Policy opinion breakdown – what the nation thinks

Recently, I put a survey on the website Reddit, specifically inviting users from the subreddits of /r/ukpolitics, /r/unitedkingdom and /r/uklabour to answer.

I got 1194 responses, which allow me to paint a fairly decent broad-strokes picture of how the UK feels on certain issues, and how those issues compare among supporters of different parties.

First and foremost, a warning on how to read statistics

I am not a professional pollster, so my questions were often overly vague, and occasionally potentially misleading. Therefore, the first rule is to assume every finding here is potentially wrong. Secondly, in the main results form (linked below), the results are simply in their raw form. That is to say that the number of respondents who supported certain parties did not reflect the national spread, so on that results page, the results are only intended to reflect the users of the parts of Reddit that answered. In this article, I have made an attempt to weight some of the more interesting results to better reflect how they might be seen nationally. Thirdly, other demographic biases are present here. There is a very strong gender imbalance, where more than 90% of respondents are male, although generally this doesn’t have a massive impact on most issues (although that is not to say that there is no impact). More important to policy belief is age, and unsurprisingly an internet poll leads to a massive underrepresentation of older people. Unfortunately, the number of people in the groups 40 – 49, 50 – 59 and 60+ were so low that I cannot fairly weight responses to include an age weighting without a very large margin of error.

Other biases do exist in the data of course, but as long as you have the three points above in mind, you should largely be able to read the data without being misled.

If you click here you can read the raw data responses, and once you have had a look there, you can come back to this article to see party-weighted results for a couple of the issues, then a more in-depth analysis of four issues: the legalisation of marijuana; opinions on the EU; state ownership of the NHS, the railways, the postal service and the utilities; and finally on voting systems.

Party weighted results

Party weighting is particularly tricky since to reflect the national opinion correctly, you would have to include all the minor parties, as well as the opinions of those who are undecided or non-voters. As such, I will simplify the following questions and then divide them by the vote share as of the last GE, and ignore non-voters and minor parties. This isn’t ideal, but it does somewhat combat the online biases. Secondly, the question asked in the poll was what party people would vote for today, so there is a small discrepancy with comparing today’s imaginary GE with the 2015 GE. Bearing that in mind, here are three issues to compare raw data and party-weighted data.


Firstly, opinions on trident. The initial poll asked for more detail to include military spending, but this is a simplified one just referencing trident.

raw                                                                 weighted by party

Trident raw  Trident weighted

As you can see, the weighting of the data here shows that in fact there is a rather large majority of the country that supports keeping trident (again, the assumption being that the average conservative voter in my poll, for example, is representative of the average conservative voter in the country).



Next, immigration:

Raw                                                                   Weighted by party


Again, the party weighting paints quite a different picture: in the raw data. a total of “too high” was 48%; in the weighted data, “too high” was 60%. If this data reflects the country accurately, it will be interesting to see how it might affect the EU referendum.


Finally, a ban on niqabs and burkas. Before even looking at the data, I should note that this was one of the questions that I later realised was misleading, as given by answers in the ‘other’ answer boxes – I assumed that people would know what niqabs and burkas were (both covering the face), whereas some responses suggested that people thought that one was a face covering and the other just a headscarf.

Raw                                                                    weighted by party


Here we see the ‘banning’ portion of the pie increase somewhat with weighting, although it is still in a minority by quite a large amount. It should be noted that the majority of ‘other’ votes were in favour of a ban, but under conditions, for example in schools.


Now, a breakdown of four issues

Legalisation of marijuana

Firstly, our overall data (raw) in response to the statement “Marijuana should be legalised for recreational purposes”

Mar All

As you can see, there is an overwhelming majority in favour of legalisation

Party by party:

Conservative                           Green                                            Labour


Lib Dem                                      SNP                                                UKIP

It is interesting to note that even amount UKIP supporters, as the least likely group to support legalisation, agree leads disagree by thirteen points. As such, unless this data does not accurately reflect the country, it would appear that this issue is one that is up for grabs for future political point-scoring.

Now interestingly, here is a break-down of the same data by age group:

Under 18                                        18 – 21                                        22 – 29


30 – 39                                  40 – 59

Mar 30 - 39 Mar 40 - 59

This indicates a somewhat counter-intuitive trend, where the young are less accepting of legalisation than the old. There are two possible explanations here: my view of the world may be wrong and the data reflects the truth; alternatively, the fact that this was an online poll on Reddit may have generated a user bias, that became especially prevalent in older groups. If the vast majority of people in their 40s and 50s do not casually use the internet for fun, the group that does may be rather unrepresentative of their age group as a whole, and so the data may not reflect the national picture.

Whatever way you look at this data, in every breakdown by age or party, there is very significant support for the legalisation of marijuana.


Concerns about leaving the EU

This section will show a party breakdown of what people thought Britain would be like out of the EU.

Overall (raw)

EU all


Party by party

Conservative                                                            Labour


Green                                                                         Lib Dem


SNP                                                                           UKIP


The key point of interest for me was that out of almost 200 votes, the Conservative pie was only one vote off being perfectly symmetrical. Now again, there could be a user bias, but either way among the Conservative voters that answered, the EU is certainly not as clear cut as believed.


State ownership

For the third breakdown, we are looking at which organisations have support to be run by the state. Firstly, the overall data (raw):

State all


Now party by party:





Voting systems

As our final breakdown, we will look at what system people would like to use to elect representatives. Firstly, the overall data (raw):


vote all


It should be noted that a very sizeable number of the 47 people who voted ‘other’ wrote “STV” (single transferable vote), evidently unaware that it is a form of PR, and thus really they should have chosen ‘PR (any)’.

Party by party:

Conservative                                       Green                                        Labour


Lib Dem                                             SNP                                              UKIP


With five of the six main parties having vast majorities in favour of replacing our FPTP system, it will be interesting to see how long it can hold on.


And finally – the best of the rest!

One of the fun things about having over a thousand people reply to the survey was that occasionally they took the chance to write something in the ‘other’ box that gave me a laugh. As such, I thought I’d share a few of them here.

In third place was that we should “nationalise /u/Duke0fWellington’s cocaine reserves” in order to fund universities.

In second place was someone saying that taking marijuana should be ‘compulsory’ for all citizens.

In first place was a bizarre historical reference in the volcano question, where one respondent suggested Enrico Dendolo (sic), a 12th century Doge of Venice.


Understanding 2008 – Part 4: How everything came together

This is the fourth of four posts explaining how the economic crisis of 2008 came about. Make sure to read Part 1 on housing bubbles, Part 2 on financial derivatives and deregulation, and Part 3 on financial players, subprime mortgages and leverage if you haven’t already done so. 


In 2001, following various issues (like the dot.com bust), the chairman of the Federal Reserve, Alan Greenspan, lowered interest rates down to 1% in an attempt to boost the economy. Big investors traditionally liked buying government bonds, as they were seen as a very safe return on investment, but 1% was such a low return rate that they started looking elsewhere. At the same time, 1% was very little to repay, so many banks borrowed more money, assuming they could make a higher return than 1% and so turn a profit.

As the housing market was booming, the banks and investors decided that this would be a good place for them to get involved and make a lot of money. For a while, many families were given easy access to credit to buy their own homes, and the mortgage brokers sold their mortgages on to investors, and they were lumped together by their thousands into Collateralised Debt Obligations (see Part 2), and a lot of people got very rich.

After a while, the market of financially prudent people looking for mortgages dried up, as they had all been given one. In order to keep making money, the mortgage lenders started looking more into the subprime market (see Part 3). Although they knew that occasionally some people wouldn’t pay back their mortgage, it wasn’t seen as overly problematic, as it just meant the investor would get their home instead, and homes were good to have since property values were rising so much.

The problem was that houses and their prices do not exist in isolation, but in relation to other ones.

Let’s imagine America street, with 20 houses. When the first house on the street goes up for sale, it’s no big deal, and no one else is affected. However, if three months later it isn’t sold, and two more houses on the street also default and go on sale, this starts to have two effects. Firstly, the simple rules of supply and demand mean that if two families are wanting to move to the street, and one house is available, the price might go up and the richer family gets it. However, if those two families are competing for three houses, then there will be no price rise, and potentially even a price drop to try and sell the house. Secondly, if a few months later there are five empty houses, not only do the occupied houses lose value from an abundance of supply, but the street starts to look empty and unappealing for new families, and demand drops too. The Smiths at 1 America Street were paying a mortgage for when their house was worth $400,000, but now their house is valued at only $100,000. It is now financially better for them to simply abandon their house and move on.

This problem started happening all over America. Banks and investors once had a collection of mortgages that paid in money, but now just own homes. Not only was their revenue stream cut off, but also the homes they now own in their thousands are constantly losing value. Various financial players try to sell off these useless assets, but everyone knows there is no more money to be made so no one is buying.

This would not have been such a huge problem if everyone had been investing their own money, as they simply would have owned a useless selection of properties, but nothing that actually harmed them. But they weren’t investing their own money. Remember the principle of leverage (see Part 3), which meant that to make these investments, the banks had borrowed huge sums of money, at an average of 33 times more than they actually had in reserve. So when it came to paying back their money, not only did they bankrupt themselves, but lost money for any institutions they were borrowing from. The whole sector was so connected that the collapse of one led to everyone losing money.

So why did the problem not just affect banks? When bank X lost all their money, it also meant that they had to tell every ordinary working person who had kept their money in that bank that their savings were gone. Moreover, the interconnectedness of the banks was not kept in America, but was spread throughout the world. For example, when Lehman Brothers collapsed on Monday 15th September, 2008, the effects meant that by Friday factories had permanently closed in China.

Understanding 2008 – Part 3: Financial players, subprime mortgages and leverage

This is the third of four posts explaining how the economic crisis of 2008 came about. Make sure to read Part 1 on housing bubbles and Part 2 on financial derivatives and deregulation if you haven’t already done so. 

A key problem in discussing financial issues is that too often the institutions and individuals are simply labelled ‘banks’ and ‘bankers’, which mixes up several very distinct groups. Here is a short list of a couple of the most important financial players, each with a simple definition of what they are. As usual, these definitions are for people not familiar with financial markets, and lack nuance, but allow for the broader picture to be understood.

Stock broker – This is somebody who buys and sells stocks and shares on the stock market. Shares are a portion of a publicly owned company, and may pay dividends and give voting rights, depending on the type.

Commodities trader – While seeming like a stock broker, a stock broker buys into companies, whereas a commodities trader buys raw materials themselves, looking for fluctuations in their prices to make returns on their money. They largely work around future derivatives. The four main commodity markets are agriculture, metals, meat and livestock, and energy.

Mortgage broker – A mortgage broker finds potential homebuyers and connects them to a mortgage lender and receives a commission.

Mortgage lender – a mortgage lender in a institution that lends money for people to buy real estate.

Investors – An investor is anybody putting up money with the hope of making a return on investment. A low risk investor might buy government bonds, which rarely fail, but have a low percentage return. An investor can be an individual or an organisation, including pension funds or even charities.

Ratings agency – The previous article described how tranches of a CDO might be labelled as safe or risky. However, all sorts of financial players may themselves be given a risk rating, even governments. The safest level given to anything is a AAA (said as ‘triple A’). The ratings agencies are the people who decide how risky a given investment might be. There are three main ratings agencies: Moody’s, Standard and Poor’s, and Fitch.

Insurers – An insurer is simply an organisation that provides insurance. The key role of the insurers in the 2008 crash was providing credit default swap insurances between banks. The main insurance giant in the crash was AIG.

Subprime mortgages

In very broad strokes, a prime mortgage is a ‘good’ mortgage, and a subprime mortgage is a ‘bad’ one.

In the same way that a government bond gets a rating, individuals also get rated on Consumer Credit Ratings, but rather than given a letter code, they are rated on a score of 0-1000, depending on how good they have been at paying back debts etc.

When someone goes to take out a mortgage, there a few things that may factor into what conditions they get. If, for example, Amy goes to get a mortgage on her house and her credit score is 600 or more (i.e. she has been good at paying back loans on time in the past), then she is likely to be able to get a good mortgage with a low interest rate, and will be expected to also provide a downpayment, of say $20,000.

A key problem in the crash was that mortgage brokers approached people like Bob, who had a credit score of 450, and couldn’t afford the downpayment. Since his conditions made it more likely that he would fail to make his repayments, he will have a higher interest rate, say 6%. This is an example of a subprime mortgage.

One type of mortgage is an ARM – an adjustable rate mortgage – where the first few years are paid at one rate, then there is a reassessment and the rate changes, usually to a higher rate. If someone could pay the low rate, but not the higher one, they may default on their loan, and the mortgage dealer would take ownership of the property.

The final piece of the puzzle is leverage, which thankfully is easy to understand. Simply put, leverage is borrowing money to make more. For example, if a bank had £100, and could buy Christmas trees at £80, and sell at £120, rather than buying one at a time, and making £40 per Christmas tree season, it could borrow £900 to have £1000, buy 12 trees for £960 (with £40 left over) and sell them for £1,440, repay the £900 + £100 of interest, and have a total of £480 at the end of the day. If our bank started with £100 and borrowed £900, it would be said that it has a leverage ratio of 9:1. Provided the borrowing is followed by the selling, the leverage ratio doesn’t matter. However, if someone borrows money at a high ratio to buy something, then can’t sell it on, it becomes extremely problematic, as not only will it itself go bankrupt, but the lender could potentially lose extraordinary levels of money too.

In 2004 the Securities and Exchange Commission passed a change regarding leverage. This led to the average leverage ratio growing from 12:1 in 2004 to 33:1 just before the crash. The larger the ratio, the more of an effect that one bankruptcy has on other institutions.

At this point, you should now understand what a housing bubble is, what a financial derivative is, who the different financial players are, what leverage is, and what the subprime mortgage market is. Part 4 will explain how all these came together to cause the crash.

Understanding 2008 – Part 2: Financial derivatives and deregulation

This is the second of four posts explaining how the economic crisis of 2008 came about. Make sure to read Part 1 on housing bubbles if you haven’t already done so. 

A very significant part of the financial world today revolves around the use of products called financial derivatives. This post will examine what they are, the two most important ones for the crash (CDOs and credit default swaps), and a brief history of their deregulation.

Firstly, what is a derivative? Essentially, it is a type of contract that itself is not worth anything, but derives its value from something else, like an asset or an index. An easy-to-understand example is one called a future. In a future, farmer Andrew and seller Bethany agree in September that come April, Andrew will sell Bethany 100 cows. Now, cows currently cost £100 each, but Andrew is concerned about the crop blight. Maybe it will kill off his neighbour’s crops, and his cows will be fatter and worth much more. At the same time, maybe his cows will be underfed and worth much less than £100. Bethany and Andrew’s future agreement means that Bethany will pay £100 per cow no matter which way the price goes. By doing this, both Bethany and Andrew can lower the risk that they will lose a lot of money over the agreement.

Now the two most important derivatives to the 2008 crash: CDOs and credit default swaps. Bear in mind that these are much more complicated contracts than I can hope to describe accurately, indeed it had been suggested that they were deliberately created to be needlessly complicated so that law makers would be unable to understand them and thus unable to ban otherwise dodgy practices. If you have never heard an explanation of these before, I personally would recommend reading their explanations several times, until you are confident enough that you could explain it to a friend; when I first learnt about them, I only half understood and had to repeatedly go back and check again.

CDOs – Collateralised Debt Obligations

To start, it should be noted that a CDO by itself is not a derivative, but more a specialised form of corporate bond. However, it becomes a derivative when combined with the CDSs below, and is then known as a ‘synthetic CDO’. Whether it is a derivative or not is irrelevant to understanding the crash, but is worth noting for those more interested in the fine details of corporate finance. So on with the definition.

A CDO is when organisation A brings together a large number of loans and pools together to create one big CDO. The CDO now sliced into ‘tranches’, lets call them safe, medium and risky. Other financial players may now invest in these three tranches, as they are sold on the bond market alongside conventional bonds. The three tranches can be imagined as three rock pools, where the highest one flows into the middle and the middle flows into the bottom one. When organisation A collects money from the various sources that make up the CDO, they first pay off money into the top rock pool, and assuming everyone pays, then then fill up the medium pool, and then the ‘risky’ bottom pool. However, if the stream of money lessens, for example when a risky loan is not paid back, the stream may fill up the top and middle pools, but only a little bit of the bottom pool. To compensate for the likelihood of failure to get the money back, each of the three pools gets a different return on investment. Investors in the safe pool may only get back 4% of their investment, whereas the medium investors may get back 6% and risky investors 8%. An important feature of the CDO is that although the loans are still passing through the bank, their ownership technically passes on to the investor in that tranche. Therefore, the bank no longer has those ‘risky’ loans on their books, and allows their business to appear more stable than it really is, were the bank to be audited.

Essentially, provided there aren’t too many failures of people to repay their loans to organisation A, things will go smoothly. Unsurprisingly, prior to 2008, there were too many unpaid loans. As you can see below, prior to the crash, the amount of money involved in these products grew staggeringly high:


Credit default swaps

The CDS, although technically complicated, can simply be thought of as a type of insurance on loan repayments. If bank A is receiving loan repayments from housing developer B, it would lose its money were B to default on that loan. As a result, it takes out a CDS from bank C, and just like any other type of insurance, they pay regular small fees, with the potential of a large payout should B default. By doing this, A lowers the amount of risk they are taking by giving B a loan.

Now, the big change from normal insurance occurs in that fact that the CDS is so complicated that it was not regulated, and so it allowed people to take CDSs out on things they weren’t involved in. For example, in our situation above, bank D could also take the CDS out from C, getting money if B doesn’t repay A. To explain why this is bad, imagine Fred takes out fire insurance on his house. He can only receive money if he loses his house, so his interests are balanced out. However, it is illegal for George to take out the same insurance on Fred’s house, because he has no balanced interest: he doesn’t live in Fred’s house, so he can only win from the house burning down, and obviously we don’t want a situation where people have financial incentives to burn down each others’ house. Moreover, the banks got wise to the fact that they could give a bad loan to homeowner X, take out a CDS, then benefit from the homeowner defaulting, which prior to 2008 became commonplace. Like the CDO market, this became ridiculously lucrative – by 2007, the outstanding CDS amount was estimated to be around $62 trillion.

Financial deregulation – a brief history

Financial deregulation is when the government loosens the restrictions on what financial institutions can do. There is a huge amount to say here, but for brevity, a few examples will be given so readers can get a general picture of how the situation has developed.

One early shift, and perhaps the birth of the modern finance sector was the changes for investment banks after the second world war. Initially, investment groups were collections of, say, a dozen wealthy businessmen, who pooled their own money and worked out where they thought the markets were growing. The rules were lifted and allowed banks to invest their clients’ money, and unsurprisingly, people are more willing to risk other people’s money than their own.

The real period of financial deregulation began in the ’80s under Thatcher and Reagan, but continued right up until 2008. One problem was that in the US, former bankers of huge institutions were repeatedly appointed to positions like chairman of the federal reserve or secretary to the treasury. Men like Donald Regan (not Ronald), Alan Greenspan, Larry Summers, Henry Paulson, Robert Rubin and others exacted undue influence on presidents who didn’t understand the complexities of the issues involved.

In 1982, the Garn – St Germain Act allowed savings banks to give out credit cards and issue non-residential real estate loans, which previously only commercial banks were allowed to do.

In the UK, in 1986, Thatcher passed a number of laws allowing more freedom for the financial services. For example, the barrier between stockbrokers and stockerjobbers was removed, allowing the creation of integrated investment banks, and foreign companies were now allowed to buy City of London firms.

A key instance of deregulation in the US is the Gramm- Leach- Bliley Act of 1999, repealing the Glass- Steagall Act from the 1930s. The latter banned the merging of retail and investment banks. When Citigroup and Travelers merged in 1998, they were given an exemption until the GLB Act passed the next year.

The following year, the Commodities Futures Moderization Act (passed under Clinton, with support from both parties) banned the Commodities Future Tradings Commission from giving any regulation for a number of derivatives, including credit default swaps.

In 2004,  the final major deregulatory act before the crisis passed, where the Securities and Exchange Commission allowed various financial institutions to increase the leverage ratio (explained in the next post), essentially allowing them to use many times more money than they held in reserves, with ratios up to 50:1 in cases like Fannie Mae and Freddie Mac.

Altogether, readers should not be surprised to see why the 2008 crash was so damaging – it was the culmination of almost 30 years of removing rules that discouraged risky trading.

Part 3 deals with the differences between the different types of financial institution, leverage and sub-prime mortgages.

Understanding 2008 – Part 1: What is a housing bubble?

I originally planned to write a single post on what caused the economic crash, but as there were so many aspects that have to be understood before seeing how they combine, I have decided to split it into four shorter articles. This first article will deal with what constitutes an economic bubble, and how it might happen in the housing market. 

Although we often hear the term ‘housing bubble’ in the news, it is normally given out of context, with no explanation as to what a ‘bubble’ actually is. Thus, it is important that we have the definition of an economic bubble before examining its causes: although the term dates from the early 1700s and has no one exact definition, it is roughly defined as when the price of a certain asset deviates greatly from its intrinsic value. What we mean by this is that if a house in country X cost $100 in 2000, and correcting for inflation, cost $200 in 2010, in the perfect world, its intrinsic value would have doubled. There are many factors that determine its intrinsic value: if the price of the bricks doubled, or if the price of labour doubled, or the house were twice as big, then we could say it is fair that the house cost twice as much. While it is impossible to work out the exact intrinsic value of any particular asset, if the house built in 2010 for twice the price is identical to the house built in 2000, we can assume its price has risen beyond its intrinsic value (although other factors beyond the house itself can increase its intrinsic value, for example house location). One pair of factors that might drive the price up without intrinsically increasing the houses value is the twins of supply and demand.

Adam Smith posed the question of the paradox of water and diamonds. Why is water, something utterly necessary for us to live and therefore in high demand, so much cheaper than diamonds, something that we don’t need at all? The answer, of course, is that that water is in great supply, while diamonds are in short supply.

Consider how this applies to housing. If the housing association builds three houses, and charges £20,000, and Anna, Bob and Claire can all afford that, then the price ought to rise only with inflation. However, if only 2 houses are built, and Anna and Bob can offer more than 20,000, but Claire can’t, and all three ask for the house, it is only natural for the housing association to raise the price to £21,000 and increase their profits. This situation of under-housing is exactly what is happening in the UK today, as can be seen in the following graph:

cbi housing shortage

When you add in the migration patterns of internal migration (away from the north of England, and towards London) to the housing shortage, it is easy to see why the following rates of inflation (2014) are so high:


In a historical perspective, the average house in 1979 was around £20,000, which in todays money is about £102,000. As it is, the average house today costs £195,000, just shy of twice the growth of inflation.

For interest, it is also worth noting that a housing shortage also drives up rents, and has lead to the UK having by far the highest average rent in Europe:

RentSource: http://www.numbeo.com/cost-of-living/rankings_by_country.jsp

Now it is important to be aware that a shortage of supply is not the only thing that can cause a bubble, and the US housing bubble prior to the crash was actually caused by a variety of other factors, such as ease of attaining mortgages (if it’s easy for people to get $120,000 in a mortgage, why only charge $110,000?). However, in understanding what caused the crash, it is only necessary to understand what a bubble is, and to know that there was a very large housing bubble, as can be seen here:


With the housing bubble (hopefully) clear, Part 2 explores financial derivatives and financial deregulation.

UKIP the Kingmaker? The unseen effects of the UKIP vote

When looking at the results of the last general election, is it very easy to judge the effect of a party by the number of seats it won. Despite getting almost 4 million votes, UKIP only won a single seat, and so were often said to have had little effect on the outcome. However, it is easy to overlook the fact that in a First Past The Post system, UKIP votes may have come at expense of one of the larger parties, and so may have changed the results despite not winning the seat.

Take, for example, the seat of Barrow and Furness:

Barrow Results

Here, we have a clear example of how UKIP did not win the seat, but may have prevented the Conservatives from winning.

Unsurprisingly, the opposite also exists, as happened in Bedford:

Bedford Results

Here, Labour could potentially have won the seat if it weren’t for UKIP taking votes from them.

It is important to here challenge the idea that UKIP voters are a ‘far right’, and are naturally Conservative voters if UKIP aren’t an option. While that is certainly true for a large number of UKIP voters, the party’s demographics, especially in terms of economic background, more closely match that of Labour, and the UKIP manifesto made several notable attacks on Conservative policy in line with Labour, for example condemning the ‘Bedroom Tax’ and promising to repeal it. As such, UKIP is liable to take voters from both parties, and if it were to collapse, its voters would be split between the parties, not solely going to back to the Conservatives, although polling data does suggest that people who voted UKIP in 2015 were more likely to have voted Conservative than Labour in 2010.

While there is no perfect way to show how UKIP may have affected the results, below are the seats where the UKIP vote was more than twice the vote difference between the Conservatives and Labour. Readers should note this method, as applied to future voting predictions, is entirely arbitrary, but works well to show the potential UKIP have to change the outcome of the next election.

Firstly, the seats that Labour could lose – in total, 31 seats, as shown on the map below:

LAB - UKIP map

Note that although UKIP did not have a strong turnout in London, it could be enough to change 5 Labour seats there.

The Conservatives have slightly less to worry about, with only 23 at risk:

con - UKIP map [fixed]

The 54 seats above represent one possibility of what could happen in 2020. The referendum in 2017, depending on its results, could mean the collapse of UKIP, but as Scotland has shown, it’s also entirely possible that their vote will go up again. The same is true for their huge vote resulting in only a single MP – voters could become disillusioned at the unfairness of their situation, but could also get fired up and push harder to get what they want. Either way, both Labour and the Conservatives will need to understand that UKIP’s influence exceeds its single MP. Labour need to win all the Conservative seats they can get to have a chance at power in 2020; the Conservatives, at only 6 MPs over the magic number of 325, will have to fight hard against UKIP’s gains if they are to retain their majority.

The UK vs Western Europe – How do we compare

This article is a straightforward comparison of how various European countries perform on a variety of metrics. For a fair comparison with the UK, non-western countries, and micro-states have been omitted. The comparisons will include any or all of the following 15 countries: Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden and Switzerland. If a country does not compare in a given list, the most likely reason is the difficulty of obtaining accurate data, not a deliberate omission to skew the picture.

Firstly, some good news when we compare healthcare systems. This chart isn’t a comparison of western Europe, but gives a pretty clear picture anyway.

NHS wins -D

As you can see, the NHS is rightly something of which all Brits can be proud.

Next, incarceration rates

Incarceration map

Source: http://www.prisonstudies.org/world-prison-brief

The above map shows the number of prisoners per 100,000 citizens. In the map, Scotland, N Ireland and England & Wales are three separate numbers, with England & Wales and Scotland being the highest two rates in western Europe. Interesting to note is the lower rate for N Ireland.

Next GDP per capita

GDP per capita

Source: IMF, 2014

The chart above shows GDP per capita, and the UK is the fourth lowest of the 16, only above Spain, Portugal and Italy.

Next a chart showing cost of living.


Source: http://www.numbeo.com/cost-of-living/rankings_by_country.jsp

The Consumer Price Index shows the cost of living as compared to the cost of living in New York City, which has the score of 100. Here, the UK has the fourth highest cost of living of the 16, only behind Switzerland, Norway and Denmark.

Next, rail prices

  1. UK            –   £3,268
  2. France      –   £   924
  3. Germany  –   £   705
  4. Spain        –   £   653
  5. Italy          –   £   336

The above list shows the price a commuter would pay annually if they were to live 23 miles away from the capital city of each of the five major western European countries. In this metric, more than any other, the UK really shows significant problems.

Next, average rent


Source: https://www.housing.org.uk/media/blog/private-renters-in-uk-pay-double-the-european-average/

While not quite as extreme as the rail difference, Brits also have to pay, by some margin, the most expensive rents per month in western Europe. At €902, it is a significant amount more than the next most expensive, Ireland, at €679.

Next, the GINI coefficient

GINI map (fixed)

Source: http://ec.europa.eu/eurostat/tgm/table.do?tab=table&language=en&pcode=tessi190, 2013 figures

The GINI coefficient is a measure of how unequal a country is in terms of wealth, where a lower number means more equality. Here, the UK is the fourth highest, behind Italy, Spain and Portugal

Next, a look at the average income of the bottom 20%

  1. Germany       –   £7,918
  2. France           –   £7,486
  3. Belgium        –   £7,308
  4. Denmark      –   £7,209
  5. Netherlands –   £6,671
  6. UK                 –    £5,639

Source: http://www.michaelmeacher.info/weblog/2014/06/the-poor-in-britain-are-among-worst-off-in-western-europe/

As you can see, our bottom 20% receive noticeably less than their counterparts in mainland Europe. This difference is even more stark when the cost of living is accounted for.

Moving off money, we shall now look at teenage pregnancies.


Source: http://www.ons.gov.uk/ons/rel/vsob1/births-by-area-of-usual-residence-of-mother–england-and-wales/2012/sty-international-comparisons-of-teenage-pregnancy.html

As the above chart shows, Britain leads in western Europe by some margin on teenage pregnancies, both in 15 – 17 and 15 – 19 rates.

Finally, slightly better news in education.





PISA 2012 Average




































































Source: http://www.oecd.org/pisa/keyfindings/pisa-2012-results-overview.pdf

PISA is an organisation that measures 15 year olds in 65 developed countries on math, reading and science. Although we do not perform overly well compared to western Europe as a whole, this is one of the few areas where the UK performs better than Scandinavia.

Overall, when looking at the ten areas above, is it quite clear that the UK has a lot of work to do, other than in healthcare. The UK, with its large wealth gap, poor pay for the bottom 20%, high rents and high railway cost, is becoming a particularly difficult country to live in if you do not make a high wage.

Keynesianism vs Austerity – responding to the crash of ’08

In the final Prime Minister’s Questions before the 2010 General Election, David Cameron said the following:

“As this is the last PMQs this parliament it is the last chance for this prime minister to show he is accountable for the decisions he has made… This prime minister would wreck the recovery by putting a tax on every job. This government would wreck the recovery.”

This article will examine a variety of economic factors and compare how the Brown/ Darling response to the crisis affected the economy compared to that of Cameron/ Osborne.

Firstly, a brief description of each of the two approaches:

Brown’s key approach was the bailout for the banks. In a classic Keynesian response, it was Labour’s understanding that the deficit would be dealt with in time, but the current priority was for the government to spend in order to fix the problems of credit for businesses and unemployment. The package had three main parts, but it essentially boiled down to £500bn of support for the banking sector. Other measures included a new top tax rate of 50p for income over £150,000, and a one year decrease in VAT from 17.5% to 15%.

Cameron’s entire plan was different as he worked on an entirely different economic model. For him, the key to economic success was to restore the global market’s confidence in the UK by a concentrated effort to end the government’s spending deficit (originally by 2015; currently aimed from 2019). In a speech on the 28th May 2010, Cameron highlighted his three key areas for economic change: firstly, ‘liberalising the economy’ through cutting red tape and keeping taxes low for businesses; secondly ‘modern support’ of the economy from the government – this included high-speed rail connecting the country, Gove’s encouragement for academies and free schools, allowing schools better to provide skills for children, and IDS’s welfare reforms, as it was seen that overly generous benefits were a disincentive for people to get back into work; finally, he wanted to ‘rebalance the economy’, and although detail was less precise in this section, Cameron pointed out that the economy was reliant on too few sectors, based in London and SE England, and he wished to ‘encourage’ technology industries throughout the UK. Important tax changes included gradually lowering the corporation tax rate from 28% to 20%, reducing the top rate of tax from 50p to 45p, and an increase in VAT from 17.5% to 20% (despite promises not to do so).

A series of graphs will now be examined relating to various economic factors, and three sections will be highlighted in each: the crash (in orange), Brown’s response (red), and Cameron’s response (blue). It is important to note that in economics, nothing is ever as simple as it seems, and a single graph is not definitive proof of anything. However, if enough areas show the same trend, it can be assumed that the correlation might start to hint at causation.

Graph of Gross Domestic Product 2004 – 2014

GDP chart 2 coloured

Here we see a sharp drop in GDP during the crash, a recovery under Brown, and a mild decrease then mild increase, overall flatlining, under Cameron.

Graph of output per job

Output per job coloured

This graph charts output per job, and shows two years of decline when Cameron takes over.

Graph of consumer confidence

CC Index colouredHere, again, Brown’s response succeeds in boosting consumer confidence, which drops again under the first few years of Cameron, eventually rising again in 2013.

Graph of UK manufacturing output


Considering that one of Cameron’s key points was that the economy was too dependent on sectors like finance, and need more manufacturing, above graph is quite damning. Even the growth in 2013 peaks at the end of Q1 2014 and heads down again.

At this point, readers should be getting a clear picture – the crash causes a slump, recovery sets in under Brown/ Darling, and the recovery stops under Cameron/ Osborne’s austerity. We have already seen this happen in GDP, job output, consumer confidence, and manufacturing output, but this same pattern is also found in:

  • Real earnings growth
  • CPI inflation
  • Monthly mortgage approvals
  • Business volume expectations
  • Industrial production output
  • Construction activity
  •  Business investment

There are several sectors where there has been a steady picture with the two governments, for example import/export balance, but almost no examples of the austerity measures being more successful than the Keynesian ones. Claims by Osborne that the treasury in bringing in more tax than ever are deliberate half-truths, concealing the fact that this is only true in terms of a whole number – when inflation is factored in, or when measured as a percentage of GDP, this is no longer true. A single claim in favour of Cameron/ Osborne’s economic strategy is that the percentage of adults in work is approaching a record high, although this was following a trend that been climbing since 2000, and does not factor in the proportion of people in part-time work.

Once again, Cameron’s claim:

This prime minister would wreck the recovery by putting a tax on every job. This government would wreck the recovery”

In light of the information above, readers can see that this claim is perhaps not as true as Cameron would like us to believe.

The Myth of Spendthrift Labour & Frugal Conservatives – UK government deficits 1961-2015

In the last two elections, the Conservative party has been incredibly successful at stating as fact the idea that the Labour party is inherently wasteful in spending, whereas the Conservatives are naturally better at holding the nation’s pursestrings – an idea that Labour did very little to challenge. However, the graph below shows that this idea has little truth to it.

Graph showing governmental deficit in billions of pounds Sterling, 1961 – 2015. 

Deficit graph

There are a number of points to note from this chart. Before any analysis, it must be noted that the numbers are as they were at the time, and thus not adjusted for inflation. This explains why the numbers get exponentially bigger as time goes on. With that in mind, let’s compare some numbers. Firstly, under MacMillan, Douglas-Home and Wilson’s first period in office, the deficit remained exceptionally small, with both Conservatives and Labour. Heath then takes office, and running a small deficit becomes the norm. As seen in the chart below, this was most  likely caused by a drop in tax receipts during a period of economic trouble. During Wilson’s 2nd office and Callaghan, the deficit more or less stays stable, although factoring in inflation perhaps a slight decrease in real terms, but not much movement regardless. The switch from Callaghan to Thatcher again takes place with a period of economic trouble, and Thatcher spends the first two thirds of her time in power running the same size of deficit, although again with inflation, her £8.5bn deficit in 1979 was in real terms larger than her £8.4bn deficit in 1986, but like Callaghan, not much movement overall. In 1988 and 1989 Thatcher has surpluses of £6bn and £0.6bn – the first surpluses since Wilson’s (Labour) surpluses of £0.9bn and £0.3bn in ’69 and ’70. At this point it is useful to look at a chart of GDP.

GDP chart

You’ll notice that so far we have had two dips – 1974 and 1979 – the first was absorbed by a Labour government with little effect on the deficit, and the second also absorbed softly, but this time by a Conservative government. Come the 1990 crash, this ability to protect government deficit levels is greatly reduced, likely due to the shift in the UK economy away from primary and secondary industries, towards tertiary ones. Major proceeds to run a series of sizeable deficits, although readers are again reminded that inflation is a key factor in these deficits appearing larger than those before. Enter Blair in 1997, and for the only time since WWII, the UK enjoys three years in a row of surpluses. A change in policy leads to a significant increase in spending, mainly on health and education, and once again a reasonably sized permanent deficit appears, although marginally smaller than Major’s. The economic crash of 2008 causes an enormous jump to £100bn in 2008, and ~£150bn in 2009. It is useful for readers to note that in the large spending jumps, both under Brown and under Major, are not in fact caused by an increase in spending: the deficit is caused by the spending being higher than tax receipts, and in both these cases the economic difficulties resulted in a sharp drop in tax receipts, thus increasing the gap between income and expenditure. A final point to note is the incredibly slow recovery from 2010 onwards. The national debt in 2010 stood at £0.76tn, and treasury estimates put the 2015 figure at ~£1.4tn, a little shy of doubling the national debt.

So when all is compared the idea of either party being spendthrift or frugal compared to the other holds little truth. Each government is largely the same as the government that preceded it, and in the past 54 years, there have been only 7 years of surplus: two with Wilson, two with Thatcher, and three with Blair. However, in politics facts matter a lot less than opinion, and unless Labour can convince the public that their ability to manage public finances is no worse than the Conservatives’, they will be at a great disadvantage in 2020.

What if “Did Not Vote” were a party? Examining the 2015 GE results in a new light.

In the 2015 GE, the voter turnout was 66.1%, not especially high, although the highest for a number of years:


This turnout meant that roughly 30m people voted, out of a possible ~46m. Turnout across the country varied greatly even among constituencies that were beside each other – in Dunbartonshire East, the turnout was 82%, compared to its neighbour Glasgow North East at 57%.

In total, just over 11m people voted Conservative, and 9m for Labour, compared to the 16m who did not vote. This article examines the hypothetical world where every non-voter was replaced by a vote for the “Did Not Vote”(DNV) party (and we’ll give them the colour turquoise).

Firstly, it is important to remember that if we used a ranked voting system, and all voters ranked every candidate (i.e. did not rank three and leave three blank), then any seat with a turnout over 50% would have to win against a DNV candidate. However, since we use First Past The Post, in any seat where the turnout was below 66.6% and the winner got below 50%, the DNV candidate must have won.

An example of where FPTP gave an unusual result would be in Belfast South (turnout 60%). Here are the results:

South Belfast

From this you can see that the winning party, the SDLP, only had 24.5% percent of the vote. However, this does not factor in the 60% turnout. In reality, only ~14% of eligible voters voted for the winning party, compared to 40% for our hypothetical DNV party.

While it might be easy to say that this was the result of NI’s multi-party system, and mainland Britain would never have as little as 14% deciding, the truth is not wildly different. If we examine Tristram Hunt’s seat, Stoke-on-Trent Central, we see similar numbers: although Hunt had a comfortable lead over his rivals (39.3% for Hunt, vs UKIP on 22.7% and the Conservatives on 22.5%), his constituency had the incredibly low turnout of 49.9%. When non-voters are included, this means Hunt only received 19.6% of possible votes, compared to 50.1% of voters ‘choosing’ DNV. This example both shows the incredibly low percentage of the vote that some MPs need to win their seat, and also the importance of realising that our thought experiment is very much just that, and not like the real world where Hunt enjoyed a comfortable majority. Conversely, in seats with very high turnouts, it is possible for the winning candidate to have won a lower percentage of cast votes than Hunt, but to have ‘defeated’ the DNV candidate.

So now lets look at the UK results as a whole.

To start, here are the real results of the 2015 GE, and the map of their placement.

GE results coloured

Results map

But when we factor in our DNV party, the results change radically:New results

From the above, you can see that the DNV vote party is the new run-away winner. Now, the DNV have more seats than the Conservatives have in real life, and the Conservatives have fewer than Labour really have. Since the SNP only lost 7 seats, they are now ahead of Labour. Plaid Cymru lost all its seats, and every Northern Irish seat was lost, bar one for the Ulster Unionists. The Liberal Democrats lost six more seats, leaving only Nick Clegg and Tim Farron. Not included in the results is the speaker, who kept his seat.

Here are the same results on a map:

Constituency map coloured

It is interesting to note that of Labour’s 43 seats, only 6 were outside the Leeds/ Wirral/ Manchester and London areas. The Conservatives tended to lose most of the cities they once had, and many of the rural constituencies along the English coastline. The SNP largely avoided losing its seats due to the high turnout, almost certainly due to the sustained political interest following the independence referendum.

Although it would impossible to create a real party like our DNV party, the above map does show possible changes to come in the next few parliaments. As the evidence shows that non-voters are more likely to come from lower-income backgrounds, it will be the challenge of both Labour and UKIP to try and convince some of the 16m non-voters if they wish to improve in 2020.