Unravelling unemployment data
Unemployment data is often referred to as a 'political football'. It is probably better described as a stick with which politicians try to beat each other. Because of this, the interpretation of the data and, in some senses the way in which it is calculated, has long since been compromised.
In an ideal world, calculating unemployment would be a simple matter of dividing the number out of work by the total labour force and expressing the result as a percentage.
However, it isn't that simple.
An alternate (and arguably more valid) way of calculating it is to express the numbers of unemployed as a percentage of that part of the working population that is economically active.
Data favoured by incumbent politicians, who normally want to keep the unemployment rate as low as possible, normally count only those claiming benefit as unemployed. Hence what is called the claimant count rate is the percentage number arrived by dividing the number of claimants by the total number of jobs, plus claimants.
The International Labour Organisation (ILO) calculates unemployment rates using a standardised definition applicable across all countries. This measure is frequently a significantly higher number than those calculated according to the methods favoured by politicos.
There are big differences in the numbers. A little piece of research I did a few years back, for example, showed at that time, a claimant count of 950,000, an ILO definition of the unemployed in the UK at 1.5 million, and an estimate for numbers of those regarded as economically inactive, but nonetheless seeking work, at 2.25 million.
Blurring the lines
The way the modern economy works also blurs the significance of the numbers. For example, self-employed individuals may be working at less than full stretch. They are unlikely to regard themselves as unemployed unless their livelihood shows signs of disappearing entirely. They may get help from a spouse who works for the business on a part-time basis but who, for the purposes of the data, is counted as a full-time employee. As an aside, some countries - Germany, for example - exclude the self-employed altogether from employment and unemployment data.
Many will have observed the phenomenon of disguised unemployment - the family-owned restaurant that employs numerous family members, but which is patently overstaffed. This is before we get into considerations of the black economy, which looms large in a number of countries.
So, the only trend of significance is the way the unemployment rate is moving - not its actual level either expressed in numbers or as a percentage. It's also best to ignore the official spin put on unemployment data, which usually reduces what is a patchwork of very different regional trends to a single number for the whole country. The figures can be easily distorted by strikes and unseasonably bad (or good) weather, the impact of which will not be captured by normal seasonal adjustments.
The significance of unemployment data, aside of course for the impact on individuals who have been thrown out of work, is that it is an indicator of the degree of spare capacity or 'slack' in an economy.
In classical economics, if unemployment falls too low, the bargaining power of the workforce increases, pay settlements rise and inflation follows. By the same token, if unemployment is rising, workers will be more concerned about their jobs, be less likely to press for higher wages, and may therefore be much more cautious about their spending and borrowing, putting a damper on economic activity.
The fulcrum point between these two undesirable outcomes is known as NAIRU (non-accelerating inflation rate of unemployment). It's anyone's guess whether or not the UK is at or anywhere near this level just now, and it is worth pointing out that the globalisation of labour markets and the impact of commodity price levels means that this magic number is even harder to calculate than usual.
Interestingly, this is one statistic the US probably does better than anyone, because it concentrates not on unemployment, but on job creation. Here the key statistic is the absolute number of jobs on offer outside of the (highly seasonal) agricultural sector - the so-called 'non-farm payroll' number. This has the benefit of being both positive and unencumbered with emotive baggage harking back to the Great Depression. It's perhaps time the UK followed suit.
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