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Reasons to be cheerful: How ILO analysis of social transfers worldwide augurs well for a basic income (with some caveats). Ian Orton. The 13th International Congress of BIEN Universidade de São Paulo, Brazil, 30 June – 2 July 2010.
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The 13th International Congress of BIEN
Universidade de São Paulo, Brazil, 30 June – 2 July 2010
In 2008 ILO launched a major macro ‘study of studies’, known as the ILO matrix on the effects of social transfers
Matrix systematically assesses a large number of papers and evaluation reports on tax-financed social transfer programmes [STs]
126 evaluation reports were studied (covering 62 programmes from 30 developing countries)
These STs reach between 300 and 350 million beneficiaries (excluding the new social security provisions for the unorganized sector in India).
Matrix was designed to:
- assist ILO campaign on the global extension of social security
- & to help support decision making and dialogue within ministries of developing countries to develop their social security systems
The matrix allows the user to search for the economic and social impact of ST programmes by:
effect (i.e. child labour effect)
impact on specific groups (i.e. children)
type of benefit (i.e. pensions, child benefit)
category of programmes (i.e. targeted, conditional etc)
and geographic region.
The STs analysed have a similar ontology to the basic income [BI], as they are:
-and a number of STs are unconditional and universal
We can anticipate the kind of effect a BI could be expected to deliver through the experience of existing STs
Detractors, proponents and neutral observers of the BI can therefore use the findings of the ILO matrix to better understand potential effects of BI
Study of studies makes an important empirical contribution to the discourse on the BI
Significantly higher scores in the ‘clear positive effect’ column for all but five of the impact sub-dimensions
In spite of some methodological limitations, a majority of the STs studied clearly generate a range of positive effects in terms of:
-enhancing human development
-supporting the full utilisation of productive capacity
-enhancing and stabilising consumption
-and facilitating social cohesion and inclusion
Positive impacts on poverty
Health and nutrition
The social status of recipients (notably women)
Stimulation of micro-economic activity and entrepreneurial small scale investments (notably in agriculture)
Importantly they have avoided significant adverse effects on labour market participation of the poor populations they serve
STs acted as an effective economic and social stabilizers at times of crisis (as per financial crisis)
This was true for:
Adult preventive health
Reduction in the worst forms of child labour
Improvements in employability
Reduction of labour market informality
Impact on social capital and solidarity
Because of the shared ontology, it can be supposed that a BI could deliver similar effects in some instances
ILO findings are really an invitation to users to explore the matrix more thoroughly, and form their own conclusions.
Programme evaluations covered by this study do not represent an exhaustive list
Studies were easily accessible online and were generally Anglophone
Although studies used are probably representative and give a good overview
Findings do not reflect the different scales of programmes
(Bolsa Familia compared with Mongolian Cash for Herders programme)
Subjective chain of interpretation open to human error
Results are thus indicative of the effects of STs
Effects on non-beneficiaries
-Research focuses on effectiveness for actual or potential beneficiaries
-Less is known about the wider effects on non beneficiaries and the local
Prevalence given to quantitative measure instead of qualitative measures
-research on STs focuses on their quantitative effects and less on the
qualitative effects of STs (i.e. Social bonds, capabilities and human
Macro economic data on the relationship of STsto economic growth
-Disaggregating the precise effect of STs on macro economic growth is
difficult and would be an important venture to understand
The message is perhaps a little mixed
Matrix better supports unconditional and universal transfers for children and the elderly (essentially a BI for the young and the old)
However, empirically, more problematic to maintain this assertion for the active population groups.
Why is this problematic?
A significant number of the STs analysed in the matrix are conditional and targeted (based on behaviour and income/wealth)
Therefore, one might suppose that their effects are related to the conditional and targeted mechanisms.
Most of the STs analysed covering these two vulnerable groups share a strong ontological similarity with the BI (unconditional or universal )
For example, the social pensions (Brazil, Namibia, S. Africa) evaluated by the ILO matrix, were not based on previous activity or earnings of the elderly (essentially a BI for the elderly)
Unconditional Child Support Grant S. African indicates a BI could deliver similar results (with regard to human capital formation and future earnings)
Evidence for the pilot BI in Namibia supports this (e.g. improved height for earnings)
To a large extent social pensions and a number of other unconditional transfers support the expectation that a BI could generate similarly positive effects as those identified in the ILO matrix.
Except for pilot BI in Namibia there are no studies on the impact of a BI because there is no fully-fledged BI covering active populations
2. The STs analysed in the ILO study which focus on the active population differ from the BI in an important ontological sense, because they are often conditional and targeted
Difficult to deduce with any certainty that the effect of a BI would be the same as a conditional and targeted STs
Evaluations of Namibian BI found:
-that economic activity rose, especially among women
-own account work saw the largest increase, (i.e. tending of
vegetable plots and the building of latrines)
-stimulated more micro-economic activity with new shops opening
Findings are important as they suggest that a BI does not act as a disincentive with regard to productive activities & labour market participation
Important as negative impact on active population is typical critique posited against BI
Need to be cautious about using the Namibian pilot scheme as absolutely conclusive evidence on the potential effect of a BI on the active population
Pilot took place in specific cultural context
Limits to how far pilot schemes can shed light on fully-fledged schemes.
Nonetheless evidence of the pilot study in Namibia is promising
Does conditionality make the difference? Does it account for the result identified in ILO matrix?
There is ambivalence over the effect of CCTs and outcomes, especially with regard to:
-Promoting attainment of developmental objectives
-Relationship between conditionalities and human rights
-Poor people’s agency and CCTs
Evidence on how pivotal conditionality mechanism is, is not clear, as demonstrated by positive results of unconditional programmes
Motivation for conditionality maybe more political (‘paternalist twitch’)
If conditionality is not pivotal, then the unconditional and universal nature of the BI could be expected to deliver similar results to matrix
Not time here, but similar doubts linger on targeting.
Introduce BI to vulnerable groups (e.g. children and elderly) and later spread to active population
Conditional and targeted approaches can be pre-cursors for achieving the goal of full society-wide basic income coverage
Conditional and targeted transfers could help cultivate a more receptive political and public culture more receptive to a BI
Or they could harden preference for paternalism and move away from conditionality and universalism
Strategically-speaking, the matrix can still be used to advance the cause of the BI (even as a Trojan horse)
The matrix supports claims for a universal unconditional cash transfers across specific population groups (i.e. children and the elderly)
More tricky to use matrix to support a BI for active population groups, although it does not rebuff such a possibility
Perhaps ambivalence on the active population can be overcome by making reference to the results of the pilot BI in Namibia...more research is needed
It offers proponents of the BI reasons to feel optimistic that it too could produce similarly positive results.
The matrix is an invitation to better understand the role of STs and the potential consequences of a BI