Some numbers about the EU

The latest figures (January 2014) from the European Central Bank (ECB) statistics pocket book have just been issued, providing comparisons between European Union (EU) countries, both in the Eurozone and outside it, on a range of measures. And some of these comparisons are not quite what I expected to see.

For instance, perhaps surprisingly in view of the current hysteria in the UK about economic migrants from Bulgaria and Romania, we find that unemployment was lower in Romania (7.3%) than it is in the UK (7.4%) for the latest month (September 2013) for which data on both was available (it’s the UK’s that is missing for October and November for reasons unknown).

I have graphed a selection of the data below, Euro countries are to the left:

ECB country data labelled

First to note, which may also surprise some, is that private sector debt in the UK is not particularly big in EU terms: Denmark and Sweden both have considerably higher private sector debt as a percentage of GDP than the UK, as do 7 countries in the Eurozone with Ireland and Luxembourg heading the list.

Government expenditure as a percentage of GDP is the most evenly distributed of all the measures. I have graphed the 2012 data, as the Q2 2013 data omitted France and Germany. The range across all countries is between 36.1% (Lithuania) and 59.5% (Denmark), with the UK’s 47.9% only a little below the Eurozone average of 49.9%. This suggests to me, for all of the political rhetoric we hear, that it is not the total spend which tends to alter much but the distribution of it. Certainly in the UK, there appears to have been a focus on a relatively small section of the welfare budget to make the savings from.

Government debt is much higher as a proportion of GDP in the Eurozone than in the rest of the EU, with no one outside the Eurozone reaching the Eurozone average of 93.4% (although the UK comes closest at 89.8%). There are 5 countries in the Eurozone with debt above 100%: Belgium (perhaps surprisingly), Ireland, Greece, Italy and Portugal. Spain’s debt is actually below the Eurozone average at 92.3%.

Unemployment statistics are unsurprisingly dominated by Greece and Spain, whose unemployment rates are around 50% higher than the next country. Unemployment rates average 12.1% in the Eurozone and 10.9% for the EU as a whole, perhaps demonstrating the advantage of keeping control of your exchange rate during an economic downturn.

The population statistics remind me what an unusual decision it was for the UK to stay out of the Euro. All the other big countries (by which I mean those with populations over 45 million) are in the Eurozone, with the next biggest EU country outside the Euro being Poland at 38.5 million (with the prospect of their joining the Euro receding somewhat last year). Most of the richer countries are too, illustrated by a much higher proportion of GDP (see below) held in Eurozone countries than their relative populations would lead you to expect.

Finally we come to GDP. This looks very differently distributed according to whether you look at amounts in Euros, or per capita, or by capita adjusted for the purchasing power in each country. The first of these is dominated as expected by the big countries of Germany, Spain, France, Italy and the UK. However, the outstanding performer when looking at GDP per capita with or without the purchasing power adjustment is Luxembourg. Eurozone countries have a higher GDP per capita than those outside (€28,500 compared to €25,500, with the gap narrowing slightly when adjusted for purchasing power).

A final thing strikes me about these statistics. As has been pointed out elsewhere, Francois Hollande is having a hell of a time considering that France’s economic performance is not that bad. In fact it is incredibly average: its Government debt sits at 93.5% compared to the Eurozone average of 93.4% and its GDP per capita when adjusted for purchasing power is bang on the Eurozone average of €28,500. France are much more representative Euro members than Germany (remarkable when you consider that the Euro was once referred to as the Deutsche Mark with a few disreputable friends) and, if Hollande’s approval ratings are any indication, the French people seem to hate that.

Carry on Clio

It’s a relatively new science, and one which binds together many different academic disciplines: mathematical modelling, economics, sociology and history. In economic terms, it is to what economists in financial institutions spend most of their time focusing on – the short to medium term – as climate science is to weather forecasting. Cliodynamics (from Clio, the Ancient Greek muse or goddess of history (or, sometimes, lyre playing) and dynamics, the study of processes of change with time) looks at the functioning and dynamics of historical societies, ie societies for which the historical data exists to allow analysis. And that includes our own.

Peter Turchin, professor of ecology and mathematics at the University of Connecticut and Editor-in-Chief of Cliodynamics: The Journal of Theoretical and Mathematical History, wrote a book with Sergey Nefedev in 2009 called Secular Cycles. In it they took the ratio of the net wealth of the median US household to the largest fortune in the US (the Phillips Curve) to get a rough estimate of wealth inequality in the US from 1800 to the present. The graph of this analysis shows that the level of inequality in the US measured in this way peaked in World War 1 before falling steadily until 1980 when Reagan became US President, after which it has been rising equally steadily. By 2000,inequality was at levels last seen in the mid 50s, and it has continued to increase markedly since then.

The other side of Turchin’s and Nefedev’s analysis combines four measures of wellbeing: economic (the fraction of economic growth that is paid to workers as wages), health (life expectancy and the average height of native-born population) and social optimism (average age of first marriage). This seems to me to be a slightly flaky way of measuring this, particularly if using this measure to draw conclusions about recent history: the link between average heights in the US and other health indicators are not fully understood, and there are a lot of possible explanations for later marriages (eg greater economic opportunities for women) which would not support it as a measure of reduced optimism. However, it does give a curve which looks remarkably like a mirror image of the Phillips Curve.

The Office of National Statistics (ONS) are currently developing their own measure of national well-being for the UK, which has dropped both height and late marriage as indicators, but unfortunately has expanded to cover 40 indicators organised into 10 areas. The interactive graphic is embedded below.

Graphic by Office for National Statistics (ONS)

I don’t think many would argue with many of these constituents except that any model should only be as complicated as it needs to be. The weightings will be very important.

Putting all of this together, Turchin argues that societies can only tolerate a certain level of inequality before they start finding more cooperative ways of governing and cites examples from the end of the Roman civil wars (first century BC) onwards. He believes the current patterns in the US point towards such a turning point around 2020, with extreme social upheaval a strong possibility.

I am unconvinced that time is that short based solely on societal inequality: in my view further aggravating factors will be required, which resource depletion in several key areas may provide later in the century. But Turchin’s analysis of 20th century change in the US is certainly coherent, with many connections I had not made before. What is clear is that social change can happen very quickly at times and an economic-political system that cannot adapt equally quickly is likely to end up in trouble.

And in the UK? Inequality is certainly increasing, by pretty much any measure. And, as Richard Murphy points out, our tax system appears to encourage this more than is often realised. Cliodynamics seems to me to be an important area for further research in the UK.

And a perfect one for actuaries to get involved in.

 

State Pension Age and its discontents

When I started writing this blog in April, one of its main purposes was to highlight how poor we are at forecasting things, and suggest that our decision-making would improve if we acknowledged this fact. The best example I could find at the time to illustrate this point were the Office of Budget Responsibility (OBR) Gross Domestic Product (GDP) growth forecasts over the previous 3 years.

Eight months on it therefore feels like we have come full circle with the publication of the December 2013 OBR forecasts in conjunction with the Chancellor’s Autumn Statement. Little appears to have changed in the interim, the coloured lines on the chart below of their various forecasts now joined by the latest one all display similar shapes steadily moving to the right, advising extreme caution in framing any decision based on what the current crop of forecasts suggest.

OBR update

However, the worse the forecasts are revealed to be, the keener it seems politicians of all the three main parties are to base policy upon them. The Autumn Statement ran to 7,000 words, of which 18 were references to the OBR, with details of their forecasts taking up at least a quarter of the speech. In every area of economic policy, from economic growth to employment to government debt, it seemed that the starting point was what the OBR predicted on the subject. The Shadow Chancellor appears equally convinced that the OBR lends credibility to forecasting, pleading for Labour’s own tax and spending plans to be assessed by them in the run up to the next election.

I am a little mystified by all of this. The updated graph of the OBR’s performance since 2010 does not look any better than it did in April, the lines always go up in the future and so far they have always been wrong. If they turn out to be right (or, more likely, a bit less wrong) this time, then that does not seem to me to tell us anything much about their predictive skill. It takes great skill, as Les Dawson showed, to unerringly hit the wrong notes every time. It just takes average luck to hit them occasionally.

For another bit of crystal ball gazing in his Statement, the Chancellor abandoned the OBR to talk about state pension ages. These were going to go up to 68 by 2046. Now they are going to go up to 68 by the mid 2030s and then to 69 by the late 2040s. There will still be people alive now who were born when the state retirement age (for the “Old Age Pension” as it was then called) was 70. It looks like we are heading back in that direction again.

The State Pension Age (SPA) was introduced in 1908 as 70 years for men and women, when life expectancy at birth was below 55 for both. In 1925 it was reduced to 65, at which time life expectancy at birth had increased to 60.4 for women and 56.5 for men. In 1940, a SPA below life expectancy at birth was introduced for the first time, with women allowed to retire from age 60 despite a life expectancy of 63.5. Men, with a life expectancy of 58.2 years were still expected to continue working until they were 65. Male life expectancy at birth did not exceed SPA until 1948 (source: Human Mortality Database).

In 1995 the transition arrangements to put the SPA for women back up to 65 began, at which stage male life expectancy was 73.9 and female 79.2 years. In 2007 we all started the transition to a new SPA of 68. In 2011 this was speeded up and last week the destination was extended to 69.

SPAs

Where might it go next? If the OBR had a SPA modeller anything like their GDP modeller it would probably say up, in about another 2 years (just look again at the forecasts in the first graph to see what I mean). Ministers have hit the airwaves to say that the increasing SPA is a good news story, reflecting our increasingly long lives. And the life expectancies bear this out, with the 2011 figures showing life expectancy at birth for males at 78.8 and for females at 82.7, with all pension schemes and insurers building in further big increases to those life expectancies into their assumptions over the decades ahead.

And yet. The ONS statistical bulletin in September on healthy life expectancy at birth tells a different story which is not good news at all. Healthy life expectancies for men and women (ie the maximum age at which respondents would be expected to regard themselves as in good or very good health) at birth are only 63.2 and 64.2 years respectively. If people are going to have to drag themselves to work for 5 or 6 years on average in poor health before reaching SPA under current plans, how much further do we really expect SPA to increase?

Some have questioned the one size fits all nature of SPA, suggesting regional differences be introduced. If that ever happened, would we expect to see the mobile better off becoming SPA tourists, pushing up house prices in currently unfashionable corners of the country just as they have with their second homes in Devon and Cornwall? Perhaps. I certainly find it hard to imagine any state pension system which could keep up with the constantly mutating socioeconomics of the UK’s regions.

Perhaps a better approach would be a SPA calculated by HMRC with your tax code. Or some form of ill health early retirement option might be introduced to the state pension. What seems likely to me is that the pressures on the Government to mitigate the impact of a steadily increasing SPA will become one of the key intergenerational battlegrounds in the years ahead. In the meantime, those lines on the chart are going to get harder and harder for some.

Time to define your ambition

The consultation on the future shape of workplace pensions has been going on for nearly a month now and ends two weeks on Friday. It is littered with errors, from completely repeated questions (Q52 = Q54) to ones which are so similar as makes no difference (Qs 41 and 44 for example) and the thrust of a lot of the questions are quite hard to answer if you do not share some of the underlying assumptions of the DWP about the process, but come on! This is our chance to put a bit of definition into the rather blurry outline of a straw man which some of the newspapers have been tilting at so vigorously!

You don’t have to answer all of the questions, but just to goad you a bit I have done so here. Agree, disagree, I would love to hear from you. But not until you have responded to one of the following addresses:

How to respond to this consultation

Pleasesendyourconsultationresponses,preferablybye-mail,to:definedambition.pensionsconsultation@dwp.gsi.gov.uk

Or by post to:

Defined Ambition Team

Private Pensions Policy and Analysis

1st Floor, Caxton House

6-12 Tothill Street

London

SW1H 9NA

 

Feedback on the consultation process

There have only been 24 posts on the blog. I think the main reason for this was identified early in the process from a contributor referring to herself only as Hannah:

Hannah

I applaud the use of an open blog but it’s obvious that there’s a bit of a problem here! Perhaps, to avoid this becoming sidetracked, you could introduce a drop-down in the comment section so that people could select what aspect of DA reform or the consultation their comment relates to – and if their comment relates instead to concerns about their accrued benefits, you could redirect them to a separate specialised member queries page?

Reply

Sam Gilbert

Thanks for this Hannah, we will look into this once the blog picks up pace.

DA Team, DWP

Of course the blog never did pick up pace because people soon realised that there comments would be lost in a stream of pension benefit queries. Not the way to encourage a consultation. If you want to comment on this or anything else about the process of the consultation, the contact details are as follows:

Elias Koufou

DWP Consultation Coordinator

2nd Floor

Caxton House

Tothill Street

London

SW1H 9NA

Phone: 020 7449 7439

Email:elias.koufou@dwp.gsi.gov.uk

Dollars and Census

November 2013 003The latest revelations from Edward Snowden that the US and UK agreed in 2007 to relax the rules governing the mobile phone and fax numbers, emails and IP addresses that the US National Security Agency (NSA) could hold onto (and extending the net to people not the original targets of their surveillance) has increased the pressure on the Government to tighten controls on the activities of the security services. This extension apparently allowed the NSA to venture up to three “hops” away from a person of interest, eg a friend of a friend of a friend on Facebook.

I have an issue with the Guardian analysis here. They say that three hops from a typical Facebook user would rope in 5 million people. However, using actual ratios from the network in their source (43 friends have 3,975 friends of friends have 1,328,361 friends of friends of friends) and the median number of friends of 99 from the original study, would lead to a number closer to 3 million. Still, it is clearly altogether too many people to be treated as guilty by association.

So it might seem like a strange time for me to be advocating that we give the Government more of our data.

The Office for National Statistics (ONS) is currently consulting on the form of the next census and the future of population statistics generally. The two options they have come down to are:

1. Keep the 2021 census pretty much as it was for 2011, although with perhaps slight changes to the questions and a greater push for people to complete them online; or
2. Using administrative data already held by the Government in its various departments to produce an annual estimate of the population in local areas. In addition there would be separate compulsory surveys of 1% and 4% of the population for checking the overall population figures and some of the sub-grouping respectively, and the ‘residents of “communal establishments” such as university halls of residence and military bases’ which are difficult to reach by other means.

In my response to the survey, I suggested that they do both, increase the compulsory surveys each year to 10% of the population and reduce the time between full censuses to 5 years. This is why.

First of all, everybody needs this data to be available. If the Government does not provide it, someone else will. Not by asking you overt questions, but by buying information about your buying preferences or search engine activities or any number of other transactions without your informed consent (eg you ticked agreement to their terms and conditions on their website) and without your knowledge. I would prefer to give my data to the ONS.

The ONS is part of the UK Statistics Authority, which is an independent body at arm’s length from government. It reports directly to Parliament rather than to Government Ministers and has a strong track record of challenging the Government’s misuse of statistics. With the exception of requests received for personal information (which are filtered off to become Subject Access Requests under the Data Protection Act), they have provided copies of all information disclosed by the ONS under the Freedom of Information Act on their website. In my view the ONS has demonstrated that it is a safe custodian of our data. They are everything the NSA is not: overt, apolitical and committed to the appropriate use of statistics.

But there are problems with the current data, which brings me onto my second point. Ten years is too long to wait for updated information. As the ONS points out in its consultation document, because of the ten year gap between censuses, the population growth resulting from expansion of the European Union in 2004 was not fully understood until 2012. There were other problems with the population data everyone had been working with before 2011, 30,000 fewer people in their 90s than expected for instance, which had serious implications for all involved in services to the elderly and those constructing mortality tables too.

So we do need more frequent census information. Five years seems about right to me, provided the annual updates can be made more rigorous. I think the ONS are right to suggest that they need to be compulsory to achieve this, but 5% of the population does not seem a large enough sample to be confident about this to me. I would prefer to see 10% completing annual surveys. This would allow 50% of the population to be covered over every 5 year census period, or 40% if the requirement was dropped in census year. There are many recent examples (see Schonberger and Cukier below) to suggest that the gains in accuracy due to increased coverage would be far greater than the losses due to the ‘messiness’ of incomplete responses.

There is a lot in the consultation document about the relative costs of the different options, but nothing about the commercial value of the data being collected. Indeed the reduction of the consultation to these two, to my mind, inadequate options seems to be very greatly influenced by the question of costs and the current cuts in budgets seen throughout the public sector. This seems to me to be very short-sighted.

However, I think this displays a failure of imagination. According to Viktor Mayer-Schonberger and Kenneth Cukier in their book Big Data, data is set to be the greatest source of wealth and economic growth looking forward. Many others agree. By taking a fully accountable and carefully controlled approach to licensing the data in its care, the ONS should be able to finance its own activities, even at the level I am suggesting, at the very least.

The ONS is very nervous about becoming more intrusive in its collection methods, citing the 35% increase in cost of the 2011 census in achieving the same level of response. It also refers to the response rates to its voluntary surveys which have dropped from around 80% 30 years ago to around 60% today. The main reasons for this in my view are the incessant requests from companies’ marketing departments masquerading as surveys on everything from phone usage to our views on banking to the relentless demands for feedback on every online purchase making us all subject to survey fatigue. This makes it all the more necessary that an organisation which is not trying to sell you anything and which is scrupulous about the protection of your data should be attempting to increase its scope and maintaining its position as the go to place for statistical data rather than falling behind its commercial rivals.

So let’s not fall into the trap of conflating all official data with the mountains of bitty fragments collected by our intelligence agencies from their shady sources. That has nothing to do with the proper, accountable collection of information to allow government and governed alike access to what they need to make better decisions.

So take part in the consultation, it matters. And when the time comes give the ONS your data. You know it makes census.

NEW vs England and Wales

The land of the four score and ten and over looks a bit different from the rest of the country

My grandfather used to say that he had had his three score and ten (that’s 70 for those brought up in a decimal age) and was now quite content to die when the time came. He said this with increasing frequency and some bewilderment before his final death at the age of four score and ten in 1991. This bewilderment was understandable: there were 222,820 over 90 year olds in 1991, already over 40% up on the 1981 total. However the changes since his death have been even more dramatic, with 440,290 over 90 year olds in 2011.

The Office for National Statistics (ONS) has recently published a statistical bulletin entitled Estimates of the Very Old (including Centenarians), 2002-2011, England and Wales, which summarises how the proportions living to four score and ten and beyond have changed over the 30 years since 1981. It shows us a population living within a population: Nonagenarian (ie the over 90s) England and Wales (NEW) within the full population of England and Wales.

Imagine for a moment NEW viewed as a different country, where people are “born” as they reach 90 and we ignore (as the ONS have done in compiling these statistics) immigration and emigration.

The first thing to notice about NEW is that the age structure looks very different to that of England and Wales. We can see this by comparing the “population pyramids”, as they are known, below, with the number of people at each age shown on a graph, males to the left in blue and females to the right in red:

The numbers fall away much faster of course at the older ages, although the shape still shows the biggest falls between ages 91 and 92 reflecting the impact on birth rates at ages (in 2011) from 92 to 97 of the First World War and its immediate aftermath. There are far more women than men in NEW, although the overall ratio has reduced from 4:1 in 1981 to around 2.7:1 in 2011. By comparison, the England and Wales population is much more balanced (there are 4% more women than men). The NEW population is somewhere between the sizes of Malta’s and Cape Verde’s full population.

Your chances of living to 100 in NEW as a newly arrived 90 year old are about the same as those of a new born in England and Wales qualifying for entry into NEW one day.

The world to which NEW belongs looks very different from that which England and Wales or the UK are used to. The largest country is not China or India, but the United States. Japan, whose overall population is about a tenth that of India has an over 90 population over twice that of India’s.

Finally, the population of NEW is growing far more quickly than that of England and Wales, or indeed the UK, with a 26% increase between 2002 and 2011, almost four times the UK rate over the same period.

My grandfather only spent a few months in NEW but, by 2011, 570 people had spent over 15 years in this land. It is going to become a much more familiar place to many of us.