Working in a low-paid dead-end job in a call centre, living with the parents and approaching 30 an old friend of mine made a decision – to pack their bags and head for New Zealand on a 12 month work visa. This was a few years back and they haven’t looked back, moving after their first year to Australia.
And they’re not the only one. Recently I’ve noticed more and more people have been following in this intrepid friends footsteps, in fact rarely a day goes by without hearing about some other person moving to Australia. But what do the stats have to say?
My first stop is the official statistics produced by the Australian Department of Immigration and Citizenship. What I’m interested in particularly is the numbers of working holiday visas – these are the ones granted to young people aged 18-30 and which last 12 months.
And here it is:
Though the figure has fallen slightly for 2009/10 the trend over the period shows a gradual increase suggesting that in the past few years an increasing number of young people are taking the opportunity to leave the UK for Australia using a Working Holiday visa.
Rather interestingly the graph shows the peak period for the number of Working Holiday visas granted was in 2008/09 coinciding with the recession. During this period some 40 182 Working Holiday visas were granted to UK citizens.
Part of the explanation may be the rising popularity of a ‘gap-year’, but as the visas are open to all people aged for 18-30 there may be another group taking increasing advantage of the Working Holiday visa programme; Twentysomethings who lack ties such as a family or mortgage (due to their unaffordability) and who find career aspirations unfulfilled, either through unemployment or the growth of the dead-end job and who therefore find both possible and attractive the prospect of leaving the UK.
It’s easy to knock the project of to measure the nations well-being – indeed it’s been variously dubbed pointless, a waste of money or an exercise in stating-the-bleeding-obvious whilst there have also been questions about how reliable a measure of well-being asking a person to gave a rating between 0 – 10 is.
This graph however, puts the whole project into context:
The graph shows what appears to be a strong correlation (R = -0.88) between the suicide rate and reported levels of life-satisfaction when these are organised in age categories.
What this suggests is a spectrum of well-being; In terms of age for groups where the overall average level of life satisfaction is lower rates of extreme emotional distress, as indicated by suicide, are correspondingly higher.
The importance of well-being therefore cannot be overstated.
Can statistics make you happy? Maybe if you’re a stats geek like me, but seriously can the path to happiness, or at least some insights into the path to follow be found through the use of statistics? The Office for National Statistics (ONS) have been engaged in work to create a quantitative measure of our national well-being and despite some criticisms in the mainstream media, along the lines that in many cases it was either pointless, or a case of stating the obvious, the work, carried out on a large scale, has produced some interesting results and points to a number of areas for future research. As the well-being data has been collected through the Labour Force Survey the analysis so far seems particularly revealing about the work we do, or indeed don’t do (though this is perhaps also a weakness as the data reveals less about other non-work factors) and in this post I will be dealing primarily with these issues of work status, occupation type and their relationship with life-satisfaction.
The most immediately striking thing about the well-being stats is the affect of age. According to the ONS figures well-being follows a ‘u’ shaped curve according to age as shown by this graph referring to responses to the question ‘Overall, how satisfied are you with your life nowadays? in which respondents were asked to give a rating on a scale of 0 -10 with 0 being not at all and 10 being completely.
What could be the reasons for this similarly high ratings given by members of the older and younger age group? One thing both groups also have in common is their level of satisfaction of the amount of free time they have. When asked ‘if they were satisfied with the amount of time to do the things that they like doing’ both younger and older people reported the highest levels of satisfaction.
It is quite likely that these higher levels are chiefly because both groups are less likely to have family commitments, or to be engaged in paid-work; For younger people this is because they are still in education, whilst for the older age group many of those aged 65+ will be retired from paid-work.
As a slight aside an interesting observation is that whilst in general life satisfaction appears to increase with age, this actually declines for the 80+ age group. There may be a number of possible explanations for this; one being poor health, which is in the ONS analysis also implicated in lower levels of well-being, or an alternative may be that social capital declines at this age leading to isolation.
So in terms of work is it that not working the answer to happiness? Well, not quite. The well-being statistics also showed that unemployment has a significantly detrimental impact on the level of well-being reported by an individual with 45% of unemployed people rating their life satisfaction as low (5-6), or very low (0-4). This compares with a much lower figure of 20% for people in employment whilst for economically inactive people this figure is 27.1% However, this latter category includes people who are caring for a relative, looking after children, or who are unable to work due to illness/disability along with students, the idle rich and retired people, who we may possibly expect to have higher ratings – indeed more people in the economically inactive group, some 30.5% also rated their life satisfaction as high (9-10) compared with 24.4% of employed people, and 16.3% of unemployed people suggesting this is a rather bifurcated group.
Because of this wide variation among the ‘Economically Inactive’ group it is particularly hard to reach any conclusion without breaking down the category and though we can clearly see that being employed is clearly far more preferable from a well-being perspective to being unemployed – something which may well be due to the stigma and low status of being in the unemployed group – an interesting comparison to make would be between the unemployed and the idle rich.
But can the type of work we do have an effect on well-being – yes, according to the ONS analysis which states that in terms of the ‘life satisfaction’ ratings, and sthe ‘how happy did you feel yesterday’ question.
higher scores appear to be given by the occupational groups who tend to have more responsibility and control over their work, as well as higher incomes (which were not controlled for in this analysis)
This seems to align the findings of the Whitehall II study, based on a sample of 10 308 civil servants, which found that low levels of control at work had a particularly detrimental effect on health. A (2004) pamphlet explaining the results of the research, which was carried out between 1985 and 1998, states:
While it is common for demands to increase as the occupational hierarchy is ascended, degree of control over work decreases with lower position. Whitehall II provides ample documentation of this: the lower the grade of employment, the less control over work. This combination of imbalance between demands and control predicted a range of illnesses. The evidence from Whitehall II suggested that low control was especially important. People in jobs characterised by low control had higher rates of sickness absence, of mental illness, of heart disease and pain in the lower back.
Whilst there is likely to be a correlation between level of control and remuneration as this was not controlled in the analysis it is not possible to tell form the data if higher levels of pay alone can increase well-being. One interesting finding however, is that those in the occupational group ‘caring, leisure and other service occupations’ as well as those in ‘professional occupations’ achieved the highest average response to the question ‘overall, to what extent do you feel the things you do in your life are worthwhile’ at 8 out of ten. the lowest averages were reported by ‘sales and customer service occupations’, ‘process plant and machine operatives’, and ‘elementary occupations’ who all averaged 7.5.
This would seem to suggest that work which involves a level of altruistic motivation, or else purports to serve a higher purpose, is beneficial for overall well-being, compared to work in which financial reward is the primary, or sole motivation. This finding is particularly relevant to questions into the role of social purpose, or public service in work and in organisations in general. Could it be that individual well-being is enhanced within organisations such as social enterprises, or other voluntary organisations where there is a strong sense of social mission?
In terms of the ONS well-being data it would appear that both younger and older persons, groups who due to their respective ages tend not to be engaged in full-time paid work, report both higher levels of life satisfaction, and higher levels of satisfaction with the time to do things. Though it is not necessarily the case that it is simply full-time work that results in lower levels of satisfaction in both measures for the other age groups, and it may certainly be the case that other commitments such as looking after children also play a role, it does seem possible that full-time work, can result in dissatisfaction with the time a person has to do things and this in turn may well be linked to the corresponding lower levels of reported well-being for these age groups. Certainly this is an area where future research may be directed as the ONS analysis does not include any details on the relationship between well-being and hours worked, or with a persons satisfaction, or not, with the hours they currently work.
Finally It is also important to note that the LFS does not collect data on voluntary work. It may be the case that, particularly among the retired group, voluntary work may play a key role in well-being. A 2005 Joseph Rowntree Foundation paper Volunteering in Retirement, suggests that voluntary work can be particularly beneficial for the health of retired people. As mentioned the ONS analysis seems to suggest that work which performs a higher purpose is beneficial to well being therefore it may be interesting in particular to analyse the role of voluntary work, or more widely make a comparison of well-being levels between workers in the voluntary, or public sector and the private sector.
Ferrie, J. (2004) Work, Stress and Health: the Whitehall II study CCSU/Cabinet Office
Office for National Statistics (2012) First ONS Annual Experimental Subjective Well-being Results 24th July 2012
Office for National Statistics (2012) Measuring National Well-being –
Measuring young people’s well-being 10th October 2012
Smith & Gay (2005) Active Ageing in Active Communities; Volunteering and the Transition to Retirement Bristol: The Policy Press
This graph was produced to analyse the relationship between a teams form and attendance at football matches as part of an investigation into the factors influencing attendance at football matches.
The key question was; Did a winning streak attract higher crowds, or conversely did a losing streak repel them? I obtained some data for Havant and Waterlooville FC which included attendance figures and results for a number of past seasons. Choosing 2009/10 and 2010/11, the last two complete years at the time, I then excluded data from cup competitions as attendance for these games varied greatly depending on the prestige of the tournament and the level the opponents played at.
The match attendance for each league game, some 42 in total, is represented by the red line whilst the blue line represents a measure of the teams form at that point in time. I created a measure of the teams form by compiling the results of the previous five league games; Awarding 1 point for a won, 0.5 for a draw and 0 for a defeat I calculated a ratio so that say if the team won all their last five games the ratio would be 1.0, but if the team won two, drew one and lost two the ratio would be 0.5.
I then plotted both sets of data on a single graph.
Whilst not a perfect fit the graph does seem to suggest that there is at least some kind of link between form over the previous five games and matchday attendances. Other factors almost certainly come into play in determining attendances. It may also be interesting to see what the measure of form can be tweaked to be a shorter, or longer time period, or maybe also made to include goals scored or conceded.
This line-graph came about as part of an investigation into the impact of ground-sharing on the attendance figures of the football clubs involved following an accusation made by a fan of Kingstonian FC that sharing a ground with AFC Wimbledon was having a detrimental effect on their clubs attendances.
As part of the analysis, which can be seen in full on my Row Z blog, I decided to look at what is perhaps one of the longest ground-sharing arrangements in the upper-reaches of English football; Between 1985 and 2003 Selhurst Park, home of Crystal Palace FC, also hosted Charlton Athletic (1985-1991) and Wimbledon FC (1991-2003).
On the graph I have plotted the average attendance figures for Palace and their respective tenants. Rather than seeing a relationship where rises in one clubs attendances corresponded with falls in the other clubs attendances (which we would expect if ground-sharing was having a negative impact on one club) it seemed that over the long-term both sets of attendance figures were rising – the nosedive of the ‘tenants’ attendance at the end of the graph is the result of the clubs 2001 announcement that it would be seeking to relocate to Milton Keynes.
One explanation for the long-term upward trend is the general rise in attendance at football games which took place at the same time. 1985, the year the graph begins, was a low-point for English football attendances; the net result of years of hooliganism and poor facilities.
Plotting the line of average football league attendances on the same graph we can see how despite fluctuations, over the long-term the attendances of Palace, and whoever there tenants are follow a very similar trajectory. If we calculate the correlation coefficient for Palace’s attendances and the league average we get a moderate-to-strong 0.64 which suggests that the variations in overall league attendances explain 41% of the variation in Palace’s attendances over the period shown.
Ultimately the lesson from the graph is that when it comes to football attendances over a long-term period a rising tide really does lift all boats.