Point Predictions and the Punctuated Equilibrium Theory: A Data Mining Approach—U.S. Nuclear Policy as Proof of Concept

Abstract

In Punctuated Equilibrium Theory (PET), information processing under the constraints of limited attention and bounded rationality leads to stick-slip dynamics in policy outcomes. Empirical work in this field often focuses on the macro level. Using the case of nuclear energy policy in the United States as proof of concept, we demonstrate how decisive budget changes in a specific policy subsystem can be linked to attention of Congress and the president. We utilize a mixed-methods data-mining approach: Maximum likelihood estimation is used to analyze the distribution of the nuclear energy RD&D budget. Then attention data of both Congress and the president are structured by means of cluster analysis and principal component analysis. Finally, these data are used in a generalized linear model to predict specific budget shifts. The article is designed as a proof of concept: In the case of nuclear energy policy, we are able to predict budget shifts without violating the assumptions of PET. More importantly: we can demonstrate that attention is not only affecting the final policy outcome but also the corridor of the possible.

Budgetary Punctuations: A Fiscal Management Perspective

“…Despite these developments in the study of punctuation patterns, there is a lack of research on how the patterns arise—that is, on the specific mechanisms that lead to punctuations—as Baumgartner et al (2009) stated earlier and Hegelich, Fraune, and Knollmann (2015) reinforced more recently. More specifically in terms of our research, even though the PET relies heavily on budgetary data, as yet little empirical research has linked PE to the general theories and practices of fiscal management.…”

What Is Known about Punctuated Equilibrium Theory? And What Does That Tell Us about the Construction, Validation, and Replication of Knowledge in the Policy Sciences?

“…Statistically, this type of policy change is reflected in a leptokurtic distribution—contrary to the “normal distribution” or “Bell curve” pattern that characterizes incrementalism—indicating that “these changes concentrate in the slender ‘central peak’ and in the ‘fat tails’ of the distribution while they tend to be absent in the ‘narrow shoulders’”(John & Bevan, , p. 89). Scholars have applied different statistical methods to identify the leptokurtic distribution (see e.g., Breunig & Jones, ; Hegelich, Fraune, & Knollmann, ). While it is beyond the scope of this article to trace these methods and applications in a detailed way, it is important to stress that different assessments of the leptokurtic distribution might have an impact on the question if a punctuation is identified or not.…”

The Communication Behavior of German MPs on Twitter: Preaching to the Converted and Attacking Opponents

“…Further studies therefore might benefit strongly from Bayesian methods (e.g. Barberá 2015) and data mining (Hegelich, Fraune, and Knollmann 2015).…”