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Alternative Social Welfare Measures Essay Sample

Alternative Social Welfare Measures Pages
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At present, gross domestic product (GDP) is the most methodologically elaborated indicator of social welfare. Its methodology has been developing since early 50s by UNSTAT and is presented in a manual of more than 700 pages. In part such extensiveness point to ever mounting methodological problems linked to aspiration to produce uniform measure of economic progress. Two criticisms are in particularly devastating for application of national GDP per capita also as the leading indicator of social welfare: (1) GDP p.c. is one dimensional measure incapable of expressing multi-dimensional concept of welfare. (2) GDP p.c. measures economic progress which is decreasingly relevant even in materialistic societies with already achieved high income per capita where non-economic aspects of social welfare become the main drivers of welfare progression.

To account for these two functional failures of GDP, an alternative indicator of social welfare has been proposed by UNDP – human development indicator (HDI). HDI measured by countries distinguishes from GDP in two important respects: (1) it is constructed as a compound indicator from three sub-indicators measured in volume terms, GDP p. c., education of population and life expectancy at birth; (2) GDP p.c. has been initially standardised relative to the threshold value at approximately 16,000$, beyond which income growth assumingly decreasingly contributes to overall HDI (methodology changed so they use the logarithm of income now, to reflect the diminishing importance of income with increasing GDP).

HDI is thus a compound indicator obtained as a simple average of three sub-indicators. When one compares country rankings by GDP per capita and by level of HDI considerable differences can be observed. Rich countries do not rank the highest in HDI when their social and human achievements lag behind their economic achievements. HDI then clearly induces countries to forward more balanced social welfare doctrine between its materialistic, social and human part. Basically the same methodological approach to construction of compound social indices has been applied extensively in various areas of welfare statistics. Some other notable examples with elaborate success in broadening our discussion on alternative social welfare doctrines are happiness and quality of life indices – such as those combining (composite) indices in the field of “having, loving and being” as conceptualised by Allardt, 1972) – their introduction as a primary welfare measures has been officially announced recently by France and Germany.

One of the most criticised aspects of composed indicators applied as a synthetic social welfare indicator is linked to observation that they usually lack serious theoretic justification for the selection of sub-indicators as representative components of social welfare measure. Are three sub-indictors of HDI equally relevant for social welfare in every of 150 countries covered by the HDI? In the case of happiness indices serious objections have been raised concerning their strong subjective bias which rule out indications on objectively achieved welfare in a society. These measures (HDI, happiness indices) are problematic also because they are produced as nonnamed measures; they are not expressed in terms of money, years of life etc. but in an abstract term of index points. This directly exposes them to scientific and political manipulation (forget not that happiness indices are proposed as a substitute measures by politicians!). In this regard, GDP fares much better as it is more directly related to welfare and sufficiently complex that it is more independent on political interference. GDP methodology provides that only comparable  (monetary) qualities are summarised in the aggregate indicator, while HDI obviously confuses apples and oranges, averages dollars with years of life.

In this regard, HDI type of indicators can not replace GDP per capita as a dominant welfare indicator. This conclusion makes clear that the first generation of alternative measures, which are meant only as non-monetary substitutes, failed. GDP is inappropriate as a social welfare indicator not only in its universal substance (monetary) but also as a concept because it implies that social welfare is summative category, simple aggregate of its constituents and not a category emerging from synergy and confrontation between its components (sub-indicators). If social welfare is meant as an integral category, this should be clearly acknowledged also in the (alternative) indicator of social welfare. The project of producing an alternative social welfare indicator GD.c goes beyond searching for the appropriate substance that best describes social welfare (money, happiness, index points) because it demands to question fundamental appropriateness of present aggregative approach to construction of such measure (irrespective of its substance).

Two alternative concepts of social welfare indicator’s composition are proposed: (1) indicator of gap between welfare components such as a gap between short-term material achievements and long-term expectations, or between objective – subjective welfare etc (Radej, Bole, 2005; Example 1, below) and (2) indicator of overlap between its components such as between economic, social and environmental component of welfare (Radej, 2010, Example 2 below). The first alternative approach is based on Calman’s (1984) thesis that human welfare is related to the gap between person’s expectations (frequently set in long-term perspective) and his/her actual (short term) achievements. Demand for more balanced welfare between short and log-term effects has been further elaborated in theory of sustainable development (WCED, 1987). Sen (1982) has taken similar path when he postulated that human welfare is less dependent on available income than on the gap between his/her “capabilities and functionalities”.

To design a gap indicator we take two composed indices of welfare, say GDP per capita to denote short term achievements and annual Adjusted net savings indicator (ANS, World Bank, 1997) to account for long-term expectations – thus implying a social welfare concept of weak sustainability (HicksHartwick-Solow; in Pearce, Atkinson, 1995). Next we organise both compound indicators orthogonally and study gap between each year’s combined indicator of achievement-expectation of a given country and diagonal in Cartesian space. Diagonal line identifies hypothetical path of balanced sustainability of development between short and long-term progression. Experimental testing of this indicator confirms that social welfare, when presented in two dimensional space usually displays more complete and sometimes significantly different path of social welfare compared to one dimensional, aggregative and monolithic presentations with GDP p.c., HDI or happiness indices.

The second alternative approach, proposed here is based on plural – usually triadic – definition of sustainable development in WCED (1987) which emerges as a result of overlap between economic, social and environmental development which is usually presented with Venn diagram with three overlapping circles. The origin of the approach is basically identical to the approach in construction HDI (with three sub-indicators), but derivation of summary indicator is entirely different. In this case we do not allow for simple aggregation of sub-indicators into compound indicator. Instead we synthesise three components with the correlation of information on how three components impact each other. This approach is not about how large but how consistent is progression in welfare components. Unfortunately, it turns out that information on cross impacts between three welfare components are not available in official statistical information systems but need to be estimated separately. This might be feasible only with the qualitative evidence and expert opinions. This kind of alternative indicator requires collection of more scattered evidence and more qualitative and soft methods in the formation of synthetic indicator. However, this

evaluative approach certainly does not imply weaker logic of reasoning about social welfare but more democratic or plural (“mixed-method”) approach in light of fundamental incommensurability of three welfare domains. This alternative proposal is exhibited in Example 2 below which is for the time being available only as an analogy to the issue under investigation. Paradigmatic turn is required when social welfare is observed from the viewpoint of integrity between its several equally important but latently conflicting components. In such a case, not primary achievements in all three components are what matters but secondary effects (side effects or unwanted effects). When one observes social welfare neither as homogenous nor aggregatable category (like GDP, HDI, happiness indices) but a heterogeneous whole in its integrity, s/he should focus on its secondary qualities (gap, overlap).

As societies grow more complex, policy-makers should be increasingly aware not only of their own agency’s primary objectives narrowly defined, but also of wider implications and unwanted effects of their (in)activity. This conforms to a thesis that the most appropriate of all alternative welfare inducing policy interventions is the one which is the most secondary effective (cf. Demsetz, in Schnellenbach, 2005). The same principle is relevant to the thought of both Hayek and Popper, who take the view that the unintended consequences of action are the principal concern of social science and that the existence of unintended consequences is a precondition for the very possibility of the scientific understanding of a complex society (Vernon, 1976).


Calman K.C. Quality of life in cancer patients – an hypothesis. Journal of Medical Ethics. 10/3(1984):124-7. Pearce, D. W. and G. Atkinson, 1995. Measuring sustainable development. In: D. W. Bromley (ed.). The Handbook of Environmental Economics. Blackwell, Oxford.

Radej B., T. Bole. 2005. Quality of life in three European regions – assessment with objective gap analysis. Presented at the SDRC Conference “Sustainability – Creating The Culture”; Aberdeen, 2-4.XI.2005. Radej B. 2010. Synthesis in Policy Impact Evaluation. Ljubljana, Slovensko društvo evalvatorjev, Working paper no. 3/2008 (August 2010), 20 pp.

Schnellenbach J. The Dahrendorf hypothesis and its implications for (the theory of) economic policy-making. Cambridge Journal of Economics, 29/6(2005):997-1009.
Sen A.K. 1982. Choice, Welfare and Measurement. Cambridge: Harvard University Press. UNDP. 1998. Human Development Report 1998. UN Development Programme. Oxford: Oxford University Press. Vernon R. The »Great Society« and the »Open Society«: Liberalism in Hayek and Popper. Canadian Journal of Political Science, 9/2(1976):261-76, http://www.jstor.org/stable/3230923, [III/09]. WCED. 1987. Our Common Future. Oxford and New York: Oxford University Press, World Commission on Environment and Development – WCED, 400 pp, http://www.un-documents.net/wced-ocf.htm, [IX/06]. World Bank. 1997. Expanding the Measure of Wealth. Washington: World Bank.

Explanation: Graph presents two orthogonally organised indicators of social welfare in three European macro regions for the period 1990-2002: EUW (Western EU members, blue line), EUCE (EU members from Eastern and Central Europe, violet line), and WB (Western Balkan, red line). Horizontal axis represents composed indicator of present short term achievements as composed from a set of economic indicators (GDP per capita, employment, inflation; 0 – countries with the poorest value of economic achievements in Europe, 1 – countries with the best achievements in Europe).

Vertical axis represents composed indicator of long-term expectations for future progress of social welfare which is represented with the indicator of adjusted net savings (ANS). This one embraces information about net savings obtained as a difference between gross savings (in GDP, as obtained from national accounts) and environmental damages (measured with indicator of CO2 emission damages in GDP) and eventual loses in human capital (measured with indicator of national expenditure for education in GDP). Balanced economic progress between short and long-term social welfare would follow the diagonal line from bottom left (0, 0) upwards (towards 1, 1).

The horizontal axis is read from left (low economic welfare) to right (high economic welfare) and can be seen as representing conventional view of economic progress. Vertical axis is meant to account for sustainability component of present economic trends. When these two views are combined, our perception of economic progress may radically change. This is the most obvious in the case of WB. We can see that they experienced moderate economic progress (horizontal shift from left to right), which suggest rather sluggish, but not at all unfavourable economic progress in short term perspective.

However such assessment of their economic progress would be entirely misleading taking into account the vertical axis showing radical deterioration in future economic prospect of WB region – do not forget the wars between some of these countries between 1991 – 1999. War years were not so bad for economy after all, but it had been disastrous for regional social welfare in future. EUCE region has experienced large improvements in short term fruits of economic progress but practically stagnated in longer term social welfare prospects (vertically). EUW region is the most advanced in economic progress (the most far right position in the graph) but not in terms of long-term economic progress (pointing probably to excessive consumerism). This example shows that two-dimensional presentation of social welfare can present its complex content in entirely simple but also more complete way.

Example 2: Three dimensional presentation of compound indicator – On the case of evaluation of Slovenian Energy Program’s (SEP) impact on Territorial Cohesion (TC) of Slovenia – 2.2: Presentation of the results (level of

2.1: Definition of TC (a correlate or overlap (‘∩’) between Tq, Ti, Te) TC = (S ∩ F ∩ E) = (Tq ∩ Ti ∩ Te)
integration between TC components)

2.3 (A-C): How the results were obtained?

Legend: Sec. A&B: Scale from -2 (strong negative) to +2 (strong positive); obtained with summation from detailed assessment matrix applying the following rule: from 0,00 to 0,20 → 0 means neutral impact; from 0,21 to 0,50 → 1, means weak positive impact; from 0,51 to 2,00 → 2 strong positive impact. Sec. C: (0,0) = neutral/absent correlation; (0,1 or 1,0) = very weak; (1,1 or 2,0 or 0,2) = weak; (2,1 or 1,2) = moderate; (2,2)= strong correlation.

Explanation: For the time being we can not present compatible example to the Example 1 above. We can only illustrate the problem on the analogous case of ex-ante evaluation of Slovenian energy program (SEP) on territorial cohesion (TC) of Slovenia. The overlapping (correlative) logic of its construction as compound indices is the same in both cases. So, TC is defined (2.1) as the overlap between three spatial sub-systems – P-physical, S-socio-cultural and E-economic. TC is a result of interaction between sub-systems: if hypothetically there were no interaction between them, overall TC would be absent (despite of eventual separate achievements in all three systems). TC is not a direct result of changes in P, S and E, but a result of overlap of overlaps.

The intermediate element in aggregation procedure are bilateral overlaps between three sub-systems, named Ti, Tq and Te and our task in evaluation is to assess impacts of SEP in terms of three overlaps – are they present, positive and balanced? – and correlation between them. We needed to find out how E related measures of SEP (in row of 2.3A) impact on social criteria of evaluation (S)? Are they balanced with the socially related measures (S) on economic criteria of evaluation (E in column of 2.3A)? This correlation describes value of Te for SEP’s impacts as very weak, with S-related measures more favourable for E criteria of evaluation than the opposite, which clearly presents unbalanced situation. The same logic is applied to interpret remaining two elements of TC in 2.3C.

Results are graphically presented in section 2.2. They present level of integration between three components of TC (Ti, Tq and Te) as a compound indicator of territorial cohesion. In the similar (three or four dimensional) approach one could construct indicators of other complex and multidimensional social welfare issues such as sustainable development, quality of life.

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