SOCIAL CHANGE AND PARTISAN IDENTIFICATION IN POST

AUTHORITARIAN CHILE

Matıas BargstedInstituto de Sociologıa

Pontificia Universidad Catolica de Chilembargsted@uc.cl

Luis MaldonadoInstituto de Sociologıa

Pontificia Universidad Catolica de Chilelmaldona@uc.cl

February 27, 2015

Abstract

Since the return of democracy in 1990, party identification has been declining steadily among theChilean public. Very few studies have attempted to understand this process in a longitudinal perspective.We address this gap by studying the evolution of mass level partisanship through an age-period-cohortanalysis applied to repeated cross sectional data from 1994 to 2014. Results from Bayesian randomintercept models indicate the presence of significant and negative effects associated to all three elementsof social change. First, strong period effects have shrunken the overall level of partisan identification,though with some noticeable setbacks during election years. Second, pronounced aging effects havereduced individuals’ propensity to identify with a party as they become older. Lastly, we find significantcohort effects whereby each successive generation is less partisan. Consequently, the effects of all threesources of change have consistently pointed in the direction of extinguishing mass partisanship fromChilean society.

1 Introduction

During the last decades several Latin American countries experienced dramatic dealigment processes whereby

significant portions of the population ceased to support or affiliate with any of the existing political parties

(Lupu, 2014a; Morgan, 2007). Within the region, Chilean society stands out as one in which these pro-

cesses adopted its sharpest form. Indeed, according to national surveys, while in 1994 more than 73% of

the Chilean adult population mentioned to identify or sympathize with a political party, in 2014 this figure

dropped to 32%.1 Similarly, the proportion of the public that mentioned to identify or sympathize with one

of the political coalitions decreased more than 30 percentage points from 71% 1994 to 40% in 2013. While

there certainly are some years where the aggregate levels of identification recover, particularly during elec-

tion years, the indisputable trend is one of decline. As a result of this brake down of mass partisanship, Chile

1Data are provided by the survey of the Centro de Estudios Publicos. In section 3.1 we provide technical details of this datasource.

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exhibits at the end of the last decade the lowest percentage of party sympathizers among Latin American

countries (Luna & Altman, 2011).

These trends have not gone unnoticed by scholars (Segovia, 2009; Toro, 2008; Morales, 2010). Un-

surprisingly, many of them express deep concerns about the possible negative consequences these changes

might have over the Chilean political system. A decrease in aggregate levels of partisan identification, by

which we mean a sense of subjective attachment with parties or coalitions, reflects less public support for

political parties in general. This decline might not only reflect current problems affecting Chilean political

parties, but might also entail new ones. When political parties experience weak support they will have, ar-

guably, more difficulties performing their key tasks such as developing credible political alternatives to the

electorate, gathering political support for new policies, recruiting prospective political leaders and candi-

dates, mobilizing voters to participate in the democratic process, and perhaps most importantly, articulating

heterogeneous social and political interests (Dalton et al., 2000).

The present article examines party identification in Chile for the period between 1994 and 2014.2 For this

we carry out an age-period-cohort (APC) analysis with repeated cross-sectional survey data that estimates

the relative importance of each of these three sources of attitudinal change. Our estimates from Bayesian

random intercept models indicate the presence of significant effects associated to all three elements. First,

we find very strong period effects that have shrunken the overall level of party and coalition identification,

though with some noticeable setbacks particularly during presidential election years. We also find strong

and negative effects associated with age whereby individuals’ propensity to identify with a party decreases

as they become older. Finally, we also find relatively strong and linear birth cohort effects which indicate

that younger generations have become progressively less partisan. From these findings we conclude that all

three sources of social change have consistently pointed in the direction of extinguishing mass level parti-

sanship from Chilean society. As party attachments are held to contribute with several benefits to political

engagement and system stability (Campell et al., 1960; Carpini & Keeter, 1996; Wattenberg, 1998; Green

et al., 2002), our results suggest some discouraging trends respect to future levels of political participation

and electoral volatility in Chile.

This article contributes to the study of party identification by addressing some limitations of past re-

search. In first place, although scholars have explored the sources of mass partisanship in some Latin Amer-

ica countries (Lupu, Forthcoming; Morgan, 2007; Samuels, 2006; Vidal et al., 2010; Perez-Linan, 2002),

2We use the terms party identification, partisanship, and party attachments interchangeably in the rest of the article

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little research exists about sources of change associated with party identification, which is an unfortunate

gap if we recall that several countries in the region have experienced some dramatic dealingment processes.

Our study contributes to fill this gap by providing evidence of the sources of social change in the Chilean

case. Doing so the article enriches the discussion about how particular mechanisms produce aggregate

changes of partisanship, and provide insights for future work that seeks to identify similar processes in other

Latin American nations and developing contexts. Second, one of the main reasons behind the vacuum of

scholarly efforts studying the sources of mass partisan change over time in Latin America is the absence of

high quality data that allows the examination of sociopolitical attitudes over a long period. We overcome this

problem of research by generating and analyzing accumulated and harmonized survey data from the Centro

de Estudios Publicos surveys. This center is a Chilean non partisan think thank which has been conducting

national opinion surveys with probability sampling since 1989. Most importantly for our purposes, most

surveys employ the same sampling design and question wordings, and thereby provide high quality data for

the analysis of social change. Finally, a third contribution of our article is methodological. The identification

problem in APC analysis has been hotly debated in social sciences. The problem relies in the fact that the

age, period, and cohorts effects cannot be estimated simultaneously because these variables are perfectly

correlated. In order to estimate the parameters of interest we employ a slightly simplified version of the

model specification proposed (Yang & Land, 2008, 2013), which we argue avoids biases associated with the

strong correlation between age and birth cohorts.

Lastly, we consider Chilean society a particularly interesting case study given that it represents somewhat

of an anomaly. Its recent history, inaugurated in 1989 with the transition from a military dictatorship to a

stable democratic regime, is a successful one. In contrast to many countries of the region, Chilean society

experimented a notable macro economic expansion, sustained growth of social programs in education, pen-

sions and health provision, and though a bit more slowly, important political reforms which deepened and

consolidated democratic rules were achieved as well (Navia & Velasco, 2003). Most importantly for current

purposes, with the democratic transition a highly institutionalized multi-party system rapidly consolidated

(Mainwaring & Scully, 1995; Kitschelt et al., 2010). This system not only resembled the previous party

system before the democratic breakdown in 1973, but has remained very stable up to this date (Valenzuela

et al., 2007).3 On the other hand, and despite the prosperous political and economic performance, there are

3Specifically, since re democratization in 1990 the Chilean party system has revolved around two multi-party coalitions: thecenter-left Concertacion por la Democracia, composed by the Socialist Party (PS), Party for Democracy (PPD), Christian Demo-cratic Party (DC) and the Radial Social Democratic Party (PRSD); and the center-right Alianza por el Cambio, composed by National

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multiple indicators of growing political dissatisfaction and malaise among the population. The decline of

party identification mentioned above is joined by increasing rates of voter abstention (Contreras & Navia,

2013; Toro, 2008) and general apathy towards political affairs (Huneeus, 1999; Joignant, 2002; Silva, 2004).

Therefore, Chile is a country with a stable and consolidated political regime, but simultaneously with high,

and rising, levels of political disenchantment. We employ this relatively complex scenario as a contextual

background motivating our analysis. Moreover, by analyzing how sociopolitical attitudes evolve in a gener-

alized context of political malaise, our study can carry out interesting implications for what can be expected

in new democracies where political disenchantment is unusually high (Torcal & Montero, 2006).

The article is organized as follows. In the next section we review some theoretical concepts that can

help contextualize our current work. We begin considering the concept of partisan identification, as well as

the comparative literature about partisan decline in advanced industrialized democracies. The next section

details all relevant information about APC methodology, research design and our statistical specification.

After this, we review the empirical results for both identification with political parties and coalitions. The

final section discusses our results and concludes.

2 Theoretical Background: Partisanship and Partisan Decline

2.1 Conceptualizations of Partisanship

Most work on party identification can been organized around two schools of thought, namely the classical

view, or Michigan model (Campell et al., 1960), and the revisionist view, represented by work, among others,

of Jackson (1975), Fiorina (1981) and Achen (1992). The classical view understands identification with a

party as an enduring and affectively charged psychological attachment. Individuals inherit their identification

from their parents and the social context in which they are raised, and are expected to maintain a relatively

stable identity across their entire life span. There is some space for change, but it is largely restricted to

situations where life conditions change significantly, such as in cases of political realignments or economic

crisis. The “revisionist” view is commonly associated with a more rationalistic view of partisan identifica-

tion. In one of the most influential expositions of this approach Fiorina (1981) claimed that partisanship is

better understood as a summary evaluation of individuals’ retrospective judgments about the positions and

Renewal (RN) and the Independent Democratic Union (UDI). The Concertacion governed between 1990 and 2010, when it was de-feated by the Alianza coalition. Most recently the Concertacion parties joined with the small Communist Party and refunded thecoalition under the name New Mayority, which swept the polls in the December 2013 general elections.

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performances of political parties (the so called “running tally”). Individuals can change or update their party

identification whenever they consider that the party they currently favor does not reflect best their political

interests. Accordingly, party identification might not only affect individuals’ perception of political objects,

as the American Voter (Campell et al., 1960) claimed, but might be itself responsive to those retrospective

evaluations.

Despite the differences between these perspectives, they share some common ground. Behind the dif-

ferent emphasis, lies a broad agreement that party identification constitutes a relatively stable and favorable

disposition towards a political party. This point is stressed by the literature which distinguishes partisanship

from vote choice. While the vote is expected to be subject to strategic considerations, candidate effects and

mass media influences, partisanship is considered to be less sensitive to the contingent forces operating at a

given moment (Miller & Shanks, 1996; Bartels, 2000; Johnston, 2006; Green et al., 2002).

Another point where the Michigan and running tally models convergence refers to the relationship be-

tween age and partisanship. Both perspectives postulate a life-cycle effect whereby individuals’ attachment

towards a party becomes stronger as they become older. Most famously, Converse (1969) proposed a theo-

retical model in which identification with parties operates as a social habit in which the degree of subjective

attachment with the preferred party increases with cumulative electoral experience, and thereby, appears

highly correlated with aging.4 While Converse’s model includes several additional elements that account for

different rates of partisan strengthening, the key point is that cumulative electoral experience leads to stronger

degree of identification only in countries with stable and long-lived party systems. Instead, in countries with

new or very young democratic regimes citizens have not had the opportunity to accumulate electoral experi-

ence, and consequently, the relationship between partisanship and age is expected to be flat. The correlation

between these variables can even be negative in countries with brief democratic experiences (10 to 15 years)

since younger people develop a partisan identification at higher rates than older individuals which are subject

to a “resistance function”. However, this last argument assumes an entirely new party system that does not

have any noticeable similarities with the party system that existed in a previous regime o political era. It also

presumes that the political experience that citizens accumulated before the democratic breakdown does not

influence the odds of developing an attachment after democracy was recovered.

4On the rational choice side, Achen (1992) proposed that individuals continuously revise their partisan identification followingan bayesian updating process in which past experiences is combined with new information from the political environment, but asindividuals’ accumulate more political experience impact of new information marginally decreases, making their identification morestable.

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There has been a great deal of empirical research during that last decades, conducting principally in

the United States and more recently in Europe, which has found support for Converse life-cycle hypothesis

(Converse, 1969; Markus, 1983; Barnes et al., 1985; Alwin & Krosnick, 1991; Green et al., 2002; Tilley,

2002; Dalton & Weldon, 2007). However, and quite unsurprisingly, soon after several scholars claimed that

the positive association between partisan strength and age is in fact a cohort or generational effect the follows

from the characteristics of the political environment in which individuals grew up (Abramson, 1976, 1979;

Dalton, 2014). What is surprising from this debate is how few of these studies actually contrast Converse’s

propositions against a cohort based explanation simultaneously accounting for the possible confounding

effects of year of birth, current age, and period of time (for a few exceptions see: Glenn & Hefner, 1972;

Knoke & Hout, 1974; Claggett, 1989; Dassonneville et al., 2012).

What can be expect for the Chilean electorate in light of these arguments? We believe Converse’s life

cycle hypothesis applies in general terms. Two reasons justify this point. First, even if Chilean democracy

was interrupted between 1973 and 1990 the current party system strongly resembles the one before the

democratic break down (Garreton, 1993), facilitating this way the renewal or updating of previous partisan

feelings among the adult population. Second, while the experience of the dictatorship certainly doesn’t count

properly as electoral experience, the military regime itself was aligned with right-wing political groups, and

since the early 80’s several center and left-wing groups, who would later give birth to the multiparty coalition

Concertacion por la Democracia, started to mobilize opposition to the military government. Consequently,

Chileans not only may have accumulated political experience over the past two decades, but the experience

gained prior to the democratic transition, among those old enough, may have also promoted to some extent

developing a partisan identification, even if it’s effect was smaller. In order to capture this possibility, our

statistical models will include a quadratic age term whereby each additional year of age has a decreasing

effect.

There are also reasons to believe we will find cohort effects. Previous studies using Chilean survey

data (Toro, 2008; Contreras & Navia, 2013) claim that there are positive associations between political en-

gagement indicators and age, which in turn, are due to generational differences. In effect, citizens who

experienced and participated in the 1988 election plebiscite, which ended the seventeen-year long military

dictatorship of Pinochet, were marked by this epic event, and consequently show, even decades later, lower

levels of political disaffection than the generations to come. If this pattern extends to partisanship, we would

expect that those cohorts who were born before 1970 shows systematically higher levels of party identifi-

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cation than those born after. Unlike these previous studies, we will employ adequate data and statistical

techniques that will allow us to contrast possible cohort effects, while holding constant age and period.

Lastly, a final caveat. Converse’s model considers the relationship between strength of partisanship and

age, not that between age and party identification per se (or what Claggett (1981) calls partisan acquisition),

which of course, is our subject of interest in this article. However, Converse’s argument can, and has, been

extended to the general case of partisan acquisition. In other words, the argument is that as citizens living in

stable and enduring democratic regimes become older, and therefore are able to cumulate more experience

with the political parties, their overall propensity to identify with a party should increase as well (Claggett,

1981; Berglund et al., 2005; Dalton & Weldon, 2007; Lupu, Forthcoming).5

2.2 Theories of Partisan Decline

While the decline of party and coalition identification in Chile has been particularly sharp, Chilean society is

not unique regarding this trend. In fact, there is large comparative literature that has been studying during the

last thirty years, without a clear outcome, whether an equivalent process of partisan decline can be observed

among advanced industrialized societies (Crewe et al., 1977; Schmitt & Holmberg, 1995; Wattenberg, 1998;

Bartels, 2000; Dalton et al., 2000).

We briefly review three influential approaches. In first place, cognitive mobilization theory, originally

developed by Ronald Inglehart and Russell Dalton, claims that aggregate levels of partisan identification

have been systematically decreasing across industrialized democracies due to continued processes of social

and economic modernization. In particular, societies that have gone through extended periods of socioeco-

nomic growth experience several structural changes that erode partisan attachments, most notably, sustained

increases in the educational rates and ample dissemination of mass media. The combination of these two

elements enables citizens to develop their preferences without the assistance of political cues provided by

parties, and reduces the costs of recollecting and processing political information (Dalton, 1984). Simulta-

neously, changes in the value systems associated with sustained increases in wealth also lead to the dissem-

ination of post-material values, which tends to undermine the importance of traditional political issues and

emphasize new issues such as environmental protection, subjective well-being, and others (Inglehart, 1990).

Consequently, the increasing level of material wealth leads to an eventual de-alignment of the party system

5Moreover, if we assume that mentioning a party with whom an individual identifies entails surpassing certain subjective thresh-old in the level of latent attachment or closeness that person feels for a party, it implies that the asociation between party identificationand age should be similar, albeit somewhat diminished, to the relationship between age and partisan strength.

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with respect to its traditional base of conflict, and provides citizens’ with certain functional independence

from political parties (Dalton et al., 2000). This perspective suggests that the main source of partisan change

among the electorate is generational replacement given that the new cohorts are subject to the forces of cog-

nitive mobilization and grow up in socioeconomically richer environments. This approach might seem to fit

well the Chilean experience given the notable economic and social advances this country experienced during

the last 25 years.

A second approach focuses on the degree of polarization of the party system. The general argument con-

tends that decreasing levels of polarization reduces both the ideological distance between political parties

and the intensity of the conflict between them. This makes it harder for voters to differentiate what parties

stand for and reduces their motivation to engage in the political process, which in turn, weakens their level of

partisan attachment (Schmitt & Holmberg, 1995; Berglund et al., 2005; Lupu, 2014b). Under a rational view

of partisanship, Lupu (2014a) argues that increasing levels of polarization imply that the expected returns

associated to one party increase as well, so the more incentives people have to develop a partisan attachment.

Comparative empirical research collaborates the positive association between polarization and the preva-

lence of partisanship. Focusing on several European countries, Schmitt & Holmberg (1995), Berglund et al.

(2005) and Schmitt (2009) have shown that the supposedly uniform and universal decline in partisanship,

portrayed by supporters of the cognitive mobilization hypothesis, is quit inexact. These authors propose that

fluctuations in the prevalence of partisanship can be better explained considering how adversary is political

competition within each country. More recently, Lupu (2014b) has confirmed for a broader range of coun-

tries that the degree of polarization is positively and strongly related to the prevalence of party identification

within a polity. There are reasons to believe that behind the collapse of party identification in Chile a gradual

process of ideological convergence could be in place. Some recent work on Chilean politics (Gamboa et al.,

2013; Bargsted & Somma, 2014) indicates that Chilean party system has, in fact, experienced certain some

degree of ideological convergence, particularly during the decade of 2000.

Lastly, the third approach we review considers the degree of responsiveness of political parties. Some

authors claim that institutional constraints and certain organizational formats can hinder political parties

ability to adapt to changing environments, engage the population into the political process and respond to

their demands (Coppedge, 1994; Burgess, 2003; Siavelis, 2012). One relatively extreme forms of unre-

sponsiveness is what Coppedge (1994) calls a partyarchy, that is, a system in which political parties have

undisputed power over the electoral and legislative process, and control relevant social organizations such as

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labor unions and large interest groups. Under this scenario, all relevant routes of political representation and

policy development are co-opted by political parties to the point where the political system becomes entirely

unaccountable to the electorate.

Recent political history of Chile provides reasons to believe that the Chilean party system, as Siavelis

(2012) argues, has indeed become a sort of partyarchy. First, up to the latest presidential election party elites

of both major coalitions have monopolized the candidate selection process in each single election with no

formal feedback by party activists such as election primaries.6 Second, the current binomial electoral system,

in which the two candidates are chosen in each legislative district, limits the impact of voters’ preferences

on electoral outcomes by securing at least one seat to members of each of the large coalitions (Navia, 2005;

Luna & Mardones, 2010).7 This has not only eroded the degree of accountability of the political system, but

has also made it very difficult for small parties to gain legislative representation. Third, party elites have been

reluctant to renew ranks of their leadership. For example, according to results from the Political Elites in

Latin America (PELA) parliamentary survey, 61.4% of Chilean congressmen between 1994 and 2006 were

serving their second or higher legislative period, while the Latin American average was only 33.4 (Boletin

8, PELA).

Our empirical analysis will no be able to identify which of these possible explanations, or combinations

of them, is the correct. As mentioned above our objective, more humble but still far from trivial, is to

empirically differentiate the effect of aging and cohort membership over partisan identification. Yet, after

reviewing the results from the APC analysis we will consider these in light of the theoretical approaches we

have discussed above.

3 APC Research Design

From an age-period-cohort perspective there are two main sources of social change: individuals themselves

may change or the composition of the population may change (Firebaugh, 1988). Change among individuals

can, in turn, be divided in two types: aging effects and period effects. In the context of this article, aging

effects refer to the changes in partisan identification that occur during individuals’ life course and that emerge

6There a few exceptions to this generalization. Before the 2012 municipal elections the center-left Concertacion carried outprimaries in 142 districts of a total 345. For the 2013 general election one of the mayor right-wing parties, National Renewal,implemented primaries in ten districts (out of a total of 60) to choose congressman candidates.

7With the binomial system a polling coalition can obtain both seats only if it doubles the number of votes obtained by thesecond-place list. With very few exceptions this rule virtually secures a seat for both of the mayor coalitions.

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from the accumulation of experience with political parties. Similarly, period effects reflect variations over

time (years in our analysis) in the level of partisan identification that apply to all age groups simultaneously.

These effects synthesize the impact of macro or system level events such as economic crisis, elections,

corruption scandals, institutional changes, and things alike (Yang & Land, 2013). The second source of

social change is captured through what is known as cohort effects. These reflect, in our context, changes in

levels of partisan identification across groups of people who experience the same historical and social events

at similar ages (Ryder, 1965).

3.1 Variables and Data Sources

We base our empirical analysis on data from the Center of Public Studies (Centro de Estudios Publicos - CEP)

surveys conducted between 1994 and 2014. These surveys use a probability multistage cluster sampling

design which is representative of Chilean adults 18 years of age and older. We employ the cumulative data

set that is available bi-annually and contains 42 cross-sectional probability surveys across 21 years.8 The

pooled data-set contains information for 59,412 individuals.9

There are multiple ways to measure party identification in the literature but all are in some way imperfect

(Johnston, 2006). In this article, we capture partisan attachments by using two dichotomous dependent

variables. The first one, identification with a political party, is captured with the survey question “Of the

following political parties mentioned in this card, with which one do you identify more or sympathize the

most?” Respondents who refused to mention any party where asked the follow up question “Well, from

which party you feel a little closer?”.10 This variable takes a value of one for all individuals who mention

a political party, either in the first or follow up question, and zero otherwise (including don’t know and non

responses). This measure presumes that respondents’ who express at least sympathy for a party are declaring

some sort of broad preference for that single party.

Our second dependent variable captures identification with political coalitions. To measure this variable

we use the survey question “Of the following political groups, with which one do you identify more or

8The Center of Public Studies (http://www.cepchile.cl/dms/lang_1/home.htm) is an internationally recognized non-partisan think thank that started to field public opinion surveys in 1987. We must constrain our analysis from 1994 onwards fortwo reasons. First, the party and coalition identification question we employ, and detail below, was introduced in 1993 and 1994,respectively. Second, only since 1994 the geographic coverage, initially limited to urban areas, is expanded to rural areas.

9Sample size varies in our statistical analysis insofar as we applied list wise deletion for missing data in any covariates anddependent variables. However, our analysis drops less than 1% of the available cases.

10The original Spanish question is “De los siguientes partidos polıticos que se presentan en esta tarjeta, con cual de ellos seidentifica mas o simpatiza mas Ud.?” The follow up question is “Bien, y de cual partido se siente un poco mas cercano?”.

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sympathize the most? With the Alliance, the Concertacian or the Toghether We Can pact?”. Similarly to the

party identification question, those respondents that refused to mention a political coalition, were asked the

follow up question “Well, from which political group do you feel a little closer?”11 All answers that mention

a political coalition are equal to one, and zero otherwise.

It is important to recall that political coalitions are a meaningful and stable political object in Chilean

politics (Gonzalez et al., 2008). Indeed both major coalitions, the New Majority (previously known as

Concertacion) and the Alliance, have always presented joint electoral lists for Congressional elections, and

with the exception of the 2005 general election, have always put forth a single presidential candidate. The

parties which compose each coalition haven’t almost varied since the early nineties. The mayor exception

was the incorporation of the Communist party into the Concertacion for the 2013 presidential election,

reason because of which the coalition changed it’s name to it current one. Given this stability of the political

coalitions, we expect that the results from the party and coalition identification variables should not be very

different. Further, by estimating statistical models for each variable we can evaluate how robust are our APC

estimates respect to two related, but different, expressions of partisan identification.

The three key independent variables for the APC models are respondents’ age, survey year (period)

and birth cohort. Age is measured as the respondents age in years divided by 10, with ranges from 1.8 to

8.5.12 We include in the analysis only respondents who are 85 years old or younger because the sample sizes

of older age groups are small.13 Twenty-one time points from 1994 to 2014, coded as dummy variables,

capture the period effects. We analyze 19 time points in models of coalition identification because data

for 2000 and 2013 are missing. Regarding cohort effects, studies measure this source of social change by

generating distinctions among broad classes of generations that capture different political formative periods

(Mannheim, 1952; Grasso, 2014). The problem of this strategy is that requires theoretical assumptions in

respect to the definition of such critical periods of socialization. To avoid this kind of modelling assumption

and following common practice in demography (Mason et al., 1973; Yang & Land, 2013), we constructed

11The original Spanish question is “Ahora, de las siguientes tendencias polıticas, con cual Ud. se identifica o simpatiza mas?Con la Alianza, con la Concertacion o con el Pacto Juntos Podemos?” The follow up question is “Bien, y de cual tendencia polıticase siente un poco mas cercano?” Notice that the this question suffered a small adjustment in the 2013 and 2014 surveys, in orderto reflect the formation of the new New Majority coalition, which merged the Concertacion parties (Cristian democracts, SocialistParty, Radical Social Democratic Party, the the Party for Democracy) with the Communist party. Specifically, these surveys askedthe following question: “Of the following political groups, with which one do you identify more or sympathize the most? With theAlliance or the New Majority”.

12This constrained the age coefficient to have less zero decimals, which helped the models convergence in parameter estimationprocedure detailed in the next section.

13We evaluated the sensitivity of our estimations to alternative measures of age, for example indicators with cut points at 84 or 86years. Our findings are robust to these changes.

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16 five-year birth cohorts ranging from cut-years 1919 or before to 1990 or after. This measure strategy of

cohort is based on the idea that contiguous years contain similar information of long-term social change. On

the ground of the disaggregate nature of this measure, note that our indicator of cohort should capture any

clustering of birth cohorts into more aggregated generations.

Finally, since our goal is to identify APC changes in reporting party identification rather than to explain

such changes, the inclusion of control variables in the statistical models has been kept to a minimum. We

include as control variables respondents’ gender (in order to account for differential mortality rates), as

well as years of education given that previous comparative and local studies indicate that it correlates both

with cohort membership and/or partisan identification (Albright, 2009; Segovia, 2009; Dassonneville et al.,

2012).14

3.2 Statistical Identification of APC effects

The empirical differentiation of cohort, age and period effects constitutes an extremely challenging method-

ological problem, which unsurprisingly has generated much research (Mason et al., 1973; O’Brien, 2000;

Glenn, 2005; O’Brien et al., 2008; Yang & Land, 2013). The most common way to overcome the linear

dependency of APC effects was suggested by Mason et al.(1973). This approach suggests applying fixed

effect regression to tabular data where all three variables (age, period and cohort) are coded with equal

length intervals. In order to avoid perfect collinearity the researcher must constrain certain parameters in a

model to be equal. In the 1970s and the 1980s, this modeling approach dominated APC analysis (Glenn,

2005). In recent years, Yang and Land (2008; 2013) proposed estimating APC effects using hierarchical

cross-classified models. This approach, which is particularly useful for analyzing repeated cross-sectional

survey data, captures simultaneously the effects of cohorts and periods as random effect variables, while the

effect of age is captured through a fixed effect coefficient. This implies modeling cohorts and periods as

contextual variables, while defining age as a variable at the lowest level of the hierarchy. 15

The cross-classified multilevel model for APC analysis has many attractive characteristics. Just to men-

tion a few, it allows researchers to easily introduce control variables into the model, to specify non linear

14Years of education is measured as an ordinal variable with nine levels: 0 years, between 1 and 3 years, between 4 and 7 years,8 years, between 9 and 11 years, 12 years, between 13 and 16 years, 17 years and 18 years or more.

15Another solution is the intrinsic estimator of Yang et al. (2008), which tries to solve the perfect linear correlation problem byremoving the effect of the null space on the design matrix. We don’t use this estimator because this does not allow the inclusion ofadditional covariates. Furthermore, O’Brien (2011) shows that the null vector as a constraint is an arbitrary choice as well, whichcan fail to identify meaningful linear time trends.

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terms such as quadratic transformations of respondents age, and perhaps most importantly, researchers can

evaluate whether substantive variables account for the variances associated with cohorts and periods (O’Brien

et al., 2008). However, the cross-classified multilevel model has one very significant weakness. In order to

identify the APC effects it is necessary to assume that the random effects of cohorts and periods are un-

correlated with the individual level predictors. Therefore, unless the cohort effects do not deviate strongly

from linearity, age and cohort random effects will be strongly correlated, which can lead to biased estimates

(Wooldridge, 2010). Recent simulation studies (Bell & Jones, 2014) show that when age and cohort effects

are indeed correlated they lead to biases of very large dimensions. Following the work of O’Brien et al.

(2008), it could be argued that researchers can incorporate cohort level predictors after which the residual

cohort random effects will distribute independently of age. While certainly true, this alternative is not an

option if the main purpose, such as ours and for a large of amount of researchers, is to precisely decompose

the aggregate trend into it’s age, cohort and period components.

A second, but more tractable, issue refers to the estimation method employed to calculate APC effects.

As well known, estimation of the cross-classified random effects models, or of any random effects model for

that matter, depends on an parametric justification of the random effects associated to the grouping variables.

This assumption presumes large samples but cohort and period measures frequently involve only a small

number of units. In our case, we have 16 cohorts and 21 periods. Simulation work on multilevel models

(Yang, 2006; Stegmueller, 2013) confirms that a small number of grouping units lead to significant biases

in both the coefficients and standard errors (and therefore confidence intervals), particularly when using

maximum likelihood methods. Instead, Bayesian estimation procedures tend to be more resistant to these

conditions.

Given these problems we alter the specification suggested by Yang & Land (2008, 2013), and employ

a simpler hierarchical random intercept model where both age and cohorts are included as fixed effects,

while periods are allowed to vary randomly according to a normal distribution. This has the double virtue of

avoiding the independence assumption between age and cohort effects since both components are explicitly

included as regressors, and second, it also avoids the problematic parametric assumption for the cohort

effects insofar we have only 16 cohorts. Moreover, we employ Bayesian MCMC estimation methods in

order to minimize the possible biases suggested by the literature when estimating multilevel models where

the grouping variable has few levels. Therefore, the basic model with age, five-year cohort fixed effects,

13

controls for gender and education, and a random period term is:

log(

πi jk

1−πi jk

)= β0 +β1Agei jk +

J

∑j=1

γ jCohorti jk +β2Sexi jk +β3Educationi jk +µk (1)

where πi jk is Pr(Yi jk = 1), and Yi jk is the dependent variable for individual i from cohort j in period k,

and indicates whether the respondent identifies with a political party or coalition. The β coefficients are

parameters to be estimated for age, gender (indicator variable for males), and education. Similarly, the J γ

coefficients are also parameters to estimated and reflect the difference between the reference cohort category

(respondents born on 1919 or before) and each of the following younger cohorts.16 The period random effect

µk, which captures the correlation between individuals’ responses within periods, is assumed to be normally

distributed (µk ∼ N(0,σ2µ )). In the results section, we complement this model with a second specification

that incorporates a quadratic age term, which we add in order to capture whether each additional year of age

has a decreasing effect.

All statistical models employ a logistic link function and are estimated with Bayesian MCMC methods.

Each model presented below was estimated using three sampling chains that ran for 60,000 iterations with

the first 20,000 dropped as a burn-in period, and were thinned to save every 40th iteration. This procedure

left a total of 3000 samples from the posterior distribution for each parameter of the models from which

we base statistical inference. Convergence diagnostics indicated the chain of all models reached a steady

state.17 For the variance parameter of the random effects we employed the widely accepted inverse-gamma

prior with shape and scale parameters set to 0.001. Regression coefficients, on the other hand, were assigned

a normally distributed prior with mean zero and very large variance (σ2 = 1010).18

Before presenting the results it is worth mentioning a last detail about the coding of birth cohorts. While

analyzing the data we noticed that the APC estimates, particularly those of cohorts, were sensitive to the

cut-off year used to define the oldest 5-year birth cohort, which is employed as the reference category.

Consequently, in order to determine in a non arbitrary way which results to select we estimated for each

dependent variable ten logit models as specified in equation 1, and which varied sequentially the cut-off year

that determined the oldest cohort. The first model defined the oldest cohort as those born in 1917 or before,16As Yang & Land (2013) mention the combination of each cohort in groups of five years is the key element that breaks the exact

collinearity the APC variables, and therefore, allows the model to be identified.17We employ the potential scale reduction factor (PSRF) suggested by Gelman & Rubin (1992), which recovered values close to

1 for all the parameters involved in the models (PSRF ≤ 1.01 for all parameters)18Models were estimated using the R library MCMCglmm (Hadfield et al., 2010).

14

while the next one used those born in 1918 or before, and so on, until the year 1926. We estimated these

ten models using both the linear and quadratic specification of age and through Maximun Likelihood. The

parameter estimates shown in this article correspond to the model with the cohort specification that achieved

the best fit, as measured by the deviance and AIC statistic. This consistently corresponded to the coding

defining the oldest cohort as those born in 1919 or before. Full results and details about these models are

available on the online supplement of this article.

4 Empirical Results

4.1 Descriptive Results

We begin the analysis by presenting standard cohort tables for party and coalition identification in Table 1 and

2, respectively. These tables shows the relationship between age and our measures of partisan identification

using five year intervals for periods and age groups. As a result, five-year birth cohorts are displayed in the

upper left-to-lower right diagonal cells. While the age, period and cohort effects are confounded in these

tables, we present them as a preliminary indication of APC patterns in our data (Glenn, 2005).

Table 1: Party Identification by Age and Period: PercentagesYear

Age 1994 1999 2004 2009 2014 Age totals18-22 82.395 60.852 58.680 52.264 34.425 52.66923-27 77.749 64.816 52.023 56.680 32.739 51.27828-32 71.234 65.299 57.219 44.986 27.291 49.88533-37 69.212 61.436 56.927 43.890 32.769 50.31738-42 75.116 61.102 55.745 42.734 26.904 49.50343-47 74.442 55.719 53.439 46.423 33.679 48.68248-52 68.641 57.665 52.957 46.331 33.089 48.31253-57 66.231 62.046 53.889 48.275 32.185 48.65358-62 64.725 51.387 53.027 46.394 39.746 47.38063-67 70.272 60.739 42.837 44.944 31.248 45.58968-72 83.775 61.661 46.358 43.304 40.126 46.42373-77 71.029 50.534 46.179 37.636 31.320 46.14578 + 73.352 58.481 47.254 35.850 19.155 43.231Years totals 73.786 60.701 53.947 46.633 32.144 49.337

Source: the Center of Public Studies (CEP) surveys for the period 1994-2014.Note: estimations use population weights provided by CEP. N of observations is 59,412.

The bottom row of Table 1 confirm the pronounced decline of party identification between 1994 and

2014: while 74 per cent of Chilean adults identified with a political party in 1994, this percentage fell about

15

10 points during each new period down to 32 per cent in 2014. Table 1 also indicates, particularly during the

last three periods, that party identification seems to decrease among the younger age groups, but the decline

is not clearly linear. Cohort effects can be observed as well. The data show the oldest birth cohorts show the

highest levels of partisanship and then each succeeding cohort displays lower party identification than the

cohorts that precede it.

Table 2: Coalition Identification by Age and Period: PercentagesYear

Age 1994 1999 2004 2009 2014 Age totals18-22 75.922 54.551 62.643 53.667 38.854 54.48723-27 72.787 58.816 54.752 60.420 40.914 54.66928-32 65.911 66.508 57.008 50.422 39.469 53.94533-37 70.954 59.812 61.846 50.471 45.217 54.86338-42 73.969 59.589 59.915 49.368 34.626 53.74743-47 74.450 58.147 57.817 48.672 48.935 52.16448-52 67.877 58.437 55.394 52.232 42.502 52.55753-57 67.753 60.717 58.846 51.447 38.011 53.34258-62 73.226 60.625 53.336 51.475 44.319 52.11263-67 73.819 64.398 48.261 46.545 40.528 50.47668-72 79.502 61.331 55.130 49.117 51.629 51.08273-77 71.029 46.525 53.149 40.378 36.201 49.85478 + 78.746 58.185 50.819 39.961 28.759 46.547Years totals 72.132 59.625 57.529 50.891 41.118 53.177

Source: the Center of Public Studies (CEP) surveys for the period 1994-2014.Note: estimations use population weights provided by CEP. N of observations is 53,558.

We also examined patterns of coalition identification. The findings indicate that APC effects on coalition

identification are very similar to trends of party identification. Of course, these tables only show the pattern

of partisanship for only two of the APC variables, leaving the third uncontrolled. To confront this problem of

confoundedness, we discuss the findings of our Bayesian hierarchical modeling approach in the next section.

4.2 Age, Period, and Cohort Effects on Partisanship

Results for the party and coalition identification random intercept logit models are located on Tables 3 and

4, respectively. The second column of each table contains the estimates of the random effects model with a

linear age specification, while the third column shows the results from the model that incorporates a quadratic

age term.

The statistical models predicting partisan identification show significant effects for age and cohorts in

both specifications. But much more unexpectedly, we find that the coefficient of age has a negative sign.

16

Indeed, Model 1 from Table 3 indicates a linear negative relationship whereby a 10 year increase in age

leads, on average, to a 19% reduction (e−0.245 = 0.81) in the odds of mentioning to identify with a political

party. Model 2 indicates that the negative effect of age tends to become smaller as respondents become

older given the positive (and significant) coefficient of the quadratic term. In terms of fit, the DIC statistics

indicates that the incorporation of the squared age term is warranted when we predict party identification.

When we consider the age effects over coalition identification (see Table 4) we find similar patterns. The

effect of age is again negative and statistically significant, but in this case the incorporation of the quadratic

term is not supported by the DIC statistic. In terms of odds ratio, Model 3 indicates that a 10 year increase

in age leads, on average, to a 15% reduction (e−0.164 = 0.85) in the odds of mentioning to identify with a

political party.

Respect to the cohort effects, Table 3 and 4 show multiple significant and negative results, though the

estimates for coalition identification tend to be a bit more weaker. According to the best fitting model

for partisanship (model 2), the odds of identifying with a party among those most recently born are, on

average, 74% lower (e−1.358 = 0.26) than of the oldest cohort group. The best fitting estimates of coalition

identification, model 3 from Table 2, indicates that the odds of identifying with a political coalition are 65%

lower (e−1.039 = 0.35) for a member of the youngest cohort compared to members of the oldest cohort. If

one inspects how the size of the cohorts vary it is clear their their effects are very close to linearity.

Period effects are synthesized in the tables as the standard deviation of the random effects (σµ ). Con-

sidering the best fitting models, these are equal to 0.431 for party identification, and 0.336 for coalition

identification. This level of variation indicates strong period effects, however, it’s not easy to convey their

magnitude by considering the dispersion parameter alone. A more intuitive sense of the results can be ob-

tained by considering the predicted probabilities of both forms of partisan attachment for each source of

social change. Figures 1, 2, and 3 plot these predicted probabilities for period, cohort and age, respectively,

using the observed values approach (Hanmer & Ozan Kalkan, 2013).19 The left panels of each figure shows

19This approach implies calculating the predicted probabilities by fixing the value of one of the APC variables for all obser-vations, while holding the rest of the variables at their observed values, and then calculating the sample mean. In formal termsthis corresponds to: N−1

∑Ni=1 Λ(xT

i jkβ + µk) where Λ(·) = exp(·)/(1+ exp(·)), µk is the estimated period random effect in whichrespondent i was interviewed, β is the vector of fixed effects estimates, and xT

i jk is the vector with covariate values from individual iwith either age or cohort variables set to a single numeric value, while the rest (including gender and education) are held at their ob-served sample values. Alternatively, when calculating the predicted values for different periods, we set both age and cohort to theirobserved values, choose a single period (year), and then calculate the sample mean. In order to calculate the confidence bands foreach predicted probability, we exploit the fact that when using MCMC methods one obtains many random draws from the posteriordistribution of the coefficients and random effects. Therefore, we calculate the predicted values for each APC variable for each ofthe 3000 random draws, after which we calculate the mean, 2.5th and 97.5th percentiles. These correspond to the point estimatesand intervals reported in the Figures. An important advantage of this method, compared to the more common strategy of calculating

17

Table 3: Hierarchical APC Models for Party Identification: Logit Coefficients

Model 1 Model 2Coeff. S.E. Coeff. S.E.

Intercept 0.938 (0.309)∗∗∗ 0.760 (0.318)∗∗

Age (scaled) −0.210 (0.064)∗∗∗ −0.213 (0.064)∗∗∗

Age2 (scaled) 0.014 (0.006)∗∗

Cohort 1920-1924 −0.111 (0.136) −0.080 (0.139)Cohort 1925-1929 −0.086 (0.139) −0.036 (0.141)Cohort 1930-1934 −0.275 (0.151)∗ −0.199 (0.158)Cohort 1935-1939 −0.328 (0.174)∗ −0.223 (0.183)Cohort 1940-1944 −0.430 (0.198)∗∗ −0.298 (0.207)Cohort 1945-1949 −0.474 (0.224)∗∗ −0.323 (0.236)Cohort 1950-1954 −0.587 (0.252)∗∗ −0.424 (0.264)Cohort 1955-1959 −0.790 (0.280)∗∗∗ −0.621 (0.293)∗∗

Cohort 1960-1964 −0.902 (0.310)∗∗∗ −0.735 (0.321)∗∗

Cohort 1965-1969 −0.975 (0.340)∗∗∗ −0.815 (0.350)∗∗

Cohort 1970-1974 −1.068 (0.370)∗∗∗ −0.921 (0.377)∗∗

Cohort 1975-1979 −1.212 (0.401)∗∗∗ −1.087 (0.407)∗∗∗

Cohort 1980-1984 −1.306 (0.433)∗∗∗ −1.197 (0.436)∗∗∗

Cohort 1985-1989 −1.315 (0.463)∗∗∗ −1.216 (0.467)∗∗∗

Cohort 1990 or after −1.440 (0.497)∗∗∗ −1.358 (0.498)∗∗∗

Education 0.090 (0.005)∗∗∗ 0.090 (0.006)∗∗∗

Female −0.230 (0.018)∗∗∗ −0.231 (0.018)∗∗∗

Period σµ 0.431 0.431DIC 78291.582 78282.091N obs 59083 59083N periods 21 21∗∗∗p < 0.01, ∗∗p < 0.05, ∗p < 0.1

Source: Center of Public Studies (CEP) surveys, 1994-2014.Note: Coefficients are posterior means from posterior distribution of parameters. Standard errorscorrespond to standard deviation of posterior distributions.

the results for party identification, and the right panels show the predicted values for coalition identification.

Predicted probabilities were based on the best fitting model for each dependent variable.

Figure 1 confirms the presence of very strong period effects for both party and coalition identification.

We observe a dramatic decrease of approximately 0.37 points of probability between 1994 and 2014 for

the former, and of 0.29 percentage points for the later. However, these trends are not monotonic over time.

Instead, they indicate that the decline of both type of attachments follow clear cyclical fluctuations that are

predicted probabilities fixing the independent variables and random effects at average values, is that our confidence intervals includeuncertainty due to variation in the estimation of both the independent variables and the period random effects.

18

Table 4: Hierarchical APC Models for Coalition Identification: Logit Coefficients

Model 3 Model 4Coeff. S.E. Coeff. S.E.

Intercept 0.798 (0.307)∗∗∗ 0.796 (0.316)∗∗

Age (scaled) −0.164 (0.064)∗∗ −0.163 (0.064)∗∗

Age2 (scaled) −0.000 (0.006)Cohort 1920-1924 0.042 (0.143) 0.041 (0.144)Cohort 1925-1929 0.053 (0.143) 0.054 (0.147)Cohort 1930-1934 −0.060 (0.159) −0.058 (0.164)Cohort 1935-1939 −0.109 (0.180) −0.110 (0.188)Cohort 1940-1944 −0.181 (0.205) −0.182 (0.212)Cohort 1945-1949 −0.223 (0.230) −0.222 (0.242)Cohort 1950-1954 −0.321 (0.257) −0.322 (0.269)Cohort 1955-1959 −0.433 (0.286) −0.431 (0.297)Cohort 1960-1964 −0.589 (0.316)∗ −0.590 (0.326)∗

Cohort 1965-1969 −0.620 (0.346)∗ −0.620 (0.354)∗

Cohort 1970-1974 −0.693 (0.377)∗ −0.692 (0.384)∗

Cohort 1975-1979 −0.822 (0.406)∗∗ −0.821 (0.413)∗∗

Cohort 1980-1984 −0.911 (0.438)∗∗ −0.909 (0.442)∗∗

Cohort 1985-1989 −0.901 (0.469)∗ −0.898 (0.473)∗

Cohort 1990 or after −1.039 (0.501)∗∗ −1.038 (0.505)∗∗

Education 0.093 (0.006)∗∗∗ 0.093 (0.006)∗∗∗

Female −0.270 (0.019)∗∗∗ −0.270 (0.018)∗∗∗

Period σµ 0.338 0.336DIC 71369.473 71369.929N obs 53264 53264N periods 19 19∗∗∗p < 0.01, ∗∗p < 0.05, ∗p < 0.1

Source: Center of Public Studies (CEP) surveys, 1994-2014.Note: Coefficients are posterior means from posterior distribution of parameters. Standard errorscorrespond to standard deviation of posterior distributions.

related with presidential election cycles.20 This is particularly evident when we observe the increase of party

and coalition identification for the presidential election of 2005 and 2009. This result indicates perhaps that

there are differences in the trends associated with period in the short and long term. Electoral cycles may

have a positive influence on partisan identification in the short run but this attitude is decreasing over the

long run.

20Presidential Election were held in December of 1993, 1999, 2005, 2009 and November of 2013.

19

Party Identification

Period (Year of Survey)

Pro

babi

lity

of id

entif

icat

ion

with

a p

arty

0.2

0.3

0.4

0.5

0.6

0.7

1995 2000 2005 2010

●

●

●

●

●

●

●

●

● ●

●

●

●

●●

●

●●

●

●

●

Coalition Identification

Period (Year of Survey)

Pro

babi

lity

of id

entif

icat

ion

with

a p

arty

0.2

0.3

0.4

0.5

0.6

0.7

1995 2000 2005 2010

●

●

●

●

●

●

●

● ●

●

●

●

●

●

●

●

●●

●

Source: Center of Public Studies (CEP) surveys, 1994-2014.Note: Predicted probabilities of party and coalition identification are calculated from model 2 and 3, respectively.

Figure 1: Predicted Values of Partisan Identification by Period

The predicted probabilities according to birth cohorts are shown on Figure 2. In this case we see almost

entirely linear reductions in levels of political identification as we move from older to younger cohorts. While

the average predicted probability of identifying with a party for someone born on 1919 or before, holding

all else at their observed values, is 0.64, this propensity drops linearly to 0.35 among those born on 1990

or after. The respective numbers are for coalition identification are 0.66 and 0.40. The difference between

the oldest and youngest cohort is statistically significant at a 95% level of confidence for party identification

(given that the intervals do not overlap), while for coalition identification it is only marginally significant.

Taken together, these results suggest pronounced declines for both forms of partisan identification, though the

erosion is slightly stronger for parties than for coalition identification. The linearity of the trends seem, at first

glance, consistent with argument that there should be generational differences in the levels of partisanship

depending on whether individuals were old enough to participate in the 1988 plebiscite. Figure 2 shows

clearly that those born before 1970 have higher levels of partisan and coalition identification than those

born after. Yet, the level of partisan identification keeps rising among older cohorts and declining among

younger ones. We interpret this as indicating that changes in mass partisanship are subject to long run forces

associated with individuals’ political socialization experiences, and which endure during the entire lifespan.

20

Party Identification

Birth Cohort

Pro

babi

lity

of id

entif

icat

ion

with

a p

arty

0.2

0.3

0.4

0.5

0.6

0.7

Before 1919

1920−24

1925−29

1930−34

1935−39

1940−44

1945−49

1950−54

1955−59

1960−64

1965−69

1970−74

1975−79

1980−84

1985−89

After 1

990

●●

●

● ●● ●

●

●

●●

●

●● ●

●

Coalition Identification

Birth Cohort

Pro

babi

lity

of id

entif

icat

ion

with

a p

arty

0.2

0.3

0.4

0.5

0.6

0.7

Before 1919

1920−24

1925−29

1930−34

1935−39

1940−44

1945−49

1950−54

1955−59

1960−64

1965−69

1970−74

1975−79

1980−84

1985−89

After 1

990

●● ●

●●

● ●●

●

● ●●

●● ●

●

Source: Center of Public Studies (CEP) surveys, 1994-2014.Note: Predicted probabilities of party and coalition identification are calculated from model 2 and 3, respectively.

Figure 2: Predicted Values of Partisan Identification by Birth Cohort

Lastly, Figure 3 shows how the probability of identifying with a political party or coalition decreases

drastically as individuals become older. The difference, on average, in levels of identification between re-

spondents 85 and 18 years old corresponds to 0.32 and 0.29 points on the probability scale for party and

coalition identification, respectively. These differences are not only statistically significant at conventional

levels (notice how the confidence intervals do not overlap when we compare the point estimates for each age

group), but are substantially very intriguing. Indeed, and in open contradiction with the expectations we set

following Converse’s (1969) habituation hypothesis, this pattern indicates that the accumulation of political

experience contributes to increasing levels of political detachment in Chile. In short, party and coalition

supporters abandon their party or coalition at higher rates the more time they have been exposed their party

or coalition. We discuss this result in more detail in the following section.

21

Party Identification

Age

Pro

babi

lity

of id

entif

icat

ion

with

a p

arty

0.2

0.3

0.4

0.5

0.6

0.7

20 40 60 80

Coalition Identification

Age

Pro

babi

lity

of id

entif

icat

ion

with

a c

oalit

ion

0.2

0.3

0.4

0.5

0.6

0.7

20 40 60 80

Source: Center of Public Studies (CEP) surveys, 1994-2014.Note: Predicted probabilities of party and coalition identification are calculated from model 2 and 3, respectively.

Figure 3: Predicted Values of Partisan Identification by Age

5 Conclusions and Discussion

In this paper we develop an age-period-cohort analysis of partisan identification in order to better understand

the decline of this form of social attachment among Chilean contemporary population. We find that all three

sources of social change have had negative impact. More specifically, we find a negative and non monotonic

influence of periods over mass partisanship, which we interpret as indicating different roles of short and long

term effects over political identifications. In the short term, we observe that party and coalition identification

are responsive to electoral cycles, which implies that elections tend to produce a boom-and-bust pattern.

However, there is also a clear decline of political attachments over the long run.

In second place, aging effects also appears to have important a negative effect. Contrary to social learn-

ing models of partisanship (Converse, 1969) or rational choice approaches (Achen, 1992) that claim that

citizens’ attachment towards parties increase as they age, in Chile we find that as people accumulate elec-

toral experience they tend to identify less with parties and coalitions. And lastly, we also found strong and

negative cohort effects, which indicate that more recently borne citizens are systematically less propense

during their entire lifespan to develop a favorable attachment towards political parties. Hence, our main

conclusion is that during the last twenty years all three sources of social change have consistently pointed in

22

the direction of extinguishing mass level partisanship from Chilean society.

What explains these trends? While a definitive demonstration of the key casual factors is beyond the

scope of this article, we consider our empirical results in light of the main theoretical approaches about par-

tisan decline that we discussed above. In first place, our empirical estimates seem at odds with the cognitive

mobilization hypothesis. Indeed, and similarly to findings from Albright (2009), we find that increasing

levels of education lead to higher levels of partisanship, and not lower such as proposed by some influential

scholars (Inglehart, 1990; Dalton et al., 2000). Strictly speaking the cognitive mobilization hypothesis is a

macro level claim about decreasing partisanship levels of as societies become wealthier, but to the extent that

the individual level association between partisanship and education is strongly positive, one would expect

that as aggregate education rates become higher there would be more partisans among the adult population,

not less. Therefore, we believe the the key explanatory factor does not relate to socioeconomic moderniza-

tion. Instead, we believe political factors might be more relevant.

One possibility, which we also discussed in section 2.2, relates to the increasing degree of ideological

convergence of the Chilean party system , which may have led its’ citizens to perceive less differences be-

tween the parties, and consequently, become less attached to them. This point seems consistent with the

cyclical pattern of the periods effects, given that the bumps in partisan identification coincide with general

elections, a time were political rhetoric, presumably, polarizes. However, the observed decline of ideological

polarization of the Chilean party system, to the extent to which it has been recorded, has not been as nearly as

dramatic as the partisan decline. According to the analysis of party manifestos of Gamboa et al. (2013), ide-

ological convergence has increased somewhat, but parties continue to differentiate themselves clearly along

ideological lines in Chile (?, Chapter 2)[for a similar position see]kitschelt.etal:2010. Therefore, to attribute

the decline of partisan attachments to increasing levels of ideological convergence would require assuming

that the public is extremely sensitive to how ideologically differentiated are political discourses. This point

seems a bit odd, and has not ever been mentioned before by the specialized literature. Therefore, while it

is likely that increasing levels of ideological convergence have promoted lower levels of mass partisanship,

there must be another element playing a more dominant role.

We believe that the key factor has been the cumulative influence of a relatively unresponsive party sys-

tem. Indeed, to the extent that political parties have failed to incorporate new leaderships, be more sensitive

to grass root activists, or more generally, to prove themselves open and sympathetic to citizens’ demands, the

long term negative period effects, the lower rates of partisan attachment among younger cohorts, and perhaps

23

most importantly, the negative effect of aging seem a likely outcome. The, at least partially, “partyarchic”

character of Chilean political parties have saturated the electorate to the point where those with more expo-

sure to them become more alienated from them. Therefore, we conclude that the organizational configuration

of Chilean parties, coupled with certain institutional features that discourages political competition, has seem

to have favored the consolidation of increasingly unaccountable party system that hampers the development

of long term partisan orientations. This statement is, of course, more a hypothesis that should be studied in

future investigation that a formal conclusion which we have proved.

Lastly, it is important to mention that the negative age effect, regardless of the possible underlying

causal mechanism, should be considered very carefully. While it openly contradicts Converse’s hypothesis

in the context of a stable and aging party system, it also confirms his general claim that the association

between aging and partisanship depends critically on the configuration of the party system. So far it has

been assumed that as long as the party system is stable and long-lived a positive association will emerge.

However, in light of our results these condition might be necessary, but not sufficient to secure high levels of

mass partisanship. To the extent that the decline of partisan identification is related to a more general process

of political disaffection, sustained o increasing levels of partisanship must be coupled by political parties that

enjoy broad favorable social reputation.

24

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