Content uploaded by Tim Vlandas
Author content
All content in this area was uploaded by Tim Vlandas on Oct 13, 2017
Content may be subject to copyright.
https://doi.org/10.1177/0010414017710261
Comparative Political Studies
1 –39
© The Author(s) 2017
Reprints and permissions:
sagepub.com/journalsPermissions.nav
DOI: 10.1177/0010414017710261
journals.sagepub.com/home/cps
Article
Grey power and the
Economy: Aging
and Inflation Across
Advanced Economies
Tim Vlandas1
Abstract
What explains the cross-national variation in inflation rates across
countries? In contrast to most literature, which emphasizes the role of ideas
and institutions, this article focuses on electoral politics and argues that
aging leads to lower inflation rates. Countries with a larger share of elderly
exhibit lower inflation because older people are both more inflation averse
and politically powerful, forcing parties seeking their votes to pursue lower
inflation. Logistic regression analysis of survey data confirms that older
people are more inflation averse and more likely to punish incumbents
at the ballot box for inflation. Panel data regression analysis shows that
social democratic parties have more economically orthodox manifestos in
European countries with more elderly people, and that the share of elderly
is negatively correlated with inflation in both a sample of 21 advanced
economies and a larger sample of 175 countries. Aging therefore pushes
governments to pursue lower inflation.
Keywords
inflation, aging, grey power, economic policy, independent central banks,
economic orthodoxy
1University of Reading, Berkshire, UK
Corresponding Author:
Tim Vlandas, Associate Professor in Political Economy, Department of Politics & International
Relations, University of Reading, Whiteknights, P.O. Box 218, Reading, Berkshire, RG6 6AA, UK.
Email: t.r.g.vlandas@reading.ac.uk
710261CPSXXX10.1177/0010414017710261Comparative Political StudiesVlandas
research-article2017
2 Comparative Political Studies 00(0)
Introduction
What explains the cross-national variation in inflation rates across developed
countries? This question has been the subject of a large body of literature in
both economics and comparative political economy. However, most studies
to date have focused on the role of ideas, institutions, and economic factors
(Cukierman, Web, & Neyapti, 1992; Grilli, Masciandaro, Tabellini,
Malinvaud, & Pagano, 1991; Iversen, 1999; McNamara, 1998), and to a
lesser extent interest groups (Posen, 1993, 1998), while paying insufficient
attention to the role of electoral politics. The conventional wisdom captures
part of the story for understanding variation in inflation rates, but the relative
absence of electoral politics is surprising in two respects. First, this absence
is at odds with the prominent role attributed to electoral politics in other polit-
ical economy literature, for instance on labor market policies (Boix, 1998;
Rueda, 2006; Vlandas, 2013a, 2013b) and the welfare state (Pierson, 1994,
1998). Second, inflation has identifiable distributive effects on different parts
of the population which should therefore care about the level of inflation
(Briault, 1995; Hibbs, 1979: pp. 712-715; Laidler, 1997; Scheve, 2004).
Electoral politics may therefore make it possible to understand why certain
ideas and institutions are chosen in the first place.
In this article, I seek to bring electoral politics back into the analysis of
inflation by focusing on the preferences, power, and influence of a powerful
social group: the elderly. This choice is motivated by both methodological
and theoretical considerations. Methodologically, any analysis of the elec-
toral determinants of inflation faces a problem of endogeneity. Many factors
that affect the electorate’s preferences for inflation such as wages, employ-
ment status, or assets may be partly endogenous to macroeconomic policy
and inflation rates. Theoretically, the chosen social group needs to have
clearly identifiable inflation preferences.
As a first test of the role of electoral politics that minimizes both pitfalls,
I choose to focus on the elderly—people aged 65 years and above. The elderly
are clearly more inflation averse, and the share of elderly in a country is
unlikely to be directly determined by inflation. Thus, the share of elderly is a
good first case to investigate the impact of electoral preferences on inflation
rates: It is highly correlated with factors that can be expected to influence
inflation preferences but is not itself determined by inflation rates. The size
of the elderly group across developed countries has also varied greatly over
time, and the relevance of aging for welfare state policies has been well
documented.
I argue that aging has important consequences for economic outcomes as
governments must increasingly take into account the economic policy
Vlandas 3
preferences of the elderly. My theoretical framework builds on clear micro-
foundations, conceptualizes several causal mechanisms, and then tests a num-
ber of observable implications. I posit that the elderly are more inflation averse
because they are more indifferent to unemployment than the rest of the popu-
lation, being outside of the labor market, but are concerned about the real
value of their savings and pensions. As the size of this politically powerful
group of voters increases, I expect that political parties increasingly compete
to attract their votes before elections by adopting economically orthodox party
manifestos, and that when in power, parties then pursue policies that contain
inflation to minimize the risk of an electoral penalty at the next election. As a
result, in countries with a larger share of elderly, parties are more economi-
cally orthodox, governments delegate monetary policy to independent central
banks to a greater extent, and inflation is lower.
I test my argument in several steps. First, using logistic regression analysis
of two separate surveys, I confirm that the elderly are more inflation averse.
Second, using regression analysis of party manifesto data, I find that political
parties in countries with a larger share of elderly have more economically
orthodox party manifestos that emphasize price stability. The results are con-
sistent with a “party competition” model where social democratic parties
become more orthodox but not with a “party constituent” model where con-
servative parties respond to the growing weight of elderly among their con-
stituents. Third, logistic regression analysis of survey data on past votes
suggests that the elderly penalize the incumbent for higher inflation more
than the rest of the population. Fourth, I show that the share of elderly is posi-
tively correlated with central bank independence (CBI) in a sample of 21
countries that are members of the Organization for Economic Cooperation
and Development (OECD) in the period since 1960.
Next, I demonstrate that the share of elderly is negatively correlated
with inflation rates in a sample of 21 OECD countries since 1960. My
panel data regression analysis controls for competing explanations and the
results hold using a wide variety of specifications and estimation methods.
These findings are not biased by nonstationarity as they hold when I run
pure cross-section, first difference, and error correction models (ECMs).
When extending my analysis to a much larger sample of 175 countries for
which data for the main variables are available, I find that the effect of the
share of elderly on inflation only holds in democracies, thereby ruling out
a purely economic effect linked to the elderly’s economic behavior. This
effect holds when excluding countries with high GDP per capita from the
analysis, suggesting that my results are not an artifact of economic mod-
ernization where aging and low inflation occur jointly as a by-product of
economic development.
4 Comparative Political Studies 00(0)
My findings have several wider implications. They show that aging has an
important political impact on economic outcomes, and that electoral politics
is a crucial factor in explaining the cross-national variation in inflation rates.
Bringing electoral politics back in therefore helps us make sense of the con-
tinuing variation in inflation rates across countries with similar institutions
and economies. This article further suggests that as countries age, achieving
low inflation becomes an increasingly strong political imperative, regardless
of what may be economically desirable.
The rest of the article enfolds as follows. The next section reviews previ-
ous literature and discusses my theoretical expectations. The second section
then tests some of the causal mechanisms, while the third section tests the
expectations of my model concerning the relationship between the share of
elderly and inflation rates. The last section concludes with some implications
for further research.
The Political Economy Determinants of Inflation
Rates
Ideas, Institutions, and Interest Groups
Three main approaches in comparative political economy have sought to
explain variation in inflation rates across developed economies over time.
The first approach has focused on the role of ideas.1 In this approach, a
new dominant economic narrative, new classical economics—and within
it monetarism (Alt & Chrystal, 1983; Friedman, 1968)—emerged as a
response to the perceived inability of governments to address the stagfla-
tion of the 1970s and convinced policy makers that any monetary-induced
employment gains over the long run fade away while resulting in higher
inflation. This in turn made low inflation policies more appealing to gov-
ernment officials (e.g., McNamara, 1998) and resulted in a shift away from
the Keynesian consensus that had prevailed in the postwar era until then
(Hall, 1986).
The second approach focused on the role of institutions and how these
may help solve the time inconsistency problem, namely how to achieve lower
inflation when policy makers may be tempted, for electoral gains, to pursue
short-term goals that may raise inflation (Alesina, Roubini, & Cohen, 1999;
McRae, 1977; Nordhaus, 1975). One solution to the time inconsistency prob-
lem that gained prominence was to partly or fully delegate monetary policy
to independent and conservative central banks, thereby convincing all actors
that the commitment to low inflation was credible (Alesina, Mirrlees, &
Neumann, 1989; Barro & Gordon, 1983; Rogoff & Sibert, 1988). As a result,
Vlandas 5
agents would expect low inflation, and this in turn becomes a self-fulfilling
prophecy even in the absence of a monetary policy tightening (Grilli et al.,
1991). Independent central banks are expected to lead to lower inflation
(Cukierman et al., 1992; Debelle & Fischer, 1994; Eijffinger & de Haan,
1996) because central banks are more conservative—in the sense that they
prefer lower inflation than elected governments—and less receptive to elec-
toral pressures.
Both approaches are valuable in showing how various institutions and
ideas affect inflation rates given certain interests in society. The problem
with the ideational approach is what it leaves unanswered, namely whose
ideas dominate policy making and why?2 Most of this literature has also
been concerned with explaining the shift to a low inflation regime over
time, making it difficult to use ideas to explain the cross-national variation
in inflation rates we observe.
In addition to ideas and institutions, several interest groups with an influ-
ence on inflation have been identified. This third approach to explaining
inflation has stressed the importance of wage bargaining, trade unions, and
the export sector (Franzese, 2003; Hall & Franzese, 1998; Iversen, 1999). In
the Keynesian era, unions moderated their wages in exchange for long-term
gains (Eichengreen, 1996; Iversen & Soskice, 2006). In countries with neo-
corporatist institutions, unions had greater incentives to exercise wage
restraint because governments were offering them various welfare benefits in
return (Cameron, 1984; Lange & Garrett, 1985), thereby minimizing both
inflation and unemployment if wage moderation was coupled with the right
fiscal and monetary policies (cf. Scharpf, 1987). Union members lack suffi-
cient power to influence inflationary outcomes in countries with highly
decentralized wage bargaining at the firm level, while large encompassing
trade unions internalize the inflationary effects of their wage claims (Calmfors
& Driffill, 1988). Both arrangements should therefore result in lower infla-
tion than in countries where unions are strong but not encompassing. Finally,
unions and employers in the export sector are inflation averse because they
have a strong interest in retaining competitiveness, so countries with larger
export sectors may exhibit lower inflation.
Moreover, Posen (1995) showed that, because of its preference for low
inflation, the financial sector has a pivotal role in supporting price stability
in the long run. Rather than being a cause of low inflation, he reasoned that
CBI was itself determined by the financial sector’s opposition to inflation.
If this is true, both low inflation and CBI are more likely in countries with
stronger financial actors,3 whether because of lobbying on the parts of
financial actors (Posen, 1995) or through the discipline of capital markets
(Maxfield, 1997).
6 Comparative Political Studies 00(0)
Aging and Electoral Politics
While valuable, previous literature tends to neglect electoral politics, which
had been the focus of older studies in comparative political economy. Indeed,
four decades ago, Hibbs (1977, 1986) showed that electoral politics cannot be
ignored because left-wing and right-wing parties have different inflation–
unemployment preferences as their respective constituencies are differently
affected by inflation and unemployment. When choosing institutions govern-
ments therefore cannot be assumed to entirely disregard electoral constraints,
and even when institutions are already given, governments could still in prin-
ciple influence inflation rates through other policies (e.g. fiscal policy, wel-
fare state benefits, and wage policies).
However, focusing on left–right differences potentially overlooks changes
in the electorate that may affect both left and right, in which case the effect
would not necessarily operate via left–right differences in government parti-
sanship. Over the long run, changes in the electorate’s preferences may be
more important than differences between different parts of the electorate at
one point in time. Rather than focusing on partisan differences, the focus of
this article is on how different groups in the population may have distinct
inflation preferences and how the size of these groups may in turn feed into
differences in inflation rates across countries. Inflation has distributional con-
sequences (Briault, 1995; Laidler, 1997), so different groups should have dif-
ferent inflation preferences. One difficulty in estimating the effect of the
electorate’s preferences on inflation is that inflation may itself affect the char-
acteristics of the electorate that shape their preferences. It is therefore crucial
to use a criterion for identifying inflation-averse groups that is as much as
possible exogenous to inflation.
One such criterion is age. Here, I focus in particular on the elderly, defined
as those aged 65 years and above.4 Elderly people who are in retirement
should care less (or not at all) about their employment prospect, as they
derive their income from pensions and/or assets5 rather than employment,
and are often net creditors, having repaid debts accumulated through mort-
gages.6 By contrast, the young and/or those in the labor force tend to care
more about employment than inflation, given that most of their income
depends on working and that they are often net debtors (Bach & Stephenson,
1974). The point here is not that inflation is entirely irrelevant for workers
nor that employment is entirely irrelevant for those above 65, but rather that
the elderly should care comparatively more about inflation than the non-
elderly. I therefore expect older individuals to be more inflation averse.
Why does it matter what preferences elderly individuals hold? One answer
is that developed economies have experienced a significant aging of their
Vlandas 7
population (Lynch & Myrskylä, 2009; Sinn & Uebelmesser, 2002; Tepe &
Vanhuysse, 2009). Almost 20% of the population in the Euro area is above
65, and 5% is above 80. The old age dependency ratio (share of 65+ over
those between 15 and 64) increased from 12.5% in 1950 to 23.8% in 2010
(European Commission, 2014, p. 23). By 2050, the share of elderly may
reach almost 30% in the European Union, with more than 10% above 80
years old (European Commission, 2014, p. 410). In sum, the elderly are a
large and growing group in the population.
The elderly are a large group but this does not tell us how their preferences
affect policies. There is a large literature in political economy that shows that
individual preferences matter for policy outcomes (Ansell, 2014; Iversen &
Soskice, 2001; Rehm, 2016; Rueda, 2006). In line with public choice theory,
we might expect that as the share of elderly moves closer to 50% of the elec-
torate, politicians will propose policies that reflect their preferences (Wilson,
1991). While they never represent 50% of national electorates, the elderly are
not only a large and growing group, but they are also a group with consider-
able political power (Goerres, 2009; Rose, 1965, pp. 13-14; Sinn &
Uebelmesser, 2002). Starting in the 1960s in the United States, the elderly
“began to think of themselves as members of an aging group” and analysts at
the time contended that the “elderly seem to be on their way to becoming a
voting bloc” (Rose, 1965, pp. 13-14). In more recent times, older people in
Europe are more likely to vote (Goerres, 2007) and are much more likely to
be members of political parties (Goerres, 2009). The 60-69 age group is more
likely to be union members than any other age group except 50 to 59 years
old (Goerres, 2009, Table 5.1). Even in a country where the share of the
elderly is comparatively low such as the United States, they may yield con-
siderable political power: They are more likely to vote than any other age
group and also more likely to vote in all elections, they are more informed
about politics and a more important source of campaign contributions
(MacManus, 2000, pp. 2, 3, 7). In the 2012 U.S. presidential election, the
elderly accounted for as much as 22% of those who voted (File, 2014).
Given their growing size and power, this has raised the question of whether
they have excessive control on the policy process. In the German case, some
authors warn of the advent of gerontocracy (Sinn & Uebelmesser, 2002, p.
157), while in the United States pensioner interest groups are seen to have
significant lobbying power (Pampel & Williamson, 1985; Pierson, 1994).
The impact of aging on policies has been most systematically explored in
welfare state studies, which suggest that “elderly power” matters for both
welfare state expansion and retrenchment (Busemeyer, Goerres, & Weschle,
2008; Esping-Andersen & Sarasa, 2002; Lynch, 2006; Sabbagh & Vanhuysse,
2006). Previous research has in particular shown that the share of elderly is
8 Comparative Political Studies 00(0)
associated with more spending on pensions (Galasso, 2006; Galasso &
Profeta, 2007; International Monetary Fund, 2004; Mulligan & Sala-i-Martin,
1999, 2003; Persson & Tabellini, 2000; Sinn & Uebelmesser, 2002) because
older and retired respondents are—not surprisingly—more supportive of
pensions (Pamp, 2015, p. 163). Conversely, they are less supportive of educa-
tion (Sørensen, 2013), and hence U.S. states with more elderly tend to spend
less on education (Fletcher & Kenny, 2008; Harris, Evans, & Schwab, 2001;
Poterba, 1998).
While the association between the share of elderly and policies is there-
fore well established, the mechanisms through which this association oper-
ates tend to be underexplored in quantitative research. Thus for instance,
consistent with most literature, a recent study notes that “the particular ways
in which social policy responsiveness [of governments to the elderly] is con-
ditioned by factors such as . . . electoral models, party politics, collective
action problems, and institutional constraints . . . remain black boxes in our
account” (Tepe & Vanhuysse, 2010, pp. 218-219). Where it is discussed, one
links the growing size of the elderly to the aging of the median voter, which
can then using a median voter theorem be expected to lead to changes in
policy. In these approaches, “the higher weight of older voters . . . shifts the
median voter equilibrium” (Persson & Tabellini, 2000, p. 130).
Aging and Inflation: A Theoretical Framework
The previous section suggests that we can expect the elderly to affect policy.
What is missing for my purpose is an identification of the different possible
mechanisms through which the growing share of elderly could influence
inflation from which to derive testable observable implications. I start from
the premise that a defining feature of democracies is “congruence between
citizen preferences and policy output” (Rehm, 2016, p. 29). This assumption
is reasonable in suggesting that governments respond to preferences but it
does not specify why they respond and what they respond to. In what follows,
I distinguish between two channels through which individual preferences in
democracies can influence government policy.
In a first indirect electoral channel, individuals choose politicians who
represent—and once elected, implement—their policy preferences. This is
where it is necessary to consider party dynamics to identify the precise mech-
anisms linking individual preferences and parties in power. Within this indi-
rect electoral channel, I distinguish between a “party constituent” model and
a “party competition” model.
In the “party constituent” model, political parties have long-lasting com-
mitments to certain parts of the electorate and/or to certain ideologies. A
Vlandas 9
higher share of the elderly may mean that they have an increased influence on
the political party that disproportionally represents them and/or that, for
example, conservative parties having a pre-existing ideological commitment
to low inflation find it easier to enact it when support among their constitu-
ents becomes sufficiently high as a result of the growing elderly electorate.7
The elderly’s party identification is higher than other groups (Butler &
Stokes, 1983; Goerres, 2009), and the evidence suggests that at least histori-
cally the elderly have been represented by conservative parties in several
Western European countries. Thus for instance, the conservative party in the
United Kingdom has historically been heavily supported by the elderly
(Whiteley, Syed, & Richardson, 1994). If the conservative party becomes
more inflation averse to reflect the growing size of inflation-averse elderly
people, we would expect a positive correlation between the inflation aversion
of conservative parties and the share of elderly across countries. However,
the evidence is mixed, and in some countries the elderly might not predomi-
nantly support the conservative parties. For instance, in a more recent analy-
sis, Goerres (2008) finds no evidence that older voters in Britain and Germany
are more likely to vote for conservative parties. Conservative parties may
also find it difficult to respond entirely to elderly constituents if this clashes
with the demands of important younger and middle-aged groups (cf. Kitschelt,
2004, pp. 9-10).
In a “party competition” model, political parties compete for all votes.
One version of this model is that parties compete for the median voter.
Previous literature has for instance used median voter models when assessing
how aging affects preferences for pension spending: As the median voter
ages, she favors greater spending on pensions (Browning, 1975; Conesa &
Krueger, 1999; Cooley & Soares, 1999; Galasso, 2006; Galasso & Profeta,
2007; Persson & Tabellini, 2000). Thus in my case, an aging median voter
becomes more inflation averse because the relative weight of her utility in old
age, when she will no longer work and instead rely on fixed income from
assets and pensions, overtakes the weight of her utility in the present which
depends on both employment opportunities and—in some cases—inflation-
protected wages. As the median voter becomes more inflation averse, both
parties have to become more inflation averse to acquire his or her electoral
support. We would therefore expect a negative correlation between the age of
the median voter, as proxied by the share of elderly, and the inflation aversion
of all political parties on average and in particular of political parties that are
forced to change their ideological position to meet their office-seeking aspi-
rations, most likely social democratic parties.
The latter model explicitly or implicitly underpins most literature on aging
and pension politics discussed earlier, and while median age for most countries
10 Comparative Political Studies 00(0)
across time is not available, most studies use the share of the elderly as a rea-
sonable proxy for median age. It is also possible—and even more plausible in
proportional representation systems—that political parties target a combination
of large groups of constituents rather than just the median voter, in which case
the share of the elderly is the more appropriate measure. Consistent with this,
there is some evidence of party competition over the elderly vote. For instance,
New Labour’s success in the United Kingdom was in large part due to its abil-
ity to attract elderly voters in the 1997 election (Tilley, 2002).
In the second—direct—channel, politicians “stay closely attuned to the
ebb and flow of public opinion and adjust policy accordingly” when in power
(Wlezien & Soroka, 2007, p. 805). There is a large and diverse literature on
policy responsiveness which does convincingly show that changes in public
opinion do lead to changes in public policy (Canes-Wrone, 2015). There are
two reasons for this: First, elected politicians want to minimize “civil disobe-
dience and protests”; second, they want to minimize the risk of “electoral
losses for themselves” (Brooks & Manza, 2006, p. 479). There is evidence
for both an ex post and an ex ante process. Elected governments who stray
too far away from average opinion are punished if there is a challenger closer
to public opinion (Hollibaugh, Rothenberg, & Rulison, 2013), and they inter-
nalize public opinion to preempt electoral losses (Erikson, MacKuen, &
Stimson, 2002; Page & Shapiro, 1983).
A similar intuition characterizes the economic voting literature but it
considers macroeconomic outcomes rather than economic policies.8
Individuals are seen to reward or punish governments in elections depend-
ing on economic performance, most notably unemployment and inflation.
This literature first analyzed popularity functions in the United States, and
later considered other advanced economies, as well as shifting the focus to
actual aggregate votes.9 It soon also started investigating the impact of ret-
rospective and prospective subjective evaluations of the economy (Erikson,
MacKuen, & Stimson, 2000; Norpoth, 1996) as well as focusing more spe-
cifically on individual voting behavior. Overall, Lewis-Beck concludes that
“changing economic conditions exert a force on Western European voters
that approaches and sometimes exceeds the force of more traditional fac-
tors” (Lewis-Beck, 1988, p. 85). Building on this literature, I argue that
elderly voters penalize the incumbent for inflation to a greater extent than
other social groups because they are more inflation averse. As a result, in
countries with a larger share of elderly, incumbent parties should face a
stronger electoral penalty for high inflation than elsewhere and should
therefore be more likely to pursue low inflation.
In sum, a growing share of inflation-averse elderly people can theoreti-
cally be expected to influence government policy and inflation because (a)
Vlandas 11
parties that traditionally represent them become more inflation averse to
reflect their growing importance, (b) parties target an aging and hence
increasingly inflation-averse median voter, (c) parties increasingly compete
for elderly votes, (d) governments target an average public opinion that is
becoming more inflation averse as a result of aging, and/or (e) the elderly
impose a larger electoral penalty on the incumbent for “excessive” inflation
and/or policies that increase inflation.
If they wish to reduce inflation, governments have several tools at their
disposal. First, they can choose certain institutions that contain inflation,
for instance by delegating monetary policy to politically independent cen-
tral banks. Second, governments can pursue policies that contain infla-
tion. Thus for instance, even when central banks are partly independent,
governments can sometimes continue to pursue inflationary monetary
policies (Posen, 1995, p. 254), and they can affect the supply of money by
altering credit rules and capital requirements for banks.10 In addition to
monetary policy tools, governments can influence inflationary outcomes
via fiscal policy, which in turn shapes aggregate demand, and they can
intervene in the wage bargaining process,11 set statutory minimum wages,
or affect the reservation wage through labor market benefits. Thus, gov-
ernments have several tools at their disposal to influence inflationary out-
comes. We can therefore expect countries with a larger share of elderly to
have more inflation-averse political parties, governments that choose
institutions which promote low inflation and that pursue policies which
lower inflation more than other countries, and in turn these countries
should exhibit lower inflation.
Finally, if the old have different levels of assets and distinct consumption
and investment behaviors (Bullard, Garriga, & Walker, 2012; Fair &
Dominguez, 1991; Lindh & Malmberg, 2000; Yoon, Kim, & Lee, 2014), then
there may be an economic association between aging and inflation. In this
case, we should observe a correlation between aging and low inflation in both
democracies and nondemocracies, as intermediation through the political
system is not necessary. If the effect operates in the political arena only, the
correlation should only hold in democracies, and we should find evidence for
the political mechanisms identified above.
Microfoundations and Causal Mechanisms
Inflation Aversion Among the Elderly
To test my assumption concerning the elderly’s inflation preferences, I rely
on two surveys. The first is the International Social Survey Program (ISSP)
12 Comparative Political Studies 00(0)
on the Role of Government which includes four waves (1985, 1990, 1996,
and 2006). I use two separate questions to derive my dependent variables.
The first question is about whether controlling prices should be the govern-
ment’s responsibility where respondents can choose: 4—definitely should be,
3—probably should be, 2—probably should not be, and 1—definitely should
not be. The second question asks respondents to choose whether the govern-
ment should “keep inflation down” or “keep unemployment down.” My key
independent variable is a dummy variable that takes value 1 if the respondent
is elderly and 0 otherwise. I control for gender, years of schooling, country as
well as time effects.
The results from a logistic regression analysis are presented in Table 1.
Elderly respondents are more inflation averse: In column 1, I use a binary
dependent variable equal to 1 if respondents choose that controlling prices
“should definitely be” government’s responsibility, and 0 otherwise; in col-
umn 2, the binary dependent variable equals 1 if respondents choose that
Table 1. The Determinants of Individual-Level Inflation Aversion.
Dependent
variable
(1) (2) (3) (4) (5)
Control
Prices 1
Control
Prices 2
Control
Prices 3
Keep
inflation
down
Inflation first
or second
priority
Regression
method Logit Logit Logit Logit Logit
Elderly 0.137*** 0.193*** 0.137*** 0.077†0.235***
Constant 0.566*** 3.066*** Several cuts −0.016 1.659***
Observations 74,134 74,134 74,134 17,088 468,452
Country fixed
effects
Yes Yes Yes Yes Yes
Time effects Yes Yes Yes Yes Yes
Pseudo R2.08 .09 .06 .05 .10
All columns control for education and gender. Column 3 uses ordinal logistic analysis on
an ordinal dependent variable (constant cuts not shown—see Appendix), while all other
columns use normal logistic analysis on binary dependent variables. Columns 1 to 4 use the
ISSP data. Using being “retired” instead of being elderly does not change the results. Column
5 uses Eurobarometer data, and is robust to the use of a dependent variable that is coded
1 if respondents choose inflation as first priority only and to the inclusion of income and/
or a measure of left–right self-placement. The variables elderly and retired are statistically
significant at the 10% level when the Eurobarometer data are restricted to the 1970s,
1980s, or 1990s, respectively. See Section 3.1 in Appendix for more details on variables and
robustness checks. ISSP = International Social Survey Program.
†p < .1. *p < .05. **p < .01. ***p < .001.
Vlandas 13
controlling prices “definitely should be” or “probably should be” the govern-
ment’s responsibility; in column 3, I rely on the full ordinal variable using
ordinal logistic regression analysis; and column 4 reports the results when my
dependent variable “Inflation down” takes value 1 if respondents choose
“keep inflation down” and 0 if they choose “keep unemployment down”.
Using age or being retired instead of being elderly does not change the
results,12 and my results are consistent with the previous literature (Lelyveld,
1999, pp. 469, 476; Scheve, 2004, p. 11; Shiller, 1997, pp. 26, 27).
Note that these results do not imply that the old have perfectly homoge-
neous preferences, but merely that they are more likely to be inflation averse,
ceteris paribus, than other age groups.13 I use being elderly and/or retired as
an instrument that captures other variables that affect inflation aversion rather
than as a factor that necessarily and intrinsically affects inflation aversion, so
these results could a priori be consistent with both a life cycle and a genera-
tional effect, but it is possible to explore which effect is at work. The ISSP
waves are too close in time to really delineate generational versus life cycle
effect, so I use instead the Mannheim Eurobarometer Trend File (Schmitt,
Scholz, Leim, & Moschner, 2008) covering the period 1970 to 2002 in 15
Western European countries. My dependent variable is derived from a ques-
tion about which issue respondents find most important, where they can
choose their first and second priority from four possibilities: “maintenance of
law and order,” “giving people more say in government decision”, “fighting
rising prices”, or “protecting freedom of expression”.
Results shown in column 5 confirm that being elderly or retired is associ-
ated with a higher likelihood of identifying inflation as a first or second prior-
ity, when controlling for gender and education. Controlling for income or
left–right placement and using a dependent variable that is coded 1 only if
inflation is first priority does not change the results.14 Rerunning the analysis
on restricted samples covering only the 1970s, 1980s, and 1990s, respectively,
shows that being retired and/or elderly is positively associated with higher
inflation aversion in each decade.15 This support for the life cycle hypothesis
is consistent with previous findings on elderly preferences toward pension and
education policies (de Mello, Schotte, Tiongson, & Winkler, 2016, p. 6).
Aging and the Economic Orthodoxy of Political Parties
Earlier, I posited that the share of elderly could influence inflation by shaping
the degree of inflation aversion among political parties competing in elec-
tions. There is to my knowledge no direct measure of anti-inflation prefer-
ences of all political parties in OECD countries. But the party manifesto
dataset project (Volkens et al., 2014), which codes all party manifestos along
14 Comparative Political Studies 00(0)
several dimensions since the 1950s, has a variable that comes close called
“Economic Orthodoxy” (per414). This variable captures whether the party
manifesto refers to “support for a strong currency”. It also captures factors
that likely have an effect on inflation such as “reduction of budget deficits”,
and “thrift and savings in the face of economic hardship”. Higher values
mean that there are more references to economic orthodoxy in a given mani-
festo in a country’s election.
Table 2 presents my results estimating the impact of the share of elderly on
economic orthodoxy when controlling for inflation, trade openness, unem-
ployment, deficits, and left cabinet seats.16 In column 1, my dependent vari-
able captures the average across all political parties’ manifestos in 10-year
period average since the 1960s. This allows me to explore how a large group
Table 2. The Share of Elderly and Economic Orthodoxy in Party Manifesto.
Column (1) (2) (3)
Dependent
variable—Economic
orthodoxy All parties
Social
democratic
parties
Gap between
conservative and social
democratic parties
Period 10 years Yearly Yearly
Share of elderly 0.186†0.187* −1.024**
Inflation rate −0.005 0.023 0.055
Trade openness 0.012 −0.006 −0.021
Unemployment rate 0.054 0.044 0.104**
Deficit 0.035 −0.108* 0.020
Union density 0.007 0.054* 0.029
Left cabinet seats 0.009 −0.002 0.014
Constant −0.750 −2.910†8.713†
Observations 94 259 174
Number of
countries
21 21 15
R2 overall .07 .14 .11
R2 within .26 .18 .02
R2 between .00 .23 .00
Results from column 1 are similar if Tobit is used instead of OLS. Note that using 5-year
period average instead of 10-year period average and lagging the share of elderly does
not change results from column 1. Results from column 2 hold if we include orthodoxy
of conservative parties as an independent variable. See Section “Aging and the Economic
Orthodoxy of Political Parties” in Appendix for more details on variables and robustness
checks. Robust standard errors clustered by country.
†p < .1. *p < .05. **p < .01. ***p < .001.
Vlandas 15
of voters who are opposed to inflation forces political parties to shift their
policy preferences toward inflation. The results controlling for country fixed
effects and time effects suggest that countries with more elderly as a percent-
age of the population exhibit more economically orthodox political parties.17
When using yearly data instead of 10-year period averages, the results are
no longer significant for the cross-party average but differ for distinct parties.
If conservative parties already represent the views of elderly voters regardless
of the size of the group, there should be no association between the share of
elderly and the economic orthodoxy of conservative party manifestos. This is
precisely what I find.18 By contrast, the share of elderly has a positive signifi-
cant effect on the economic orthodoxy of social democratic party manifestos as
shown in column 2.19 Using the same model, I now interact the share of elderly
with the economic orthodoxy of conservative parties as an independent vari-
able20 and plot the interacted effect in Figure 1. This shows that social demo-
cratic parties only respond to an increase in the economic orthodoxy of
conservative parties in countries with a large elderly population. Column 3
confirms that the gap in economic orthodoxy between conservative and social
democratic parties is negatively associated with the share of the elderly. Overall,
Figure 1. Effect of conservative party economic orthodoxy on social democratic
party economic orthodoxy at different levels of share of elderly.
Calculated using results from column 2 in Table 2 when including an interaction term
between the orthodoxy of conservative parties and the share of elderly (country and time
effects included).
16 Comparative Political Studies 00(0)
these findings are consistent with the claim that social democratic parties have
become more economically orthodox to compete for elderly votes.
Aging, Economic Voting, and Inflation
While the previous section shows that parties compete in terms of programs
to attract elderly votes by becoming more economically orthodox, it says
nothing about the incentives of political parties to contain inflation once in
power and why having a large share of elderly might have an effect on these
incentives. To test whether the elderly punish the incumbent more than non-
elderly/non-retired individuals, I use individual-level voting data from the
second, third, and fourth waves of the Comparative Study of Electoral
Systems.21 This covers elections in a range of parliamentary democracies
between 2001 and 2016. For each election of the lower house in all elections
taking place in these countries during this time period, my dependent variable
is coded 1 if the respondent voted for an incumbent party at the last election
and 0 otherwise. I control for gender, income, education, being unemployed,
and being elderly, as well as national inflation and unemployment rates. The
latter two variables are a weighted average of the election and pre-election
years in inflation and unemployment rates, respectively.
Table 3 presents the results. In column 1, the results from a logistic regres-
sion analysis suggest that being a retired respondent increases the likelihood
of voting for the incumbent, while gender has no effect and being unem-
ployed has a negative effect. Higher inflation and higher unemployment both
reduce the likelihood of an individual voting for the incumbent, in line with
previous economic voting literature. Having voted for the current incumbent
in a previous election increases the chances of voting for that incumbent in
the current election. In column 2, I interact inflation with the dummy variable
“retired” and plot the interaction in Figure 2. Consistent with my expectation,
this reveals that an increase in inflation reduces the probability of voting for
the incumbent party much more for retired than for non-retired respondents.
Note that replacing the retired dummy with an elderly dummy does not
change the results.22
Aging and Central Bank Independence
To test the impact of the share of elderly on the choice of institutions that
affect inflation, I collect data for 21 OECD countries in the period 1960 to
2000 on the share of elderly and CBI, as well as a battery of controls. CBI has
been shown to be introduced to lower inflation, and indeed is associated with
Vlandas 17
Table 3. The Impact of Being Elderly and Inflation on Support for the Incumbent.
Column (1) (2)
Dependent variable Vote for incumbent Vote for incumbent
Regression method Logit Logit
Retired respondent 0.169*** (0.022) 0.289*** (0.031)
Inflation rate −0.038*** (0.004) −0.026*** (0.004)
Retired × Inflation −0.046*** (0.009)
Male respondent 0.010 (0.017) 0.010 (0.017)
Unemployed respondent −0.185*** (0.045) −0.187*** (0.045)
Unemployment rate −0.084*** (0.003) −0.084*** (0.003)
Past vote for incumbent 2.553*** (0.018) 2.552*** (0.018)
Constant −1.673*** (0.131) −1.694*** (0.131)
Observations 88,077 88,077
Pseudo R2.25 .25
Education and income controls included but not shown. The results are the same if being an
elderly respondent (i.e., aged 65 years old and older) is used instead of being retired. Standard
errors in parentheses.
†p < .1. *p < .05. **p < .01. ***p < .001.
Figure 2. Effect of inflation on support for the incumbent conditional on whether
respondent is retired.
Calculated using results from column 2 in Table 3.
18 Comparative Political Studies 00(0)
lower inflation. Many CBI indices exist (Alesina et al., 1989; Cukierman
et al., 1992; Eijffinger & de Haan, 1996; Grilli et al., 1991), but I choose the
Cukierman index (Cukierman et al., 1992) partly because it is widely used
and partly because the update by Polillo and Guillén (2005) has the best cov-
erage for my time period. Note however that this index does not capture the
European Central Bank’s (ECB) monetary stance, and therefore limits my
sample to pre-EMU times.23 I control for real GDP growth, unemployment,
deficit, trade openness, industrial employment, left cabinet share, union den-
sity, wage coordination, and social transfers. I also include country and time
effects but note that dropping these or running more parsimonious models
does not change the results.
Table 4 shows the results and reports robust standard errors clustered by
country. In column 1, I run the regression on yearly data. The share of elderly
and unemployment both have positive and significant coefficients at the 5%
level, while trade openness has a positive association and social transfers
have a negative association at the 10% level. In column 2, I run the regression
on 5-year period average. The coefficients for the share of elderly and unem-
ployment are still positive and significant, while trade openness and social
transfers become significant at the 5% level. In column 3, I run the regression
on 10-year period average. The result for the share of elderly is unchanged.
Overall, the results concerning the preferences of the elderly and the empiri-
cal mechanisms linking the share of the elderly to inflation are consistent
with my expectations.
Empirical Tests of the Determinants of Inflation
To test the impact of the share of elderly on inflation rates, I collect annual
data for 21 OECD countries in the period between 1960 and 2000.24 This time
period allows me to test the determinants of cross-national variation in infla-
tion both in the relatively low inflation period of postwar Europe, the high
inflation episodes of the 1970s and the—very—low inflation thereafter. I ini-
tially focus on developed economies because they have more established
democracies, more comparable economic structures and development levels,
and then extend my analysis to a sample of 175 countries.
My main dependent variable is the inflation rate, measured by the percent-
age change of the consumer price index from a year earlier, which is most
directly relevant to people’s purchasing power. My main independent vari-
able is the share of the population that is 65 years old and above. My baseline
model controls for various economic, institutional, and political factors that
are likely to affect inflation and are discussed with the results.
Vlandas 19
There are two types of problems with time-series cross-section (TSCS)
data. The first is that the error structure may suffer from heteroskedasticity
and/or autocorrelation which would lead to unreliable test statistics when
using ordinary least squares (OLS). I report robust standard errors clustered by
country throughout to address the panel structure of my data and neutralize the
biases that autocorrelation25 and heteroskedasticity26 would have on standard
errors. The second issue concerns the temporal structure of the data. If both
my dependent and my key independent variables are heavily trended upward
or downward—or more formally have nonconstant means—then they may be
nonstationary and any statistically significant association between them may
Table 4. Determinants of Central Bank Independence.
Column (1) (2) (3)
Dependent variable CBI CBI CBI
Period Yearly 5 years average 10 years average
Regression method OLS OLS OLS
Share of elderly 0.045** (0.015) 0.048** (0.015) 0.042* (0.016)
Real GDP growth −0.003 (0.002) −0.007 (0.007) −0.013 (0.014)
Unemployment rate 0.013* (0.005) 0.012* (0.005) 0.011 (0.007)
Deficit 0.005 (0.004) 0.005 (0.007) 0.005 (0.010)
Trade openness 0.002† (0.001) 0.004* (0.002) 0.006** (0.002)
Industrial employment −0.199 (0.444) −0.637 (0.483) −0.621 (0.713)
Left cabinet share −0.000 (0.000) 0.000 (0.000) 0.001 (0.001)
Union density 0.001 (0.001) 0.002 (0.001) 0.003 (0.001)
Wage coordination 0.012 (0.010) 0.021 (0.022) 0.016 (0.037)
Social transfers −0.011† (0.006) −0.015* (0.007) −0.015 (0.008)
Constant −0.096 (0.233) −0.058 (0.214) −0.070 (0.266)
Observations 699 162 94
Number of countries 21 21 21
Country fixed effects Yes Yes Yes
Time effects Yes Yes Yes
R2 overall model .11 .11 .14
R2 within model .58 .70 .73
R2 between model .00 .00 .00
See Section 3.4 in Appendix for more details on variables and robustness checks. CBI =
central bank independence; OLS = ordinary least squares. Robust standard errors clustered
by country in parentheses.
†p < .1. *p < .05. **p < .01. ***p < .001.
20 Comparative Political Studies 00(0)
be spurious. The Im-Pesaran-Shin unit root test for the inflation variable
rejects the null hypothesis that all panels contain a unit root and the Fisher
panel unit root test similarly rejects the null hypothesis of a unit root at the 5%
level. However, both tests fail to reject the null hypothesis of nonstationarity
for the share of elderly.27
In principle, spurious correlations occur when both variables are non-
stationary, which is not the case here. Nevertheless, in the next sections I
use a wide range of model specifications and approaches to ensure that
my results are not spurious. First, I start by running a purely cross-sec-
tional model, which removes any bias arising from the temporal dimen-
sion. Second, when running a TSCS on levels of inflation and the share of
elderly, I include both time dummies and a trend. Third, I run a model
with both my dependent variable and key independent variable in first
difference, and they become stationary thereby removing all risks that
this association is spurious. Fourth, I run an ECM which models the tem-
poral dynamics. Fifth, I rerun all these models on a world sample and
check whether removing the high-income countries changes the associa-
tion. The association holds throughout, and this is not driven by economic
development as I include GDP per capita in all my regressions, and
removing countries with high GDP per capita in the world sample does
not change my results.
Cross-Sectional Analysis of Inflation
The bivariate correlation coefficient between inflation and the share of elderly
in my sample of 21 OECD countries since 1960 is −.2797 (significant p value
of .000). I compute the average for the whole time period for all variables and
run a cross-sectional OLS analysis on 21 OECD countries.
Given limited degrees of freedom, I include only essential independent
variables. I start by including the share of elderly, GDP growth, the unem-
ployment rate which may put downward pressure on inflation through its
effect on wages, and the degree of capital openness as capital may exit coun-
tries where inflation is deemed too high.28 I then add the degree of trade open-
ness which makes inflation more costly, and CBI which can be expected to
lead to lower inflation. As shown in Table 5, the model performs well: 82%
of the variation in the dependent variable is explained by the variation in the
independent variables. The coefficients for capital and trade openness are
negative and significant while unemployment is positive and significant, and
CBI is not significant. The share of elderly is negative and statistically sig-
nificant, and the results are robust to the inclusion of additional controls such
Vlandas 21
as left control of cabinet, union density, or deficits, and to the exclusion of
outliers (Greece, Portugal, Spain, Germany, and Sweden). Equally, stepwise
deletion of insignificant variables does not change the results.29
TSCS Analysis
As I have more degrees of freedom when keeping both the time and cross-
sectional dimensions, I can include more controls in the TSCS analysis. In
addition to the variables discussed in the previous section, I include the
following variables: Union density can be expected to lead to higher infla-
tion by increasing the bargaining power of workers or to lower inflation if
the Olsonian effect dominates; left control of the government should be
associated with higher inflation; and wage coordination allows unions to
internalize the effects of their wage claims—which could otherwise lead to
inflation. I choose a wage coordination index which takes values between
1 (low coordination) and 5 (high coordination; Visser, 2013). Inspections
for collinearity did not reveal any problems with this wider set of indepen-
dent variables.
I start with an empty model with just the share of elderly, and then intro-
duce stepwise country fixed effects, time effects, and then a trend.30 The full
results are presented in Table 6. The share of elderly is negative and statisti-
cally significant: An additional 1 percentage point increase in the share of
elderly is associated with 0.648 percentage point fall in inflation rates. The
unemployment rate and capital openness are both negative and significant,
Table 5. Cross-Sectional Determinants of Inflation.
Dependent variable Inflation
Share of elderly −0.23265* (0.130)
Capital openness −2.31281*** (0.389)
Unemployment rate 0.13585* (0.064)
Real GDP −0.46660* (0.257)
CBI 1.73463 (1.414)
Trade openness −0.00821* (0.005)
Constant 12.01223*** (2.462)
Observations 21
R2.82
See Sections 4.1 and 4.2 in Appendix for more details on variables and robustness checks,
respectively. CBI = central bank independence. Robust standard errors in parentheses.
*p < .1. **p < .05. ***p < .01.
22 Comparative Political Studies 00(0)
while left control of the cabinet, wage coordination, and CBI are not statisti-
cally significant. Union density has a positive and significant association.
Crucially I control for GDP per capita which captures the changing level of
economic development of countries over time. This is important because it
may be that economic modernization results in both higher life expectancy
and falling inflation. However, the variable is not statistically significant. As
country and time effects are included, my results are not driven by unob-
served heterogeneity. The trend is negative but not statistically significant.
I carry out a battery of robustness checks. Including a lagged dependent
variable or lagging all independent variables does not change the results.
Using generalized least squares or reporting panel-corrected standard errors
with an AR(1) process instead of robust clustered standard errors does not
change my result concerning the share of elderly. Dichotomizing the depen-
dent variable to take value 1 if inflation is above 10 (very high inflation) and
0 otherwise, and running a logistic model does not change the results: The
share of elderly continues to be significant at the 10% level.31
Table 6. TSCS Determinants of Inflation.
Dependent variable Inflation
Share of elderly −0.648* (0.269)
Unemployment rate −0.313** (0.109)
GDP per capita, 1,000s 0.228 (0.176)
Capital openness −0.885* (0.339)
Trade openness −0.032 (0.023)
Union density 0.099*** (0.023)
Left parties, % cabinet posts 0.001 (0.003)
Wage coordination 0.078 (0.167)
Central bank independence 1.486 (1.122)
Constant 10.946** (2.893)
Fixed effects Yes
Time effects Yes
Trend −0.080
Observations 597
Number of countries 21
R2 within model .77
R2 overall model .44
R2 between model .01
The dependent variable is inflation rate as captured by consumer price index. See Sections 4.1
and 4.3 in Appendix for more details on variables and robustness checks, respectively. TSCS
= Time-Series Cross-Section. Robust standard errors clustered by country in parentheses.
†p < .1. *p < .05. **p < .01. ***p < .001.
Vlandas 23
In addition, controlling for a squared term of union density,32 debt, deficit,
terms of trade, educational attainment, industrial employment, social trans-
fers, union authority, union concentration, home ownership, structural unem-
ployment, employment protection legislation, whether the country is in
Europe, or whether the country is a Liberal Market Economy does not change
the results.33 I have also rerun my analysis when replacing the share of elderly
by the dependency rate,34 and the results are unchanged. Finally, I carried out
a stepwise jackknife country exclusion, and the results are robust to the exclu-
sion of any one country.35
TSCS Analysis on First Difference in Dependent and
Independent Variables
As noted previously, inflation is stationary but the share of elderly is nonsta-
tionary. While my cross-sectional analysis cannot by design be biased by
nonstationarity and my earlier TSCS analysis included both time effects and
a trend, I now rerun my analysis on the first difference of both inflation and
the share of elderly, where both variables are nonstationary36 and hence can-
not be spuriously related. As before, I first run an empty model while control-
ling for country and time effects as well as including a trend, the coefficient
is negative and statistically significant. This association is robust to a jack-
knife stepwise country exclusion.37
Next, I add my independent variables and present the results in Table 7.
The coefficient for the share of elderly remains negative and statistically sig-
nificant. The first difference in unemployment is negatively associated,
whereas the first difference in GDP per capita and wage coordination are not
significantly associated. Union density, left-wing control of cabinet, and CBI
are all included in levels for theoretical reasons38: Only union density is sta-
tistically significant at the 10% level.
Removing country fixed effects, replacing the share of elderly by the
dependency rate, or rerunning the regression with generalized least squares
or panel-corrected standard errors with an AR(1) process does not change my
results.39 I check the robustness of my results for the same additional controls
as in the previous analysis on levels and the effect of the share of elderly on
inflation remain negative and significant.40 Rerunning a more parsimonious
model with just the first differences in the share of elderly, unemployment,
GDP per capita, and the level of CBI does not change my results. As before,
jackknife stepwise country exclusion does not change my results. Careful
examination of inflation rate over the whole sample reveals that there are
outliers in the 1970s and in the 1990s. I therefore rerun the analysis while
excluding the 1970s and then excluding the 1990s from my sample. The coef-
ficient for the share of elderly remains statistically significant.41
24 Comparative Political Studies 00(0)
Overall, I conclude that the association between inflation and the share of
elderly is not spuriously driven by nonstationarity, omitted variable bias,
unobserved country or time heterogeneity nor by problems with the structure
of my errors.
Dynamics of Adjustments: ECM
A more formal way of investigating time dynamics is to use an ECM. So far,
my results have shown that there is a robust association between the share of
elderly and inflation but have revealed little about the dynamics of adjust-
ment. I therefore use a single-equation ECM of the standard form.42 In the
first column of Table 8, I report a parsimonious model with the share of
elderly as my only independent variable. The results suggest that the short-
run effect of an increase in elderly on inflation is 0.042 but not statistically
significant. This makes sense conceptually as once one clearly distinguishes
between long- and short-run effects, one cannot expect inflation rates to
directly and instantaneously respond to a change in the share of the elderly.
Table 7. First Difference Analysis.
Dependent variable First difference inflation rate
Share of elderly (first difference) −1.209† (0.634)
Unemployment rate (first difference) −0.418* (0.170)
GDP per capita, 1,000s (first difference) −0.100 (0.209)
Wage coordination (first difference) 0.112 (0.125)
Union density −0.023† (0.012)
Left-wing parties in % cabinet posts 0.000 (0.003)
Central bank independence 0.581 (0.450)
Constant 0.619 (1.095)
Observations 644
Number of countries 21
Fixed effects Yes
Time effects Yes
Trend 0.024
R2 within model .37
R2 overall model .34
R2 between model .00
See Sections 4.1 and 4.4 in Appendix for more details on variables and robustness checks,
respectively. Robust standard errors clustered by country in parentheses.
†p < .1. *p < .05. **p < .01. ***p < .001.
Vlandas 25
Table 8. Results From an Error Correction Model.
Column (1) (2)
Dependent variable First difference in inflation
Inflation (lagged) −0.140*** −0.459***
Share of elderly (first difference) −0.042 −1.095
Share of elderly (lagged) −0.111*** −0.228†
GDP per capita (first difference) −1.048**
GDP per capita (lagged) 0.446**
CBI (first difference) 2.512
CBI (lagged) 1.165
Capital openness (first difference) −0.482
Capital openness (lagged) −0.444**
Employment in industry (first difference) −8.318
Employment in industry (lagged) 5.856
Union density (first difference) 0.068†
Union density (lagged) 0.023
Unemployment rate (first difference) −0.137
Unemployment rate (lagged) −0.101
Coordination (first difference) 0.089
Coordination (lagged) 0.057
Social transfers (first difference) −0.382*
Social transfers (lagged) −0.137
Left share of cabinet seats (first difference) −0.001
Left share of cabinet seats (lagged) −0.001
Deficit (first difference) 0.154**
Deficit (lagged) −0.065
Long-run effect of elderly on inflation −0.7949738*** −0.4961375*
Constant 2.184*** 6.340**
Observations 1,089 558
Number of countries 21 21
R2 within model .10 .59
R2 overall model .08 .31
R2 between model .01 .61
The coefficient for the short-term effect of a change in the share of elderly and of the lagged
inflation capturing the adjustment process (or error correction) can be interpreted as such,
but interpreting the long-run effect requires recalculating the coefficient (and its associated
standard error) directly using the Stata nlcom command (this is reported in the row “Long
run effect of elderly on inflation”). See Section 4.5 in Appendix for more details on ECMs and
for a range of robustness checks. CBI = central bank independence; ECM = error correction
model. Robust standard errors clustered by country.
†p < .1. *p < .05. **p < .01. ***p < .001.
26 Comparative Political Studies 00(0)
The long-run effect is calculated by taking the negative of the ratio of the
coefficient of the lagged share of elderly to the coefficient of the lagged
dependent variable and is equal to −0.79, with an adjustment process (error
correction) of 0.14 per period.43 In other words, the total long-run effect of 1
percentage point increase in the share of elderly is 0.79 percentage point
lower inflation, but in t + 1 this initially results in 0.14 × 0.79 reduction in
inflation, and so on. Because the estimate of the long-run coefficient −0.79 is
a recalculation from two estimated coefficients, we need to also recalculate
the standard error to assess whether it is statistically significant, which we
can do using the Stata command nlcom. As can be seen in the last row before
the constant, the long-run effect is statistically significant at the .001 level.
Note that including country fixed effects does not change the results.
Next, I recalculate the long-term effect when including one control at a
time by itself: Controlling for trade openness, capital openness, CBI, GDP
per capita, union density, unemployment rate, wage coordination, social
transfers, left governments, deficit, home ownership, or employment protec-
tion legislation does not change the results.44 I then stepwise add the follow-
ing variables in both lagged and first difference (to calculate their short- and
long-term effects), and then rerun the regression with each new additional
variable: GDP per capita, CBI, capital openness, employment protection leg-
islation, union density, unemployment rate, wage coordination, social trans-
fers, left share of cabinet, and deficit. For each regression, I calculate the
long-term effect of the share of elderly which remains negative and signifi-
cant.45 Note that as more independent variables are included, the size of the
sample is reduced as data availability is not consistent across variables. In
column 2, I report the final model which includes country and time effects as
well as a trend: The long-term effect of the share of elderly on inflation
remains negative and statistically significant.46
Ruling Out Economic Modernization and an “Economic”
Channel With A World Sample
It would in principle be possible that OECD countries have developed eco-
nomically in a way that has jointly led to aging and lower inflation. As econo-
mies modernize, the birth rate falls and longevity increases at the same time as
economic institutions become more effective at containing inflation. However,
this alternative “economic modernization” narrative of aging and falling infla-
tion is unlikely to bias my results because I control for GDP per capita which
captures economic modernization throughout my empirical analysis in previ-
ous sections. Because OECD countries are broadly at a similar level of
Vlandas 27
economic development and have aged significantly, I now extend my analysis
to include countries with many different levels of economic development,
share of elderly, and inflation rates by collecting data on a much larger sample
including 175 countries between 1960 and 2013.47 This also allows me to
investigate whether my argument “travels” to developing and emerging
economies.
I first start by calculating period average for all variables that are available
for a large number of countries. I run a series of cross-sectional regressions
with just the share of elderly on the right-hand side, and then add stepwise
GDP growth, unemployment, a democratic index, stock market capitaliza-
tion, and left control of the executive.48 The coefficient for the share of elderly
is negative and significant, while the size of stock market is negatively asso-
ciated with inflation.49 Controlling for national income per capita does not
change the results. Including an index of CBI that is available for 93 coun-
tries in 2003 and running a cross-sectional analysis does not change my
results concerning the impact of the elderly.50
Next, I run a TSCS regression analysis on the yearly data while including
both time and country effects. Some countries have very high inflation which
might be driving results, so I impose several restrictions on the dependent
variable (<100, <50, and logarithmic transformation) which does not change
the results. Rerunning the analysis in first differences while controlling for
GDP growth or national income per capita does not change the results. I then
rerun this analysis on GDP growth and the share of elderly in both lags and
first differences, while including time and country effects, to be able to calcu-
late long-run effects. As was the case in the sample of OECD countries, the
long-run effect of the share of elderly is negative and significant.51 I then
return to my analysis in levels and add stepwise unemployment, stock market
size, a democracy index, and left executive. Replacing GDP growth by
national income per capita does not change the results.52
I noted earlier that the relationship between inflation and the share of the
elderly could occur through economic rather than political mechanisms.
Given my earlier evidence on the political mechanisms, it is clear that at least
part of the effect occurs through the political arena, but this does not rule out
an additional nonelectoral economic mechanism. One way to explore this
issue further is to compare the effect of the elderly on inflation rates in coun-
tries with different degrees of democracy using an additive index of the
degree of democracy that takes values 0 to 10 (higher values suggest more
democratic institutions).
I rerun a simple model of inflation as a function of GDP growth, time
dummies, and include an interaction term between the share of elderly and
28 Comparative Political Studies 00(0)
the democratic index, and present the interaction in Figure 3. The share of
elderly is only negatively and significantly associated with inflation when
countries have a democratic score of 8, 9, or 10 (i.e., when they have “high”
democracy scores). If the causal mechanism operated mainly through a non-
electoral channel, the effect would be statistically significant regardless of
the degree of democracy. This interaction is unchanged if we include coun-
try fixed effects, or we control for unemployment or stock market size.53 If
we include national income per capita, which neutralizes the effect of eco-
nomic modernization, we observe that the negative effect of the share of
elderly on inflation only holds in countries with a democratic score of 9 or
10.54 Finally, we can exclude all countries that are economically modernized
by restricting the sample to countries with national income per capita under
US$20,000.55 The results are unchanged, so the association between infla-
tion and aging does not occur through an economic mechanism nor is it
biased by broader economic modernization dynamics.
Figure 3. Effect of share of elderly on inflation depending on degree of
democracy.
This graph plots the interaction effect between the share of elderly and the index of
democracy in a regression that controls for GDP growth and time dummies and where
all observations with a dependent variable with values higher than 100 are excluded from
analysis. The confidence interval uses robust standard errors clustered by country. Note that
including country effects, replacing GDP growth by national income per capita, or excluding
all countries with national income per capita above US$20,000 does not change the results
(see Section 4.6 in Appendix).
Vlandas 29
Conclusion
Previous literature on the determinants of inflation emphasizes the role of
ideas and institutions, and to a lesser extent interest group. While these
approaches are valuable, this article has argued that by neglecting the role of
electoral politics, these explanations miss out an important determinant of the
cross-national variation in inflation rates. For both methodological and theo-
retical reasons, this article has focused on the share of elderly to show how
aging affects inflation rates through electoral politics.
I have argued that countries with a larger share of elderly exhibit
lower inflation because elderly voters are inflation averse, numerous,
and politically powerful. Political parties therefore compete for their
votes before elections and are influenced by their preferences while in
government because they fear electoral penalties at the next section. As
a result, in countries with a larger share of elderly, governments pursue
lower inflation.
A wide range of findings support this argument: Older voters are more
inflation averse, countries with more elderly have more economically
orthodox political parties, the electoral punishment for inflation is higher
among elderly voters, and countries with more elderly exhibit higher CBI
and lower inflation. I have tested the latter association between the share of
elderly and inflation rates using a wide variety of specifications, methods,
and samples. My results show that the magnitude of this effect is suffi-
ciently strong to suggest we were missing an important determinant of
inflation rates, and the evidence does not suggest that nonstationarity, omit-
ted variable bias, unobserved heterogeneity, or economic modernization are
biasing this association.
Although this article has focused on the effect of only one social group—
the elderly—on one main economic outcome—inflation—this represents an
important contribution to the comparative political economy literature in sev-
eral ways. First, my findings show convincingly that electoral politics, not
just institutions or ideas, also matter for explaining variation in inflation
rates. Further research should analyze the impact of other electoral groups on
inflation. Second, extending my argument beyond the case of inflation would
suggest that aging may have important effects on other economic outcomes
and policies. This represents a valuable avenue for further research. Third,
aging may have represented a powerful driver behind the shift to a low infla-
tion regime in the past decades, though it is unlikely to alone explain such a
shift. Looking to the future, as populations continue to age, the political
imperative to keep inflation low may force politicians to adopt suboptimal
economic policies.
30 Comparative Political Studies 00(0)
Acknowledgments
I am grateful to Bob Hancke, David Soskice, Chiara Benassi, Abel Bojar, Michael
Zemmour, Achim Goerres, Daphne Halikiopoulou, Margarita Gelepithis, Elvire
Guillaud, Baptiste Francon, Jerome Bourdieu, Jonathan Golub, Julian Garritzmann,
Marius Busemeyer, and Marco Simoni for their comments on this article. In November
2015, I received helpful comments when I was invited to present this article at the
University of Konstanz and at a workshop organized jointly by the Paris School of
Economics and the University Paris 1 Pantheon-Sorbonne. I also had very helpful
discussions with James Reade about error correction models. Abel Bojar kindly
agreed that I use a dataset on individual voting behavior in Europe which we are using
in a separate joint project on economic voting and social groups. For excellent
research assistance, I am thankful to Sergen Bahceci and Christos Vrakopoulos. Last
but not the least, I would also like to thank four reviewers and the editors of CPS for
their excellent constructive comments. All remaining errors are my own.
Declaration of Conflicting Interests
The author declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The author received no financial support for the research, authorship, and/or publica-
tion of this article.
Notes
1. This short summary does not do justice to the sophistication of the argument—
for a more comprehensive review, see Iversen and Soskice (2006).
2. McNamara (1998) does discuss what made the new paradigm attractive: a com-
bination of policy failure (in dealing with oil shock), policy innovation (mon-
etarism), and policy emulation (seeing Germany as an example of good policy).
Here, I do not wish to suggest that these are irrelevant, rather that this must be
completed by an analysis of electoral politics.
3. Cukierman, Web, and Neyapti (1992) similarly suggested that the likelihood of
making central bank independent was a function of the size of financial markets,
and subsequent literature has by and large confirmed Posen’s contention that
central bank independence and low inflation require political support to be sus-
tained in the long run—see Berger, de Haan, and Eijffinger (2001); Hayo (1998);
Kuttner and Posen (2009); and Miller (1998).
4. Goerres (2009, pp. 1-10) discusses the pros and cons of different cutoff points.
For the purpose of minimizing the risk of capturing people who are not yet
retired in our measure of inflation-averse old people, it is safe to put the cutoff
point at 65.
5. Elderly’s preferences are relative: What matters is their inflation preferences
relative to the rest of the population, and similarly for their position in terms
Vlandas 31
of income sources, asset wealth, and so on. The Organization for Economic
Co-Operation and Development (OECD; 2013, p. 78) shows that over-65s relied
to a large extent on nonwork sources of income such as public transfers or capital
income in the 2000s. The retired increasingly do not rely on inflation-adjusted-
defined pension benefits. Pension benefits have become less generous in several
countries, and some defined pension schemes are not (or not sufficiently) infla-
tion adjusted, and hence inflation may still have adverse effects (OECD, 2013, p.
25). The elderly also have higher home ownership rate and derive a larger part of
their income from capital, including noninflation-adjusted-defined contribution
schemes (ibid: 77-79). Estimates of the loss imposed by inflation over 20 years
for noninflation-adjusted benefits are as large as one third (see Antolin, 2009).
6. In most OECD countries, more than 70% of the over-65s own their houses—see
OECD (2013, p. 77).
7. Here, I implicitly draw on the distinction between opportunistic and composi-
tional mechanisms discussed in Ansell (2014, p. 12).
8. For general overviews, see Lewis-Beck and Stegmaier (2007), Norpoth (1996),
Lewis-Beck and Stegmaier (2000).
9. See Paldam (1991) for an early treatment of the determinants of vote change in
17 developed democracies.
10. This mechanism applied to a greater extent in the 1960s and 1970s—see for
instance, Zysman (1977) on France.
11. For instance in France, the government extends wage agreements to most work-
ers in a sector regardless of whether they are unionized.
12. See Table A4 and Table A5 in Appendix.
13. Similarly, there is a large literature (e.g., Boix, 1998; Rueda, 2006) that posits
an impact of for instance labor market position on political preferences without
necessarily implying that all individuals within a subcategory have totally homo-
geneous preferences.
14. See Tables A19 and A20 in Appendix.
15. See Table A21 in Appendix.
16. See Table A24 in Appendix for results with stepwise insertion of independent
variables.
17. The results hold when using Tobit instead of ordinary-least-squares (OLS)
regression, when using 5-year period average and lagging the share of elderly—
see Appendix Table A25.
18. See Table A25 in Appendix.
19. The results for conservative and social democratic parties are the same when
using 5-year period average.
20. See Table A35 in Appendix.
21. This dataset comes from a much wider and ongoing research project on eco-
nomic voting and social groups with Dr Abel Bojar.
22. See Table A42 in Appendix.
23. This is perhaps for the better as the European Central Bank (ECB’s) policy may
have different effects in distinct countries, and some authors have argued that
unlike national central banks the ECB no longer represents a credible threat
32 Comparative Political Studies 00(0)
to excessive wage agreements. See Hancké (2013) and Johnston (2012). See
Footnote 24.
24. See Section 4 in Appendix for countries included and more information on all
variables. Most of my data are available until 2012, but my index of central bank
independence is available only until 2000. Thereafter, Eurozone countries share
the same currency, and monetary policy is carried out by the ECB. The com-
mon monetary policy of the ECB may introduce polarizing inflation dynamics.
By removing the sanction that national central banks could impose on the shel-
tered sector, the European monetary union leads to polarization between shel-
tered and nonsheltered sectors. Cross-national variation in inflation rates may
also be affected by these polarizing dynamics as countries without coordinated
wage bargaining will experience greater inflationary pressures in the absence
of national central banks that can punish deviations—see Hancké (2013) and
Johnston (2012) for more on this.
25. The Woolridge test of autocorrelation rejects the null hypothesis that there is no
autocorrelation. See Table A63 in Appendix.
26. I reject the null hypothesis of homoskedasticity using the modified Wald test for
groupwise heteroskedasticity. See Table A64 in Appendix.
27. See Tables A52 and A53 in Appendix.
28. See Table A66 in Appendix.
29. See Tables A66 to A70 and Figure A67 in Appendix.
30. Table A71 in Appendix.
31. See Tables A71 and A72.
32. To capture the Calmfors and Driffill (1988) hypothesis.
33. See Tables A73 and A74 in Appendix.
34. The dependency rate is the number of elderly divided by working age popula-
tion—see Table A75 in Appendix.
35. See Table A76 in Appendix.
36. See Tables A55 and A58 in Appendix.
37. See Tables A78 to A80 in Appendix.
38. The argument about the inclusiveness and strength of union movements is an
argument about the level of union density. Similarly what matters for the left is
the level of control rather than increase in percentage of cabinet seats, and central
bank independence only changes rarely so running it as a first difference would
artificially limit its potential effect.
39. See Table A78 in Appendix.
40. See Tables A81 to A83 in Appendix.
41. See Table A83 in Appendix.
42. See Section 4.5 in Appendix for details on the error correction model (ECM).
43. See Section 4.5 in Appendix for the proof of how the long-run effect and error
correction can be derived from this empirical model.
44. See Table A90 in Appendix.
45. See Tables A91 and A92 in Appendix.
46. The short-term and recalculated long-term effects of each independent variable
are reported in Table A92 in Appendix.
Vlandas 33
47. Depending on model specification, the number of countries and years that are
covered by my analysis vary as a result of differences in the data availability of
each independent variable.
48. See Section 4.6 in Appendix for variable source and description, and all results
discussed in this section.
49. Consistent with Posen’s argument.
50. See Table A96 in Appendix.
51. See Table A98 in Appendix.
52. See Table A99 in Appendix.
53. See Figures A101 to A103 in Appendix.
54. See Figure A102 in Appendix.
55. See Figure A104 in Appendix.
References
Alesina, A., Mirrlees, J., & Neumann, M. (1989). Politics and business cycles in
industrial democracies. Economic Policy, 4, 55-98.
Alesina, A., Roubini, N., & Cohen, G. (1999). Political cycles and the macroecon-
omy. Cambridge, MA: MIT Press.
Alt, J., & Chrystal, K. (1983). Political economics. Brighton, UK: Wheatsheaf Books.
Ansell, B. (2014). The political economy of ownership: Housing markets and the
welfare state. American Political Science Review, 108, 383-402.
Antolin, P. (2009). Private pensions and the financial crisis: How to ensure adequate
retirement income from DC pension plans (OECD report). Paris, France: OECD.
Retrieved from http://www.oecd.org/daf/fin/44628862.pdf
Bach, G., & Stephenson, J. (1974). Inflation and the redistribution of wealth. The
Review of Economics and Statistics, 56, 1-13.
Barro, R., & Gordon, D. (1983). A positive theory of monetary policy in a natural rate
model. Journal of Political Economy, 91, 589-610.
Berger, H., de Haan, J., & Eijffinger, S. (2001). Central Bank Independence: An
update of theory and evidence. Journal of Economic Surveys, 15, 3-40.
Boix, C. (1998). Political parties, growth and equality. Cambridge, UK: Cambridge
University Press.
Briault, C. (1995, February). The costs of inflation. Bank of England Quarterly
Bulletin, pp. 33-45. Retrieved from http://www.bankofengland.co.uk/archive/
Documents/historicpubs/qb/1995/qb950102.pdf
Brooks, C., & Manza, J. (2006). Social policy responsiveness in developed democra-
cies. American Sociological Review, 71, 474-494.
Browning, E. (1975). Why the social insurance budget is too large in a democracy.
Economic Inquiry, 13, 373-388.
Bullard, J., Garriga, C., & Walker, C. J. (2012). Demographics, redistribution, and
optimal inflation. Federal Reserve Bank of St. Louis Review, 94, 419-439.
Busemeyer, M.-R., Goerres, A., & Weschle, S. (2008). Demands for redistributive
policies in an era of demographic aging: The rival pressures from age and class
in 15 OECD countries (MPIfG Discussion Paper 08/3). Köln, Germany: Max-
Planck-Institut für Gesellschaftsforschung.
34 Comparative Political Studies 00(0)
Butler, D., & Stokes, D. (1983). Political change in Britain. London, England:
MacMillan Press.
Calmfors, L., & Driffill, J. (1988). Bargaining structure, corporatism and macroeco-
nomic performance. Economic Policy, 3, 14-61.
Cameron, D. (1984). Social democracy, corporatism, labor quiescence, and the rep-
resentation of economic interest in advanced capitalist society. In J. Goldthorpe
(Ed.), Order and conflict in contemporary capitalism (pp. 147-178). New York,
NY: Oxford University Press.
Canes-Wrone, B. (2015). From mass preferences to policy. Annual Review of Political
Science, 18, 147-165.
Conesa, J., & Krueger, D. (1999). Social security reform with heterogeneous agents.
Review of Economic Dynamics, 2, 757-795.
Cooley, T., & Soares, J. (1999). A positive theory of social security based on reputa-
tion. Journal of Political Economy, 107, 135-160.
Cukierman, A., Web, S., & Neyapti, B. (1992). Measuring the independence of
Central Banks and its effect on policy outcomes. The World Bank Economic
Review, 6, 353-398.
Debelle, G., & Fischer, S. (1994). How independent should a Central Bank Be? In
Conference on Monetary Policy in a Low Inflation Regime. North Falmouth, MA.
Retrieved from http://EconPapers.repec.org/RePEc:fip:fedbcp:y:1994:p:195-
225:n:38
de Mello, L., Schotte, S., Tiongson, E., & Winkler, H. (2016). Greying the budget:
Ageing and preferences over public policies. Kyklos, 70, 70-96.
Eichengreen, B. (1996). Institutions and economic growth: Europe since World War
II. In N. Crafts & G. Toniolo (Eds.), Economic growth in Europe since 1945 (pp.
38-72). Cambridge, UK: Cambridge University Press.
Eijffinger, S., & de Haan, J. (1996). The political economy of Central-Bank
Independence (Special Papers in International Economics, No. 19). Princeton,
NJ: Princeton University.
Erikson, R., MacKuen, M., & Stimson, J. (2000). Bankers or peasants revisited:
Economic expectations and presidential approval. Electoral Studies, 19, 295-
312.
Erikson, R., MacKuen, M., & Stimson, J. (2002). The macro polity. New York, NY:
Cambridge University Press.
Esping-Andersen, G., & Sarasa, S. (2002). The generational conflict reconsidered.
Journal of European Social Policy, 12, 5-21.
European Commission. (2014). The 2015 ageing report underlying assumptions and
projection methodologies. Brussels, Belgium: Author.
Fair, R. C., & Dominguez, K. (1991). Effects of the changing U.S. age distribution on
macroeconomic equations. American Economic Review, 81, 1276-1294.
File, T. (2014). Young-adult voting: An analysis of presidential elections, 1964-2012
(Current Population Survey Reports). Washington, DC: U.S. Census Bureau.
Fletcher, D., & Kenny, L. (2008). The influence of the elderly on school spending in a
median voter framework. Education Finance and Policy, 3, 283-315.
Vlandas 35
Franzese, R. (2003). Multiple Hands on the Wheel: Empirically modeling partial
delegation and shared policy control in the open and institutionalized economy.
Political Analysis, 11, 445-474.
Friedman, M. (1968). The role of monetary policy. American Economic Review, 58,
1-17.
Galasso, V. (2006). The political future of social security in ageing societies.
Cambridge, MA: MIT Press.
Galasso, V., & Profeta, P. (2007). How does ageing affect the welfare state? European
Journal of Political Economy, 23, 554-563.
Goerres, A. (2007). Why are older people more likely to vote? The impact of ageing
on electoral turnout in Europe. The British Journal of Politics and International
Relations, 9, 90-121.
Goerres, A. (2008). The grey vote: Determinants of older voters’ party choice in
Britain and West Germany. Electoral Studies, 27, 285-304.
Goerres, A. (2009). The political participation of older people in Europe. Basingstoke,
UK: Palgrave Macmillan.
Grilli, V., Masciandaro, D., Tabellini, G., Malinvaud, E., & Pagano, M. (1991).
Political and monetary institutions and public financial policies in the industrial
countries. Economic Policy, 6, 341-392.
Hall, P. (1986). Governing the economy: The politics of state intervention in Britain
and France. Cambridge, UK: Polity.
Hall, P., & Franzese, R. (1998). Mixed signals: Central Bank Independence, coor-
dinated wage bargaining, and European Monetary Union. International
Organization, 52, 505-535.
Hancké, B. (2013). Unions, central banks and EMU: Labour market institutions and
monetary integration in Europe. Oxford, UK: Oxford University Press.
Harris, A., Evans, W., & Schwab, R. (2001). Education spending in an aging America.
Journal of Public Economics, 81, 449-472.
Hayo, B. (1998). Inflation culture, central bank independence and price stability.
European Journal of Political Economy, 14, 241-263.
Hibbs, D. (1977). Political parties and macroeconomic policy. American Political
Science Review, 71, 1467-1487.
Hibbs, D. (1979). The mass public and macroeconomic performance: The dynam-
ics of public opinion toward unemployment and inflation. American Journal of
Political Science, 23, 705-731.
Hibbs, D. A., Jr. (1986). Political parties and macroeconomic policies and outcomes
in the United States. The American Economic Review, 76, 66-70.
Hollibaugh, G., Rothenberg, L., & Rulison, K. (2013). Does it really hurt to be out of
step? Political Research Quarterly, 66, 856-867.
International Monetary Fund. (2004). World economic outlook. Washington, DC: Author.
Iversen, T. (1999). Contested economic institutions. New York, NY: Cambridge
University Press.
Iversen, T., & Soskice, D. (2001, December). An asset theory of social policy prefer-
ences. American Political Science Review, 95(4), 875-894.
36 Comparative Political Studies 00(0)
Iversen, T., & Soskice, D. (2006). New macroeconomics and political science. Annual
Review of Political Science, 9, 425-453.
Johnston, A. (2012). European Economic and Monetary Union’s perverse effects on
sectoral wage inflation: Negative feedback effects from institutional change?
European Union Politics, 13, 345-366.
Kitschelt, H. (2004). Diversification and reconfiguration of party systems in postin-
dustrial democracies. Bonn, Germany: Internat. Politikanalyse, Friedrich-Ebert-
Stiftung.
Kuttner, K., & Posen, A. (2009, January). Central Bank Independence: Conservative,
yes, but causal? Paper Presented at the ASSA Annual Meeting, San Francisco, CA.
Laidler, D. (Ed.). (1997). Where we go from here: Inflation targets in Canada’s
Monetary Policy Regime. Toronto, Ontario, Canada: C.D. Howe Institute.
Lange, P., & Garrett, G. (1985). The politics of growth: Strategic interaction and
economic performance in the advanced industrial democracies, 1974-1980. The
Journal of Politics, 47, 792-827.
Lelyveld, I. (1999). Inflation or unemployment? Who cares? European Journal of
Political Economy, 15, 463-484.
Lewis-Beck, M. S. (1988). Economics and elections: The major Western democra-
cies. Ann Arbor: The University of Michigan Press.
Lewis-Beck, M. S., & Stegmaier, M. (2000). Economic determinants of electoral out-
comes. Annual Review of Political Science, 3, 183-219.
Lewis-Beck, M. S., & Stegmaier, M. (2007). Economic models of voting. In R.
Dalton & H.-D. Klingemann (Eds.), The Oxford handbook of political behavior
(pp. 518-537). Oxford, UK: Oxford University Press.
Lindh, T., & Malmberg, B. (2000). Can age structure forecast inflation trends?
Journal of Economics & Business, 52, 31-49.
Lynch, J. (2006). Pension inequality and pension policy preferences in Europe: Self-
interest, policy feedbacks, or none of the above? (Working Paper). New York,
NY: Council for European Studies.
Lynch, J., & Myrskylä, M. (2009). Always the third rail? Pension income and
policy preferences in European democracies. Comparative Political Studies, 42,
1068-1097.
MacManus, S. (2000). Targeting senior voters: Campaign outreach to elders and oth-
ers with special needs. Lanham, MD: Rowman & Littlefield.
Maxfield, S. (1997). Gatekeepers of growth: The international political economy of cen-
tral banking in developing countries. Princeton, NJ: Princeton University Press.
McNamara, K. (1998). The currency of ideas. Ithaca, NY: Cornell University Press.
McRae, C. (1977). A political model of the business cycle. Journal of Political
Economy, 85, 239-263.
Miller, G. (1998). An interest group theory of central bank independence. The Journal
of Legal Studies, 27, 433-453.
Mulligan, C., & Sala-i-Martin, X. (1999). Gerontocracy, retirement and social secu-
rity (NBER Working Paper No. 7119). Cambridge, MA: National Bureau of
Economic Research.
Vlandas 37
Mulligan, C., & Sala-i-Martin, X. (2003). Social security, retirement, and the single-
mindedness of the electorate (NBER Working Paper No. 9691). Cambridge, MA:
National Bureau of Economic Research.
Nordhaus, W. (1975). The political business cycle. The Review of Economic Studies,
42, 169-190.
Norpoth, H. (1996). Presidents and the prospective voter. The Journal of Politics, 58,
776-792.
Organisation for Economic Co-Operation and Development. (2013). Pensions at a
glance (OECD report). Paris, France: Author. Retrieved from http://www.oecd.
org/pensions/public-pensions/OECDPensionsAtAGlance2013.pdf
Page, B., & Shapiro, R. (1983). Effects of public opinion on policy. American Political
Science Review, 77, 175-190.
Paldam, M. (1991). How robust is the vote function? A study of seventeen nations over
four decades. In H. Norpoth, M. S. Lewis-Beck, & J. D. Lafay (Eds.), Economics
and politics: The calculus of support (pp. 443-467). Ann Arbor: University of
Michigan Press.
Pamp, O. (2015). Political preferences and the aging of populations. New York, NY:
Springer.
Pampel, F., & Williamson, J. (1985). Age structure, politics, and cross-national
patterns of public pension expenditures. American Sociological Review, 50,
782-798.
Persson, T., & Tabellini, G. (2000). Political economics. Cambridge, MA: MIT Press.
Pierson, P. (1994). Dismantling the welfare state? Reagan, Thatcher and the politics
of retrenchment. Cambridge, UK: Cambridge University Press.
Pierson, P. (1998). Irresistible forces, immovable objects: Post-industrial welfare
states confront permanent austerity. Journal of European Public Policy, 5,
539-560.
Polillo, S., & Guillén, M. (2005). Globalization pressures and the state: The world-
wide spread of Central Bank Independence. American Journal of Sociology, 110,
1764-1802.
Posen, A. (1993). Why Central Bank Independence does not cause low inflation:
There is no institutional fix for politics. In R. O’Brien (Ed.), Finance and the
international economy (pp. 40-65). Oxford, UK: Oxford University Press.
Posen, A. (1995). Declarations are not enough: financial sector sources of Central Bank
Independence. In B. Bernanke & J. Rotemberg (Eds.), NBER Macroeconomics
Annual, 1995 (pp. 255-295). Cambridge, MA: MIT Press.
Posen, A. (1998). Central bank independence and disinflationary credibility: A miss-
ing link? Oxford Economic Papers, 50, 335-359.
Poterba, J. M. (1998). Demographic change, intergenerational linkages, and public
education. American Economic Review, 88, 315-320.
Rehm, P. (2016). Risk inequality and welfare states: Social policy preferences, devel-
opment, and dynamics. Cambridge, UK: Cambridge University Press.
Rogoff, K., & Sibert, A. (1988). Elections and macroeconomic policy cycles. The
Review of Economic Studies, 55, 1-19.
38 Comparative Political Studies 00(0)
Rose, A. M. (1965). The subculture of ageing: A framework for research in social
gerontology. In A. M. Rose & W. A. Peterson (Eds.), Older people and their
social world: The sub-culture of the aging (pp. 3-16). Philadelphia, PA: F.A.
Davis.
Rueda, D. (2006). Social democracy and active labour-market policies: Insiders, out-
siders and the politics of employment promotion. British Journal of Political
Science, 36, 385-406.
Sabbagh, C., & Vanhuysse, P. (2006). Exploring attitudes towards the welfare
state: Students’ views in eight democracies. Journal of Social Policy, 35,
607-628.
Scharpf, F. (1987). A game-theoretical interpretation of inflation and unemployment
in Western Europe. Journal of Public Policy, 7, 227-257.
Scheve, K. (2004). Public inflation aversion and the political economy of macroeco-
nomic policymaking. International Organization, 58, 1-34.
Schmitt, H., Scholz, E., Leim, I., & Moschner, M. (2008). The Mannheim
Eurobarometer Trend File 1970-2002 (Version 2.0.1). Retrieved from https://
dbk.gesis.org/dbksearch/sdesc2_eng.asp?no=3521&search=3521&search2=&d
b=e
Shiller, R. (1997). Why do people dislike inflation? In C. Romer & D. Romer (Eds.),
Reducing inflation: Motivation and strategy (pp. 13-70). Chicago, IL: University
of Chicago Press.
Sinn, H., & Uebelmesser, S. (2002). Pensions and the path to gerontocracy in
Germany. European Journal of Political Economy, 19, 153-158.
Sørensen, R. (2013). Does aging affect preferences for welfare spending? A study of
peoples’ spending preferences in 22 countries, 1985-2006. European Journal of
Political Economy, 29, 259-271.
Tepe, M., & Vanhuysse, P. (2009). Are aging OECD welfare states on the path to
gerontocracy? Journal of Public Policy, 29, 1-28.
Tepe, M., & Vanhuysse, P. (2010). Elderly bias, new social risks and social spending:
Change and timing in eight programmes across four worlds of welfare, 1980-
2003. Journal of European Social Policy, 20, 217-234.
Tilley, J. (2002). Political generations and partisanship in the UK, 1964-1997. Journal
of the Royal Statistical Society: Series A (Statistics in Society), 165, 121-135.
Visser, J. (2013). Database on institutional characteristics of trade unions, wage
setting, state intervention and social pacts, 1960-2011 (Version 4). Amsterdam
Institute for Advanced Labour Studies AIAS, University of Amsterdam.
Retrieved from http://uva-aias.net/en/ictwss
Vlandas, T. (2013a) Mixing apples with oranges? Partisanship and active labour mar-
ket policies in Europe. Journal of European Social Policy 23(3), 3-20.
Vlandas, T. (2013b) The Politics of Temporary Work Deregulation in Europe: Solving
the French Puzzle. Politics & Society 41(3), 425-460.
Volkens, A., Lehmann, P., Matthieß, T., Merz, N., Regel, S., & Werner, A. (2014).
The Manifesto Data Collection. Manifesto Project (Version 2014a). Berlin,
Germany: Wissenschaftszentrum Berlin für Sozialforschung.
Vlandas 39
Whiteley, P., Syed, P., & Richardson, J. (1994). True blues: The politics of British
conservative party members. Oxford, UK: Clarendon Press.
Wilson, G. (1991). Models of ageing and their relation to policy formation and service
provision. Policy & Politics, 19, 37-48.
Wlezien, C., & Soroka, S. N. (2007). The relationship between public opinion and
policy. In R. J. Dalton & H.-D. Klingemann (Eds.), The Oxford handbook of
political behaviour (pp. 799-817). Oxford, UK: Oxford University Press.
Yoon, J.-W., Kim, J., & Lee, J. (2014). Impact of demographic changes on infla-
tion and the macroeconomy (IMF Working Paper 14/210). Washington, DC:
International Monetary Fund.
Zysman, J. (1977). The French state in the international economy. International
Organization, 31, 839-877.
Author Biography
Tim Vlandas (PhD, London School of Economics) is associate professor in political
economy at the University of Reading.
