Exploring the stability term – conceptualisation and measurement

The Energy-Stability-Area (ESA) model of organisational density and diversity (Gray and Lowery 1996; Lowery and Gray 1995) since its inception has become the main population ecology model explaining the size of interest group populations. While the conceptualisation and measurement of the energy and area terms have become ever more sophisticated, the stability term is mostly left out altogether. Following Olson (1982), the stability term was conceptualised by Gray and Lowery (1996) as a profound change to the polity such as a political regime change, foreign occupation, and secession from or integration into a new state. Olson (1982) assumed that after such major disruptions to the political system, interest group formation begins anew and continues exponentially until another major disruption. The population ecology models of the vital rates of interest groups (Lowery and Gray 1996, Hannan and Carrol 1992) refuted the assumption of exponential growth in organisational densities. Nevertheless, Olson’s assumption of disruption and growth after a profound polity level change were never tested. Gray and Lowery (1996) conceptualised the stability term as the age of the interest group system, that is, the time since the respective states joined the Union. However, they noted that they did not expect any meaningful effect, as unless one assumes a century-long time lag, stability could not be relevant for their empirical cases (the contemporary American states). Indeed, the stability term is in this setting constant. Studying the determinants of the densities of healthcare, higher education, and energy policy interest group populations in four post-communist EU member states, Labanino et al. (2021a), however, conceptualised the stability term as the ratio of pre-transition (1989) and contemporary (2018) population densities. The analysis found a curvilinear relationship between 1989 and 2018 densities. However, the study did not explore the causal process linking the effect of 1989 densities on the number post-transition organisations. As our population ecology dataset contains the formation and dissolution rates of a total of 52 energy policy, higher education, and healthcare populations across four countries (Czech Republic, Hungary, Poland, and Slovenia) between 1989 and 2019, we can model how the 1989 population size affects the vital rates of post-transition populations through time. We measure the number and the ratio of communist-era organizations, respectively on yearly formation rates (and where possible, on mortality rates), and explore the implications on density dependence. Our analysis rests on the assumption that communist era and post-transition organizations follow different advocacy strategies (Gallai et al. 2015), and on the observed lower mortality rates of communist era organizations (Labanino et al. 2021b). We also test alternative time-series models, following the structural model of the POS framework (Meyer and Minkoff 2004). Our study contributes to population ecology models beyond an alternative conceptualisation and measurement of the stability term. Human organisations are resilient even after political and economic sea change, which must be reflected in the analysis of relatively young interest group systems.