Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
  1. Home
  2. Search

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

1 results

  • Dangerous dyads in the post-Soviet space: explaining Russia's military escalation decisions, 1992–2010

  • Paolo Rosa, Adriana Cuppuleri
  • Journal:
    Italian Political Science Review / Rivista Italiana di Scienza Politica / Volume 51 / Issue 3 / November 2021
    Published online by Cambridge University Press:
    22 January 2021, pp. 355-372
    Print publication:
    November 2021
    • Article
      • You have access
      • Open access
    • PDF
    • HTML
    • Export citation

  • This paper analyses the military behaviour of Russia from 1992 to 2010. The method used is a combination of the dyad analysis introduced by Stuart Bremer in 1992 and the analysis of unit-level variables, which is distinctive of foreign policy analysis. We empirically test a set of hypotheses about the determinants of Russia's military behaviour in the post-Cold War period by considering the impact of changes of international variables – relative power, the presence of military alliance pacts, the territorial salience of the dispute – and state-level variables – the degree of democracy/autocracy and regime vulnerability. A bivariate and a multivariate analysis are carried out to explain the separate and joint impacts of independent variables.