To the Better Place
The ‘better society’ (or the better place), is not characterised by, for example democracy, freedom of expression, or a low taxation, these are merely means-to-an-end measures that all represent a particular point of view.
What we are looking for are policy outcomes that nobody in their right mind can disagree with. For example, a low murder rate is a universal good. It is absurd to claim that a high number of murders is good, so is low infant mortality and a clean environment.
To use the terminology of the philosopher John Rawls a ‘better place’ is one that is characterised by an “overlapping consensus”. That is characterised by outcomes which people can agree on despite, “considerable differences in…conceptions of justice provided that these conceptions lead to similar political judgements (Rawls 1999: 340).
We devised a list of desirable goals based on and consistent with John Rawls’ concept of an ‘overlapping consensus’. These were low infant mortality, long life expectancy, high GDP per capita, low CO-2 emissions, low levels of homicide, and years of education.
These were combined into an index using z-scores. This index, we contend, is less culturally biased than the existing measures, as well as it is broader in coverage (it includes all UN member states) and also comprises variables not currently in other measures, such as environmental protection.
For the sake of developing this index, we hold that the following are positives that no one would disagree with:
-Low CO-2 emissions (measures by tonnes per 100.000 people);
-Low Infant mortality rate
-Long life expectancy
-Low homicide rate
-Many years of education
-High GDP per Capita in Purchasing power parities
These measures are combined into an index.
However, we cannot just add them up and divide them by six. The figures for CO-2 emissions and GDP are very high – both running into thousands -whereas the opposite is true for years of education. So, in this case we are not comparing like with like.
Statistically this problem can be resolved using so-called Z-scores. The Z-Score is a standardized value that measures how far a value is from the mean (average), which is measured in standard deviations. A value of 0 indicates the mean value while a positive value represents a value that is above the mean and negative value represents a value below the mean. The Z-Score is measured in standard deviations.
Thus using Z-scores, we can compare them, even if the actual numbers are different. Technically speaking this is gives you an idea of how many standard deviations below or above the mean a score is. For example, in Afghanistan, the average income was around 500 US Dollars per year. By contrast it is about 44.000 US Dollars in Belgium. To compare these figures, we measure how far each is from the mean – or the average. The Z-score for Afghanistan is thus -0.61, whereas the score for Belgium is 1.3. In this way, we have a more manageable figure