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Legitimation, cooptation, and repression and the survival of electoral autocracies

Legitimation, Kooptation und Repression und das Überleben von elektoralen Autokratien

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Abstract

Conceptualizing the “three pillars of stability”, Gerschewski (2013) proposes legitimation, cooptation and repression as the fundamental principles of lasting autocratic rule. Recent studies put this so-called WZB model to an empirical test and probe the effects these three factors have on regime survival in light of autocratic elections (Lueders and Croissant 2014). Their finding that the WZB model has only limited explanatory power in competitive autocracies has sparked a broader debate about the empirical application of the model as such (Kailitz and Tanneberg 2015; Lueders and Croissant 2015). Our paper contributes to this debate in several ways: (1) rather than analyzing each pillar’s effect in isolation, we investigate their combined effect; (2) rather than assuming causal symmetry, we expect to find different explanations for autocratic stability and breakdown, respectively; (3) by focusing on configurations of the pillars, we are in the position to identify distinct types – or “worlds” (Gerschewski 2013) – of (un)stable autocracies. Using the data from Lueders and Croissant (2014) on elections in hegemonic and competitive authoritarian regimes between 1990 and 2009, we apply fuzzy-set Qualitative Comparative Analysis to empirically investigate which, if any, combination of the dimensions of legitimation, cooptation, and repression lead to the survival of autocratic regimes and which ones to their breakdown. Our findings suggest that single pillars in isolation are causally irrelevant; that the WZB model is, indeed, capable of identifying stable autocracy types but it does not perform well in identifying the reasons why autocracies break down; and that the two viable types of autocracies identified by us are meaningfully distinguished by their different legitimation strategies.

Zusammenfassung

Das Modell der „drei Säulen der Stabilität” (Gerschewski 2013) geht von Legitimation, Kooptation und Repression als den grundlegenden Prinzipien andauernder autokratischer Herrschaft aus. Jüngste Studien testen das sogenannte WZB-Modell empirisch und untersuchen die Effekte, welche die drei Faktoren auf das Überleben von Regimen im Kontext von autokratischen Wahlen haben (Lueders and Croissant 2014). Der Befund, dass das WZB-Modell nur eingeschränkte Erklärungskraft in kompetitiven Autokratien hat, löste eine breitere Debatte über die empirische Anwendung des Modells aus (Kailitz and Tanneberg 2015; Lueders and Croissant 2015). Unser Artikel trägt zu dieser Debatte in mehrerer Hinsicht bei: (1) Anstatt lediglich den Effekt einer jeden Säule isoliert zu betrachten, untersuchen wir das Wechselspiel der Säulen. (2) An Stelle von kausaler Symmetrie gehen wir von unterschiedlichen Erklärungen für autokratische Stabilität und Instabilität aus. (3) Durch den Fokus auf die unterschiedlichen Konfigurationen der Säulen sind wir in der Lage, verschiedene Typen – oder „Welten” (Gerschewski 2013) – von (in)stabilen Autokratien zu bestimmen. Mit den Daten von Lueders and Croissant (2014) zu Wahlen in hegemonialen und kompetitiven autoritären Regimen zwischen 1990 und 2009 führen wir eine fuzzy-set Qualitative Comparative Analysis durch, um empirisch zu untersuchen, welche Kombinationen der Dimensionen von Legitimation, Kooptation und Repression zum Überleben und welche zum Zusammenbruch von autoritären Regimen führen. Unsere Ergebnisse zeigen auf, dass einzelne Säulen allein keine kausale Relevanz haben, dass das WZB-Modell aber durchaus in der Lage ist, stablie Autokratie-Typen zu bestimmen wenn man denn die Kombination der verschiedenen Säulen untersucht. Um die Gründe für den Zusammenbruch von Autokratien auszumachen eignet sich das Modell nicht. Die zwei aus der Analyse resultierenden überlebensfähigen Typen von Autokratien unterscheiden sich wesentlich durch ihre verschiedenen Legitimations-Strategien.

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Notes

  1. We use the terms autocracy and authoritarian regime interchangeably.

  2. INUS stands for a condition that itself is not sufficient while being a necessary parts of a combination of conditions that is unnecessary but sufficient for the outcome (Mackie 1965).

  3. Highly unequally distributed sets such as the skewed outcome in Lueders and Croissant’s (2014) data, create analytic problems not only in logistic regression, but also in set-theoretic methods (Schneider and Wagemann 2012, Chap. 9.2). We take those challenges head on and employ recently developed parameters that are adequate for distinguishing meaningful set relations from those that are mere artifacts of the skewed data. For the analysis of necessity, this means that we test whether a superset of the outcome is empirically trivial because it is so much bigger than the outcome set and/or its own negated set. For the analysis of sufficiency, we test whether a given subset of the outcome is empirically trivial because it is so small that it is also a subset of the negation of the outcome (Ragin 2008; Schneider and Wagemann 2012).

  4. The Appendix is available at Schneider’s Dataverse (https://dataverse.harvard.edu/dataverse.xhtml?alias=cqs).

  5. Future research might use a more fine-grained distinction and use fuzzy sets and incorporate information on how close (non-)defeat was.

  6. See the Appendix of Lueders and Croissant (2014) for detailed information about their indicators.

  7. For a current overview on the debate about measuring legitimacy, see von Haldenwang (2016). Gerschewski (2013) and also Roller (2013) generally discuss availability and reliability problems of data in authoritarian settings.

  8. We are aware of the potential pitfalls of these legitimation indicators, however, use them as well since our goal is not to innovate indicators but rather to test the WZB model from a set-theoretic perspective by using the same data and operationalization as Lueders and Croissant (2014).

  9. As already observed by Kailitz and Tanneberg (2015), this operationalization is highly problematic when referring to the category of electoral regimes since it is merely an artifact of the applied definition for this type of autocracy. We discuss the implications of this operationalization for our findings in Sect. 4.2.

  10. The Appendix includes histograms of each base variable and calibrated fuzzy set. It also contains scatter plots of each fuzzy set plotted against its base variable. For further information about the raw data, see Lueders and Croissant (2014, 341).

  11. We also do not identify any meaningful disjunction as a superset of the outcome.

  12. We consider rows with two or more cases as having enough empirical evidence (n.cut \(\geq 2\)). For larger N QCA, it is common practice to raise the frequency cutoff in order to take the increased chance of misclassified cases into account. It is also important to point out that for the outcome electoral defeat results remain unchanged even with n.cut \(=\) 1. In short, our finding that the WZB model is not good at explaining electoral defeat of autocrats is not an artifact of our choice of frequency thresholds.

  13. Since no assumption on any of the logical remainder passes as an easy counterfactual, the intermediate solution is identical to the conservative solution. For the parsimonious solution formula, see the Appendix.

  14. Out of the 126 cases of elections with outcome no electoral defeat, only seven are inconsistent in kind and another seven inconsistent in degree (Schneider and Rohlfing 2013; Rohlfing and Schneider 2013).

  15. Notice that condition diff_leg also passes the consistency threshold but not that of RoN. Likewise, none of the disjunctions between single conditions passes the empirical criteria for being non-trivially necessary.

  16. Our results of outcome no electoral defeat are robust against the alternative frequency threshold of 1 (see Appendix). The reason for this is straightforward: by raising n.cut from \(\geq\)1 to \(\geq\)2, only one truth table row is turned into a logical remainder row (row 48, cf. Table 7 in the Appendix).

  17. The R script includes robustness tests using higher and lower consistency thresholds.

  18. Since no assumption on any of the logical remainder passes as an easy counterfactual, the intermediate solution is identical to the conservative solution.

  19. These are cases that are members of the adaptive but not the rigid authoritarian type (see below).

  20. Some cases contradict our claim that adaptive authoritarian regimes are resilient. They are listed as deviant consistency cases in Table 7. Notice, though, that autocratic defeat in elections does not necessarily mean democratization. In Iran, for instance, the autocratic electoral defeats in 1997, 1998 and 2004 refer to the beginning and end of the reformist but nevertheless authoritarian Khatami regime.

  21. Botswana is even categorized as democracy in the dataset of Wahman et al. (2013).

  22. The logic of this graph is adopted from Goertz and Mahoney (2005), see also Mello (2012).

  23. Table 10 in the Appendix specifies the Boolean expression for each of the four areas.

  24. See Table 11 in the Appendix for the names of the cases.

  25. See the R script for the use of the theory evaluation functions from the SetMethods package (Medzihorsky et al. 2016).

  26. Puzzling cases and in need for closer within-case scrutiny are the non-stable autocracies in area TE and the stable autocracies in \(\sim\)T\(\sim\)E, for they contradict both Gerschewski’s and our model. See the Appendix for further insights to be gained from the theory evaluation.

  27. Such more in-depth investigations are particularly needed in adaptive autocracies because this type of authoritarianism seems to be on the rise.

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Acknowledgements

We thank Aurel Croissant and Hans Lueders for sharing their data and Bruno de Paula Castanho e Silva for his help in preparing the data.

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  1. Central European University, Nador utca 9, 1051, Budapest, Hungary

    Carsten Q. Schneider & Seraphine F. Maerz

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  1. Carsten Q. Schneider
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Correspondence to Carsten Q. Schneider.

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Schneider, C.Q., Maerz, S.F. Legitimation, cooptation, and repression and the survival of electoral autocracies. Z Vgl Polit Wiss 11, 213–235 (2017). https://doi.org/10.1007/s12286-017-0332-2

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