What women want:
Su¤rage, female voter preferences and the scope of government*
Patricia Funk
SITE - Stockholm School of Economics
Christina Gathmann
Stanford University
This draft: October 2005
Abstract
How women su¤rage a¤ected the size of government is poorly understood. While aggregate data suggest that US states with su¤rage had
higher expenditures than the ones without, individual data from elections describe women as more conservative during that period. This
paper uses of a unique data set of issue votes to fully describe voter
preferences and to directly estimate policy e¤ects. With surveys on all
195 federal votes held in Switzerland between 1981 and 2003, we …nd
evidence for gender gaps in multiple dimensions. Secondly, we analyze
support for costly projects. Consistent with the gender gaps in preferences, women approve higher expenses in certain areas, but oppose
them in others. Overall, we …nd larger gender di¤erences regarding the
scope than the size of government. Di¤erence-in-Di¤erences estimations
for the aggregate su¤rage e¤ects support the view that scope mattered
more than size in the last 50 years. JEL: H10, H50, J16, K00.
*Correspondence: Patricia Funk, Stockholm Institute for Transition Economics (SITE), Stockholm
School of Economics, Email: Patricia.Funk@hhs.se; Christina Gathmann, Department of Economics and
Stanford Center for International Development, Stanford University, Email: cgathman@stanford.edu.
We thank Renee Adams, Ulf Axelson, Erik Bergloef, Tore Ellingsen, Daniel Ferreira, Mariassunta Gianetti,
Henning Hillmann, Helena Svaleryd and various seminar participants of the Stockholm Institute of Transition Economics, the Stockholm School of Economics, and the University of Uppsala for useful comments and
suggestions. We are grateful to Werner Seitz, Magdalena Schneider and Elisabeth Willen from the Swiss
Bureau of Statistics, Andreas Ladner, Klaus Armingeon, Hans Hirter and Christian Bolliger from the University of Bern and Francois Loretan from SIDOS for invaluable help in collecting the data. All remaining
errors are our own.
1
Introduction
At the heart of every democracy lies the hope that the preferences of its citizens are best possibly
re‡ected in policy outcomes.1 A big change in voter preferences might have occurred when women
received the right to vote. Since women su¤rage roughly doubled the electorate, we would expect
government to take quite a di¤erent form, if women have di¤erent policy preferences than men.2
Even though granting women the right to vote caused a big change in the electorate in many
countries, surprisingly little is known about the nature of female voter preferences and the resulting
policy responses. Even worse, research on female voter preferences seems hard to reconcile with
the studies on aggregate su¤rage e¤ects.
For the U.S., Lott & Kenny (1999) found that adoption of women su¤rage remarkably increased
government expenditures between 1870 and 1940. Concerning female voters’preferences, however,
the literature suggests that at least until the presidential election of 1964, women voted more
right-wing than men (see e.g. Seltzer, Newman & Leighton (1997), Edlund & Pande (2002)). Since
rightist cabinets are generally found to increase government expenditures less than leftist cabinets,3
these results seem somewhat contradictory. Either, a one-dimensional “left-right”-wing indicator
describes female policy preferences insu¢ ciently,4 or the aggregate su¤rage estimates capture more
than the transmission of female voter preferences into outcomes such as the size of government.5
This paper studies the e¤ects of political participation of women in Switzerland. The fact that
1
While the Downsian (1975) model has a rather optimistic view on that issue (electoral competition forces the policy makers to implement the median voter’s position), rent seeking models are
more suspicious about the politicians willingness to pursue the voters interests (see e.g. Grossman
& Helpman (1996)).
2
Gender has been found to matter in India: female policy makers invested in projects directly
relevant to the needs of their own genders. Depending on the regional area, female leaders allocated
resources to drinking water and roads di¤erently than men; see Chattophadhyay & Du‡o (2004).
3
See Tavares (2004) for an overview of the literature.
4
Note that policy preferences a¤ect outcomes not only through voting, but also through policy
making.
5
The early data set (1870-1940) certainly poses restrictions on the amount of control variables.
1
Switzerland is the world leader in the use of direct democracy6 provides us with a unique data set
for studying gender di¤erences in voting. Alone between 1981 and 2003, 203 federal votes have
been held, with survey data available for 195 of these issues. Since the issues span all major policy
areas, gender di¤erences can be described in as many dimensions as necessary. Not only voter
preferences, but also the …scal consequences of female political participation at the federal level are
straightforward to identify. By analyzing a sub-set of issues with implied increases or decreases
in government spending, it becomes very obvious whether and in which areas women voted more
pro-government than men.
The big advantage of our data set is the large amount of issues, we have voting choices upon.
Even though the federal micro-data allow to fully describe voting choices over a large span of policy
areas, we complement our analysis with an estimation of the reduced-form su¤rage e¤ects. Since
Switzerland was one of the latest western countries that adopted su¤rage (on a federal level in
1971, on a Cantonal level between 1959 and 1990), we have an ideal data set for re-estimating
the aggregate su¤rage e¤ect (with a large number of controls) and to check consistency with the
…ndings from the federal level.
Our main results are the following:
(1) The federal survey data display signi…cant gender di¤erences in many political areas. Gender
gaps are largest in the areas of “environmental policy”, “energy policy”, “military policy”, “social
policy”and votes involving equalization of women and men. Due to lower turnout of women, female
preferences are slightly under-represented in most of the votes.
(2) A one-dimensional characterization of voter preferences does not capture the full dimensionality of the gender gap. Most of the gender di¤erences prevail after controlling for party-ideology.
Furthermore, di¤erences in characteristics (e.g. education, employment, proxy for income etc.)
6
See Ladner & Braendle (1999).
2
explain the gender gap in certain social a¤airs, but not in most other areas.
(3) The gender gap in voter preferences translates into …scal policy outcomes in a predictable
way. In accordance with their preferences, women support issues with a positive e¤ect on social,
environmental and public transport expenditures, and a negative e¤ect on defense and agricultural
expenditures. While women undoubtedly had an e¤ect on the scope of government (increase in
certain types of expenditures and decrease in others), the total size e¤ect is small. Women were
two percent more likely to say “yes” to votes with a positive e¤ect on the size of government.
(4) Cantonal data support the …nding that scope matters more than size. In a di¤erence-indi¤erence setting, where the identifying period is between 1959 and 1990, the reduced-form e¤ect
of women su¤rage is even negative for most types of revenues and expenditures. Only for culture,
transport and environmental expenditures, insigni…cant positive e¤ects are found.
(5) The main di¤erence between the Cantonal and federal results concerns social expenditures.
While women approved projects with a positive e¤ect on federal social expenditures (between 1981
and 2003), woman su¤rage reduced aggregate Cantonal social expenditures between 1959 and 1990.
The explanation for this di¤erence seems to lie in the di¤erent time periods. For social expenditures,
in contrast to the other expenditures, we …nd robust evidence for a time-varying gender gap. One
reason seems to be the latest increase in a sub-group of women (single/divorced and/or employed),
which supports certain types of social expenditures.
Our article is related to several strands of the literature. As for the political preferences of
women and men, there is a substantial literature in political science, which tries to explain the
reversal of the gender gap in elections.7 A recent economic paper on that topic is by Edlund &
7
While women were considered as more right-wing in the postwar era (“traditional gender gap”),
there was a process of gender alignment in the 80’s, and in many developed countries, women got
more left-wing than men in the 90´s (“modern gender gap”); see e.g. Inglehart & Norris (2000),
Inglehard & Norris (2003). A common explanation for this reversal in gender gap is societal
modernization, which brought a break-up of traditional family units, a transformation in sex roles
and increased labor force participation of women. As for empirical evidence on that subject,
Inglehard & Norris (2000) compare men and women’s election patterns for a large range of countries.
3
Pande (2002), who focus on divorce patterns (and the related income changes) as the main driver
of the changing gender gap.8 In contrast to this substantial literature, which captures political
preferences of men and women in a one-dimensional right-left scale, similar research on issue voting
is basically absent.9 Only Berman (1993) looks at gender di¤erences in issue voting in an indirect
way. By focusing on ballots in Arizona in 1914 and 1916, he compares outcome by precinct with
respect to the share of women as registered voters. Similar to the literature on the gender gap
in elections, Berman (1993) …nds that the addition of women to the electorate had signi…cant
short-term e¤ects and strengthened conservative components.10
According to our best knowledge, we are the …rst to directly analyze a broad range of voting
choices. Therefore, we certainly add to the …ndings from opinion polls11 and electoral preferences.
Furthermore, by directly comparing women’s and men’s voting choices on projects with …scal consequences, the impact of female political participation on the size of government is straightforward
to identify.
In contrast, the e¤ect of female political participation on the size of government has only been
studied with aggregate data so far.12 Since most of the countries introduced su¤rage in the beConsistent with their theory of societal modernization, they generally …nd a larger gender gap
(i.e. left-scale women - left-scale man) in industrialized countries than in transition countries and
within industrialized countries, di¤erences between age cohorts. As such, these authors advance
the political science literature on the gender gap, which focused on the United States and proposed
explanations speci…c to the U.S. (see e.g. Mueller (1998)).
8
The setting is an economy, where the male income distribution …rst-order-stochastically dominates the female one, and where there is positive sorting in the marriage market. Divorce then
a¤ects the taste of redistribution among middle-income voters. Women, who …nancially lose from
divorce, tend to vote more left, and men, who …nancially win, tend to vote more right. Empirical
evidence consistent with this hypothesis is provided in Edlund & Pande’s (2002) study.
9
The big bulk of research focused on the electoral gender gap (i.e. voting decisions in elections)
or related, the partisan gender gap (i.e. gender di¤erences in party identi…cation); see Conover
(1988) for a review of the literature.
10
Precisely, he …nds that precincts with a relatively large percentage of female (registered) voters
were more negative towards a progressive labor package and the abolishment of the death penalty,
but more positive towards prohibition.
11
Gender di¤erences have been discovered in areas involving force, and to a smaller extent in
compassion and regulation issues (see e.g. Shapiro & Mahajan (1986) or more recently, an overview
by the Center for American Women and Politics (1997)). However, opinion polls include the whole
citizenship, and not only the voting population. Furthermore, as Matsusaka & McCarty (2001)
demonstrate, statements from opinion polls are bad predictors for later voting behavior.
12
See Lott & Kenny (1999), Abrams & Settle (1999) and Stutzer & Kienast (2004). While Lott
4
ginning of the century, the data basis is comparatively poor. Furthermore, reduced-form estimates
of women su¤rage with aggregate data (di¤erence-in-di¤erence estimation) help to understand the
total impact of female political participation (voting and policy making), but only to the extent
that well-known problems such as endogeneity of policy adoption and unobserved trends of early
and late adopters are absent. Next to our direct estimates of the …scal gender gap (with micro
data), we contribute to this strand of literature by re-estimating the aggregate su¤rage e¤ect with
Swiss panel data. The later time period of adoption bears the advantage of having a larger amount
of control variables. In addition, we use Cantonal voting records on all federal issues to carry out
robustness tests in a unique way.13
The structure of the paper is as follows: Section 2 gives an overview of the institutional background in Switzerland. Section 3 compares female and male voter preferences. The policy e¤ects
on the federal level are analyzed in Section 4. Section 5 presents the reduced-form su¤rage e¤ect
with Cantonal data. Robustness tests are presented in Section 6, and a discussion rounds up in
Section 7.
2
Institutional Background
When describing the institutions of Switzerland, federalism and direct democracy are certainly the
key characteristics.
2.1
Federalism in Switzerland
Switzerland has a federalist structure with three levels (federal level, Cantonal level, community
& Kenny …nd that su¤rage increased total revenues and expenditures (but not the di¤erent subcategories), Abrams & Settle (1999) analyze social welfare spending and posit an increase after
female political participation. Only Stutzer & Kienast (2004), in parallel work to ours, …nd a
negative e¤ect of women su¤rage on Swiss Cantonal expenditures.
13
The key idea is to directly estimate male (…scal) voter preferences for the Cantons and to check,
whether they pose a potential source for omitted variable bias.
5
level). While expenses on the federal level account for about 40 percent of total expenditures,
the Cantons and communities have also a strong role in providing public goods. For instance, the
constitution states that all responsibilities retain with the cantons unless they were explicitly ceded
to the federal government.14 As can be seen from table A1 in the Appendix, there are many areas
with shared responsibilities, where Cantons and communities provide a substantial share of public
goods next to the federal level.
The distribution of revenues between federal, cantonal and local levels is decentralized as well.
Cantons have the authority to tax labor and capital income which account for roughly 50 percent of
cantonal and local revenues.15 In contrast, the federal government relies mostly on indirect taxes,
the sales tax and several consumption taxes. Since tax revenues are not shared between di¤erent
levels of government or cantons, there is substantial variation in the tax burden across cantons.16
2.2
Direct Democracy
No other country uses direct-democracy as intensively as Switzerland. Alone on the federal level,
more than 450 ballots have been put forward since the country’s foundation in 1848 (see Ladner
& Braendle (1999: 284)). While citizens may propose changes/additions to the constitution by
initiatives,17 the referendum gives them the control power by voting on actions of the government.
Mandatory referenda are hold e.g. on changes in the constitution or the joining of international
organizations. In contrast, all laws issued by the government underly the facultative referendum,
if 50’000 eligible voters or 8 Cantons require it within 100 days since the formal resolution.
14
The federal level has the sole responsibility in international relations, defense, customs and
currency, atomic energy, media, postal service, telecommunication as well railways and air tra¢ c.
Shared responsibilities with the Cantons exist in agricultural policy, civil and criminal law and
taxes. In the areas of environmental policy, social security system, roads and industrial and labor
regulation, the federal government provides the legal basis while Cantons execute the federal laws.
15
Local jurisdictions can levy a surcharge on Cantonal direct taxes and raise their own property
taxes.
16
See for example Feld (2000) for an analysis of tax competition between cantons.
17
A federal vote will occur if more than 100’000 eligible voters sign.
6
Extensive use of direct democracy can also be found on a Cantonal level. The most important
direct-democratic elements are again the initiative, and the referendum. However, the 26 Cantons
in Switzerland di¤er widely in their provision and strength of direct-democratic instruments.18
Generally speaking, direct democracy is stronger in German-speaking parts of Switzerland, and
weaker in the French-Speaking part. Direct democracy in its purest form was or still is performed
in a couple of Cantons called “Landsgemeindekantone”(town-meeting Cantons). In these Cantons,
the parliament has very little power, but the citizens meet up in town-meetings to decide on laws,
elect the judges, set income tax rates and decide on cantonal spending (see Moeckli, 1987).19
As will be shown later, the (former) town-meeting Cantons, which have the strongest form of
direct democracy, were also the ones which gave women the right to vote at the latest. As such,
the very direct democratic system in certain Swiss Cantons may actually have inhibited the step
towards women su¤rage.
2.3
... and the Long Road to Women Su¤rage
Switzerland was among the last countries in Europe to introduce voting rights for women. At the
federal level, su¤rage was granted in 1971, half a century later than in the United States and many
European countries.20 Since an extension of voting rights requires a change in the constitution,
voters have to approve it in a mandatory referendum.21
The …rst federal referendum on the adoption of women su¤rage was held in 1959. Yet, the
18
See Trechsel & Serduelt (1999) for a systematic overview of the Canton’s direct-democratic
institutions between 1970 and 1996.
19
Historically, the function of the parliament has only been to support the citizens with carrying
out the issues which have been decided at the town-meeting. The law-making authority lies solely
in the hands of the eligible citizens.
20
In Europe, women su¤rage was adopted by Finland in 1906, Denmark in 1915, Germany, Austria, Poland and Russia (all 1918), Sweden in 1919, Spain and Portugal (both 1931), and Italy in
1945.
21
First attempts to introduce women su¤rage at the cantonal level failed in several Cantons
(Neuenburg, Basel, Glarus, Zurich, Geneva and St. Gallen) in 1920/21. In 1929, a petition of
250000 citizens supporting women su¤rage was sent to the parliament but neither the government
nor the parliament reacted.
7
referendum failed as only 1 in 3 men voted for adoption. In 1971, the referendum passed with
almost 2 in 3 men voting in favor of women su¤rage. Still, in eight cantons out of a total of 26,
less than 50 percent of men voted for its introduction. As for the change in support of women
su¤rage, one potential explanation is that the Swiss Government wished to sign the European
Human Rights Convention, but only with restrictions (“Vorbehalt”) because women did not have
the right to vote.22
3
Political Preferences of Women and Men
The votes that attract most citizens interests are no doubt the federal votes. With decisions on
health policy, changes in unemployment insurance, directions in environmental policies, or membership in international organizations being taken on a federal level, top turnout rates of 80 % have
been reached.23
In the following, we will analyze gender di¤erences in voting on national votes held between
1981 and 2003. Even though women received the right to vote on a federal level in 1971, systematic
surveys have only been held after 1981. The data set is a repeated cross-section survey of between
500 and 1,000 respondents24 and contains detailed information on the respondent’s demographics,
economic situation, Canton of residence as well as political values and attitudes. We dropped all
respondents under the age of 21, who were not eligible to vote until March of 1991, and under 18
thereafter.
22
See Seitz (2004) for more details on the political struggle for women su¤rage and the overall
representation of women in politics.
23
Between 1950 and 2000, votes on foreign in…ltration and the membership in the European
Economic Area have reached turnout levels of more than 70 percent.
24
The VOX-surveys started with interviewing around 500 citizens, but then steadily increased
the sample up to 1000 in the early 90’s. Not only the number of respondents, but also the number
of questions has been enlarged over time. As such, more details about marital status (divorce as
a single category compared to a joint category with the widowed prior to 1992) or the household
structure have been added.
8
3.1
Votes with the largest gender gaps: the top-10
In order to get a feeling for the most gender-sensitive issues, we ranked all the votes according to
the gender gap (% yes women -% yes men) in the population. Table 1 displays the 10 votes with
the biggest gender gap in the approval rates.
— insert Table 1 here —
As can be seen therefrom, big gender gaps occurred in the area of equal rights. Women seem to
be more reluctant towards discrimination, no matter whether it concerns gender, race, or opportunities for the disabled. Environmental and energy policy is another area, where gender divides.
Women are more pro-environment and less favorable of a nuclear based energy policy. Finally,
issues involving risks provoke gender gaps as well. The fact that women voted e.g. against relaxing
the speed limit on Swiss national highways is consistent with the view that women are more risk
averse than men (see e.g. Dwyer, Gilkeson & List (2002)).
At a …rst glance, it seems that the most gender-sensitive issues are typical “value issues”.
Attitudes towards the environment, the disabled, the security on streets, or experiments with
animals are all issues that entail strong value-statements and hardly a¤ect a voter’s economic
position. As such, typical “economic issues”, with e¤ects on the income distribution, were not
among the most gender-sensitive in the last 20 years. However, whether they matter to a smaller
extent will be analyzed subsequently.
3.2
Classi…cation of the Votes into di¤erent Policy Areas
We classi…ed the votes held between 1981 and 2003 into 7 broad categories, with most of the broad
categories having further subcategories. The subcategories are built so that all the votes in a certain
9
subcategory pursue the same policy direction.25 For instance, there were votes on agricultural
policy, which either targeted at liberalizing, or at further subsidizing agriculture. Therefore, two
separate subcategories “Against subsidizing Agriculture”and “Pro liberal Agriculture”were built.
In the Appendix, table A2 provides an overview of the titles of the votes, which will be analyzed.
As can be seen therefrom, major policy areas ranging from Environmental Policy, Transportation
Policy, to Military and Social Policy are covered. For the sake of overview, we focus on the policy
areas where we suspect a possible e¤ect on federal expenses. We also analyzed policy areas with no
obvious e¤ect on the federal budget (e.g. International Politics, Swiss Law & Direct Democracy,
Immigration Politics, Gen-Technology), but relegate these results to the footnotes.
3.3
Participation and Voting Outcomes in di¤erent Policy Areas
So far, surveying a representative sample of the Swiss population has displayed gender gaps in
several areas. However, to the extent that participation rates between men and women di¤er, male
and female voter preferences receive a di¤erent weight.
The purpose of this section is to estimate the gender gap among the voters in the di¤erent policy
areas. In order to asses, how well female preferences are represented through the voters, we also
estimate participation rates and the di¤erence between the gender gap voters/total population.26
The model to be estimated is the following:
25
See http://www.admin.ch/ch/d/pore/va/index.html for a listing of all the votes. The parliamentary debates and arguments of the initiative’s supporters are also often included in the comments on initiatives. All comments by the federal council and parliamentary resolutions can be
viewed online at http://www.ads.bar.admin.ch/ADS.
26
Since the questionnaire asked also non-voters, how they would have voted, policy preferences
are known for a representative sample of the whole Swiss population. If the gender gap covering
the whole population is very di¤erent from the one found in the voting population, then voters
seem to be non-representative.
10
Yesij =
+
j
F emalei + "ij
Yes is a binary variable denoting the decision of citizen i, either to participate (turnout model),
or to support a vote in subcategory j (“yes”=1, “no”=0). For the moment, we are interested in
the pure di¤erence between women and men’s voting choices and only include a dummy for the
sex. Later on (Section 3.4), we will investigate more closely why women vote the way they vote
(e.g. because of lower education, lower income etc.) and control for various characteristics.
On average, the data show a statistically signi…cant 1.5 percent di¤erence of voting yes or no
in a federal ballot between men and women. However, there are much larger gender di¤erences in
voting behavior for speci…c policy issues.
Table 2 reports marginal coe¢ cients of a probit model. As can be seen from the …rst row, female
voters have signi…cantly di¤erent approval rates in the …elds of “Environmental & Nuclear Policy”,
“Transportation Politics”, “Agricultural Policy”, “Social Security”, “Culture” and “Military Policy”.27 Speci…cally, women voted more in favor of protecting the environment, the rights of elderly
and disabled people, the use of public instead of private transportation, the reduction of military
and the preservation of culture (see also Longchamp and Bieri, 2001). In contrast, men were more
likely to support a nuclear energy policy, a reform of the unemployment insurance, which included
reductions in bene…ts, and to relax the speed limit on national highways.28
27
From the votes in other areas, the largest gender di¤erences were discovered in the area “Equal
Rights of Women and Men”, where women were 11% more likely to support equalization. Signi…cant gender di¤erences were also found in the areas of “Gentechnology”, where women were
6% more likely to oppose. Finally, “Immigration Policy” divided gender, with women being more
open towards foreigners. No signi…cant gender gaps were found in votes on joining international
organizations, concerning directions of drug policy and regulating the housing market.
28
Our …ndings match the results from public opinion surveys, which normally cover a subset of
11
Women did not only vote di¤erently, but also participate di¤erently. As for the total sample,
male turnout was 62 % and female turnout was 54 %. For the individual policy areas, women
generally had a slightly lower turnout (see column 3), with the turnout gap being lowest for
“women-speci…c”topics such as maternity leaves or the legalization of abortion (latter not shown).
Therefore, women’s preferences are slightly under-represented in most of the issues.
Concerning selection into the voting decision, di¤erences between the gender gap in the voting
and the whole population are not that big (compare rows 1 and 2). One exception is the area of
equal rights of women and men (results not shown), where “feminists”were mobilized to a greater
extent.29 There, female preferences might be well represented even despite a slightly lower turnout.
— insert Table 2 here —
3.4
The nature of the gender gaps
So far, we focused solely on di¤erences between female and male policy preferences. Whether these
gender gaps occur out of di¤erences between women’s and men’s characteristics (e.g. di¤erences in
income, the level of education, location etc.), or rather because women are di¤erent (biology, values
or attitudes)30 remained unchecked. Furthermore, even though gender gaps have been discovered in
policy issues, quite well. For instance, in a comparison of Swedish Attitudes, gender di¤erences in
economic, environmental and social issues have been found, with women opposing nuclear energy,
and favoring medical care, environmental protection and sex equality (Eduards (1982)). Also,
Norris (1988) found for European Countries that women were more left on policies such as nuclear
energy, unemployment and defense. Finally, our result that women seem to be more social than
men, con…rms what other studies have found: Schlesinger & Heldman (2001) attribute part of
women’s higher support for compassionate domestic policies to di¤erent values in altruism and
egalitarism; similarly, Canadian women seemed to oppose the free-trade agreement with the States
because they had more egalitarian values and were less persuaded about the virtues of competition
(see Gidengil (1995)). Finally, sex di¤erences in racial attitudes have also been discovered in Seltzer
& Newman (1997), where women have expressed more positive feelings towards blacks.
29
Schumaker & Burns (1998) found gender gaps between policy makers to be bigger than within
the citizen population. In our case, a similar e¤ect seems to be going on between citizens and voters
in the area of Equal Rights.
30
It has been argued in the literature that women’s nurturing and kin-keeping role gives rise to
di¤erent policy preferences (see Schlesinger & Heldmann (2001)).
12
multiple dimensions, they might be explained by an underlying one-dimensional “party-ideology”
variable. If so, this would justify the focus on di¤erences in electoral gender gaps as a collapsed
form of gender gaps in policy preferences.
Table 3 …rst row replicates the pure gender gap in the di¤erent policy areas. Row (2) controls
for the demographic variables age, education, religion and language. Since women are generally
less well educated than men (see Appendix A3 for Summary Statistics), gender di¤erences should
disappear if di¤erent education is the driver behind the gender gaps. However, as can be seen from
the results in row 2, only certain redistributive issues (reduction unemployment bene…ts, subvention
health premia) are a¤ected by the inclusion of demographics. A similar picture emerges, if controls
for employment, civil status and house-ownership (as a proxy for income) are added (Row 3). Most
gender gaps cannot be explained by di¤erences in characteristics.
Row (4) adds a measure for self-stated party-ideology.31 The gender gaps disappear only for the
three social votes “longer maternity leave”, “reduction unemployment bene…ts”, “subvention health
premia”and the votes on military expenses. Therefore, a one-dimensional “left-right”-indicator at
best captures some gender di¤erences regarding re-distribution and size of the army, but leaves out
many other dimensions of the gender gaps in voter preferences.
Finally, row (5) adds geographic area as well as Time- and Canton- Fixed E¤ects to the previously described controls.32 As can be seen from the estimated coe¢ cients, signi…cant gender gaps
prevail in the area of environmental and nuclear policy, agricultural policy, certain social issues,
military and cultural policy.
— insert Table 3 here —
31
This “left-right”-measure takes values from 0 to 10, with 10 being maximally right. Self-stated
party ideology is immune to changes in party-de…nition and -structure and therefore most commonly
used in the literature (see e.g. Edlund & Pande (2002)).
32
The indicator Party-Ideology is dropped, because there are quite a few missing observations.
13
Summing up, we note that gender di¤erences in policy preferences evolve around issues involving
solidarity and risk: while women solidarize more with certain local groups (the disabled, the aged),
solidarity is also present in a more global context (peace, protection of the environment). Gender
di¤erences in risky issues were found in votes on the security on the streets, or health risks from
the consumption of alcohol or tobacco.
These di¤erent gender gaps cannot be collapsed into one dimension. An indicator for partyideology captures at best preferences for re-distribution, but leaves out most other dimensions.
Furthermore, only the gender gap for redistribution can (partly) be explained by di¤erences in
women’s and men’s characteristics. Gender gaps in other areas seem to arise out of di¤erent values,
since adding characteristics does not make them disappear.
4
Women Su¤rage and Government Expenditures at the Federal level
While the last section described and explained the nature of the gender gaps, this section studies
the policy impacts of having female voters. Due to data availability, we focus on voting outcomes.
However, when women received the right to vote, they also obtained other possibilities of political
in‡uence such as the right to sign initiatives and referenda. Therefore, women most likely had an
impact on the types of votes that were held as well. However, since approval of the vote is needed to
have an impact on government policy, a focus on voting outcomes seems a natural starting point.
4.1
Approval of Costly Projects
So far, votes in di¤erent policy areas were studied. While certain votes had …scal implications
involved, others did not. The goal of this section is to asses gender di¤erences in the approval of
costly projects.
The data set consists of a sub-sample of propositions, which had unambiguous implications for
14
…scal policy (i.e. increase or decrease expenditures, increase or decrease taxes etc.). The government (federal council) prepares detailed comments for each initiative before the vote, which include
implied expenditures and taxes in the case of electorate approval. Likewise, the government publishes details and …scal consequences for each new law and executive order.33 With this information,
we were able to identify 71 propositions, where the …scal consequences were straightforward (see
Appendix A4 for an overview). For instance, we excluded propositions where a proposed increase
in expenditures was accompanied by a proposed tax to …nance it. Only propositions, which clearly
led to an increase or decrease in expenditures, subsidies, grants or taxes were taken.
For the sake of overview, we de…ne a variable “More Government”, which comprises propositions
implying an increase in federal expenditures, taxes, debt, grants or subsidies. Similarly, the variable
“Less Government”contains the propositions, which acceptance leads to a decrease in expenditures,
taxes, grants/subsidies or debt.
The econometric model is similar to the one before, i.e. probit estimates of the e¤ect of female
sex on the approval of projects in di¤erent …scal categories.
Table 4 columns 1 and 2 show the e¤ect of female voting on the size of government. As can
be seen therefrom, women were slightly more supportive of projects leading to an expansion of the
government. Overall, they were two percent more likely to say “yes”to votes with a positive e¤ect
on the size of government.
More important than the …nancial consequences might be the subject of the vote and will
therefore be examined in more depth. In order to understand better, which types of expenditures women were supporting, we further categorized the 71 propositions with predictable …nancial
consequences. In particular, we distinguished votes a¤ecting social expenditures, environmental
expenditures, agricultural expenditures, cultural expenditures, public transport expenditures and
33
The parliamentary debates and arguments of the initiative’s supporters are also often included
in the comments on initiatives. All comments by the federal council and parliamentary resolutions
can be viewed online at http://www.ads.bar.admin.ch/ADS.
15
defense expenditures.
As can be seen from the rest of table 4, the gender gap is the biggest for environmental expenditures, followed by public transport, social, agricultural,34 cultural and defense expenditures.
Women supported higher expenditures, if they were invested in environmental protection, in public
transport or social security, but opposed expenditures on military a¤airs or subsidies for agriculture.
— insert Table 4 here —
Therefore, women seem to have di¤erent preferences in many dimensions, in particular regarding the environment, social security, agriculture, defense and public transport. As for the …scal
implications, the e¤ects seem to depend on the type of expenditure. While environmental and
social expenditures would have risen, if only women had voted, expenditures for defense and agriculture had declined. Therefore, female voters had a bigger impact on the structure rather than
the size of government.
4.2
Women as pivotal voters
Even though women supported increases in certain types of expenditures, they only a¤ected expenditures, if they changed the voting outcome. Furthermore, due to lower participation, women’s
impact might be smaller than suspected from the approval rates.
Since the data present a representative sample, we can roughly evaluate whether women actually
changed the voting outcome.35 Table 5 depicts all the votes, where women and men had accepted
di¤erent voting outcomes. From these 15 votes, women changed the outcome in 4 cases (i.e. the
34
Women’s greater opposition towards subsidizing agriculture partly stems from the fact that
women more often live in cities. Therefore, the gender e¤ect turns smaller as soon as a control for
urban location is added.
35
Obviously, untruthful reporting might cause some distortions.
16
…nal result corresponded to the one preferred result by women, but men would have preferred the
opposite). As such, in roughly 2 percentage of all federal votes, women actually changed the result.
As for the …nancial consequences, in one case, women caused an increase in 70 Mio. franks yearly,
since they opposed a reduction of unemployment bene…ts, and in the other case, they voted for
cancelling subsidies for parking spaced, which led to yearly savings of 20 Mio. Swiss franks. In the
other two of the four proposals, where women changed the outcome, the …nancial consequences are
unclear.36 Compared to total government expenditures of 164 billions in 2003, the …scal impact of
women voting in federal elections was small.
— insert Table 5 here —
5
Women Su¤rage and Policy E¤ects on the Cantonal level
The federal data bear the great advantage that voting choices of women and men can be directly
compared for a wide range of policy issues. However, the data are only available since the beginning
of the 80´s and restricted to voting at the polls. Since women are likely to have in‡uenced politics
since the beginning of su¤rage, and possibly also through other channels (like policy making and
voting at elections), we re-estimate the reduced-form su¤rage e¤ects with Cantonal data. The panel
data range from 1950-2000 and allow to relate women su¤rage to government expenditures over a
longer time-horizon.
5.1
Background information
Su¤rage adoption occurred late, on a national as well as on a Cantonal level. However, there is
36
At a …rst glance, women’s lower acceptance rates in the votes on “Ecological and modern
agriculture” and “Easier access to real estate by foreigners” might seem in contrast to what we
previously found. However, a detailed analysis of the votes shows that the opponents of the …rst
vote feared that the reform did not go far enough, and in the second vote, ecological concerns (fear
of too many new buildings) played a major role. See: http://www.polittrends.ch/vox-analysen.
17
substantial disparity among the Canton’s timing of introduction.
Table 6, …rst column shows the year of women su¤rage adoption on a Cantonal level.37 As can
be seen therefrom, the french-speaking Cantons (Waad, Neuenburg and Geneva) gave women the
right to vote around 1960, while the Cantons Appenzell-Ausserrhoden and Appenzell-Innerrhoden
introduced su¤rage roughly 30 years later. As for the Canton Appenzell-Ausserrhoden, it is the
only Canton were su¤rage adoption was involuntarily, and mandated by the federal court in 1990.
Table 6, columns 2 and 3 show the fraction voting yes in the two referendums by Canton.
Obviously, there is a strong positive correlation between the share yes on the federal referenda and
the Cantonal timing of introduction. Cantons are clearly ranked according to their support for
women su¤rage and the ranking is roughly stable over time. Between the two referenda in 1959
and 1971, the percentage change of voting yes increased between 20 and 30 percent in all cantons.
— insert Table 6 here —
5.2
Estimation Strategy and Data
The purpose of this section is to investigate the e¤ect of su¤rage on policy outcomes. Using a panel
of 25 Cantons38 from 1950-2000, we are interested in which form female su¤rage a¤ected revenues
and expenditures. Since policy outcomes might be a¤ected by other factors than female voters, we
include a broad range of socio-demographic and economic control variables.
The average impact of women su¤rage on outcome Y is estimated by di¤erence-in-di¤erence
(DD):
37
Similar to the federal level, voting rights for women at the cantonal level had also to be approved
by the male electorate in a Cantonal referendum.
38
The Canton Jura was founded in the year 1977 and is dropped from the sample.
18
Yst =
s
+
t
+ b1 (Dummyf sst F emalest ) + b Zst + ust
We capture the su¤rage e¤ect by a variable Dummyf s
F emale, which is constructed as
the product of an indicator variable for su¤rage adoption (1 if su¤rage is granted, 0 otherwise)
multiplied with the fraction of women older than 20. Intuitively, for su¤rage having an e¤ect,
women must be eligible to vote (and be older than 20).39 Yet, the main e¤ects do not hinge on this
particular speci…cation.
As control variables Z, we include socio-demographic variables (e.g. age structure, share foreigners, religion, education, divorce rates), economic variables (unemployment rate, female labor
force participation) and subsidies / revenue shares from the federal level. Canton-…xed-e¤ects pick
up time-invariant heterogeneity between the Cantons, and time-…xed e¤ects control for common
trends in the development of revenues and expenditures.
Table 7 presents summary statistics for early and late introducers. Early introducers are the
Cantons which adopted Cantonal su¤rage before it was adopted on a federal level (i.e. Cantonal
acceptance before or at the same day of the national referendum). As can be seen therefrom,
early and late introducers di¤er considerably, and most obviously in terms of language and use of
direct democracy. As will be discussed in the robustness Section, these institutional and cultural
di¤erences prove to be the strongest predictors for the Cantons timing of su¤rage adoption and
mitigate concerns of endogeneity.
— insert Table 7 here —
39
The voting age was reduced to 18 in 1991, but we only have 5-year age-classes.
19
5.3
Results
Table 8 depicts the estimation results. As can be seen therefrom, the average e¤ect of giving women
the right to vote was signi…cantly negative for most types of expenditures and revenues. Only for
culture, transport and environment expenditures, insigni…cant positive e¤ects are observed.
Concerning the economic signi…cance of the e¤ects, let us interpret the e¤ect of su¤rage on
overall expenditures. With an average share of 51.4 percent women in the total adult population, the
impact of su¤rage on real per capita expenditures was a reduction of 961 Sfr. (=e(0:514
0:076)
1000).
Evaluated at the mean level of expenditures, the reduction of 961 Sfr. corresponds to a decrease
of nearly 20 percent. As such, su¤rage had a statistically and economically signi…cant negative
impact on overall expenditures and most individual expenditure categories. Not only expenditures,
but also revenues were negatively a¤ected by su¤rage adoption.
As for the controls, most of the coe¢ cients seem to be plausible. More federal revenues induced
the Cantons to spend more (signi…cant positive e¤ects of share revenues and subsidies), a higher
share of elderly people had a large e¤ect on health expenditures, and a higher share of unemployed
increased Cantonal expenditures. A bit puzzling seems to be the negative coe¢ cient before higher
education in the education-expenditure regression. While there is a strong positive correlation
between a Canton´s share of higher educated youngsters and education expenditure, the positive
e¤ect disappears as soon as time-…xed e¤ects and the controls are added. Yet the sign of the
coe¢ cient is not that big to pose a serious concern.
— insert Table 8 here —
Overall, the data suggest that granting su¤rage to women exerted a sizeable negative e¤ect on
nearly all types of revenues and expenditures. How can we reconcile these …ndings with the results
from the federal data?
20
Note …rst that from the policy preferences discovered from the federal data, we found the
greatest gender gaps in the expenditure categories “Environment”, “Defense”, “Public Transport”
and “Social A¤airs”. While “Defense”and “Public Transport”are mostly federal duties (see Table
A1 in the Appendix), the general directions in the …eld of environment are also taken on the federal
level (see footnote 14). Furthermore, the sub-category “Environment”was built later than the other
categories (i.e. in the year 1970), so that less variation might also be a cause for an insigni…cant,
albeit positive e¤ect.
The biggest puzzle poses the signi…cant negative e¤ects of women su¤rage on social expenditures
(welfare and education). Since identi…cation in the estimations stems from the period between 1959
and 1990, the earlier time period might be a possible explanation (remember Edlund & Pande’s
(1999) model, which predicts a change in the female demand for re-distribution over time). Whether
the gender gap on social issues widened over time will be more carefully examined in the robustness
section.
6
Robustness
So far, the aggregate estimates more than con…rm the view that allowing women to politically
participate did not lead to an in‡ation of the government. However, while the micro-data are
unambiguous to interpret, di¤erence-in-di¤erence estimates (as all estimates with aggregate data)
are not immune to potential endogeneity bias. Furthermore, we discovered a di¤erent female impact
on social expenses on a Cantonal level between 1959 and 1990 and on a federal level after 1981.
Whether the di¤erent time-period can explain this gap remains to be seen.
21
6.1
6.1.1
Endogeneity of Adoption
Endogeneity and Di¤erence-in-Di¤erence Estimation
A strict textbook endogeneity problem (causality from expenditures to su¤rage adoption) is obviously not possible, since male voters decided on su¤rage adoption. If we talk about an endogeneity
problem in di¤erence-in-di¤erence estimations, we usually refer to some omitted variable that a¤ects
both, su¤rage adoption and expenditures.
Yet, Di¤erence-in-Di¤erence-estimation is so popular precisely because endogeneity is less of a
concern. Since Canton-Fixed-E¤ects absorb any time-invariant heterogeneity between the Cantons,
omitted variables that simultaneously a¤ect the expenditure level and su¤rage adoption do not pose
a problem. Only if there is an omitted variable that causes di¤erent trends in expenditures between
early and late adopters, the estimated coe¢ cients might be biased.
6.1.2
Estimating Cantonal Voter Preferences
Since su¤rage adoption occurred after the majority of the male voters approved it, male preferences determined su¤rage adoption, but might have had an independent e¤ect on expenditures.
Therefore, …scal voter preferences are the key candidate for omitted variable bias.40 Again, if male
voters’preferences di¤er between early and late adopters, but the gap is constant over time, it does
not bias the estimations. Only if there is a di¤erent trend between early and late adopters’male
preferences, if might bias the estimated su¤rage e¤ect. In addition, the amount of the gender gap
itself might di¤er between early and late introducers, e.g. because a large di¤erence between female
and male preferences might have delayed adoption. Then, the long-term e¤ects of women su¤rage
might di¤er from the estimated short-term e¤ect.41
40
Voter preferences unrelated to spending do not pose a problem. Since we control for a whole
bunch of Canton characteristics, …scal voter preferences are likely to be partly captured by those.
41
Di¤erence-in-Di¤erence estimation basically compares early introducers’expenditure-change after su¤rage adoption with the respective expenditures of a control group of non-adopters (i.e. the
22
With our unique data set of federal issue votes, we can recover Cantonal male preferences
from 1950-1970 (remember that su¤rage adoption occurred in 1971 at the federal level), and total
Cantonal voter preferences thereafter. Since we have information about the Cantons’share yes on
all federal votes (only the surveys are restricted to the votes after 1981), we can build an intuitive
measure for …scal voter preferences. For the …ve decades between 1950 and 2000, we measure the
Cantons’…scal voter preferences as the average share yes on proposals with an implied increase in
expenditures.42 Since this measure of voter preferences is extensively discussed in another paper,43
we are very brief here. We would only like to mention that in many areas, the Cantonal and federal
level have shared responsibilities, and that preferences measured from federal voting data are a
good proxy for voter preferences at the Cantonal level. Furthermore, since all Cantons voted on
the same federal issues, these voter preferences are directly comparable between the Cantons.
We will use our measure for voter preferences to check, whether early introducers had a di¤erent
trend in male voter preferences between 1950-1970, and whether the gender gap di¤ers between
early and late introducers.44 If both is not the case, concerns for biases are minimal.
Table 9 …rst column shows that early introducers were …scally less conservative than late introducers. Remembering that early introducers had signi…cantly higher expenditures than late
introducers, this comes at no surprise. Whether early introducers had a di¤erent trend in male
voter preferences is investigated by including a linear time trend and an interaction term “time
early adopter”. As can be seen from column 2, there was no trend in …scal voter preferences
between 1950 and 1970, and neither a di¤erence between early and late introducers. As such, it
seems safe to assume that there is no di¤erent trend in male voters’preferences, which could dislate introducers). Therefore, the period of identi…cation ends when the latest adopter introduces
su¤rage.
42
The classi…cation into votes with implied …scal consequences is analog to the previous analysis
in section 4, where the federal votes with survey data were analyzed.
43
See Funk & Gathmann (2005).
44
Since Cantonal and federal su¤rage adoption di¤ered in time, we cannot just plug in the omitted
variable into the regressions.
23
tort the estimated su¤rage coe¢ cients.45 What about di¤erent gender gaps between early and late
introducers? If the gender gap di¤ers, then we would observe a di¤erent e¤ect of the introduction
of su¤rage on average voter preferences. Column 3 …rst analyzes how voter preferences changed
after su¤rage was allowed. As can be seen therefrom, support for costly projects fell. However,
since other factors could account for the drop in approval, we cannot conclude that su¤rage was the
cause for it. Straightforward to interpret are di¤erences between Cantons. Column 4 shows that
the decrease in approval for costly projects was not di¤erent between early and late introducers. As
such, there seems to be no evidence for a di¤erent gender gap between early and late introducers.
Summing up our discussion on endogeneity, we note that early and late introducers do have
di¤erent …scal preferences, but that these di¤erences persist over time. Therefore, omitted variable
bias is unlikely the case. Even though …scal preferences might matter for the decision to adopt
su¤rage or not, we suspect that (time-invariant) cultural and institutional factors are at least as
important (and cannot cause an omitted variable bias, since they are captured by the Canton-Fixede¤ects). A detailed micro-data study on su¤rage adoption reveals that language is the strongest
predictors for a men’s probability of voting “yes” in the 1971 national referendum on su¤rage
adoption.46 Therefore, the well-known Swiss “Roestigraben”, which has since ever divided germanspeaking and french-speaking voters, seemed to exist for the su¤rage question as well.47
45
We also performed the standard approach in the literature, i.e. to compare growth rates of the
dependent variable prior to the policy adoption. If no di¤erences between early and late introducers
is found, it is normally concluded that the chance for omitted variables causing di¤erent trends
is small. In our case, we compared growth rates of expenditures between early and late adopters
between 1950 and 1959. Late introducers had a slightly higher expenditure growth than early
introducers, but the di¤erence is not statistically signi…cant. Therefore, signi…cantly di¤erent
expenditure trends already prior to su¤rage adoption are not prevalent.
46
We exploited a survey held in 1972 (“Swiss voting study, 1972”), where, among others, Swiss
men were asked whether they voted yes or no in the 1971 referendum. We …nd that language is the
most important factor, with non-german speaking men being 12 % more likely to vote yes. Apart
from language, well-educated and mobile men were more likely to vote yes, but men, who indicated
reading the newspaper frequently, were more likely to vote no. Therefore, in direct-democratic
Cantons, where people are more active and generally better informed (see Benz & Stutzer (2004)),
opposition against women su¤rage might have been stronger (all estimations are available upon
request).
47
For many political issues, german and french-speaking Cantons show consistently di¤erent voting patterns. The name “Roestigraben” stands for a valley, which geographically separates the
24
6.2
Time-Varying Gender Gaps
While the gender gap seems to be similar across Cantons for a given point of time, the gender
gap might vary over time, and hence be di¤erent at di¤erent times of su¤rage adoption. Due to
diverging results of female political participation on social expenditures between 1959-1990 on a
Cantonal level and 1981-2003 on a federal level, we suspect a time-varying gender gap for this
expenditure type.
If there is widening gender gap for social expenses over time (with women becoming comparatively pro-expenditures), the data should show the following: 1) A positive time trend of su¤rage
on social expenditures, and 2) A bigger su¤rage e¤ect for late introducers.
Table 10 shows that this is precisely the case. Not only is there a positive time trend on social
expenditures (see …rst row), but also do late-adopting Cantons have a higher estimated su¤rage
e¤ect (see lower part). Since di¤erent gender gaps between early and late adopting countries have
not been found for a given point of time, the results point to a time-varying gender gap.
Discriminating between all the possible explanations for the increasing female support for social
expenditures goes beyond the scope of this paper. However, we checked whether the dynamics can
be explained with an increase in female participation and/or a change in the composition of the
electorate, and found no support for that.48 Rather, there seems to be a change in average female
german-speaking part from the french-speaking part, but refers to the di¤erent voting behavior of
these two language-regions.
48
First, we estimated female participation rates based on turnout in Cantonal elections. The
basic intuition behind the procedure is straightforward: if women did hardly participate after they
received the right to vote, then turnout (de…ned as number of voters divided by the number of
eligible voters) would drop sharply. Under the identifying assumption that the male propensity to
vote was una¤ected by the introduction of su¤rage, female participation rates can be estimated
from the regressions, which relate overall turnout to the introduction of women su¤rage. Even
when estimating the e¤ect of an increase in female voters among the voting population on social
expenditures in di¤erent subsequent time-periods, there are more positive e¤ects in later periods (all
the estimations are available upon request). Therefore, increasing political participation of women
is not the cause for the dynamic su¤rage e¤ect on social expenditures. However, since turnout
adaption occurred quite rapidly is Switzerland (see e.g. Ballmer-Cao (1988)), it is unlikely the cause
for the dynamic pattern a priori. Secondly, concerning composition of the electorate, we compared
voters’and non-voters’political attitudes in 1995 (Selects Study) and 1975 (Political Action Study),
where surveys are available. As the data show, voters did not signi…cantly distinguish themselves
from non-voters in 1975. In 1995 however, it was the case for both genders that the non-voters
25
“social preferences”over time. In the spirit of Edlund & Pande (2002) and Schlesinger & Heldmann
(2001), who claim that changing marital patterns and increased labor market participation of
women49 are responsible for women’s relative shift to the left, we investigated whether it is this
growing sub-group of women, which favors social expenses. Adding interaction terms (“single
women”, “working
women”) to the estimates for social issues in table 3, we …nd signi…cant
coe¢ cients in the area of age insurance. There, it is only the subgroup of single/divorced and
working women, who oppose an increase in the retirement age. For the cleanest redistributive issue
(subvention of health premia), the female dummy turns insigni…cant, as soon interaction terms
are added, but the interaction terms themselves are not signi…cant. As such, it becomes evident
that a subgroup of women (working and/or unmarried), which dramatically increased since the
early 70-ties, supports at least certain types of social expenses. Plausibly, not only the change in
the household structure, but also the increased longevity of women has increased the demand for
governmental support after retirement. Therefore, several dimensions of social change (female labor
force participation, marriage structure, life expectancy) could account for the dynamic su¤rage
e¤ects, we found in the Cantonal data.50
7
Discussion
When it comes to describing the e¤ects of political participation of women, the simple equation
“more women = more government” summarizes current research results fairly well.51
In this article, we hoped to demonstrate that adding more dimensions helps not only to characterize female voter preferences better, but also to more fully understand the …scal policy response
were ideologically more left. As such, the increasing e¤ect of su¤rage on social expenditures cannot
be explained by enhanced mobilization of left-wing female voters.
49
According to Schlesinger & Heldman (2001), entry in the labor market might increase women’s
awareness of horizontal discrimination and raise the need for support with the kids.
50
Concerning women’s support for child care facilities, the federal data do not allow to carry out
such test, since this public good is provided at the communal level.
51
One exception is Stutzer & Kienast (2004).
26
of women’s political participation.
Using a unique data set on issue voting in Switzerland, we were able to compare women and
men’s voting choices on 195 di¤erent ballots between 1981 and 2003. We found the largest gender
gaps in areas such as environmental policy, nuclear energy policy, defense, social and health issues
and equal rights of women and men. Therefore, we can safely say that women di¤er from men in
their policy preferences in more dimensions than just the taste for redistribution. In fact, these
multiple gender gaps can rarely explained by a one-dimensional right-left indicator.
In line with preferences, women’s desired …scal policy depends on the topic. While women
were more likely to support higher government expenditures, if they were e.g. invested in the
protection of the environment, women opposed governmental funds being invested in the military
or for subsidizing agriculture.
Overall, women seemed to have a much bigger impact on the scope rather than the size of
government. The Cantonal data only support this view. Our di¤erence-in-di¤erence estimation
even reveals a negative adoption e¤ect on total and most types of expenditures and revenues. Only
for transport, culture and the environment, the e¤ect seems to be (insigni…cantly) positive.
The main di¤erence between the results on the Cantonal and federal level concerns social expenditures. The di¤erent time period o¤ers an explanation, since social expenditures exhibit a
time-varying gender gap (with an increasing su¤rage e¤ect over time). Since a subgroup of women
(single and/or employed) supports certain types of social expenditures, further changes in marriages
patterns and female labor force participation might enlarge the set of female voters supporting a
more social government. As such, even though there are no signs that female political participation
was the reason for the growth in government in the late twentieth century, we cannot rule out that
there will be a substantial e¤ect on social expenditures in the future.
An unresolved issue concerns the negative overall su¤rage e¤ect, which stands in contrast to
27
…ndings for the U.S. As for the plausibility of a more conservative e¤ect of female political participation over the horizon 1959-1990 (where identi…cation in our DD-setting comes from), we note
that it does not contradict the gender gap in policy preferences. First, Switzerland has, as many
other countries (see Inglehart & Norris (2003)), seen women shifting to the left, with women becoming more left-wing than men after 1983 (see Kue¤ner (2004)). Since party-a¢ liation best explains
preferences for redistribution, we would expect a negative su¤rage e¤ect on social expenses before
1983. The negative estimated su¤rage e¤ect on Cantonal social expenses is therefore consistent
with preference for redistribution during that time. As for the other expenditure types, we neither
…nd inconsistencies with preferences identi…ed at the federal level.
Nonetheless, there might be a connection between the women su¤rage e¤ect and the institutional form of the Cantons. Since women su¤rage increased the degree of direct democracy,52 this
strengthening of direct-democracy might help explain the more negative e¤ect in Switzerland and
the United States. We can asses the magnitude of this e¤ect by comparing Cantons with and without mandatory referenda. In the Cantons, where no mandatory law- and budget-referenda exist,
the control power of the citizens got strengthened by women su¤rage due to the relaxed hurdle of
signature requirements. In the other Cantons, where referenda are mandatory, the control power
did not change after women received the right to vote. Therefore, if the strengthening of direct
democracy was the driver behind the negative e¤ect on expenditure, we would expect a more negative e¤ect in Cantons without mandatory referenda. However, results from regressions including
a dummy for mandatory referenda and interaction terms with female su¤rage are not supportive of
this view.53 As such, the negative adoption e¤ect seems to be present in Cantons with and without
52
In many Cantons, the signature requirements for launching an initiative or referendum remained
unchanged. Since the number of eligible voters doubled, it became easier to collect the necessary
number of votes.
53
The budget-referendum seems to be the most important instrument to control government
expenditures (see Feld & Matsusaka (2003)). We therefore ran some regressions including a dummy
for the existence of a harsh form of budget referendum as well as an interaction term between this
mandatory budget referendum and women su¤rage. The results indicate no signi…cant interaction
28
mandatory budget referendum, and unrelated to a potential strengthening of direct-democratic
in‡uence.
Coming back to the title of the paper (“What women want”), we hope to have provided satisfactory answers given the data set at hand. In view of the di¤erences between the United States
and Switzerland, more research from other countries would be highly appreciated. Women su¤rage
is a complex, but unfortunately under-researched topic in economics.
References
[1] Abrams, B.A. and R.F. Settle (1999), ”Women’s Su¤rage and the Growth of the Welfare
State”, Public Choice, 100: 289-300.
[2] Ballmer-Cao, T.-H. (1988), Le Conservatisme Politique Féminin en Suisse: Mythe ou Réalite?,
Geneva, Switzerland.
[3] Berman, David R. (1993): ”Gender and Issue Voting: The Policy E¤ects of Su¤rage Expansion
in Arizona”, Social Science Quarterly, 4: 838-850.
[4] Benz, M. & A. Stutzer (2004): ”Are Voters Better Informed When They Have a Larger Say in
Politics? Evidence for the European Union and Switzerland”, Public Choice, 119(1-2): 31-59.
[5] Center for American Women and Politics CAWP (1997), ”The Gender Gap: Attitudes on
Public Policy Issues.”www.cawp.rutgers.edu
[6] Chattopadhyay, R & E. Du‡o (2004), ”Women as policy makers: Evidence from a randomized
experiment in India”, Econometrica, 72(5): 1409-1443.
[7] Conover, P. (1988), ”Feminists and the Gender Gap”, Journal of Politics, 50(4): 985-1010.
term for total expenditures. All regressions are available upon request.
29
[8] Downs, A. (1957), An Economic Theory of Democracy. New York: Harper & Row.
[9] Dwyer, P., Gilkeson, J.H. & List, J. (2002), ”Gender Di¤erences in revealed risk taking: evidence from mutual fund investors”, Economics Letters, 76: 151-158.
[10] Edlund, L. and R. Pande (2002), ”Why Have Women Become More Left-Wing? The Political
Gender Gap and the Decline in Marriage”, Quarterly Journal of Economics, 117: 917-61.
[11] Eduards, M. (1981), ”Sweden”, in Lovenduski J., and J. Hills (edt.).The Politics of the Second
Electorate. London: Routledge & Kegan Paul.
[12] Erie, S.P. and M. Rein (1998), ”Women and the Welfare State”, in Mueller C. The Politics of
the Gender Gap. London: Sage.
[13] Feld, L.P. (2000): ”Tax Competition and Income Redistribution: An Empirical Analysis for
Switzerland”, Public Choice, 105: 125-64
[14] Feld, L.P. and J.G. Matsusaka (2003), ”Budget Referendums and Government Spending: Evidence from Swiss Cantons”, Journal of Public Economics, 87: 2703-24.
[15] Funk, P. and C. Gathmann (2005), ”Estimating the E¤ect of Direct Democracy on Policy
Outcomes: Preferences Matter!”, Stanford Center for International Development Working
Paper Series Nr. 248
[16] Gidengil, E. (1995), ”Economic Man - Social Women?”, Comparative Political Studies, 28(3):
384-408.
[17] Grossman, G. and Helpman, E. (1995), ”Electoral Competition and Special Interest Politics”,
Review of Economic Studies, 63(2): 265-86.
30
[18] Inglehart, R. and P. Norris (2000), ”The Developmental Theory of the Gender Gap: Women´s
and Men´s voting behavior in a Global Perspective”, International Political Science Review,
XXI: 441-463.
[19] Inglehart, R. and P. Norris (2003), ”Rising Tide: Gender Equality and Cultural Change around
the world”, Cambridge University Press.
[20] Kue¤ner, S. (2004), ”Do women vote di¤erently? The gender gap in Switzerland (translation)”,
Master thesis, University of Bern.
[21] Ladner, A. and M. Braendle (1999), ”Does Direct Democracy matter for Political Parties?”,
Party Politics, 3: 283-302.
[22] Levitt, S.D. (1996), ”How do senators vote? Disentangling the Role of Voter Preferences, Party
A¢ liation, and Senator Ideology ”, American Economic Review, 86(3): 425-441.
[23] Longchamp, C. and U. Bieri (2001), ”Women and Men as voters: how did they decide (translation).”http://www.gfsbern.ch/gfs/gender.html
[24] Lott, J.R. and L.W. Kenny (1999), ”Did Women’s Su¤rage Change the Size and Scope of
Government?”, Journal of Political Economy, 107: 1163-98.
[25] Matsusaka, J.G. & McCarty, N.M. (2001), ”Political Resource Allocation: Bene…ts and Costs
of Voter Initiatives ”, The Journal of Law, Economcis and Organization, 17: 413-448.
[26] Moeckli, (1987), Die schweizerischen Landsgemeinde-Demokratien. Bern, Switzerland.
[27] Mueller, C. (1998), The Politics of the Gender Gap. London: Sage.
[28] Norris, P. (1998), ”The Gender Gap: A Cross-National Trend?”, in Mueller C.The Politics of
the Gender Gap. London: Sage.
31
[29] Schlesinger, M. & C. Heldman (2001), ”Gender Gap or Gender Gaps?”, The Journal of Politics,
63(1), 59-92.
[30] Schumaker, P. & Burns, N.E. (1988), ”Gender Cleavages and the Resolution of Local Policy
Issues”, American Journal of Political Science, 32(4), 1070-1095.
[31] Seitz, W. (2004), ”Ein Streifzug durch 100 Jahre Kampf um die politische Gleichstellung der
Frauen in der Schweiz. Gleichstellungspolitische Strategien und die ambivalenten Wirkungen
der direkten Demokratie”, mimeo, Bundesamt f½ur Statistik, Switzerland.
[32] Seltzer R., Newman J., and M. Leighton C. (1997), Sex as a Political Variable. London: Lynne
Rienner Publishers.
[33] Shapiro, R. & H. Mahajan (1986), ”Gender Di¤erences in Policy Preferences: A Summary of
trend From the 1960’s to the 1980’s”, The Public Opinion Quarterly, 50(1), 42-61.
[34] Stutzer, A. and L. Kienast (2004), ”Demokratische Beteiligung und Staatsausgaben: Die
Auswirkungen des Frauenstimmrechts”, mimeo, University of Zurich, Switzerland.
[35] Tavares, J. (2004), ”Does right or left matter? Cabinets, credibility and …scal adjustments ”,
Journal of Public Economics, 88: 2447-2468.
[36] Trechsel, A. and U. Serduelt (1999), Kaleidoskop Volksrechte: Die Institutionen der direkten
Demokratie in den Schweizerischen Kantonen 1970-1996, Basel and Muenchen: Helbing and
Lichtenhahn.
A
Canton-Level Panel Data
The canton level data on expenditures and revenues are taken from the annual collections on public
…nances of Switzerland (Federal Department of Finance, various years). Data are available on paper
32
format before 1980 and electronically after 1980. Real per capita expenditures (in 1000 Sfr. and
2000 prices) are built for the following types: total cantonal expenditures, security, education,
culture, welfare, tra¢ c, environment, and agriculture. For the years 1967 and 1968, no separate
expenditure data for Cantons and communities were available, but only expenditures for Cantons
and their communities together. Values for these years were obtained by linear interpolation. The
expenditure-categories “culture”and “environment”were created later, in the years 1977 (culture)
and 1970 (environment). Total revenue data are available for all years except the years 1968 and
1969. Cantonal shares from federal revenues are unavailable for the years 1968, 1969 and 1990-1993.
As for federal subsidies, data were unavailable for the years 1950-1952, 1968-1977 and 1990-1993.
These values were obtained by linear interpolation. Data on the budget de…cit data were completely
collected for all the years.
For the canton characteristics, most variables are from the decennial population census with
intermediate values interpolated. Data for the population in rural and urban areas is only available
since 1970. The education variable is measured as the share of high-school graduates in percentage
of the 19 year-old population. Data on average per capita income in the cantons is available since
1965. The unemployment rate is calculated as the number of registered unemployed relative to the
active population from the State Secretariat for Economic A¤airs after 1975 and as the number of
unemployed in percentage of employed persons from the population census before 1975. Population
density is measured as the log of the number of people (in 1,000) per square kilometer. Variables
of the household structure are again from the population census and include: the percentage of
single-parent households, the share of married people in the group older than 20, the group of
divorced people in the same age group. Also from the population census are data on the percentage
of foreigners in the total population, the share of Catholics and citizens in di¤erent age classes
(i.e. between 0 and 19, between 20 and 39, between 40 and 64, between 65 and 79, older than 80).
33
Female labor force participation is measured as the share of women older than 15 who work.
Information on the existence of a mandatory budget referendum is taken from Trechsel and
Serduelt (1999), who systematically collected information for cantons without a town-meeting from
1970 to 1996. For previous years or Cantons not covered by Trechsel and Serduelt (i.e. the townmeeting Cantons), we gathered data from all the Cantonal Public Record O¢ ces and supplemented
missing information from old canton laws and constitutions.
34
Table 1: Introduction of Women Suffrage in Swiss Cantons
Women Suffrage
Adopted in
Canton (Year)
Yes Votes in
Federal Referendum
of 1959 (%)
Yes Votes in
Federal Referendum
of 1971 (%)
Neuenburg (NE)
Wadt (VD)
Geneve (GE)
Basel-Stadt (BS)
Basel-Land (BL)
Tessin (TI)
Zuerich (ZH)
Wallis (VS)
Luzern (LU)
1959
1959
1960
1966
1968
1969
1970
1970
1970
51.3
52.2
60.0
46.8
37.3
37.1
36.2
30.5
21.3
83.9
82.0
91.9
82.2
79.9
75.3
66.8
79.9
62.7
Zug (ZG)
Freiburg (FR)
Schaffhausen (SH)
Aargau (AG)
1971
1971
1971
1971
29.8
24.3
31.9
22.8
71.1
59.9
56.7
50.2
Bern (BE)
Glarus (GL)
Solothum (SO)
Thurgau (TG)
1971
1971
1971
1971
35.5
19.1
30.0
19.9
66.5
41.3
64.1
44.1
St. Gallen (SG)
Uri (UR)
Schwyz (SZ)
Graubuenden (GR)
Nidwalden (NW)
Obwalden (OW)
Jura (JU)
Appenzell Aussenrhoden (AR)
Appenzell Innerrhoden (AI)
1972
1972
1972
1972
1972
1972
1977
1989
1990
19.3
14.6
14.2
22.4
19.5
14.3
N/A
15.5
4.9
46.5
36.3
42.2
54.8
55.8
46.7
N/A
39.9
28.9
Canton
Notes : The table reports the year women were given the right to vote at the cantonal level and the fraction of voting men that supported
the introduction of women suffrage in the two federal referendums 1959 and 1971. Since the canton Jura separated from Bern only in
1977 to become an independent canton, no separate results for the federal referendums are available. The canton AppenzellInnerhoden was forced to adopt women suffrage by the Swiss Supreme Court in 1990.
Table 2: Summary Statistics for VOX-Data on Federal Propositions, 1981-2003
Women
Mean
Std. Dev
Mean
Men
Std. Dev
T Statistic
Difference
Knowledge, Information & Education
Know Details Vote
Opinion from Newspaper
Opinion from Radio
Opinion from TV
Education: Compulsory
Education: Apprentice/Spec Schools
Education: University
0.74
0.73
0.53
0.67
0.24
0.70
0.06
0.44
0.45
0.50
0.47
0.43
0.46
0.23
0.82
0.81
0.55
0.72
0.12
0.77
0.11
0.39
0.39
0.50
0.45
0.32
0.42
0.32
37.9
35.2
8.1
19.3
-67.7
32.0
41.5
Work and Income
Employed
Income
Own-House
0.52
10.91
0.40
0.50
10.42
0.49
0.71
20.40
0.43
0.45
10.50
0.50
84.2
13.3
13.6
Civil Status
Single
Married
Divorced
0.22
0.62
0.06
0.41
0.49
0.23
0.30
0.65
0.03
0.46
0.48
0.17
40.4
13.2
-24.5
Socio-Economic
Age
Protestant
Have Kids
46.73
0.45
0.40
17.10
0.50
0.49
46.99
0.45
0.32
17.82
0.50
0.47
3.1
-1.3
-18.3
Area
Urban
Nongerman
0.65
0.29
0.48
0.45
0.64
0.28
0.48
0.45
-3.02
-3.25
Notes: All the variables except income and age are Dummy-Variables.
Table 3: Gender Differences in different Policy Areas, with controls
Internat. Politics
Female Dummy
Female Dummy
(with Controls)
Observations
Pseudo R Squared
Swiss Law and Direct Democracy
Joining
international
Organizations
0.010
(0.017)
Equal Rights
Women and
Men
0.115
(0.027)***
More
Direct
Democracy
0.037
(0.021)*
Pro
Legalization
Abortion
-0.064
(0.039)*
0.028
(0.022)
2803
0.1782
0.164
(0.034)***
1234
0.2705
0.007
(0.026)
1898
0.2353
-0.011
(0.042)
517
0.1309
Environm. & Nuclear Pol.
Female Dummy
Female Dummy
(with Controls)
Observations
Pseudo R Squared
Agricultural Policy
Female Dummy
(with Controls)
Observations
Pseudo R Squared
Drug Policy
Pro
Pro
restricting
easier
foreigners integration
-0.040
0.064
(0.021)*
(0.031)**
Liberal
Drug
Policy
-0.010
(0.024)
-0.089
(0.031)***
1038
0.0732
-0.013
(0.027)
1654
0.1333
Fiscal Pol.
0.066
(0.035)*
835
0.1345
Culture & Leisure
Pro
Environmental
Protection
0.088
(0.013)***
Against
Nuclear
Policy
0.097
(0.017)***
Against
Subsidizing
Agriculture
0.073
(0.030)**
Pro
liberal
Agriculture
0.006
(0.020)
Pro Reduct.
Federal
Debt
-0.039
(0.016)**
More
Culture
0.038
(0.024)
More leisure,
reduction
work hours
0.008
(0.019)
0.069
(0.015)***
5711
0.1163
0.124
(0.020)***
2892
0.0706
0.060
(0.034)*
906
0.0625
0.012
(0.023)
2429
0.1441
-0.049
(0.018)***
2811
0.0017
0.057
(0.039)
759
0.1196
0.028
(0.030)
1823
0.3862
Housing
Education
Relax
speed
limits
-0.124
(0.023)***
Pro
cheap
rent
0.004
(0.041)
Pro
free
education
0.052
(0.042)
-0.135
(0.042)***
683
0.0947
0.004
(0.046)
522
0.1318
0.051
(0.054)
389
0.0702
Transportation Politics
Gentech.
Female Dummy
Immigration Politics
Against
Gentech. &
Animal test.
0.068
(0.017)***
0.064
(0.020)***
2901
0.0714
Against
Pro
Against
further road
public
subsidizing
construction transportation parking space
0.076
0.030
0.121
(0.016)***
(0.020)
(0.060)**
0.030
(0.020)
2807
0.0928
0.021
(0.023)
2102
0.0895
0.116
(0.069)*
271
0.0897
Social Security
Female Dummy
Female Dummy
(with Controls)
Observations
Pseudo R Squared
Protection
Motherhood
0.051
(0.026)**
Pro
reduction
un. benefits
-0.043
(0.025)*
Pro increase
retirement
age
-0.072
(0.035)**
0.035
(0.031)
1312
0.1802
-0.008
(0.030)
1437
0.1904
-0.066
(0.040)
754
0.0955
Health Policy
Female Dummy
Female Dummy
(with Controls)
Observations
Pseudo R Squared
Pro decrease
Pro
retirement
support for
age
the disabled
0.093
0.146
(0.024)***
(0.043)***
0.073
(0.026)***
1726
0.0535
0.120
(0.049)**
508
0.0907
Military
Restricting
advertisment
alcohol/tabac
0.133
(0.02)***
Pro subv.
health insur.
premia
0.058
(0.020)***
More
individual
resp. health
-0.050
(0.021)**
Less
Military
0.134
(0.021)***
1726
0.0693
0.034
(0.023)
1767
0.0699
-0.043
(0.023)*
1107
0.0797
0.061
(0.024)**
2300
0.1755
0.242
(0.017)
Notes: The table reports estimates from a probit model, with marginal coefficients being reported. For four votes (Legalization Abortion, Cheap Rents, Support for the
disabled and Individual Responsibility Health Care), only decisions of voters have been asked - there only coefficients for voters are reported. In the model with
controls, age, education, houseownership, marital status, employment, religion, urban area as well as language are controlled for. Also included are Canton- and Time
fixed effects. Robust standard errors are in parantheses.
Table 4: Voting in Favor of More Government in Federal Referendums
Voting for More Government
Less Government
Observations
Pseudo R Squared
(1)
More
Gov.
0.022
(0.006)***
32174
0.0003
(2)
Increase
Exp.
0.043
(0.007)***
18960
0.0013
(3)
Increase
Sub/Grant
0.023
(0.022)
1910
0.0001
(4)
Increase
Taxes
-0.008
(0.009)
11304
0.0001
(1)
Less
Gov.
-0.016
(0.009)*
11803
0.0002
(2)
Decrease
Exp.
0.021
(0.014)
5186
0.0003
Female Dummy
(with Controls)
Observations
Pseudo R Squared
0.017
(0.007)***
27115
0.037
0.034
(0.009)***
15655
0.0424
0.059
(0.029)**
1216
0.1414
-0.007
(0.011)
10183
0.08
-0.020
(0.011)*
10125
0.043
0.010
(0.017)
4003
0.1064
Female Dummy
Voting for Less Government
Supporting Increases in Specific Expenditure Types
Observations
Pseudo R Squared
(3)
Decrease
Sub/Grant
-0.024
(0.016)
3920
0.0004
(4)
Decrease
Taxes
-0.081
(0.035)**
748
0.0054
(1)
Increase
Social
0.074
(0.012)***
6686
0.0044
(2)
Increase
Environm.
0.116
(0.019)***
2450
0.0113
(3)
Increase
Agricult.
-0.033
(0.040)
631
0.0008
(4)
Increase
Cultural
0.038
(0.024)
1679
0.0011
Female Dummy
(with Controls)
Observations
Pseudo R Squared
-0.016
(0.018)
3651
0.0627
-0.079
(0.040)**
702
0.0587
0.055
(0.014)***
6117
0.0743
0.072
(0.022)***
2322
0.0953
-0.031
(0.045)
614
0.0781
0.057
(0.039)
759
0.1196
Female Dummy
Opposing Increases in Specific Expend.
Observations
Pseudo R Squared
(5)
Increase Pub.
Transport
0.107
(0.035)***
778
0.0087
(1)
Decrease
Social
-0.059
(0.021)***
2211
0.0026
(2)
Decrease
Defense
0.047
(0.016)***
3645
0.0017
(3)
Decrease
Agric.
0.060
(0.026)**
1200
0.0036
Female Dummy
(with Controls)
Observations
Pseudo R Squared
0.101
(0.040)**
733
0.1325
-0.054
(0.024)**
2068
0.0705
0.063
(0.022)***
2548
0.1174
0.043
(0.029)
1124
0.0781
Female Dummy
Notes: The table reports estimates from a probit model, with marginal coefficients being reported. In the model with controls, age, education,
houseownership, marital status, employment, religion, urban area as well as language are controlled for. Also included are Canton- and Time fixed
effects. Robust standard errors are in parantheses.
Table 5: Summary Statistics for Canton-Level Data, 1950-2000
Early Adopters
Mean
Std. Dev
Late Adopters
Mean
Std. Dev
T Statistic
Difference
Expenditures Per Capita (in 2000 SFr)
Overall
5471.57
Health
941.65
Education
1347.66
Welfare
716.54
Security
504.92
Culture
181.44
Traffic
743.22
Environment
207.71
Agriculture
310.26
Finance
379.07
Growth Rate Expenditures
0.037
3607.75
977.71
936.69
687.42
318.57
267.97
451.15
142.13
286.12
284.71
0.065
4554.42
546.45
723.75
423.58
395.02
84.49
1123.39
241.99
641.13
339.29
0.042
2805.23
419.28
515.45
323.97
200.28
47.30
1487.31
196.17
544.67
348.71
0.084
-4.94
-9.06
-14.28
-9.42
-7.16
-6.05
5.84
2.81
13.05
-2.13
1.207
Revenues Per Capita (in 2000 SFr)
Overall
Tax Revenues
Federal Subsidies
Shares on Federal Revenues
Debt
Deficit
Growth Rate Revenues
5279.49
2804.23
555.89
316.31
6321.53
-93.48
0.003
3490.78
2125.23
545.37
279.41
5358.24
749.66
0.346
4465.19
1649.60
880.30
276.53
3766.53
-18.93
0.000
2793.29
992.09
899.38
189.83
1910.14
404.82
0.412
-4.49
-12.26
6.41
-2.77
-7.81
2.18
-0.148
Political System
Leftist Parties (%)
Fractionalization of Parliament
26.42
4.10
11.43
1.35
14.89
3.04
10.57
0.97
-17.71
-14.60
Direct-Democratic Control
Dummy Mandatory Budetref.
0.35
0.48
0.94
0.24
27.57
4.75
2.33
1.91
1.83
1.11
77.51
0.91
4.35
33.09
26.74
1.06
7261.85
1.66
7.01
3.72
0.00
12.78
-19.10
-13.80
3.11
1.30
-10.21
-8.14
-16.02
18.93
4.40
-3.51
-7.91
-12.27
-0.10
-9.14
-22.96
Control Variables
Age 0 to 19 (%)
Age 20 to 39 (%)
Age 40 to 64 (%)
Age 65 to 79 (%)
80 and Older (%)
Population Density
Unemployment Rate
Foreigners (%)
Rural (%)
Catholics (%)
Single Parents (%)
Mean Annual Income
Divorced (%)
Female Labor Force Part. (%)
Education
Language: Nongerman
27.64
5.36
31.27
30.52
1.88
28.26
29.59
2.61
27.81
9.83
1.83
10.15
2.42
1.14
2.51
727.09
1466.47
121.23
1.17
1.69
0.54
16.28
7.32
10.83
21.07
16.35
56.07
55.12
24.22
61.39
5.84
1.24
5.61
10082.65 11996.95 4731.45
3.96
2.21
2.61
41.39
6.80
41.35
10.58
6.92
7.70
0.46
0.50
0.00
Notes : The table reports summary statistics over the whole sample period (1950-2000) separately for cantons adopting in
1971 or earlier ("early adopters") and those adopting after 1971 ("late adopters").
Table 6: The Adoption Effect of Women Suffrage on Expenditures
Overall
Health
Welfare
Education
Security
Finance
Culture
Admin.
Transport
Women Suffrage
-0.076
(0.036)**
-0.188
(0.086)**
-0.096
(0.055)*
-0.128
(0.044)***
-0.084
(0.038)**
-0.231
(0.088)***
0.078
(0.349)
-0.006
(0.051)
0.146
(0.100)
Fraction Aged 20-39
0.001
(0.008)
0.025
(0.008)***
-0.039
(0.008)***
-0.093
(0.022)***
-0.003
(0.002)
-0.478
(0.090)***
0.001
(0.003)
-0.006
(0.002)***
0.022
(0.007)***
-0.127
(0.023)***
0.013
(0.012)
-0.009
(0.003)***
0.004
(0.017)
0.125
(0.020)***
0.142
(0.019)***
0.146
(0.020)***
0.130
(0.023)***
0.231
(0.062)***
0.005
(0.005)
1.261
(0.273)***
-0.010
(0.010)
0.014
(0.004)***
-0.007
(0.018)
-0.458
(0.061)***
0.108
(0.029)***
-0.055
(0.007)***
0.077
(0.047)
0.111
(0.037)***
0.042
(0.014)***
0.078
(0.014)***
-0.025
(0.013)*
0.028
(0.043)
0.014
(0.003)***
-0.409
(0.163)**
0.007
(0.005)
-0.007
(0.003)***
0.008
(0.011)
-0.012
(0.031)
-0.028
(0.018)
0.002
(0.005)
0.047
(0.014)***
-0.000
(0.022)
1202
0.97
1202
0.93
1202
0.97
Fraction Aged 40-64
Fraction Aged 65-79
Fraction Older than 80
Higher Education
Log Population Density
Percentage Foreigners
Fraction Catholic
Unemployment Rate
Share Divorced
Share Single Parents
Female Labor Force
Share Federal Revenues
Federal Subsidies
Observations
R-squared
-0.004
-0.011
(0.010)
(0.008)
-0.005
-0.005
(0.010)
(0.008)
-0.046
-0.016
(0.010)*** (0.007)**
-0.124
-0.049
(0.032)*** (0.023)**
-0.009
0.002
(0.003)***
(0.002)
0.255
-0.252
(0.106)** (0.100)**
-0.006
-0.012
(0.004)* (0.003)***
-0.002
-0.004
(0.002)
(0.001)***
-0.029
0.001
(0.009)***
(0.007)
-0.142
-0.135
(0.026)*** (0.015)***
-0.038
0.003
(0.014)***
(0.012)
-0.005
-0.001
(0.003)
(0.003)
0.059
0.004
(0.036)*
(0.008)
0.072
-0.027
(0.018)*** (0.014)*
1202
0.97
1202
0.97
0.052
-0.033
0.001
-0.057
(0.019)*** (0.047)
(0.011)
(0.024)**
0.065
-0.011
0.004
0.000
(0.020)*** (0.047)
(0.012)
(0.022)
-0.058
-0.014
-0.011
0.003
(0.017)*** (0.038)
(0.011)
(0.020)
-0.157
-0.254
-0.054
-0.101
(0.063)** (0.146)*
(0.038)
(0.070)
-0.006
0.012
-0.003
-0.013
(0.005)
(0.008)
(0.003)
(0.006)**
-0.738
0.116
0.290
-0.190
(0.290)**
(0.799)
(0.161)*
(0.266)
-0.018
-0.030
-0.010
0.022
(0.007)** (0.017)* (0.005)** (0.009)**
-0.010
0.023
0.001
0.002
(0.004)** (0.009)** (0.002)
(0.005)
0.012
0.019
-0.006
0.087
(0.018)
(0.022)
(0.009)
(0.022)***
-0.092
-0.397
-0.196
-0.251
(0.040)** (0.094)*** (0.027)*** (0.057)***
0.348
-0.135
-0.065
-0.048
(0.036)*** (0.096) (0.018)***
(0.036)
-0.047
-0.023
0.000
-0.014
(0.008)*** (0.023)
(0.005)
(0.009)
-0.002
-0.038
-0.003
-0.018
(0.030)
(0.030)
(0.013)
(0.028)
-0.067
0.137
0.017
0.339
(0.041)
(0.059)** (0.024)
(0.058)***
1202
0.89
601
0.89
1202
0.89
1202
0.81
Agriculture Environment
-0.122
(0.113)
0.500
(0.386)
0.022
(0.020)
-0.014
(0.020)
-0.066
(0.023)***
-0.044
(0.077)
-0.018
(0.005)***
-1.926
(0.234)***
-0.027
(0.008)***
-0.017
(0.005)***
0.009
(0.018)
-0.149
(0.048)***
0.080
(0.032)**
0.018
(0.008)**
-0.010
(0.060)
0.109
(0.038)***
-0.017
(0.062)
0.108
(0.063)*
0.086
(0.045)*
0.067
(0.152)
0.037
(0.013)***
2.344
(0.995)**
0.075
(0.023)***
0.032
(0.013)**
0.079
(0.028)***
-0.840
(0.121)***
-0.304
(0.128)**
-0.059
(0.030)**
0.031
(0.081)
0.192
(0.069)***
1202
0.90
777
0.70
Notes: The dependent variable is the log of real per capita expenditures in 1000 Swiss Franks (the basis for deflation is the year 2000). The variable Women Suffrage is constructed as the share of women
in the adult population for the years after introduction and zero otherwise. Robust standard errors reported.
Table 7: Dynamic Effects of Women Suffrage
Years
Y 1-5
Y 6-10
Y 11-15
Y 16-20
Y 21+
Social Expenditures
Expenditures
Overall
Health
Welfare Education
0.003
0.059
0.033
0.014
(0.004)
(0.012)*** (0.007)*** (0.006)**
-0.022
-0.063
-0.012
-0.066
(0.041)
(0.090)
(0.060)
(0.049)
-0.131
-0.042
0.059
-0.101
(0.046)***
(0.122)
(0.077)
(0.061)*
-0.149
0.054
0.106
-0.113
(0.056)***
(0.153)
(0.101)
(0.080)
-0.146
0.217
0.178
-0.031
(0.070)**
(0.180)
(0.115)
(0.090)
-0.008
0.526
0.468
0.169
(0.089)
(0.226)** (0.146)*** (0.111)
Security
0.016
(0.004)***
-0.009
(0.039)
-0.014
(0.043)
0.040
(0.051)
0.101
(0.068)
0.242
(0.079)***
Finance
-0.050
(0.010)***
-0.270
(0.097)***
-0.487
(0.107)***
-0.601
(0.144)***
-0.594
(0.185)***
-0.655
(0.225)***
Other Expenditures
Admin.
Transport
-0.026
0.018
(0.006)***
(0.011)
-0.035
0.204
(0.053)
(0.119)*
-0.022
0.008
(0.065)
(0.122)
-0.233
-0.066
(0.084)***
(0.149)
-0.322
-0.162
(0.097)***
(0.185)
-0.405
0.242
(0.121)***
(0.248)
Agriculture
-0.032
(0.010)***
-0.105
(0.134)
-0.623
(0.136)***
-0.649
(0.161)***
-0.698
(0.188)***
-0.692
(0.225)***
Environm.
-0.002
(0.036)
0.179
(0.284)
0.141
(0.311)
0.389
(0.370)
0.375
(0.427)
0.299
(0.490)
Table 8: Gender Differences, Selection and Turnout Decisions
Internat. Politics
Female Dummy
(Turnout)
Female Dummy
(Yes; Voters)
Female Dummy
(Yes; All)
Joining
international
Organizations
-0.023
(0.013)*
0.010
(0.017)
0.010
(0.017)
Swiss Law and Direct Democracy
Equal Rights
Women and
Men
-0.045
(0.022)**
0.173
(0.032)***
0.115
(0.027)***
Environm. & Nuclear Pol.
Female Dummy
(Turnout)
Female Dummy
(Yes; Voters)
Female Dummy
(Yes; All)
Pro
Environmental
Protection
-0.102
(0.010)***
0.081
(0.014)***
0.088
(0.013)***
Female Dummy
(Turnout)
Female Dummy
(Yes; Voters)
Female Dummy
(Yes; All)
Pro
Legalization
Abortion
0.026
(0.031)
-0.064
(0.039)*
Agricultural Policy
Against
Nuclear
Policy
-0.045
(0.015)***
0.086
(0.020)***
0.097
(0.017)***
Against
Subsidizing
Agriculture
-0.047
(0.025)*
0.103
(0.035)***
0.073
(0.030)**
Pro
liberal
Agriculture
-0.120
(0.016)***
-0.026
(0.023)
0.006
(0.020)
Pro
restricting
foreigners
-0.101
(0.017)***
-0.057
(0.022)***
-0.040
(0.021)*
Fiscal Pol.
Pro Reduct.
Federal
Debt
-0.089
(0.015)***
-0.025
(0.018)
-0.039
(0.016)**
Transportation Politics
Gentech.
Against
Gentech. &
Animal test.
-0.090
(0.015)***
0.064
(0.021)***
0.068
(0.017)***
More
Direct
Democracy
-0.097
(0.016)***
0.021
(0.025)
0.037
(0.021)*
Immigration Politics
Against
Pro
Against
further road
public
subsidizing
construction transportation parking space
-0.158
-0.112
-0.091
(0.016)***
(0.018)***
(0.031)***
0.048
0.016
0.105
(0.021)**
(0.025)
(0.069)
0.076
0.030
0.121
(0.016)***
(0.020)
(0.060)**
Relax
speed
limits
-0.079
(0.021)***
-0.106
(0.027)***
-0.124
(0.023)***
Pro
easier
integration
-0.051
(0.030)*
0.095
(0.038)**
0.064
(0.031)**
Drug Policy
Liberal
Drug
Policy
-0.026
(0.021)
0.001
(0.029)
-0.010
(0.024)
Culture & Leisure
More
Culture
-0.060
(0.021)***
0.075
(0.029)**
0.038
(0.024)
More leisure,
reduction
work hours
-0.057
(0.016)***
-0.013
(0.022)
0.008
(0.019)
Housing
Education
Pro
cheap
rent
0.009
(0.031)
0.004
(0.041)
Pro
free
education
-0.062
(0.039)
0.068
(0.051)
0.052
(0.042)
Social Security
Female Dummy
(Turnout)
Female Dummy
(Yes; Voters)
Female Dummy
(Yes; All)
Protection
Motherhood
0.009
(0.024)
0.033
(0.032)
0.051
(0.026)**
Pro
Pro increase
reduction
retirement
un. benefits
age
-0.079
-0.007
(0.022)***
(0.031)
-0.051
-0.044
(0.030)*
(0.043)
-0.043
-0.072
(0.025)*
(0.035)**
Health Policy
Female Dummy
(Turnout)
Female Dummy
(Yes; Voters)
Female Dummy
(Yes; All)
Restricting
advertisment
alcohol/tabac
-0.103
(0.022)***
0.166
(0.025)***
0.133
(0.020)***
Pro subv.
health insur.
premia
-0.058
(0.018)***
0.048
(0.023)**
0.058
(0.020)***
Pro decrease
Pro
retirement support for the
age
disabled
-0.084
-0.033
(0.018)***
(0.031)
0.080
0.146
(0.025)***
(0.043)***
0.093
(0.024)***
Military
More
individual
resp. health
-0.045
(0.021)**
-0.050
(0.021)**
Less
Military
-0.082
(0.014)***
0.033
(0.018)*
0.024
(0.017)
Notes: The table reports estimates from a probit model, with marginal coefficients being reported. In the first row, the dependent variable is voter participation (1 if voted, 0
if abstained). The dependent variable in rows two and three is the voting decision (1 for approval, 0 for disapproval), for voters (row two) and the total population (row
three). Robust standard errors in parantheses.
Table 9: Women's demand for social expenditures
(1)
Increase
Social
Female Dummy
Female Dummy * Employed
Female Dummy * Divorced
Employed
Divorced
0.029
(0.026)
0.057
(0.033)*
0.204
(0.108)*
-0.031
(0.025)
-0.004
(0.081)
(2)
Increase
Social
Female Dummy
Female Dummy * Employed
Female Dummy * Divorced
Employed
Divorced
Age (in Years)
Vocational Degree
University Degree
Single
Protestant
Own a House
Urban Area
NonGerman Region
Observations
Pseudo R Squared
3791
0.0079
Observations
Pseudo R Squared
0.016
(0.028)
0.053
(0.035)
0.185
(0.109)*
-0.046
(0.028)*
-0.003
(0.082)
-0.001
(0.001)*
-0.041
(0.022)*
-0.007
(0.033)
0.040
(0.021)*
-0.031
(0.016)*
-0.055
(0.017)***
0.059
(0.016)***
0.069
(0.018)***
3632
0.0245
Notes: The table reports estimates from a probit model, with marginal coefficients being reported. The dependent
variable is support for increases in social expenditures. The omitted educational category is no vocational degree, the
omitted employment category unemployed/nonemployed, and the omitted civil status is married/widowed. Robust
standard errors reported.
Real Expenditure Per Capita (Adj.)
Figure 1: Real Expenditure Per Capita for Early and Late Adopters
400
200
0
-200
-400
-600 -20
-15
-10
-5
0
5
10
15
Years To/Since Adoption
Late Adopters
20
25
30
Early Adopters
Notes : Numbers reported are population weighted
Notes : The figure reports real per-capita expenditures (in 1950 SFr) after taking out a common linear trend. Numbers reported
are population weighted. Early adopters are cantons that extended voting rights at the cantonal level prior to 1971 (see Table
1 for a list of those cantons).
Table A1: The Ten Propositions with the Largest Gender Gap
Title of Federal Proposition
Equal Representation of Women in Federal Administration
Abandon Nuclear Energy
Against Racial Discrimination in the Military
For a Car-Free Sunday Per Quarter
For Equal Rights of the Disabled
Reducing Tobacco Use
Saving the Waters
Raise Speed Limit to 130/100
Revision of Social Security (without raising retirement age)
Abandon Animal Experiments
Number
Vote
461
365
414
498
500
404
381
358
444
374
Type of
Vote
Initiative
Initiative
Initiative
Initiative
Initiative
Year of Vote
Gender Gap (%)
Yes Women - Yes Man
2000
1990
1994
2003
2003
1993
1992
1989
1998
1992
0.175
0.161
0.153
0.149
0.146
0.141
0.140
-0.132
0.129
0.128
Notes : The table shows the ten federal propositions with the largest gender gap (column (5)). Also shown is the official number, the type and year of the vote.
Source : VOX Surveys, 1981-2003
Table A2: Expenditures by federal level, in percentage of total Expenditures
Federal
Cantonal
Community
Education
Culture & Leisure
Health
Social Welfare
Traffic
Environment
National Economy (e.g. agriculture)
Justice, Police, Firefighter
Defense
Foreign Relationships
Fincance & Taxes
14.9
13.2
1.3
51.9
57.2
15.9
73.2
7.7
92.3
100
81.4
51
31.7
60
27.4
20.2
21.7
18.9
68.2
3.5
0
0.1
34.2
55.1
38.7
20.7
22.6
62.5
7.8
24.2
4.1
0
17.4
Total Expenditures
(in 1000 SFR.)
21'970'918
3'645'549
15'103'881
23'142'653
12'073'533
4'819'496
6'708'680
6'543'899
5'401'944
2'148'301
10'084'024
Total Expenditures
38.7
33.5
27.8
119'439'476
Source: Öffentliche Finanzen der Schweiz 1999