Social capital and support for the welfare state in Russia

Abstract

Few tasks are more important in a post-communist setting than rebuilding the welfare state. We study individual preferences for increasing social welfare spending to reduce inequality. Using two surveys of about 34,000 and 37,000 Russians, we show the great importance of the “bridging” type of social capital for redistribution preferences in Russia, as it precludes possibilities of cheating and free-riding on the welfare state. Instrumenting social capital with education, climate, and distance from Moscow, we deal with endogeneity concerns and also contribute to our understanding of the deep roots of social capital in Russia. We claim that social capital in post-socialist countries could help mobilize public support for redistribution even where institutions are weak.

Keywords:

• Preferences for redistribution
• inequality
• social capital
• bridging social capital
• trust
• corruption
• Russia

Acknowledgments

This article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project “5–100”. We thank participants in seminars at the National Research University Higher School of Economics, Columbia University, and IMT Lucca.

Notes

1. According to the World Bank World Development Indicators Database, the Gini index in Russia increased from 23.8% points in 1988 to 41.6 in 2012.

2. The “tunnel effect,” a term coined by Hirschman and Rothschild (1973), implies that the poor may see increasing inequality as a sign of forthcoming opportunities for their own upward mobility, just as drivers stuck in a traffic jam inside a two-lane tunnel become optimistic when they see another lane start moving. Ravallion and Lokshin (2000) find evidence of a tunnel effect in 1990s Russia.

3. https://www.hks.harvard.edu/saguaro/glossary

4. https://fom.ru/

5. To be more precise, we obtain aggregated social capital measures that are conditioned on individual characteristics such as age, gender, etc. Details of the procedure are explained in the section entitled “Empirical strategy.”

6. In practice, however, it is necessary to account for the fact that the existing income distribution itself is at least partially the product of government redistribution and public goods provision; thus establishing a causal link in this setting is not a trivial matter.

7. FOM, one of the largest polling companies in Russia, conducts several Georating surveys every year, starting from 2003. The surveys cover the majority of Russian regions and are representative of their population, although respondents for every wave are not the same. Topics of the surveys also vary to include those deemed most important at the moment. The topic of social capital was represented only once in 2007, while general preferences for redistribution were included in the 2008 survey. More information about the Georating surveys can be found in Oslon (2006). A Russian-language description of the structure of the sample can be found at https://bd.fom.ru/report/cat/cult/sci_sci/ans_sociology/georating.

8. To obtain a comparative perspective for preferences for redistribution, we use the aforementioned WVS question that is close to ours: “Incomes should be made more equal vs. We need larger income differences as incentives.” The original 10-point scale was recoded to the binary one.

9. All calculations for redistribution preferences and generalized trust exclude “Don’t know” responses.

10. We give preference to OLS estimation, as it appears to be more robust to such specification issues as model underspecification and heteroscedasticity. As a robustness test we ran a probit-model as well, and obtained results similar to what the OLS estimation provides.

11. Our overall strategy of obtaining conditional trust is similar to that used by Algan and Cahuc (2010).

12. Table 4 presents results for only one of the inequality measures, namely the Gini coefficient. Results for the alternative indicator (share of the population with incomes below the subsistence level) are similar and available upon request.

13. Our results are also robust to the inclusion of the share of those who answered “don’t know” to the questions about generalized trust and solidarity. Thus, we eliminate the potential that non-responses biased our results due to the social capital of those who dropped out of the sample.

14. The fact that our estimates for the effect of individual-level demographic variables are similar to those in the rest of the literature on preferences for redistribution provides reassurance that the survey question we rely on is a relevant proxy for redistribution preferences.

15. Although both Corruption (INDEM) and Willingness to bribe (INDEM) assess regional corruption in 2010, we believe they may be used as measures of corruption for 2008, because this institution is unlikely to evolve rapidly. Nevertheless, in our main specification we give preference to a corruption assessment provided in 2004.