Historical Trust Levels Predict Current Welfare State Design
Andreas Bergh and
Christian Bjørnskov
No 144, Ratio Working Papers from The Ratio Institute
Abstract:
Using cross-sectional data for 76 countries, we apply instrumental variable techniques based on pronoun drop, temperature and monarchies to demonstrate that historical trust levels predict several indicators of current welfare state design, including universalism and high levels of regulatory freedom. We argue that high levels of trust and trustworthiness are necessary, but not sufficient, conditions for societies to develop successful universal welfare states that would otherwise be highly vulnerable to free riding and fraudulent behavior. Our results do not exclude positive feedback from welfare state universalism to individual trust, although we claim that the important causal link runs from historically trust levels to current welfare state design.
Keywords: Social trust; Welfare State (search for similar items in EconPapers)
JEL-codes: Z13 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2009-10-29
New Economics Papers: this item is included in nep-cbe and nep-soc
References: Add references at CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://www.ratio.se/pdf/wp/ab_cb_historical.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found (http://www.ratio.se/pdf/wp/ab_cb_historical.pdf [308 Permanent Redirect]--> https://www.ratio.se/pdf/wp/ab_cb_historical.pdf [308 Permanent Redirect]--> https://ratio.se/pdf/wp/ab_cb_historical.pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hhs:ratioi:0144
Access Statistics for this paper
More papers in Ratio Working Papers from The Ratio Institute The Ratio Institute, P.O. Box 5095, SE-102 42 Stockholm, Sweden. Contact information at EDIRC.
Bibliographic data for series maintained by Martin Korpi ().