Download this Paper Open PDF in Browser

Historical Trust Levels Predict Current Welfare State Design

28 Pages Posted: 2 Dec 2009  

Andreas Bergh

Research Institute of Industrial Economics (IFN); Lund University - Department of Economics

Christian Bjørnskov

Aarhus University - Department of Economics and Business; Research Institute of Industrial Economics (IFN); Center for Political Studies

Date Written: December 1, 2009

Abstract

With cross-sectional data for 76 countries, we use IV techniques to show 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 successfully develop universal welfare states that would otherwise be highly vulnerable to free riding and fraudulent behaviour. Our results do not exclude a positive feedback from welfare state universalism to individual trust, although we claim that the important causal link goes from historically trust levels to current welfare state design.

Suggested Citation

Bergh, Andreas and Bjørnskov, Christian, Historical Trust Levels Predict Current Welfare State Design (December 1, 2009). Available at SSRN: https://ssrn.com/abstract=1516334 or http://dx.doi.org/10.2139/ssrn.1516334

Andreas Bergh

Research Institute of Industrial Economics (IFN) ( email )

Box 55665
Grevgatan 34 2nd floor
Stockholm, SE-102 15
Sweden
0707790734 (Phone)

HOME PAGE: http://www.ifn.se/web/AndreasB

Lund University - Department of Economics ( email )

P.O. Box 7082
S-220 07
Lund
Sweden

HOME PAGE: http://www.nek.lu.se/

Christian Bjørnskov (Contact Author)

Aarhus University - Department of Economics and Business ( email )

Fuglesangs Allé 4
Aarhus V, DK-8210
Denmark

Research Institute of Industrial Economics (IFN) ( email )

Box 55665
Grevgatan 34, 2nd floor
Stockholm, SE-102 15
Sweden

Center for Political Studies

Landgreven 3
Copenhagen K, DK-1301
Denmark

Paper statistics

Downloads
139
Rank
175,413
Abstract Views
782