The cost of youth unemployment

Paul Gregg and Lindsey Macmillan

In hard times, young people face two hurdles to finding work.  First, firms tend to hold onto their existing experienced staff but stop recruitment to reduce their workforce. This collapse in new vacancies hits young people hardest. Second, with more unemployment comes more choice of potential employees for firms who are hiring. Firms favour previous experience placing young people in a catch 22 situation of not being able to get the experience they need to get work because they can’t get the work in the first place. For the least educated or those who are unlucky enough to experience long periods out of work now, it is increasingly hard to get that break that opens the door to the labour market.

As the number of youths who are out of work continues to rise the exchequer is left counting the cost. Each 16-17 year old in receipt of benefits costs an average of £3,660 a year whilst each unemployed 18-24 year old who claims costs an average of £5,600 a year. Even though many young people don’t claim benefits, just 19% of 16-17 year olds not in education or employment and 65% of 18-24 year olds with the sheer number of young people out of work, plus the additional tax and NI revenue lost through the lack of earnings, the numbers are non-negligible. In total, the current cost of youth unemployment to the exchequer is £5.3 billion per year. The productivity loss to the economy, often calculated as the wage foregone to measure the output lost, is £10.7 billion. The large numbers not claiming benefits and the low value of benefits relative to potential earnings makes an important point that work incentives are very strong for this group.

On top of these current costs, there are also long-term scars to youth unemployment in the form of future unemployment spells and lower wages. We can see from previous generations’ experiences of youth unemployment that the longer the period spent out of work in youth, the more time spent out of work later in life and the lower potential wages were when in work. This evidence on the future costs of youth unemployment comes from two UK birth cohorts that track all babies born in a window for the rest of their lives. By chance, the participants in the first cohort were aged 21 when the 1980s recession hit and in the second cohort, the participants were aged 20 when the 1990s recession hit. Around one in five young people in the first cohort spent over 6 months out of work before age 23, and it was similar in the second. Furthermore these people spent about 20% of their time unemployed 5 years later and 15% even 12 years later.

For males in the second birth cohort, an extra month out of work before age 25 raised the proportion of time out of work between age 26 and 30 by three quarter of a per cent; an extra year out of work in youth led to 10 months more unemployment later in life. It is a very similar story for wages with an extra month unemployed when young associated with 1% lower wages in their early thirties. It’s possible that these legacies may not reflect just the pure effect of youth unemployment but also that those experiencing more unemployment are less well educated and come from deprived backgrounds. The great advantage of the birth cohort studies is that so much is known about the young person’s childhood from their education to their attitudes and beliefs, their health, their wider circumstances and almost as much is known about their parents.  The evidence suggests that about half of the later lower wages and higher unemployment exposure stems from these background differences between people and about half is a result of the unemployment itself.

The cost to the individual’s future is therefore large. However, it doesn’t end there. There is also a future cost to the public purse in terms of future benefit claims and tax revenues lost from lower earnings as a result of this scarring. Estimates from the second birth cohort suggest that the average unemployed young man will cost the exchequer a further £2,900 in future costs with the average unemployed young woman costing £2,300 a year. Aggregating these up in the context of the current youth unemployment crisis leads to further future costs to the exchequer of £2.9 billion. The future productivity losses in terms of output lost are estimated to be £6.7 billion. If we add the exchequer costs together to give the combined future and current costs of youth unemployment (discounted to adjust future costs to be equivalent to today’s) the total cost to the exchequer is therefore £28 billion. These numbers suggest that doing nothing about youth unemployment is and will continue to cost us dear.

Statistical myopia, measures of unemployment and economic reporting

Neil Davies

Today the ONS published a statistical bulletin of labour market statistics, which was widely reported as evidence of an increase in unemployment.  However, the executive summaries provided by the ONS did not include sufficient information about the precision of the statistics.  This led newspapers to report ‘changes’ in important features of the economy, such as the unemployment rate, that may in fact be due to chance.

Labour market statistics, provided by the ONS, are estimates, not exact measures.  The statistics are   calculated from surveys of thousands of people.  This means that the statistics are subject to sampling variation.  Therefore, if the ONS were to repeat their survey and calculate all their statistics on a different group of people we would not expect them to be the same.  The ONS provide estimates of the size of this variation in additional tables: they estimate the range in which their statistics would be expected in 95% of samples.  However, these ranges are not reported in the executive summaries, or in the much of the discussion of what the statistics show.  The findings of the ONS bulletins are faithfully reported to the public by newspapers, but unfortunately without a measure of sampling variability, it is not possible to tell if the level of unemployment has changed, or if the reported change is consistent with chance.

The summary of latest labour market statistical bulletin reports the following statistics, to which I have added confidence intervals using the measures of sampling variation provided by ONS later in the document:

• The employment rate for those aged from 16 to 64 for the three months to November 2010 was 70.4 (70.0, 70.8) per cent, down 0.3 (0.0, 0.6) on the quarter.  The number of people in employment aged 16 and over fell by 69,000 (-62,000, 200,000) on the quarter to reach 29.09 (27.53, 30.64) million.
• The unemployment rate for the three months to November 2010 was 7.9 (7.7, 8.1) per cent, up 0.2 (-0.1, 0.5) on the quarter.  The total number of unemployed people increased by 49,000 (-37,000, 135,000) over the quarter to reach 2.50 (2.42, 2.58) million.
• There were 157,000 (137,000, 177,000) redundancies in the three months to November 2010, up 14,000 (-14,000, 42000) on the quarter.
• The inactivity rate for those aged from 16 to 64 for the three months to November 2010 was 23.4 (23.1, 23.7) per cent, up 0.2 (-0.1, 0.5) on the quarter.  The number of economically inactive people aged from 16 to 64 increased by 89,000 (-26,000, 204,000) over the quarter to reach 9.37 (9.23, 9.50) million.

There are 7 estimates of change in levels.  All seven of these changes are consistent with what might be expected from sampling variation, so the statistical bulletin provides no strong evidence of a quarter on quarter change in any of these statistics.  The statistical bulletin contains further statistics that report the change in employment in sub-groups of population, by age or by region.  Each of these sub-populations is smaller, and hence less precisely measured.  Therefore estimated changes in unemployment in sub-populations, such as youth unemployment, are more likely to be due to sampling variation.  However, we cannot know, as the sampling variation of these sub-populations are not provided by the ONS, so it is not possible to tell if these differences are important, or if they are just due to chance.

Understandably, given the executive summaries of the statistical releases, newspapers report that unemployment is rising, when the data do not support this.  This leads newspapers to miss the bigger story: unemployment is still very high after the recession, and there is little evidence of falls in employment.  The ONS could help by stating confidence intervals in their statistical bulletins to enable journalists to easily interpret whether the information in a report is consistent with chance, or if there is evidence of a genuine change.  We know long term measures of unemployment, for example annual measures, with much more precision, because we have larger samples, so if measures of precision were to be more widely reported then debates over the economy might be slightly less myopic.

The season of goodwill

Sarah Smith

Charities might rightly feel that they have had a tough year. First the recession which many charities claim hit their donations. Then, the announcement of public spending cuts which will affect thousands of charities which rely on government funding.

The festive season should therefore bring a brief respite and provide a temporary boost to charity incomes as this is the time of year when people really do dig a little deeper and give more to charity than during the rest of the year. The chart below shows average weekly household donations to charity for each month in the year – there is a spike in march/april, coinciding with the end of the tax year, but a greater spike in December. Santa, it appears, has a greater effect on giving than the tax man. These averages are for households that actually give to charity; the proportion of households who give is also slightly higher in December than at other times of year, but it is the amounts that people give that show the biggest increase at Christmas. The average weekly amount given is nearly £12 in December – more than twice the average amount over the preceding three months.

Source: Living Costs and Food Survey, 2008

It is hard to say exactly what accounts for the festive increase – other than it being the season of goodwill to all men. Some of it may be religiously motivated; the evidence shows that religion is strongly associated with charitable giving and that people who are religious are more likely to give to charity and to give more. Yet as religiosity has declined in the UK over the past thirty years, Christmas giving has remained high and, if anything ,has increased over time. In 2008 (which is the latest year for which we have data) giving in December was 60 per cent higher than the average over the rest of the year; thirty years ago (over the decade 1978-88) it was roughly 16 per cent higher.

As part of the Big Society, the government is keen to encourage charitable giving. Research that we carried out on behalf of HM Treasury showed that tax incentives are not particularly effective at encouraging people to give more. The majority of people do not respond to changes in tax incentives by changing how much they give, although this does mean that Gift Aid style incentives that allow the charities to claim back the tax paid on donations can help to boost charities incomes (more than rebate-style incentives which rely on donors to adjust their giving). Understanding the December effect could give insights into what motivates people to give and be used to design more effective policies. As charities enter 2011 facing up to the reality of cutbacks in public spending both they and the government will be keen to ensure that higher giving is not just for Christmas.