#indyref night: how I’ll be following [somewhat technical]

September 16, 2014

Yesterday I put something up at the UEA Politics blog, on how to interpret the results from each local authority area as they come in.

Of course, it’s a small step from producing prior beliefs regarding regional offsets, to producing a full-blown projection mechanism.

In this note I give some Jags code for revising projections based on some reasonable priors. The link to the GitHub code is contained therein.

This code might help you know the likely outcome three hours in advance. Unfortunately, to know the likely outcome, you’ll have to forfeit your sleep and wait for each local area to report. Your call.

Update: Updated version of the note — now incorporating a turnout model — is here.

Are Scots more left-wing?

September 15, 2014

Ailsa Henderson’s analysis of Scottish (and English and Welsh) values has gone some traction recently. It’s part of an edited collection (to which I have also contributed) put together by Phil Cowley and Rob Ford.

The chapter (and Spectator excerpt) argue that Scots are not distinctive in terms of their political attitudes. Specifically, it argues that on general issues of left versus right, attitudes towards welfare, and authoritarian-liberal issues, Scots are not significantly more left-wing, welfare-friendly, or liberal than those in England.

This analysis has been well-received by those opposed to independence. If Scots are not distinctive in their values, then value distinctiveness cannot be a well-grounded basis for independence.

There’s just one problem with the analysis — if you look at the latest BES data, it’s not born out. Here’s my replication of Professor Henderson’s work. There are three scales, and if you want to look up the BES codebook [PDF] you’ll see the Likert-type questions these scales are based upon (questions lr1-lr5, al1-5, and a variety of questions with rather heterogeneous names).


As the graph shows, there are significant differences between Scots, English, and Welsh. Scots are significantly less authoritarian than the English, significantly less concerned by abuse of welfare schemes by immigrants or fraudsters, and significantly more left-wing. The error bars — which show the 95% confidence intervals — don’t overlap.

You might at this point say that whilst these differences are statistically significant, they are not substantively significant. But then your argument becomes, “Scots and those in the rest of the UK are different, but not very dramatically”. The argument then becomes a matter of degree, not a matter of kind.

What can Deutsche Bank possibly mean?

September 13, 2014

Yesterday (Friday 12th) Deutsche Bank claimed that Scottish independence would be

“a political and economic mistake as large as Winston Churchill’s decision in 1925 to return the pound to the Gold Standard or the failure of the Federal Reserve to provide sufficient liquidity to the US banking system, which we now know brought on the Great Depression in the US.”

This quota was contained in a subscriber-only research report. I’ve only been able to find a five-page PDF document (of which two pages are regulatory disclosure), so it’s possible that this claim is based on considerably more analysis than I have seen. But I find it difficult to imagine that Deutsche Bank mean what they say.

Deutsche Bank might mean that the negative consequences of Scottish independence for the world will be as bad as the negative consequences for the world of the Gold Standard decision or of insufficient liquidity in 1929. But this seems implausible. The UK’s share of world GDP now (3.9 percent) is much smaller than its share in 1925 (4.3%). It is certainly much smaller than the US’s share of world GDP in that same period (13.4%). (Figures from the Maddison project). So whatever the decision, the negative consequences of Scottish independence for the world are unlikely to be as bad as the negative consequences of the cited examples.

Of course, Deutsche Bank might also mean that the negative consequences of Scottish independence for Scotland will be as bad as the negative consequences for the UK of the Gold Standard decision, or the negative consequences for the USA of insufficient liquidity in 1929.

Let’s take the negative consequences for the UK of the Gold Standard decision to be the sharp drop in output between 1925 and 1926, which saw GDP decline (1990 Geary Khamis-adjusted US dollar terms) from 231,806 to 223,270 million. That’s a fall of almost four percent.

The negative consequences for the US of insufficient liquidity are much more serious. Consider the much longer decline in US GDP between 1929 and 1933. Here, GDP declined from 843,334 million (1990 US dollars) to 602,751 (1990 US dollars) — a fall of almost 29 percent.

Of these two, the Great Depression is by far the more dramatic, and has been given most play in the media.

Does Deutsche Bank really mean then that GDP in an independent Scotland would fall between 4 and 29 percent? It’s difficult to say, because the document that I saw doesn’t contain any growth projections for an independent Scotland. Producing growth projections would be difficult, because it’s uncertain which currency an independent Scotland would use. The report suggests that sterlingisation would be the worst option, because an independent Scotland would have to build up currency reserves which would force fiscal contraction.

But unless Deutsche Bank views sterlingisation as by far the most likely option, that means that their growth forecasts for this option have to be even worse than between -4 and -29 percent in order to create an overall projection of this magnitude.

In either case, if analysts reporting to me suggested that the economic consequences of independence were likely negative, but spanned a range between 4 and 29 percent, I’d be asking some hard questions about their models. That’s the difference between Scottish GDP per capita being approximately the same as GDP in the rUK, and Scottish GDP per capita being approximately the same as Spanish GDP per capita.

Perhaps I’ve taken Deutsche Bank’s comments too literally, and they don’t mean that the economic consequences of independence for Scotland will be equivalent to a contraction of between 4 and 29 percent. But if Deutsche Bank’s comments can’t be interpreted in this way, it strongly suggests that they view the economic consequences as negative, and reached around for the scariest historical comparator they could find. That’s irresponsible.

NSS results for politics 2014

August 19, 2014

The results of the 2014 National Student Satisfaction Survey are now out. As with last year’s release, the full data are contained in huge .xlsx files on HEFCE’s website.

Here are the tables for overall satisfaction for all 77 first-degree awarding institutions in the field of politics, together with associated confidence intervals.


Congratulations to Chester and Coventry.

The ballad of #Signon Dy, or constituency-level election results in R

August 6, 2014

CLEA — the Constituency Level Elections Archive — is potentially a fantastic resource. Constituency results for most countries, and Britain in particular, are hard to find in systematic form. CLEA offers systematic results, and has great temporal and spatial coverage.

But… I found it really hard to read the CLEA data into R. It’s supplied as a fixed-width file (no, really), with pre-cooked SPSS and Stata versions. But the Stata version is version 13 only (released last year, with a non-backwards-compatible file-format: what gives?), and the SPSS import in R choked.

Reading the data into R as a fixed width file was difficult not just because I had to enter the lengths correctly (which took some doing), but also because some of the names caused parsing difficulties. Selfishly, parties and individuals in other countries have chosen to use non-ASCII characters (the impudence!), and so I had to spend some time figuring which non-Unicode formatting the data used.

Additionally, some of the strangest meta-characters pop up in candidate and constituency names. My favourite is the story of “#signon dy”, who apparently contested New York’s 2nd Congressional district for the Liberation Whig Party in 1984.

#Signon’s unusual typography is too early to be a hash-tag — but too weird to be an encoding error, which might explain the o&#briens and o&#neils of this world. Lovely though the name is, it causes big problems for R import — since R by default uses the hash character to delimit a comment section, ignoring everything on the remainder of that line. Tracking down this problem took some time…

Anyway, I’ve posted some code on GitHub to pull in the CLEA data properly. Hope you find it useful!

UK’s non-participation in Schengen costs UK travellers £29m in dead time

June 30, 2014

Believe it or not, academics work hard over the summer. In the past four weeks, I’ve made two research trips abroad, to Bergen and Barcelona. They were great trips — but I worked hard to prepare my presentations.

In both trips, I spent time waiting in passport control. On my trip to Bergen, I only had to do this at the end of the first leg, between Norwich airport[1] and Schiphol. Since the Netherlands and Norway both participate in Schengen, I was able to clear arrivals and get on to the city centre bus within about ten minutes.

Without wishing to sound unduly precious — my time is important to me. Specifically, it has an opportunity cost.

The opportunity cost of time lost in transit has been recognized by the government, most notably in its calculations of the economic benefit of HS2. According to WebTAG 2013 (to be used in subsequent infrastructure evaluation), the value of business time is £31.96/hour; the value of leisure time drastically less at £6.04/hour.

Information like this allows us to calculate the costs to UK passengers of the UK’s non-participation in Schengen. (This is only a small fraction of the total cost: the cost of processing passengers is far larger).

Specifically, we can say that the cost to UK passengers is:

  1. number of business visits by UK nationals returning from Schengen participating countries per year *
  2. average wait in hours *
  3. opportunity cost of business time +
  4. number of non-business visits by UK nationals returning from Schengen participating countries per year *
  5. average wait in hours *
  6. opportunity cost of non-business time

Thanks to Travelpac data from the ONS (in turn derived from the International Passenger Survey), we know that there were 4,463,471 business visits by UK residents returning to the UK, and 34,216,766 non-business visits by UK residents returning to the UK. This gives us information for (1) and (4).

We don’t know anything about the average wait in hours at passport control, because the UK Border Force (wisely?) doesn’t collect this information. Rather, it collects information on the percentage of passengers processed within a certain amount of time (25 minutes, for European Economic Area visitors).

Almost all (>95%) passengers are processed within this time, presumably because the Border Force has got better at distributing resources since the chaos of 2012.

If we take one minute and twenty five minutes as lower and upper bounds (and this is quite generous to the Border Force, because the real maximum times are north of two hours), then we can estimate the average time, Taagepera-style, by taking the geometric mean, or five minutes. This gives us information for (2) and (5).

We can then plug the WebTAG 2013 figures in to get the following:

  • cost to business passengers: £11,887,710
  • cost to other passengers: £17,222,439

for a total of over £29 million.

This is a very, very conservative estimate of the cost to UK residents, because it doesn’t count the cost to us of waiting in line to have our passports checked in other member states.
If wait times in other member states are similar to those in the UK, then the cost is double this figure.

This estimate is also very conservative because it ignores the cost to government. It costs £2.85 to process each passenger visit. This number can’t be multiplied by the number of visits from Schengen member states, because it ignores fixed costs, and different (likely higher) costs for non-EEA visitors. But the processing cost is very much larger, because it doesn’t just include the 38 million visits of UK nationals from Schengen countries, but the visits of all visitors coming from Schengen countries.

29 million might seem like small potatoes — but whenever I have to show my passport flying to a Schengen member state, I feel like I would quite like my slice of that money back.

[1] Sorry, Norwich International Airport — an airport which tries to justify the pretensions embodied in its name by the most ridiculous forms of security theatre.

Independence, accountability, and quality of competition authorities

June 24, 2014

I’m just heading to Barcelona for the 2014 conference of the ECPR Standing Group on Regulatory Governance. I’ll be presenting a paper that I’ve written with Christel Koop, on the quality of competition authorities. We want to explain why some competition authorities generally are regarded quite well, whereas others are regarded as striving but failing. In particular, we’re interested in design features like independence and accountability. For me, this is because I’ve done previous consultancy research which has suggested these things matter.

You can find a draft of the paper here. It’s still very drafty, and the analysis will likely change — but since due to a scheduling snafu there’s nowhere to put it on the conference website, I thought I should put it on my own site.

Key claims/findings:

  • We can analyse star ratings from the Global Competition Review as if they were ranks
  • We can do so using an exploded logit model
  • We find that both independence and accountability have a positive effect on quality at the 10% level or better
  • These results are even more robust if you think an exploded logit model is a barmy way of going about things, and use an ordered probit instead

Party support in EP elections, East of England edition

May 26, 2014

Although the availability of official electoral data in the UK continues to be execrable compared to any other European country, the good people at Chelmsford Borough Council have at least proceeded swiftly to publish a spreadsheet showing party support at the local authority level.

I’ve put these in a slideshow below, but you can download the pngs from the list below, or tweet me for printable PDFs/R source code.

This slideshow requires JavaScript.

Economic hurt doesn’t make people think about economics

May 26, 2014

On Twitter, Duncan was musing about the link between London’s relative economic success and Labour’s relative electoral success there.

Another tweeter (sorry, can’t remember who) suggested that this was particularly puzzling given the (presumed) resonance Labour’s emphasis on living standards ought to have with people in parts of the country that have been doing less well.

The logic here is clear: poor economic conditions cause people to think about the economy, and select the party that they think is doing best on that issue. Unfortunately, people don’t seem to follow that logic.

Here’s a plot from the latest BES data showing the percentage of respondents who say that the most important issue facing the country is the economy in general, or unemployment.


Weird, no? Reading from left to right, the better your economic situation, the more important it becomes to you, until we get to the people who’ve done really well. Or, reading from right to left: the more your economic situation has worsened, the less important it is to you.

Why is that? Here’s another graph of “most important issue” responses. Now, the most important issue is migration.


Here, economic “losers” are more likely to think immigration is a big issue than are economic “winners”. So it looks like economic hurt makes people more likely to think about cultural and economic threats, rather than the economy in general.

This pattern is robust to controls for ethnicity and education, which have also been invoked to explain London exceptionalism.

I should note: I’m not an expert on electoral behaviour, and I’ll gladly defer to others who can make more sense of this pattern than I can.

Which are the best performing government departments? (2013/4 update)

May 23, 2014

A year ago, I blogged about the best-performing government departments, judged by the traffic light ratings of the Major Projects Authority.

Last year, the data was buried — release on a Friday at 5pm. This year’s release of the MPA ratings has been buried beneath the local election results.

You can find this year’s data on the gov.uk website. The data refer to evaluations made as of September 2013 — so really, we’re comparing 2012 to 2013.

When we average department ratings, how does their relative performance change?
Here’s a table which will help (apologies for tabular presentation – but plotting this as a slopegraph is awkward).

Dept 2012 2013 Change
CO 3.20 2.88 -0.33
DoH 3.71 2.96 -0.75
DEFRA 3.50 3.00 -0.50
DfID 4.00 3.00 -1.00
HMT 2.50 3.00 0.50
HO 3.42 3.15 -0.27
DCMS 2.80 3.17 0.37
MOD 3.46 3.24 -0.22
DfT 3.47 3.25 -0.22
MoJ 3.50 3.33 -0.17
DWP 3.33 3.36 0.03
FCO 3.67 3.40 -0.27
ONS 2.80 3.40 0.60
BIS 3.50 3.45 -0.05
DECC 5.00 3.50 -1.50
DfE 3.50 3.50 0.00
DCLG 3.25 3.67 0.42
HMRC 3.67 3.75 0.08
NS& I 2.00 5.00 3.00

In terms of relative improvement — bouquets to NS&I, ONS, HMT, and DCLG; brickbats to DECC, DfID, and DoH.

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