The Local Elections in Graphs

After recovering from the all night election analysis at the BBC, I've put together some graphs that show some of the key results in the key wards we cover.

Some topline results

The following graphs show some of the interesting results we saw across the key wards. The first thing to realize about these elections is that they were in very Conservative leaning areas. Even after the UKIP surge, the mean ward result in our dataset looked like this:

Nonetheless, the UKIP share is an incredible performance for a small party. But the picture is very different when we look at the ward distribution. The ward results look surprisingly similar to the status quo with the tories capturing more than half the wards. 

In particular, UKIP goes from second in vote share to fourth in seats. As Steve Fisher, another BBC psephologist and lecturer at Trinity College Oxford, argues, this discrepancy is largely the result of UKIP's vote distribution. The violin plot below shows the vote distribution for each party i.e. how many wards each party got a given percentage of the vote in. If we look at the Liberal Democrats and Labour, they show a highly skewed distribution: they get very low shares in a high proportion of wards with a long tail of better performances where they manage to get seats. By contrast, the UKIP vote is close to normally distributed with little skew. 

The point is inadvertently put best by the UKIP Mayor of Ramsey who tweeted:

@redhotsquirrel UKIP had 879 second places add that to the wins and 55% of our candidates came first or second
— Mayor of Ramsey (@MayorOfRamsey) May 5, 2013

The distribution of UKIP's vote ensures that they receive a very high number of second place results.

It's not only the vote distributions that cause problems for UKIP. It's also the distribution of their vote changes. The following graph shows the distribution of the vote changes for each party since the 2009 elections. Given that the three major parties each started from a more efficient baseline (in terms of votes to seats) than UKIP, UKIP would ideally want to have a more skewed set of changes. However, we see exactly the opposite. Labour made 209 gains from a 7.9 percentage point increase compared with UKIP gaining 118 seats from an 11 percentage point gain. This is at least partially because of it's skewed vote increases. Labour has a long tail of increases which, along with its initially skewed performance, led to its strong ward performance.

Thanks to Steve Fisher, John Curtice and Rob Ford for their work on the results and the whole BBC elections team. Note: this post does not reflect the views of the BBC.

How the BBC elections work

Some background. The BBC monitors the results in a set of councils intended to be representative of the election as a whole. In this election they monitored 21 of the 35 councils. With people posted in each area to phone in the results as they happened. This allowed us (the psephologists) to get an up to the minute picture of the election as it happened (mostly at 2am when there was no election programme on air). We collect a variety of demographic and political information about all of the key wards covered and we use this to help inform the viewers about what the results mean, particularly through John Curtice's analysis.

Will general election turnout stop UKIP repeating their performance?

UKIP's record breaking performance has the world (or that subset of it that follows English local elections closely) talking about whether they might repeat this performance at the general election. If they did, then they might replace the Liberal Democrats as the third party in the House of Commons.

Before getting carried away with speculation on Nigel Farage's role in a future coalition government, it is worth considering some factors that might limit this. One factor is the odd electorate that votes in local elections. While the BBC's projected national share accounts for the difference in the areas that vote, it doesn't account for the difference in the electorate that turns out. These differences can be large, just 31% of eligible voters made it to polling stations yesterday compared to the 65% who voted on election day.

These differences aren't random either. In particular, local elections voters are much older  those at general elections (broadly, the elderly will turnout in every election whereas the young tend to only show up for high profile contests). Conservatives and liberal democrats have been the traditional beneficiaries of this differential turnout but UKIP has a strong base of support among the elderly.

So what would these results have looked like if the turnout had been 65% rather than 31%. To give a rough answer to this question I looked at how much share UKIP gained since 2005 (a general election) in each ward depending on how turnout changed between the 2005 General Election and 2013's local contests.

	UKIP vote change 05-13
Turnout change 05-13	-0.065
	(2.42)*
_cons	17.810
	(15.14)**
R2	0.03
N	163

* p<0.05; ** p<0.01

As expected, UKIP improved their performance more in contests that saw a sharper drop in midterm turnout. However, this would not have been sufficient to dent their performance greatly: they would lose a total of 2 percentage points bringing them from a 23 point PNS to a 21 point result.

While UKIP benefited from low turnout, it is not enough to begin to explain their huge electoral gains. It will take more than robust turnout to reverse their success in these elections.


Note: These results are also robust to a set of controls:

	UKIP vote change 05-13
Turnout 05-13	-0.061
	(2.25)*
Population Density	-0.015
	(0.29)
% aged 65+	0.293
	(2.05)*
% white	-0.156
	(0.67)
% aged 18-24	-0.193
	(1.27)
_cons	28.916
	(1.31)
R2	0.10
N	160

* p<0.05; ** p<0.01

Caveats:

• See previous post
• I realise I'm in danger of contributing to the "questions to which the answer is no" genre of blog writing. In my defense I didn't know that the answer would definitely be no in advance. 

Blown away: How much impact did wind farms have on the UKIP vote?

UKIP's rapid rise has led to certain gaps in their policy platform. The party's core issues of immigration and Europe have been fully articulated but the rest of the platform is still in a state of flux. Another line of policy has been to take up various "NIMBY" (not in my back yard) issues. For instance, their Yorkshire and Lincolnshire webpage gives high prominence to the wind farms. In fact it's the only policy area mentioned on the site other than Europe.

So what should we make of this NIMBY focus? Is it a key part of their appeal or just window dressing around their core anti-immigration/EU message? 

Taking a first look at this, I've compared the UKIP performance in wards where there is a wind farm to those without one. I was helped in this by a wikipedia article listing the coordinates of all onshore wind farms in the UK (I am very intrigued about who put this together) and the ever useful mapit API. 

For now I'm simply analysing the difference across the BBC's keywards (those councils that they analyse in detail) that have declared results  (as of 3.31pm 3/5/2013), so these results are very preliminary. Among these wards, 19 have wind farms and 14 of these have UKIP candidates standing.

In these 14 wards UKIP averaged 32.7% of the vote, this compares with a share elsewhere of 24.6% (n = 1170). If this is robust (a big if), it would make the presence of wind farms one of the biggest effect on UKIP share.

Of course, it may simply be that UKIP does well in rural areas, which also tend to be the ones containing wind farms. 

A quick regression analysis suggests that this isn't the case. Although the difference is not quite as large as the raw figures, they still perform 6 percentage points better in wards with wind farms that those without. 

	UKIP 2013 share
Population density	-0.054
	(3.49)**
Wind Farm	6.160
	(2.86)**
_cons	25.689
	(73.17)**
R2	0.02
N	1,083

* p<0.05; ** p<0.01

So the analysis so far suggests that NIMBY issues may have some potential for UKIP. 

But wind farms are only relevant to a small number of wards. A second NIMBY issue that might have more wider relevance is High Speed 2. The proposed route of the train line cuts through many councils being counted today. UKIP have been slower to jump on this issue, but we can look at whether it's helped their vote. The potentially affected postcodes are listed by safe-move.co.uk and were coded up using mapit.

Unlike their wind farm success, the regression suggests that there is little difference in UKIP performance in wards affected by HS2.

	UKIP 2013 share
Population density	-0.051
	(1.94)
HS2	-2.919
	(0.81)
_cons	11.580
	(18.25)**
R2	0.02
N	291

* p<0.05; ** p<0.01

So far then, UKIP's share does not appear to have been driven primarily by NIMBY issues. Their possible success in mobilizing support around wind farms has not been replicated for HS2, which is potentially much more widely relevant. 

The lack of an effect of HS2 might be seen as a missed opportunity for UKIP. However, it also underscores a positive result for them: their strong showing is not merely the result of canny use of local issues but a genuine national shift in their favour. 

Caveats:

• These are obviously preliminary results and there may be other factors to control for. I hope to analyse some of these in future posts.
• The worst affected HS2 postcodes are in Buckinghamshire which the BBC is not covering due to large boundary changes. 
• It is questionable whether these effects should be seen at ward level or perhaps at district level. I'll look at this question in more detail later.
• Obviously correlation =/= causation.
• Ideally, I would show the regression for the changes in the shares since 2009 and 2005 but UKIP has fielded candidates in so many new locations, that there simply aren't enough results for comparison.
• This blogpost does not reflect the opinion of the BBC or my department. 

Why predicting stock markets from Google Trends could be bad news for science.

A new study from Tobias Preis at the Warwick Busines School appears to show that Google Trends data can predict falls in stock prices. The theory is that investors search for information about stocks they are thinking about divesting before doing so.  

While I've been sceptical about some uses of Google Trends data in the past (see here and here for details), the latest study has a solid theoretical mechanism and strong data analysis to support it.

So why am I unhappy to see this study?

Well, the publication of this article guarantees one thing about the future. There will be bots using Google Trends as part of their trading strategy. And if people are using this trading strategy, then there is an incentive for others to manipulate the Google Trends data to try and exploit this strategy. 

The number of searches required to shift Google Trends is reasonably high but not at all out of the question for someone with access to a botnet (and there are a lot of people with access to botnets). We could even see a new high frequency trading style battle between different trading and searching algorithms each trying to fool the other about their intentions.

Now, people will probably argue that the botnet response will remove the profit in the Google Trends trading strategy. This may be true, but the reported 326% over 7 years return suggests significant room for reducing the signal of Google Trends before it becomes unprofitable to trade off it.  

However, even if Google Trends still returns sufficient information that it can be used as part of a trading strategy, the results may have devestating externalities for other users of Google Trends data. While there has been a great deal of hyperbole around Google Trends, there have been successful uses of it for measuring different variables from flu outbreaks, to economic trends, to issue attention. The usefulness for these applications may be casualties in the race to make Google data only marginally profitable for trading. 

So I'm happy to see new uses of these data but I worry that a profit incentive may ultimately make them entirely worthless. Here's hoping to be wrong. 

Zombie nation? (an update on a sleepless world)

Sadly this isn't a post about German trance band made famous by this piece of popular music (slightly NSFW) but a follow up to my previous post about sleep reduction and the economy. It stirred up plenty of debate here and at Marginal Revolution and EconLog so I thought I'd follow up with some amendments and replies. Thanks to everyone who linked and commented- working through a new idea like this is exactly what I hoped the blog would allow.

Is 2.5 hours realistic?

Plenty of responses were sceptical whether modafinil could reduce sleep to 2.5 hours a night regularly. This is a fair point and the figure is definitely toward the extreme end of reported experiences on the Internet and most of these were not long term users. I used the 2.5 hours as an extreme case (which it's fair to say is probably not achievable for most people with current medicine) but the more common experiences seem to be people who reduce their sleep by a few hours habitually and people who use the drugs to stay up for extended periods once in a while without suffering the drastic cognitive declines insomnia normally entails. It'd probably be possible to keep people up for this long but I'll agree with the commenters that this is likely unsafe. So current drugs such as Modafinil are probably not capable of changing a whole population over to a 2.5 hour sleep schedule, so we would probably be looking at smaller increases in the work day than the 34% discussed. Still, the mechanisms of increased productivity should still apply albeit at a smaller magnitude.

40 hour weeks are as much as we can do

Other commenters suggested that a 40 hour work week is the maximum productive number of hours people could manage. This may be true at present but most of the studies on these drugs do suggest they have a substantial impact on reducing fatigue and maintaining performance. I'd see this 40 hour limit as a contingent fact of our normal mental state rather than a cast iron rule. These drugs are doing more than keeping users awake in an undead state but actually prolonging the time that they are able to be alert.

An arguably stronger effect of this class of drugs would be increasing the productivity of those already working long hours. The current usage of these drugs seem to support this view. A study of doctors found that their performance during long shifts was significantly improved by taking modafinil. The authors conclude that:

 Our results suggest that fatigued doctors might benefit from pharmacological enhancement in situations that require efficient information processing, flexible thinking, and decision making under time pressure. However, no improvement is likely to be seen in the performance of basic procedural tasks.

Sleep is important

At the moment this is definitely true and there is convincing evidence that sleep promotes memory consolidation. What we don't seem to know (it'd be good to hear from any sleep experts who have a more complete answer) is how much sleep is required and whether these functions are affected (positively or negatively) by wakefulness drugs.

People enjoy sleep

I am genuinely not sure if this is true. I certainly enjoy dreaming (which is only a small proportion of total sleep), snoozing (that half asleep phase after you wake up) and feeling refreshed. But I'm not sure I like sleeping 8 hours simply because it meant I was asleep for 8 hours. If I could feel equally refreshed and remember just as many dreams after 3 hours I'd probably be just as satisfied. I'm not sure if the number of hours in which I was not experiencing anything is something I value in itself so much as for the effects it has on me.

I don't want to work more hours

This was probably the most commonly made point. Whether this is valid comes down to whether we care about the proportion of our time that we are at work or the total amount of work we do in a day. The American Time Use Survey in the previous post suggests that (at least on work days) people spend more of their waking hours working than all other activities combined (this includes household tasks and caring for dependents). If we do get extra wakeful time it could all go to leisure but this would be a huge increase in the proportion of our waking lives spent in leisure. This of course is no bad thing but our current tendency spend a high proportion of our time on work suggests that people do not value leisure so much as to forgo wages substantially.

The split I suggested would increase leisure time much more proportionally than it would work time. Nevertheless, it is an open question whether we fundamentally dislike working more than 8 hours a day regardless of the time we spend in leisure. It is possible that regularly working 11 hour days would be unpleasant regardless of how much leisure time was available for relaxing. There may be timetable that can allow extended breaks of several hours during the day but everyone knows lunch breaks don't feel as good as real time off.


Signalling?

Nelly wrote that:
"These drugs may make someone more productive on a daily basis, but wouldn't necessarily make someone more productive on an hourly basis. Maybe more importantly, it is quite possible that those who would choose to take these drugs would be negatively selected. They would likely be taking them to become more competitive, which would be in line with your increasing the labor supply argument."


This is an interesting point and might be true to begin with. However, if the negative selected individuals are managing to compete with those with a higher underlying skill, it might make sense for skilled people to take these drugs as well in order to maintain their position. In a jobs market where the payoff to human capital is partially positional (i.e. almost every jobs market), people with higher talent are disadvantaged by people with lower talent using drugs to catch up. If the talented can't stop the dopers from using drugs, then they may be pushed towards joining them.

This creeping economic pressure to use these drugs is still the most convincing argument against their use. But this is roughly analogous to the economic pressures to use any other technology. Workers who refuse to use any motorized transport limit their job opportunities and only a few farmers still use pre-industrial methods. That's not to say that cars and fertilizer are purely positive developments but they still spread rapidly.

These pressures mean that if we do decide that we don't want to live in a society that relies on these drugs, we may have to actively regulate them rather than leaving the decision to individuals.

The Sleepless World: One more piece of low hanging fruit?

Update: more detail on the argument and responses to it here

Tyler Cowen at Marginal Revolution is a major proponent of the Great Stagnation thesis: that new innovations are not having the same impact on productivity as those we saw in the previous 150 years. Think of iPads versus electricity and cloud computing versus the railroad. Hence, we can expect to see slowing growth in GDP per capita as future productivity gains will take much more effort to unlock. This week The Economist took up this line of thought with a thorough briefing on the subject that broadly agreed with Cowen, although with some equivocation.

Overall, I think the argument has a lot of merit but there may be at least one more piece of low hanging fruit: a vast reduction in our need for sleep.

The American Time Use survey reports that an average American work day includes 8.8 hours of work and 7.6 hours of sleep. Sleep is the second largest single use of time. However, new drugs such as Modafinil appear to vastly reduce the need for sleep without significant side effects (at least so far). Based on reports from users, it seems that people could realistically [edit: potentially (see update)] cut their sleep requirements to as few as 2.5 hours a night without a decrease in mental acuity. That gives us another 5 hours to distribute over the day.

Workers would probably prefer to allocate the bulk of that extra time to leisure but I doubt employers will let that happen. Let's make a generous breakdown and give work an extra 3 hours and let workers spend another 2 as they wish. This increases working hours by around 34% and potentially increases leisure time by 80%. This increases the number of hours a worker spends at work from around 1800 hours a year now to about 2,400.

So would this lead to an increase in productivity? That partially depends on how we measure it. If we look at output per worker, then a 34% increase in hours worked would be a substantial boost in productivity and would surely lead to increased economic growth. This alone makes a sleepless world a classic example of low hanging fruit (although it may be closer to an increase in labour force participation than a productivity boost from innovation).

However, there are also reasons to think that output per worker hour may be improved by longer hours. Let's assume that the additional hours worked allow companies to keep the same production with a quarter fewer workers.  Why hire four workers for a task, when you can hire the three workers who are most productive to do more hours?

That process would be a major gain for firms. They can hugely reduce costs by spreading the fixed cost per worker over more hours of work. More hours worked shouldn't increase costs of healthcare, training and fringe benefits so the fixed costs fall in line with their reduced workforce.

There are also productivity boosts by lengthening the work day itself in terms of travel time, starting up computers and lunch breaks that we wouldn't expect to increase at the same rate as hours worked. The longer work day may also push forward globalization as workdays overlap for longer periods across time-zones.

Once again though, the gains go even deeper than this. Probably the largest productivity improvement  of all will be in human capital accumulation and the returns an individual can expect from it. From the perspective of a student, a sleepless world is an increase of a third in expected working lifespan giving a longer time period for her to benefit from the investment she has made in her human capital. It also means she can potentially finish her education in a shorter time or use the additional waking hours in employment, reducing the opportunity cost of an extended university education.

The sleepless world may finally begin to reverse the age inequality in employment (at least temporarily). Young people will accumulate job experience at a faster rate through more hours of work experience. They may also be more willing to adopt the new drugs than older generations increasing their relative value as employees.

So given the benefits, do we want to grab this piece of low hanging fruit?

The main argument against it is that it will not be a voluntary choice for an individual. If these drugs become widely available then workers who are willing to use them will easily out-compete those who do not. In addition, if the drugs are expensive then it will further increase inequality between those who can afford them and those for whom the price is prohibitive. However, a Google search of various dubious websites suggest the current drugs retail for around $5 a day. At that price, even those working at minimum wage would find it worthwhile to buy the pills.

The final argument against is that a rapid introduction of these pills would amount to an increase in the labour supply and cause a fall in hourly wages or unemployment. However, it's likely that individuals would generally still see an increase in their overall income and their additional leisure time (2 hours extra) would allow this to be translated into an increase in demand in the economy through increased consumption.

Overall the transition to a sleepless world seems beneficial to humanity. There's nothing special about the 7 hours of sleep we get right now and I think people would rightly be opposed to a change that made everyone spend an extra hour asleep every day.

Caveats:

• I've never used Modafinil. This is because I don't know where to buy it, I have some moral qualms about using it when the rest of the world is not and because it is still a bit early to conclude that there are no long term health effects;
• Some people I've talked to have raised the issue of environmental damage. I think the total environmental impact of a sleepless world could be positive or negative but surely the damage would be lower per unit of output (because there are a lot of fixed carbon outputs per work day such as commuting and building overheads). At the very least, a sleepless world looks like a more environmentally friendly growth strategy;
• This argument is premised on the safety of these drugs. Clearly the calculus will change if they are shown to have negative long term consequences;
• For those people who already work long hours with little sleep, these drugs should at least make that lifestyle less dangerous. There is convincing evidence that chronic lack of sleep is harmful in normal circumstances;
• The precise amount of sleep that a Modafinil user can get by with seems to vary but all sources I've seen suggest it is dramatically lower;
• The short term costs of a rapid change might be substantial so gradual adoption is probably preferable from the standpoint of welfare.

Making maths easier to follow in sociology

One issue I have when I read a maths-heavy social science paper is that it's difficult to skim through them. Some people might think this is because they are denser and more complex. This is certainly true in some cases but I don't think that's actually the main issue. The key requirement for skimming is that you can start reading the text at any point. If I'm familiar with a topic I can usually jump into an interesting looking patch of text in a paper and go from there. It's good to have the additional definitions and background at the start of the piece for those who are new to the area but it can be safely skipped by anyone already aware of the issues.

Unfortunately this is rarely possible with maths as the symbols used are defined throughout the piece, so any skimming soon requires flicking back through the article to find the definition of each symbol. Some notation is used consistently enough for its meaning to be inferred from context but its pretty rare and the point of using mathematical notation is not to create a system of hieroglyphs that each cover a unique concept. What this inevitably means is that I have to start at the very beginning of a paper and work through in order to make sure I don't miss any definitions. I've read econometrics textbooks that use notation they defined three chapters earlier!

I think there might be a better way to do this.

What if every mathematical symbol in a paper could have its definition brought up by rolling the mouse over it or clicking on it.

I envision a latex package for it working something like the following:

\definemathsymbols{i}{An individual survey respondent.}
\definemathsymbols{\epsilon_{uik}}{The uniform component of measurement error.}

Any subsequent use of the symbol would insert the mouseover text on the right so that a reader who is skimming can easily find out what your idiosyncratic notation means.

Then if you wanted to redefine a symbol you would just use the command again:

\definemathsymbols{i}{The currently selected ego in the simulation.}

These definitions are not designed to give a complete understanding of what's being done in the paper but they should allow a casual reader to skim a few equations and work out whether it's worth diving deeper into.

Not sure of the technical difficulties in implementing this but I think it could make a reader's job much easier.

If anyone wants to collaborate on writing a package or pointing in the direction of an existing one I'd be interested to hear from you.