Ronald F. Inglehart Laboratory for Comparative Social Research announces the next regular seminar, which will be held as a Zoom session on September, 30 at 16-30 p.m. (GMT+3). Boris Sokolov (LCSR HSE), Emil Kamalov (EUI), Ivetta Sergeeva (EUI), and Margarita Zavadskaya (University of Helsinki / EUSPb / LCSR HSE) will deliver a report “Can Media Framing Help Governments Avoid Blame for Welfare Retrenchment? Evidence from a Conjoint Experiment in Russia”.

A link to Zoom session is available upon request via lcsr.event@hse.ru.

Abstract. Every policy produces winners and losers. Deep structural reforms and welfare retrenchment often impose costs upon various groups of the national population. As the studies of the US and European states show, one of the most crucial negative political consequences of such reforms is the decrease in mass support for the government responsible for the initiation of the reform. However, sometimes governments manage to avoid popular outrage for welfare retrenchment. Several viable strategies of political blame avoidance have been identified in the previous literature, including (a) shifting the blame to subordinate or competing political actors; (b) providing compensations to most vulnerable groups affected by the reform; and (c) framing the public perception of reform via various media channels.

In this project we focus on the latter strategy and test whether intentional media framing of a potentially unpopular welfare reform may help a non-democratic government to escape political losses associated with the reform. Drawing on the existing literature on political support, we identify a variety of media frames that may potentially affect mass attitudes toward government in the context of a major welfare retrenchment reform. These frames can be grouped into five thematic categories: (1) economic context, (2) geopolitical context, (3) institutional blame redistribution (the statesperson who takes public responsibility for the reform), (4) social solidarity (e.g. compensation for deserving social groups), 5) compliance with 'the Western standards'.

We estimate the effects of those frames by using a conjoint vignette experiment about a hypothetical healthcare reform in Russia, introducing mandatory insurance payments and a partial transition to fee-for-service medicine.  For this purpose, we collected data via a F2F survey (N = 1619) conducted as part of the July 2021 omnibus survey held by the Levada-center, one of the leading Russian polling organizations. Our analysis focuses on two dependent variables: (1) support for a hypothetical reform (1-5 scale) and (2) aggregated index of political support if the reform would indeed have occurred (average score over items measuring support for president, prime minister, government, parliament, and governor of a respondent's region of residence; each asks how would a respondent's attitude toward a particular institution change, had the reform been indeed implemented).

We find that individual support for reform increases when a fictional newspaper article describing this reform emphasizes that (a) "The reform implies subsidies for vulnerable categories of citizens: the poor, pensioners, and some others", and (b)  "the Russian economy is in a stable condition, so now is the right time to make the long-overdue changes and to avoid problems in the future". It decreases when the article informs respondents that the reform has been announced by the President of the Russian Federation. No experimental attributes have significant pooled-sample effects on the index of political support, although there are some intriguing interactions and sub-group effects, which will be discussed during the presentation.

The project is supported by the Center for Advanced Governance, the program ‘Evidence-based Policy Making 2020’.

Additional sources

• Our theory is presented in this paper (in Russian): http://inion.ru/site/assets/files/6085/04_sokolov-_zavadskaia-_kamalov.pdf.
• More details about our study design can be found at: https://osf.io/326qb.

Everyone interested is invited!

The working language is English.