
(7)
RE
0.982***
(243.18)
(8)
RE
0.982***
(250.30)
-0.00818
-0.00580
0.00453
0.0109
0.0111
-0.0101*
-0.0101*
-0.00784
(-1.47)
0.343*
(2.13)
-0.0109
(-0.51)
0.795
(1.79)
-0.0275*
(0.40)
0.371
(0.85)
-0.0254*
(0.99)
0.0664
(0.15)
-0.0256*
(0.98)
0.0713
(0.16)
-0.0258*
(-2.16)
0.361
(1.81)
-0.0125*
(-2.16)
0.361
(1.81)
-0.0125*
(-1.64)
0.393*
(2.00)
-0.0137*
(-1.91)
(-2.11)
(-2.00)
(-2.02)
(-2.02)
(-2.23)
(-2.23)
(-2.39)
-0.0246
(-0.19)
1.081*
(2.55)
-0.330
(-0.70)
-1.584**
(-3.03)
-0.0124
(-0.13)
-0.0124
(-0.13)
No
Yes
Yes
Yes
-1.575**
(-3.01)
0.000741
(0.06)
Yes
No
No
0.0528
(0.48)
-0.00442
(-1.40)
No
No
No
No
No
No
Yes
Yes
No
Yes
No
No
No
No
No
No
No
No
1748
No
1748
No
1748
No
1748
No
1744
Yes
1748
Yes
1748
Yes
1744
Family Farms
Country
Dummies
Year dummies
Time period
dummies
Random effects
Observations
t statistics in parentheses. Constant, time period , year and country dummies excluded. Model 1-4 calculated with Panel-Corrected Standard
Errors and a Common Ar(1) error correction term. Random effects models 5-8 calculated with standard errors clustered by country. * p <
0.05, ** p < 0.01, *** p < 0.001
50