I got 2 “best in section” cups in the North Cheshire Photographic Society Annual Exhibition.
And a Very Highly Commended
Plus a few other minor awards. I came equal third in the points table.
I got 2 “best in section” cups in the North Cheshire Photographic Society Annual Exhibition.
And a Very Highly Commended
Plus a few other minor awards. I came equal third in the points table.
I live in Stockport and I am often surprised about housing costs (buying or renting) being quoted. I “sort of” knew that London and the South East are more expensive. This article collects together some information revealing some big differences.
My view now is that London is such a special case that it should always be analysed and quoted separately. The impact on people, and the policies that might be needed, shouldn’t be lost by considering only broader averages such a “region” or “country”. The experiences of people in London can’t be generalised to England or the UK, and English or UK averages don’t reflect the specific problems in London.
(Caution: different sources give different numbers, and all the numbers vary significantly over time. But in all cases London stands out as a special case).
Renting costs and buying prices for houses are shown for London and the next 3 biggest cities. (Plus Stockport, where I live!) Renting costs are from Rentright Ltd (February 2013), and buying prices are from BBC’s UK house prices July to September 2012. (Some other sources show a smaller renting cost ratio between London and the rest).
The heights of the columns are relative to London’s, which are therefore 100%.
This shows “first time buyer deposits as years of saving capacity, two person household”, from “Oxford Economics - Housing Market Analysis July 2011“.
Apart from showing that London is a special case, this also shows that an average for England is not very representative of either London or a number of other regions. Such an average exaggerates the problem for people in the “North”, while under-estimating the problems for people in the “South”, especially Londoners.
(Or put another way, this shows that experiences of Londoners don’t represent the experiences of people elsewhere, especially in the “North”. To a lesser extent, the experiences of people in the “South” generally don’t represent the experiences of people in the “North” either, or vice versa).
The average percentage of households owning their own homes (often with a mortgage) is less than the nearly 80% of some older cohorts, and various sources show that the percentage is typically dropping. The effect in London is much more pronounced than elsewhere. (From “Oxford Economics - Housing Market Analysis July 2011” 2010 values).
Not only do costs differ between London and the rest, but average wages do too. These values are taken from “Changes in real earnings in the UK and London, 2002 to 2012” (Figure 1: Median hourly earnings excluding overtime of all employees, UK and London) published by the Office for National Statistics 2013.
Since this UK value includes the London groups, the UK value excluding the London groups is presumably somewhat lower. Once again, this graph reveals that London is a special case. (This graph does not take into account people without work).
Here is another major difference between London and the rest: Growth in output.
Even here, London is a special case, emphasising that analysis should represent London separately from the rest of the UK.
An engineer’s observation:
All humans make errors; all human processes sometimes result in errors.
Guns amplify human errors.
This was triggered [sic] by this news article:
There were (at least) two very different sorts of error:
When someone says “guns don’t kill people, people kill people“, is that supposed to make me feel better?
No! If people can amplify their errors with guns this scares the shit out of me!
People concerned with the difficulties faced by young people wanting houses will probably be examining the latest English Housing Survey. As expected, there are some misleading news articles:
News articles quite accurately point out that people under 35 only own about 10% of the houses. An important missing question is: “how many should they own?“ Here is a more informative view. This graph comes from the tables released with the survey; the orange columns show how 100% of the houses are spread over various age ranges:
It is seen that the headline is really “people aged 25 to 34 only own about 10% of the houses”. I doubt if “people under the age of 25 only own a small percentage of the houses” is particularly noteworthy. It would be far more surprising if they owned a lot!
(The “55-64″ age range which looks smaller than expected comprises people born about 1948-1957. In other words, this is part of what is often called the “baby boom”).
I think it is more interesting and useful to concentrate on people 25 and over. With an average age at end of full time education of about 19, and the need to work for a while to get money for a deposit and qualify for a mortgage, this is where anguish begins. These are the young people who are worried that they may be in their 30s or 40s before they get a house, if they ever do.
So here is a graph that imagines that the important potential house-owning population are those aged 25 and older. The orange columns are 100% of the houses, (except for the tiny percentage owned by the 16-24 group), as in the graph above. The blue columns are 100% of the people of 25 and over. This graph shows how these are spread over various age ranges.
In other words, if the percentage of houses owned by each age range were exactly the same as the percentage of this age range in the “25 and over” population, houses would be spread evenly across all ages, and the orange and blue columns in an individual age range would be the same height. The graph shows that the spread is not even.
There are only two parts of this graph which significantly stand out:
Is that it? Are these young people doomed to only half the house-ownership percentage that would be expected from their percentage of the population? Will this cohort only ever own half as many houses as older 10-year cohorts? That is certainly a major concern both of these people themselves and of anyone interested in intergenerational fairness.
It won’t be as bad as that, because no 10-year cohort reaches its peak house-ownership while they are aged 25-34. Here is a graph from “The effect of baby booms on the housing crisis of younger people“.
The mapping of birth dates to ages at 2012 is:
Look at the 1956-1965 cohort: its percentage of house-ownership has been rising for 3 decades or more. First-time buying hasn’t been stopping at 35 before now. It is unlikely to have stopped at 35 with younger people.
The average age of first time buying is certainly increasing. (One of several factors is the increased average age at end of full time education). I predict that house buying will be spread over decades, like early cohorts. (I wonder if it will be spread over more years, just as education and having children are spreading over more years as life expectancy increases?)
I also suspect by examination of the graphs that today’s younger people won’t reach the 80% house-ownership of some earlier cohorts. But this is really guesswork because it is decades away.
It should be blindingly obvious that comparing trends in house prices with trends in food prices is not justified. It is hard to believe that the people writing and promoting such articles honestly believe it is justified – it would raise the question of how they had enough working brain cells to operate a word processor!
In fact, of course, they probably don’t believe it is justified, and I hope their readers don’t either. It is an interesting (but probably fruitless) way of making a point about house prices, as long as their readers are not analytical.
Why compare with food? Why not compare with computer chips? Although Moore’s Law isn’t exactly related to prices, it is interesting to see what food would cost had it halved in price every two years for 40 years. They don’t make coins small enough to pay the current price of a what a chicken would be! And a house that cost £30,000 in 1972 would now cost 3p.
Or: try comparing trends in house prices with trends in the times and costs of building railways. I suspect the Victorian railway builders would raise their eyebrows at the quoted costs and times (20 years) for building the HS2 railway. Yet the nature of the project is somewhat closer to the nature of building sufficient houses (on sufficient land) to satisfy the housing needs of young people and bring the prices down via the law of supply and demand.
There is no logical reason whatsoever to expect house prices to track the prices of computer chips, food, motor cars, or any other mass-produced commodity items that don’t rely on such a limited resource as land. Such comparisons are a distraction from attempting to solve the real problems.
Previous posts have provided graphs of the proportions of various groups in the electorate:
I want to publish a graph with two more age groups plotted, because these groups are discussed either alone or in comparison with other age groups. It is often unclear in discussion whether it is a general age group at a particular time or a cohort defined by birth dates that is being discussed. Here they are age ranges; obviously their members currently overlap a lot.
Rather than update those earlier posts, I’m publishing an extended graph below. This graph is a super-set of the others; the plots for the previous 4 groups are unchanged:
The reason for publishing a graph of the percentages of these groups in the electorate is to enable the potential extent of their political influence to be discussed. But (as with the 1945-1965 cohort myths 2 & 3) the political influence of any age group or generation or cohort is often greatly exaggerated and mis-understood.
People born since 1979:
This became larger than the pre-1945 group about 2009. It became larger than “Pensioners” in 2012. It will be larger than the 1945-1965 cohort (often misleadingly called “baby boomers”) by 2015.
People under the age of 35:
Because I’ve treated this as an age group rather than a generation or cohort it only changes slowly over decades. It has been a larger group than “Pensioners” for many decades, but this may change after about 2020 because the trends of these two groups are in opposite directions. By 2020 it will be slightly larger than the 1945-1965 cohort, but it will be nearly the same even before then.
My difficulty (mentioned above) in deciding whether “generation” discussions are about age ranges or cohorts or something else is similar to a criticism of Jilted Generation by James Wilhelm in Intergenerational Justice Review 2012, issue 1 (Page 29). “Given the singular importance of the “generation” concept, a more rigorous discussion and justification for this choice would have been welcome in the opening chapter. Although a few supportive graphs with accompanying commentaries are utilised, a reasoned discussion of why the specific definition of the “generation” concept was adopted does not feature.”
(Once again I’ve used the animation published by the Office of National Statistics. The graph was plotted using values at intervals of 5 years. Percentages after 2012 are estimates.)
It is well-established that the average age of first time house buyers is greater than it was a few decades ago. This graph is from today’s BBC article Have young people never had it so bad?
There are various reasons for this. One reason that tends to be neglected is that the average age of the end of full time education is also greater than it was a few decades ago. If one of the factors involved in buying a house is the number of years spent earning money to contribute to a deposit on the house, then there would naturally be some correlation between the two trends.
Example: I was born in 1947 and bought my first house in 1975 (aged 28), at the left of the above graph. About 75% of my year went to a Secondary Modern school and left full time education at 15. (On the council estate where I lived at the time, many children were not entered for the 11+ because their parents wanted them to start work at 15!) About 5% of us went to university (my parents were unusual). So the average age at the end of full time education was months over 15.
Now the minimum school leaving age (since 1972) is 16, and about 35% of people go to university. The average age at the end of full time education now is closer to 19. It was lower than this for the people born 1983 who were 29 and buying their first house at the right of the above graph. But it was at least a year or two higher than 15. I would have predicted an average age of first time house buyers now of about 28 (26 + 2) without considering any other factors. And that was my age when I bought my first house in 1975!
This is just one factor. There is a consensus that an important problem is a shortage of suitable houses, with implications for house prices because of the law of supply and demand. Another reason is a high level of youth unemployment. But the effects of all of these must surely be judged against the expectation that the age of first time house buying will naturally tend to rise as the age of the end of full time education and the entry into work rises.
(It will be interesting to see what happens after 2013 and 2014 when people must be in full time education or apprenticeships or work-with-training until 17 then 18 respectively).
1. Surely the state pension age should have risen at least as fast as the average age of the end of full time education? Why isn’t it already about 3 or 4 years higher than it was just a few decades ago, to maintain a similar average interval between starting work and claiming a pension? (This point is separate from increasing life expectancy).
2. The changing length of full time education has distorted the figures for youth unemployment, making the trends appear worse than they are:
Here is another post on the Intergenerational Foundation’s blog:
The blog post appears to have been triggered by, and certainly quotes, a shoddy article “INSURANCE OR RIGHT?“, based on 1908 pension law, at the Longevitas Ltd website. Then it appears uncritically to assume this demands an urgent national debate. The UK has been debating state pensions for the last century; why does re-examination of a 1908 law warrant such an urgent debate? What new information renders the results of previous debates invalid?
In summary, the Longevitas article says:
“At the root of this problem is the little-discussed question of whether an old-age pension is an insurance or a benefit of right. When the first UK-wide state pension commenced in 1909, a twenty-year-old male had a 34.8% chance of surviving to the then-pension age of 70. Once retired, a seventy-year-old male had a life expectancy of 8.0 years. The original state pension in the UK therefore had the hallmarks of a social-insurance system — the probability of surviving to receive the pension was relatively modest. The system as constructed was affordable not just because survival probabilities were low and life expectancy was short, but also because benefits were means-tested….
“This then raises a question: what would the state pension age have to be to restore the eight-year life expectancy of the original Old-Age Pension Act of 1908? The answer is 80 years old, and a twenty-year-old male would have a better than evens chance (54.5%) of reaching that age.”
The Intergenerational Foundation’s blog post changed this to the following:
“The UK government would have to increase the state pension age all the way to 80 if it wanted to keep the proportion of people who receive it to the same level as when it was first introduced in 1908, according to a recent article from the think-tank Longevitas.”
The Intergenerational Foundation’s blog post erroneously equated restoring the life expectancy at state pension age with restoring the proportion of people who receive state pension. There are surely some obvious questions about either comparison:
The Intergenerational Foundation’s blog post links to another blog post by the same author (David Kingman): “What can we learn about pensions from the Victorians?” These articles don’t query why we have moved on over the last century. Might there not have been good reasons, including the hardship caused by the original scheme, or the introduction of the concept of contributions and National Insurance? And they don’t discuss the perverse incentives arising from means testing, which are likely to discourage investing in one’s own future if this reduces what one can get from the state.
The state pension system needs to move forward from where we are now, not revert to a system that was superseded long ago. Any new pension system must take into account the decades of contributions via National Insurance that has entitled many millions of people to a state pension under the social contract.
Note that there is a redistributive aspect to the NI and state pension system. Higher-rate taxpayers build up years of entitlement at the same rate as lower-rate taxpayers, and with the new flat-rate scheme being introduced this is more pronounced because the extra state pension that better-off people could accumulate no longer exists. (And, of course, state pension is taxed as income).
I don’t know enough to judge whether this is scare-mongering or credible. The Institute and Faculty of Actuaries claims “New research from the Institute and Faculty of Actuaries shows that continuing to ignore resource constraints may have substantial financial, political and social costs“.
The report itself and its evidence are contained in these PDFs:
I found this via New Scientist, which says:
“Aled Jones of Anglia Ruskin University in Cambridge, UK, and his colleagues drew together evidence about a wide range of environmental problems, from water shortages to atmospheric pollution to climate change. They plugged these into models used to predict the values of pension funds.
“Jones ran several scenarios, varying how quickly governments and industry responded to environmental problems. The results are published by the UK’s Institute and Faculty of Actuaries (IFA). In almost all cases the value of funds began to fall before 2100. In the worst-case scenario, where governments and markets did nothing, values dropped steeply from around 2020 and fell to zero by 2050.”
These are comments on “Spending Power Across the Generations” by David Kingman, published on 23 January 2013 by the Intergenerational Foundation. I was directed to the report as follows:
So a more accurate title would be: “Some recent trends in spending behaviour by different age groups”.
I was working on this section before I knew about this report. I’m publishing it here because this report is mostly an example of the first way of comparing generations below, not the second way. (However, the report also adds “trends over about 10 years”, and these diagrams do not deal with trends).
It is easiest and tempting (especially for younger people observing older people) to compare different generations at the same real date, for example 2013:
The obvious problem is that people in the 2 generations are at different life stages, and however fair the system is the comparison will show massive differences. That is life! Trends will be different for different generations if only because some changes matter only to one generation and some only to the other. (A change to the cost of end-of-life care only affects Generation P while a change to the cost of education only affects Generation Q).
Perhaps the main valid use for this sort of comparison is for marketing purposes, deciding what products to make and how to promote them.
Comparing different generations at the same life stages may defuse some resentment. For example, comparing the age 15-25 stage of people born 1945-1950 and people born 1980-1985 will show startling differences. About 75% of people born 1945-1950 left school at 15, another 20% finished full-time education by 18, and only 5% went to university. This contrasts with a minimum school leaving age of people born 1980-1985 of 16 and 35% going to university. It puts so-called “free university” for the 1945-1950 cohort into perspective.
But while this may defuse some resentment, the differences are likely to be so wide-ranging and dramatic that few lessons can be learned. And how many young people really care about the early struggles of people decades older than them? They have their own current problems, and may lash out verbally in frustration and anger anyway.
These are comments on “Spending Power Across the Generations” by David Kingman, published on 23 January 2013 by the Intergenerational Foundation.
I believe for the reasons below that the report doesn’t make its case. Whether or not any of its assertions and conclusions are true needs information and analysis not included in the report and which may not even exist.
There are 2 main uses of “generation“: familial (biological) generation, (not applicable in this report), and social generation or generational cohort. While the latter is often used in the context of intergenerational issues, for example “baby boom generation or cohort”, “Generation X”, “Generation Y”, “Millennial Generation”, that meaning is not being used in this report.
This report talks of people mostly in terms of age ranges, for example “pensioners”, “under-30s”, “working-age people”, “young people”, “People aged 50–74″, “people aged 65 and over”, “people aged 16–34″, “people aged 55-64 and 65+”, “all of the age groups below 45″, “People aged 65–74″, and “the over-75s”. (I spotted 2 generational cohorts: “the generation born before World War Two” and “baby boomers”).
This is not a trivial point, because over time an “age group” behaves very differently from a “cohort”. The individuals in a particular cohort stay the same (except for dying), while the individuals in an age group are a fluid set. This can have important, and sometimes counter-intuitive, consequences:
One consequence of the use of age groups instead of (generational) cohorts is that statistics about the age group over time do not necessarily reflect the life-experiences of the individuals passing through that age range. This is important for this report because it shows trends over about 10 years.
(An obvious consequence of having such a large variety of age ranges in the report is that the individuals being talked about in one paragraph are often not the ones being talked about in the next! The theme of the report is vaguely “young = unfortunate” and “old = fortunate”, where “young” and “old” are ill-defined).
The report discusses spending on just 4 items: “Theatres and Cinema Tickets”, “Overseas Travel”, “Food and Eating Out”, and “Driving and Petrol”. The assumption appears to be that a fall in expenditure in these is caused by reduced disposable income while a rise is caused by increased disposable income. Like so many arguments used in intergenerational analysis, this is an obvious example of the cum hoc ergo propter hoc and/or post hoc ergo propter hoc fallacies.
A personal example: throughout much of my career I was something of a workaholic. Despite (then) being a highish-rate tax payer, I spent little on those items, partly because I simply didn’t want to spend my time on them. (I didn’t learn to drive until my early 30s so the “driving and petrol” item wasn’t directly relevant. I bought my first car out of income. I bought my latest car at 63 out of life savings). Now that I’m 65 and retired I still spend little of my income on them, preferring to spend my time and money on such things as house improvements and my main hobby (photography).
The inclusion of these 4 items says more about the interests of the author of the report than about society as a whole! They are not all the “important categories” he claims. Obviously “food” matters, but not “dining out”. Surely “savings and pensions” have to be included? Clothing and footwear, recreation and sports, household goods and furniture? And gas, water, and electricity, all of which have a discretionary element. “Transport” would be a better item than anything implying possession of a motor car, and to be fair the report does include public transport. And the magnitudes of this spending and these trends matters a lot, for example:
There are various reasons why spending on these items varies from person to person and/or over time. Spending on these items proves little about “spending power“, despite assertions, but mostly about “some spending decisions“.
(Note: I’m not denying the possibility that there is a causal relationship between actual spending power and these spending decisions; simply that the report itself doesn’t make the case).
The report concludes “This analysis supports the view that the older generation have enjoyed more favourable economic conditions during the first part of the 21st century”. I wish! It has economically been the worst decade of my adult life. But now that 38 years of mortgage payments are over, and I’m willing to spend my life-savings, and I’m getting my state pension, I’m comfortable. Appearances can be deceptive.
Although the report is not explicitly stated to be about intergenerational unfairness it is likely to be read that way. I’ve used “A checklist for Intergenerational Unfairness” to see whether it can plausibly be read as evidence of intergenerational unfairness.
1. Is there more than one generation?
There are lots of age groups rather than generations, but I won’t quibble. The report has something to say relating to people of different ages.
2. Is it intergenerational?
Is it concerned with “relationships between children, youth, adults and seniors, particularly in terms of treatment and interactions“? Is there an element of cause and effect?
No. I don’t think the word “intergenerational” should be used about this report. (There is only one insignificant use within the text: “Restaurant bills also proved to be weighted intergenerationally”. But the report is published by the Intergenerational Foundation which is cited throughout it).
3. What is fair?
The report doesn’t identify by analysis what fair numbers would be. Therefore it cannot be said whether the trends imply unfairness. They may just be things the author doesn’t like.
4. Have the people concerned been consulted?
Apparently not. Their spending was sampled, but not their reasons.
My comments on this report are similar in several ways to those in “Commentary on “Intergenerational Fairness Index” by the Intergenerational Foundation“. This probably arises from a failure to start with a properly formulated hypothesis, then, in addition to identifying what supporting evidence is needed, to identify what evidence is needed to refute alternatives. This failure makes the process more like theology or ideology than science.
It is hard to deduce a person’s spending power from the narrow set of items covered by this report. There are too many other things that people may or may not spend their money on. (I don’t use a mobile phone except for emergencies, or have a smart phone or an iPad or mobile computing of any sort, in spite of being a webmaster for several websites, blogs, and social media accounts). Priorities change over generations.
The large variety of age ranges covered in the report gives the impression of having to grab whatever data can be found, rather than using data specifically to test the hypothesis.
I believe this report is really about:
“Some recent trends in spending behaviour by different age groups”.