One aspect of the current economic transference of the labour market is increasing in-work poverty, mixing unemployment and underemployment, more as part of a continuum of employment, with part-time, zero hour, and low paid remuneration, based on increasing of inequality. There is a widening as well as record wealth divide in many countries around the world. Some economics workers refer to the Gini coefficient and index, but this itself can be misleading, especially as it inadequately represents the scale of absolute poverty at the bottom and misses off the difference between poor and very poor, which can be the difference between being hard up and affording to live. Destitution, hunger and often is with respect to particularly disadvantaged groups or sectors within society, so that the reality for groups driven into poverty can be far worse than the very general Gini index can accommodate.
The following article also mentions availability of data, like unemployment statistics can be very misleading, or even if in the same direction, can underestimate the real situation and related circumstances for those suffering poverty. Limitations and even worse biased selection of samples of the population used in data collection, with resultant statistical error and questionable validity mean absolute poverty at the bottom is often far worse than statistics based on official available figures:
Useful reports on In-work poverty by Joseph Rowntree Foundation, discussing the various elements that contribute to falling incomes for the poorest in work:
Search of ‘in-work poverty’ from Joseph Rowntree Foundation site provides some interesting demographics and details of reality behind the statistics:
“Child poverty is increasingly a problem in working families”
It is a typical graphical representation from official sources illustrating rising UK in-work poverty statistic (2001/02 compared with 2011/12). It is useful as it highlights a problem of in-work poverty mushrooming in UK, but it is also problematic to compare 2001 to 2011, as standard of living rose especially so for the poorest, but has rapidly fallen since 2010 and continued to fall since 2011. It also has to be borne in mind that the division is very general rich and poor, whilst in reality there are divisions of poor, with many shades of poor, with the poorest without means or with family able to supplement inadequate means, having the greatest fall in the standard of living in UK.
This statistic has been featured in many recent articles and newspaper reports on in-work poverty in UK relating to the latest in-work poverty situation. However, I have felt every time I read this information on in-work poverty increasing that it is often unintentional, but sometimes intentional affect, by comparing the two of making people think that out-of-work poverty is falling, whereas in-work poverty rising, but in reality both are rising, just in-work poverty is mushrooming. Often headlines state in-work poverty is now a bigger problem than out-of-work poverty. It is actually an unnecessary association, but it is a factor of comparing two variables, namely in and out of work poverty as a percentage of total poverty.
It was important to emphasise that this is something though that is often missed from illustrating the rise of in-work poverty and not a criticism of this graphical representation. In-work poverty is indeed a very real problem in itself, with many more going to work, but still not having a living wage and even benefits increasing due to inadequate income. However benefits have been cut per individual, so although the benefits bill in terms of government expenditure can rise and needs to with real inflation, as opposed to the inadequate official inflation figures is rising even more for the poor, due to the much higher weighting of essentials in the cost of living.
So for those having to rely on benefits, it is a very real cut and those not in work unless they have any other sources of support, such as family and not everyone has family or family that can provide financial support are left even more impoverished. But the way that the comparison appears is a factor in the way that statistics work, or rather are used. A lot depends on presentation of variables and associations, interactions, often with different types of error. There are many good books on statistics used in psychology and economics that explain these various aspects of using and presenting statistics (see recommended reading references note below for some books I like).
The case in point is that it would be interesting to examine further, by including in the graph, on the same scale, increasing poverty both in and out of work, but also still illustrating the massive increase of in-work poverty. This would help to illustrate both problems at the same time. That is, in and out of work poverty are both increasing in the UK. This is also quite possibly the case in many countries around the world that are currently praising themselves on falling official unemployment figures, bearing in mind many countries such as UK also use manipulate statistics to try to show unemployment as much lower than it actually is.
OECD forecasts, based on recent trends, inequality rising and GDP growth slowing in spite of population growth increasing:
Disguised unemployment, making official figures appear not anywhere near as bad as they really are still exists just its not featured in official figures, along with an enormous growth of underemployment, much lower job security and falling incomes of lower to middle incomes in many countries, but especially those following ‘Austerity’ policies such as UK. So Prof. Stiglitz in a lecture on the reality of US along with most of developed world, especially North Atlantic bordering countries, but with macroeconomic linkages throughout the world, still being in a Great Depression (24:00 in video) UK is even worse, but all are in a Great Depression.
The North Atlantic malaise: failures in economic policy
“not just a lost decade, but unless anything is done we could be talking about a lost quarter century..”
Recommended reading references for books on statistics:
My favourite books on statistics, especially relevant for psychology, include one of my recent set books Andy Field, ‘Discovering Statistics Using IBM SPSS Statistics’ (4th Ed) (2013) Published by Sage and available as a book or on Kindle. Also the heavy weight book Barbara G. Tabachnick and Linda S. Fidell ‘Using Multivariate Statistics’ (2013) Published by Pearson.