Table 2

Studies from the UK on benefit changes

AuthorPopulationStudy typeType of policy variation and disability benefit scheme investigatedResult: regression coefficient (p value)CommentsVA
Disney et al (2003)4950–64 year oldsInterrupted times series with panel dataPolicy change that included a combination of changes to eligibility requirements and benefit generosity. IWA, 1995Fixed effects logistic regression of policy change on employment 0.10 (OR 1.11) (p=0.3)The authors concluded that the weak results may reflect either a weak, or indeed no, relationship between the policy change and employment. Did not control for changes in wages13
Clasen et al (2006)48Men 25–64 years oldInterrupted times series with panel dataPolicy change that included a combination of changes to eligibility requirements and benefit generosity. IWA, 1995Hazard model of transitions, model coefficients and exact p values not reported.
−25 to 49 year olds
Employment: long-term sick: No significant effect
Inactivity: employment: positive effect (p<0.1)
Unemployment: long-term sick: No significant effect
−50 to 64 year olds
Employment: long-term sick: negative effect (p<0.1)
Inactivity: employment, no effect.
Unemployment: long-term sick: positive effect (p<0.1)
The authors concluded that the IWA made transitions from inactivity into employment more likely for 25–49 year olds. Among older workers the IWA decreased flow from employment into long-term sick. However, they also found IWA increased flow from unemployment into long-term sickness, therefore the IWA did not contribute to overall decrease in movements onto IB. Health status and wages were not controlled for in the analysis.12
Faggio and Nickell (2005)42Men age 25–54 yearsDifference in differences study with ecological dataVariation in benefit generosity only. IVB/IB, 1982 to 1999.Linear regression of the log of the ratio of benefits and wages on non-employment
All: 0.037 (p=0.009)
Low education: 0.089 (p<0.001)
The authors concluded the level of IB was positively associated with male inactivity and a much bigger impact was observed for those without qualifications. They find much larger effects associated with low regional wages. Health status and labour market conditions not controlled.10
Disney and Webb (1991)40Men 18–69 yearsInterrupted time series with ecological data
And cross-sectional analysis
Variation in benefit generosity only. IVB/IB, 1979 to 1984Linear regression of replacement rate (benefits/wages) on probability of IVB receipt
0.292 (p<0.001)
Also include a cross-sectional analysis of various factors on employment, but this does not include disability benefits as an independent variable
The authors concluded that the trend in IVB receipt was explained by the ageing of the workforce, changes in the replacement rate, in the health status of the workforce and in income and housing tenure. However, the dominant variable was unemployment. They did not control for health status, education or labour market conditions in the time series analysis.9
Bell and Smith (2004)4125–59-year-old menTime series study with ecological dataVariation in benefit generosity only. IVB/IB, 1984 to 2001Regression of benefit level on labour force non-participation
Elasticity 0.26 (p=0.002); however, controlling for separate age trends reduced the coefficient and it became not significant.
The authors concluded that there was a sizable effect on male labour market participation of changes in benefit levels. This was particularly the case for the least educated men. Did not control for wages, health status or labour market conditions.7
  • IB, incapacity benefits; IVB, invalidity benefits; IWA, Incapacity to work Act; VA, validity assessment.