assessing party membership figures: the mapp dataset
Assessments of party decline and decline of traditional forms of political participation often rely on the argument of party membership decline. Most studies analysing trends in party membership over time focus on aggregate country-level data at a few points in time. While they allow grasping general membership trends, they are not without shortcomings. This article presents the Members and Activists of Political Parties (MAPP) dataset related to the MAPP project. The dataset makes a large amount of data on party membership available to the larger public. The dataset provides 6,307 party membership data observations (M) covering 397 parties in 31 countries, mostly between 1945 and 2014. The article discusses the existing literature and data on party membership trends, how membership trends have been assessed so far, and the potential added value of the MAPP dataset.
Keywordspolitical parties party membership party organisations
Three articles have fundamentally contributed to the development of party (membership) research: the article by Katz et al in the European Journal of Political Research (1992), the update by Mair and van Biezen in Party Politics (2001), and the second update by van Biezen et al in the European Journal of Political Research (2012). What these articles have in common is that they provide a comparative longitudinal assessment of party membership figures using a collective dataset that has been updated over time. These articles were groundbreaking in the sense that, before their publication, early research on party membership (figures) consisted of case studies of single countries or parties with few systematic cross-national comparisons (with partial exceptions, such as Bartolini, 1983; von Beyme, 1985; Sundberg, 1987). Relying on ‘objective’ membership figures provided by political parties (Mair and van Biezen, 2001; van Haute and Gauja, 2015a, b), their conclusion point toward a deepening decline of party membership over time, to the point that it now concerns almost all democracies.
The first stream of research (Figure 1, top right) looks at party members and activists as a free resource for parties in electoral campaigns (see for example Fisher et al, 2006). The second stream of research (Figure 1, left) looks at party membership as one of the three faces of party organisations, the party on the ground (see for example Katz and Mair, 1995). The third stream of research (Figure 1 bottom right) investigates party membership as one form of political participation and looks at who joins and why (see for example Whiteley et al, 1994; Seyd and Whiteley, 2004). These three fields are relatively independent of each other (few co-citations), but they share a common reference to our three groundbreaking articles, which is illustrated by their centrality in Figure 1.
The conclusions of these groundbreaking articles have also become central in the literature. They have served as the foundation of party (membership) research. Party membership decline has become a straightforward indicator of declining organisational health of parties (Dalton and Wattenberg, 2000; Dalton et al, 2011). Today, it is often mobilised as the opening statement in many researches, and is rarely challenged (with some exceptions, see Delwit, 2011; Kölln, 2015).
PRESENTATION OF THE MAPP DATASET
One of the main objectives of the MAPP project was to conduct the largest data collection so far on party membership figures. In order to do so, it directly relies on the past efforts of scholars involved in the data collection for the three founding articles and tries to extend and complement it. Consequently, it relies on a convenience sample of thirty-one countries2 for which country expert(s) could be identified and have agreed to contribute to this collective effort. (A full list of the country experts involved in the data collection is available in Electronic Supplementary Material).
The dataset is available on the project’s website www.projectmapp.eu, either in the form of individual country datasets, or as an integrated comparative dataset.
For each unit of observation (M), country experts also provided information about the country (country name in English, country ISO codes) and the party (party acronym, full name in original language, full name in English, year of foundation, year of origin for parties with earlier roots, year of disappearance, and party family).3 The MAPP project team added three party ID variables, one that is specific to the MAPP project and, when available, the party ID used in the Political Party Database project (PPDB, http://www.politicalpartydb.org), and the Parliament and government composition project (ParlGov, www.parlgov.org) in order to facilitate the merge of the MAPP dataset with other large-scale comparative projects in the field of comparative politics.
The dataset also provides information regarding the source of the collected data. As mentioned in the introduction, the aim was to collect ‘objective’ party membership figures either directly provided by political parties themselves, or reported by institutions (in countries where parties are required to disclose their membership data), by the media, or in other academic publications. We are aware of the shortcomings of objective membership figures and the variance in the quality of the sources. As pointed by van Haute and Gauja (2015a, b), the quality of the data varies across countries, parties, and time. Quality improves when state institutions require parties to publicly disclose their membership figures. Quality also varies depending on the organisational capacity of the parties, as well as institutional or legitimacy factors that can push parties to inflate their membership numbers or make them reluctant to disclose them at all. Nevertheless, some of these hurdles are progressively removed. With the development of new communication technologies, parties have better tools today to maintain their membership databases. In parallel, growing party distrust may have affected the symbolic value of party membership and created incentives for parties to become more transparent and open to academic research, and more ready to disclose their membership figures. Furthermore, some of these measurement problems are relatively minor when looking at long-term trends (Scarrow, 2000). While some problems and difficulties remain, ‘there is little the analyst of party membership can do about this’ (Mair and van Biezen, 2001: 8). Besides, the only available alternative, the subjective measure based on individuals reporting their party membership in population surveys, is not without its own shortcomings (van Haute and Gauja, 2015a, b). Therefore, we believe that the dataset provides a unique, solid contribution to our empirical knowledge of party membership.
MAIN CONTRIBUTION AND OPPORTUNITIES OF THE MAPP DATASET
Compared to the existing data analyses on party membership, the MAPP dataset presents two main advantages. It contains more time points, and more parties. Combined, these two advantages make the MAPP dataset the largest available dataset in terms of data points (M) on party membership figures. In this section, we stress the empirical contribution of the MAPP project, and we sketch the opportunities and new avenues for research that the MAPP dataset opens.
The MAPP dataset offers more time points and covers more parties than the existing studies, which ultimately provides many more observations (M). As a matter of comparison, at the party level, Katz et al (1992) relied on around 510 observations of M/E ratios, Mair and van Biezen (2001) relied on 352 observations (M)4, and van Biezen et al (2012) added 307 new observations (M). Compiling the data from the appendix of the three articles together would allow to work on a time-series cross-sectional database of a little more than 1,000 observations, whereas the MAPP dataset relies on a total of 6,307 observations.
With fewer observations, prior studies had more limited options for their data analysis. They mostly discuss national aggregate membership data over all (available) parties as a proportion of the electorate (aggregate M/E per country) to run longitudinal cross-national comparisons (Katz et al, 1992; Mair and van Biezen, 2001; van Biezen et al, 2012). This leaves only two or three time points per decade per country. Even then, they had to use proxies for missing observations. Missing data have been estimated using either membership data for up to two years prior or after the time point as proxies, assuming temporal equivalence, or by computing averages from prior and post observations (the choice between the two strategies being not always clear).
The MAPP data confirm the downward trend between mid-1960 and 2010 at the aggregate level. However, the MAPP data show more fluctuation along the regression line. When expanding the data coverage from 1945 until 2010, as the MAPP data allow, the trend appears more curvilinear than linear, which confirms how crucial the starting point of the longitudinal study is (Norris, 2002; Scarrow, 2000). Besides, much of the trend was driven by the drop in membership of one single party, the Centre Party (KESK), which in the twenty-first century returned to its early 1950s membership levels after reporting historically high membership levels between the end of the 1960s and the end of the 1980s.
Being able to disaggregate trends by parties is crucial as it allows testing for more solid explanatory models of party membership trends. Given the data limitations, most previous studies focused on aggregate country-level membership trends and have investigated the effect of macro-level explanatory variables. More specifically, two approaches have dominated in the literature. The first one -modernisation theories- is rooted in the supply side (Scarrow, 1996) and looks at broad societal changes linked to post-industralisation, which would have shifted participation repertoires to more individual modes of political action (Norris, 2002; Marien and Quintelier, 2011). The second one –the institutional approach– investigates the impact of the type of political regime (Bartolini, 1983; Tan, 2000), the size of the polity (Weldon, 2006), the electoral system (Norris, 2002), or party laws (Pedersen, 2003; Scarrow, 1996). If these models are fit to explain aggregate country-level longitudinal trends, they fail to explain why in certain polities, some parties experience party membership gains while other experience membership losses, as it is the case in Norway in recent years (Figure 4).
The MAPP dataset is the first large-scale database that allows testing for other, party-related factors.5 Our intention here is not to test these alternative explanations, but rather to propose a research agenda for the field. The pairing up of party ID used in other large-scale comparative datasets offers unprecedented opportunities.
Finally, intra-party life and dynamics are expected to affect party membership ratios. Many single case studies have documented how internal dissatisfaction or intra-party conflicts may lead to collective exit (for a general discussion on the application of the exit-voice-loyalty model to party membership, see van Haute, 2015). Another avenue for research could therefore be linking factionalism, as expressed in the parliamentary party group or during leadership or candidate selection contests, and party membership figures.
The examples illustrate how the MAPP dataset offers unprecedented opportunities to test new, alternative explanations of party membership fluctuations beyond the general decline thesis.
Further details on the MAPP dataset and access to the dataset are available in the MAPP project website: www.projectmapp.eu.
The countries are: Australia, Austria, Belgium, Brazil, Canada, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Italy, Lithuania, Mexico, the Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom.
The ‘party family’ variable was coded by country experts, using the same coding scheme as the Making Electoral Democracy Work project (MEDW) that distinguishes between nine categories: (Former) Communist, Christian Democratic/Religious, Conservative, Ecology, Ethnic and Regional, Liberal, National, Social Democratic, and Special Issue.
In 20 per cent of the cases, the total membership levels stated in the 2001 article were collected for the same years as the M/E ratio computed in the annexes from the 1992 article.
Kölln (2015) is the first attempt to test these on a sub-set of six countries.
We would like to thank all country experts who contributed to the data collection: Baras Montserrat, Barberà Oscar, Barrio Astrid, Bennie Lynn, Bolin Niklas, Christophorou Christophoros, Correa Patricia, Cross William, Delwit Pascal, Ennser-Jedenastik Laurenz, Enyedi Zsolt, Espirito Santo Paula, Gauja Anika, Heidar Knut, Holsteyn Joop van, Ikstens Jānis, Indridason Indridi, Ionascu Alexandra, Jastramskis Mažvydas, Jupskås Anders Ravik, Kenig Ofer, Kocijan Bojana, Koole Ruud, Kosiara-Pedersen Karina, Krasovec Alenka, Ladner Andreas, Linek Lukas, Paczesniak Anna, Pettai Vello, Rahat Gideon, Ribeiro Pedro Floriano, Ridder Josje den, Rodriguez Teruel Juan, Sandri Giulia, Soare Sorina, Spier Tim, Voerman Gerrit, Weeks Liam, Westinen Jussi, Zemanik Michal. The MAPP project is supported by the Belgian Fonds National de la Recherche Scientifique (FRS-FNRS) via a MIS grant (Mandat d’Impulsion Scientifique – Incentive Grant for Scientific Research).
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